Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

Application of Selection Mapping to Identify GenomicRegions Associated with Dairy Production in SheepBeatriz Gutierrez-Gil1*, Juan Jose Arranz1, Ricardo Pong-Wong2, Elsa Garcıa-Gamez1, James Kijas3,

Pamela Wiener2

1 Dpto. Produccion Animal, Universidad de Leon, Leon, Spain, 2 The Roslin Institute and R(D)SVS, University of Edinburgh, Roslin, Midlothian, United Kingdom, 3 Animal,

Food and Health Sciences, CSIRO, Brisbane, Australia

Abstract

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, withincome from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemesfocused on milk production have led to the development of ‘‘dairy breeds.’’ This study investigated selective sweepsspecifically related to dairy production in sheep by searching for regions commonly identified in different European dairybreeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both Europeandairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme geneticdifferentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions withreduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breedpairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled ascore candidate convergence regions and further investigated for candidate genes. Following this approach six regions weredetected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genesdesignated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were notassociated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported insheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have beenidentified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate thepotential value of selection mapping to identify genomic regions associated with dairy traits in sheep.

Citation: Gutierrez-Gil B, Arranz JJ, Pong-Wong R, Garcıa-Gamez E, Kijas J, et al. (2014) Application of Selection Mapping to Identify Genomic Regions Associatedwith Dairy Production in Sheep. PLoS ONE 9(5): e94623. doi:10.1371/journal.pone.0094623

Editor: Bernhard Kaltenboeck, Auburn University, United States of America

Received November 19, 2013; Accepted March 19, 2014; Published May 1, 2014

Copyright: � 2014 Gutierrez-Gil et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors gratefully acknowledge support from the Spanish Ministry of Economy and Competitiveness (Project AGL2009-07000), Institute StrategicGrant funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the financial support of the European Science Foundationthrough the GENOMIC-RESOURCES Exchange Grant awarded to Beatriz Gutierrez (EX/3723). BGG is funded through the Spanish ‘‘Ramon y Cajal’’ Programme fromthe Spanish Ministry of Economy and Competitiveness (State Secretariat for Research, Development and Innovation). The funders had no role in study design,data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Since their domestication 8 000–9 000 years ago (reviewed by

[1]), sheep (Ovis aries) have been used by humans for the

production of wool, meat and milk. Adaptation to very different

geographic and climatic conditions and the specialization for

specific characteristics have resulted in a phenotypically highly

diverse species. The first documented modifications to sheep by

human-imposed selection had taken place by the time that

illustrations and records first appeared c. 3 000 BC and primarily

concerned morphological and coat colour traits with the initial

major morphological changes including reduction in the length of

the legs, lengthening of the tail and alteration of horn shape [2].

Initially, sheep were kept solely for meat, milk and skins.

Archaeological evidence suggests that selection for woolly sheep

may have begun around 6000 BC.

Dairy sheep are mainly found in Europe, especially in

Mediterranean areas, where they have been traditionally exploited

as a dual purpose species, with income from both meat and milk.

Sheep milk has a higher solid content than cow or goat milk,

which means that it is particularly suited to processing into cheese.

Historically, most sheep milk has been produced by multipurpose

local breeds with low-to-medium milk yields and raised under

traditional husbandry conditions [3]. More recently, moderniza-

tion of husbandry methods and the establishment of breeding

schemes focused on milk production have led to the development

of ‘‘dairy breeds’’, facilitated by the implementation of quantitative

genetics-based breeding and the use of artificial insemination [2].

The market for sheep milk and sheep dairy products appears to be

growing, even in those countries without a history of sheep

dairying [4].

Selection sweep mapping strategies, in which regions of the

genome are identified that show patterns consistent with positive

selection, can be used as a complementary approach to linkage

mapping and genome-wide association study (GWAS) analysis to

identify regions of the genome that influence important traits in

livestock. Various methods have been applied to livestock and

other domesticated animals, with the aim of identifying genomic

regions with characteristics that reflect the influence of selection:

extended low diversity haplotypes [5], overall low heterozygosity

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(e.g. [6,7]), specific diversity patterns [8], extreme allele frequen-

cies [9] and between-breed differentiation [10,11,12]. Because of

their well-documented selection pressures and highly-developed

genetic resources, domesticated animal species also provide a

valuable resource with the potential to identify the molecular

pathways underlying phenotypic traits through the use of selection

mapping approaches [10,13].

To perform a search for signatures of selection related to dairy

production in sheep, we used genotypes obtained with the Illumina

OvineSNP50 BeadChip (Illumina Inc., San Diego, CA) for a number

of European breeds genotyped within the framework of the Sheep

HapMap Project [14]. These breeds include several selected

primarily for dairy production and others not used for dairy. In

order to specifically target regions under dairy-related selection

and not related to other traits that may have been under selection

in the sheep populations, only selection signatures commonly

identified in different European dairy breeds were considered. We

applied two approaches for the detection of selection sweeps: (i) we

looked for regions with extreme genetic differentiation between

each dairy breed and a closely related non-dairy breed, and (ii) we

looked for regions of the genome with reduced heterozygosity in

the dairy breeds using two methods. We then searched for

candidate genes that could be selection targets within the regions

that were identified in multiple breeds and using multiple analysis

methods. For these regions we also looked for correspondence with

previously reported QTL related to dairy production traits in

cattle or sheep. Although the selection history of dairy cattle is

quite different from that of dairy sheep, in particular because

breeding schemes in sheep are focused on more localized (and in

many cases isolated) breeds than the global dairy cattle population,

comparison of our results with studies in cattle allowed us to

evaluate whether some of the same regions/genes show evidence

of selection in both dairy sheep and dairy cattle.

Materials and Methods

DataSamples. We analysed a subset of the dataset generated in

the Ovine HapMap project [14], which included 5 dairy and 5

non-dairy sheep breeds (Table 1).

Genotypes. After an initial quality control procedure de-

scribed in detail elsewhere [14], this dataset provides the genotypes

of 49,034 SNPs (using the Illumina OvineSNP50 BeadChip) distrib-

uted across the 26 autosomal ovine chromosomes and chromo-

some X (only one of the markers genotyped belongs to

chromosome Y). Markers were filtered to exclude loci assigned

to unmapped contigs. The analyses reported here focused on the

remaining 44,545 of these SNP located on autosomes. The

positions of the markers according to the Sheep Genome Assembly

v2.0 (update September 2011) were used for the analyses.

Selection Sweep Mapping Analysis Methods

(i) Genetic differentiation: Pair-wise FST calculations.In order to search for genomic regions that have been under

divergent selection in dairy and non-dairy breeds, we

examined genetic differentiation across the genome for five

breed pairs. The selection of sheep breeds to serve as non-

dairy partners for dairy breeds was based on the shortest

divergence time estimates reported by the Sheep HapMap

project (based on the extent of haplotype sharing and

correlation of linkage disequilibrium values; Supplementary

Information Figure S10 and Figure 3 in [14]), and close

relationships according to additional Principal Component

Analyses (PCA) performed in a selection of breeds (described

in detail in File S1).

The following pairs of breeds of European ancestry were

considered in the differentiation analysis:

a. Chios (Greek, dairy) vs Sakiz (Turkey, non-specialized)

b. Churra (Spanish, dairy) vs Ojalada (Spanish, meat)

c. Comisana (Italian, dairy) vs Australian Poll Merino (Austra-

lian, originated in southwest Europe, wool)

d. East Friesian Brown (highly specialized dairy) vs Finnsheep

(Finland, primary wool, more recently used as a meat

producing breed)

e. Milk Lacaune (French, highly specialized dairy) vs Australian

Poll Merino (Australian, originated in southwest Europe,

wool)

f. Milk Lacaune (French, highly specialized dairy) vs Meat

Lacaune (French, meat)

For each of these pairs, unbiased estimates of Weir and

Cockerham’s FST [15], a measure of genetic differentiation, were

calculated as functions of variance components, as detailed in

Akey et al. [16]. This type of approach to selection mapping,

exploiting between-breed allele frequency differences, has been

applied in studies of humans [16] and domesticated animals

[10,11,12,17,18] where it has been demonstrated to be effective in

identifying genes that are associated with breed differentiation.

(ii) Reduced diversity: Observed heterozygosity. For all

the breeds included in the pair-wise FST calculations,

observed heterozygosity (ObsHtz) was calculated for each

SNP marker. This approach has previously been applied in

selection mapping studies of chickens [6,7], pigs [19] and

dogs [20].

(iii) Reduced diversity: Regression analysis for detec-tion of regions with asymptotic heterozygositypatterns. For all the breeds included in the pair-wise FST

calculations, tests of significant asymptotic relationships

between heterozygosity and distance from a test position

were performed across the genome based on the approach of

Wiener and Pong-Wong [8]. This method detects regions

with patterns of variation consistent with positive selection:

an asymptotic increase in marker variation (heterozygosity; y)

with increasing distance (x) from a selected locus y = A +B Rx

(where R is the asymptotic rate of increase; B is the difference

between heterozygosity at the test position and the

asymptotic level; A is the asymptotic level of heterozygosity).

For each regression (performed in Genstat, [21]), we

recorded the parameters of the asymptotic regression, their

standard errors, the significance level associated with the

regression (p) and the variance explained by the curve.

Positive and increasing regressions (0,R,1, B,0) were

considered as being in the direction predicted by positive

selection. Analysis of simulated data suggests improved

precision of this selection mapping approach compared to

an alternative haplotype-based method as well as robustness

to demographic influences [8].

Protocols for Selection Mapping AnalysesIn order to determine appropriate parameters for the above-

mentioned analyses, we investigated their behaviour on a test

genomic region encompassing the myostatin (GDF-8) gene, which

is known to have been under selection in the Texel breed (details

in File S2).

Window/bracket sizes. Based on the analysis of the

myostatin gene (File S2), window and bracket sizes for the three

methods were established. For the differentiation and reduced

heterozygosity analyses, FST and ObsHtz values, respectively, were

Selection Signatures in Dairy Sheep


averaged across sliding windows of 9 SNPs (FST-9SNPW, ObsHtz-

9SNPW). For the regression analysis, the test position was moved

every 50 Kb across each chromosome and all markers within

10 Mb of this position (10 Mb-bracket size) were considered in the

asymptotic regression. A –log(p) value was determined for each test

position.

Identification of selection signals by individual

methods. Evidence of positive selection was interpreted for

window estimates in the extreme of the empirical distributions, as

suggested by Akey et al. [10,16] and employed in various

subsequent studies (e.g. [11,13]. Specifically, we considered the

positions showing signatures of selection as the top 0.5th percent of

the distributions for differentiation (FST) and asymptotic regression

(–log(p), for regressions in the predicted direction) or the bottom

0.5th percent for observed heterozygosity. Based on the results of

the analysis of the myostatin gene (File S2), a selected ‘‘region’’ was

defined as the range of positions within 2 Mb of each other

showing evidence of selection by any of the three methods. An

additional criterion for selected regions was that they were

identified in at least two breed pairs, for FST, or two dairy breeds,

for heterozygosity-based methods (with distances up to 2 Mb

allowed between the regions identified for different breeds). For

genetic differentiation, we further required that regions of extreme

FST must be detected in at least two different pairs of dairy – non-

dairy breeds that did not share a common breed (e.g. top regions

found only in the Milk Lacaune-Australian Poll Merino and

Comisana-Australian Poll Merino but not in other studied pairs

were not included in the list of differentiated regions). By requiring

at least two breeds (or breed pairs) for the initial identification of

candidate regions for each methodology, this selection mapping

strategy will not identify dairy gene variants occurring in only one

breed.

Criteria for Identification of Regions with SharedSelection Signals

Based on the selected ‘‘regions’’ identified by the individual

methods through the overlapping of at least two breeds or breed

pairs, and taking into account that the FST-based method is

expected to specifically target traits relevant for dairy production,

whereas signals detected by heterozygosity-based methods may not

be specific for dairy-related selection, we defined a ‘‘convergent

candidate region’’ (CCR) as one where a signal was identified by

the pair-wise FST comparison and at least one of the reduced

heterozygosity methods. Hence, a CCR was labelled where there

was overlap between the position ranges of the candidate regions

identified by the genetic differentiation methodology and at least

one of the two heterozygosity-based methods, such that each CCR

was associated with a region identified in at least two breeds (breed

pairs) and using at least two different methods.

Identification of Candidate Genes within CCR RegionsWe identified the genes mapping to the end of each CCR using

the genome browser of the sheep genome reference sequence

(v2.0; http://www.livestockgenomics.csiro.au/cgi-bin/gbrowse/

oarv2.0/) and identified the corresponding orthologous regions

in the bovine genome (Cow (UMD3.1) using Ensembl (http://

www.ensembl.org/Bos_taurus/Info/Index). A systematic extrac-

tion of all the annotated genes contained within the orthologous

genomic ranges in cattle was performed using Biomart (www.

biomart.org). Subsequently, an exhaustive search was performed

for candidate genes previously linked to cattle dairy traits [22]. In

addition, genes not included in this database but reported as

candidate genes in the literature in relation to milk production or

dairy-related traits were also identified. We also looked for

correspondence with genes for which signatures of selection have

been reported in studies of dairy cattle [23,24,25] and sheep

[14,26].

We evaluated correspondence of the CCR with QTL reported

for milk production and other functional traits related to dairy

production in sheep (based on the SheepQTL database, http://

www.animalgenome.org/cgi-bin/QTLdb/OA/index). We also

examined overlap between the CCR and QTL influencing milk-

related traits, mastitis and other functional traits related to dairy

production in cattle (based on the CattleQTL database; http://

www.animalgenome.org/cgi-bin/QTLdb/BT/index), positioned

on the bovine genome reference sequence (UMD_version 3.1).

Results

Regions Identified by Individual MethodsGenetic differentiation. The level and range of the top

0.5% of FST values averaged in sliding windows of 9 SNPs (FST-

9SNPW) varied among the five breed pairs (Figure 1). The lowest

Table 1. Breeds included in the present study.

Group Breed nameNumber ofsamples Aptitude

Dairy Chios 23 High milk production

Churra 96 Double purpose breed(milk and lamb production

Comisana 24 Highly-specialized dairy breed

East Friesian Brown 39 Highly-specialized dairy breed

Milk Lacaune 103 Highly-specialized dairy breed

Non-dairy Australian Poll Merino 98 Meat production

Meat Lacaune 78 Meat production

Ojalada 24 Meat production

Sakiz 22 Triple-purpose (milk, meat, wool)

Finnsheep 99 Primary used for wool production;more recently used for meat production.

The classification established into Dairy and Non-dairy groups are presented together with some details about the breed aptitude.doi:10.1371/journal.pone.0094623.t001



http://www.livestockgenomics.csiro.au/cgi-bin/gbrowse/oarv2.0/


http://www.ensembl.org/Bos_taurus/Info/Index


www.biomart.org

www.biomart.org

http://www.animalgenome.org/cgi-bin/QTLdb/OA/index

http://www.animalgenome.org/cgi-bin/QTLdb/OA/index

http://www.animalgenome.org/cgi-bin/QTLdb/BT/index

http://www.animalgenome.org/cgi-bin/QTLdb/BT/index

genome-wide differentiation within a pair was found, as expected,

for the Milk Lacaune-Meat Lacaune pair (0.076), whereas the

highest levels of genetic differentiation were found for the East

Friesian Brown-Finnsheep pair (0.752, for the 9SNP-window

centered on marker OAR3_185527791) (Table 2).

Twenty-eight genomic regions distributed across 15 autosomes

were identified in at least two dairy-non-dairy breed pairs (Table

S1, where a reference number has been given to each of them:

FST-CandidateRegionX, FST-CRX). The largest number of FST-

based candidate regions per chromosome was found on OAR3 (5

regions). The length of the FST-based candidate regions varied

from 0.215 Mb (OAR3, FST-CR8) to 9.211 Mb (OAR6, FST-

CR14).

Reduced observed heterozygosity in dairy breeds. Fifty-

five regions showing reduced observed heterozygosity (ObsHtz-

CR1–ObsHtz-CR55) in more than one dairy breed were found

across 21 of the 26 autosomes (Table S2; where a non-dairy breed

showed reduced heterozygosity in the same region, this is also

indicated). Eight of the candidate regions found in dairy breeds

covered intervals larger than 3 Mb. The largest was that on

OAR13 (ObsHtz-CR42; 56.061–63.781 Mb), followed by one on

OAR6 (ObsHtz-CR27:34.576–41.863 Mb), while the smallest

region was a single window centered on marker on OAR2

(ObsHtz-CR9; 211.205 Mb). A normalized observed heterozy-

gosity (NObsHtz) (based on that introduced by Rubin et al. [6])

was also calculated for all breeds analysed, again averaged in 9-

SNP windows. There were no regions in the extreme lower end of

the distribution (NObsHtz,-6) in the dairy breeds although the

region on OAR6 (ABCG2 gene region) had a value of 25.99 for

the Meat Lacaune breed.

Regression analysis for detection of regions with

asymptotic heterozygosity patterns in dairy

breeds. Three regions ranging in size from 0.1 to 4.0 Mb were

identified with asymptotic heterozygosity patterns (bracket

size = 10 Mb) in two or more dairy breeds (RegBrack10-CR1–

RegBrack10-CR3) (Table 3, where a non-dairy breed showed

reduced heterozygosity in the same region, this is also indicated).

The myostatin analysis suggested that a bracket size of 10 Mb

was optimal for identification of selected region. However, because

this is a new methodology, the results obtained for the dairy breeds

with all three bracket sizes (5-, 10- and 20-Mb) were compared to

aid interpretation of results based on this approach. The number

of candidate regions identified in at least two dairy breeds

decreased with increasing bracket size. For the 5-Mb bracket size,

a total of seven candidate regions were observed, whereas only

three and one candidate regions were observed for the 10- and 20-

Mb bracket sizes, respectively (Table 3). The region commonly

identified through the use of all three bracket sizes was located on

OAR6 (RegBrack5-CR6, RegBrack10-CR2 and RegBrack20-

CR1). The signal for this region was seen in Milk Lacaune

(34.875–38.875 Mb, 10-Mb bracket) and Comisana (36.125–

38.325 Mb, 10-Mb bracket) breeds. In addition, the Meat

Lacaune variety also showed extreme results for this region for

all three bracket sizes (34.375–38.175, 10-Mb bracket). Another

region on OAR2 (104 Mb) was identified by both of the smaller

bracket sizes.

Some of the inconsistencies between bracket sizes were

investigated further. In several cases, where regions were not

found in the top 0.5% of –log(p) values for a particular bracket

size, they did appear in the top 1% of –log(p) values. Regarding

the region on OAR20 (,50 Mb) that was identified in two dairy

breeds using the 10-Mb bracket size (RegBrack10-CR3, Table 3)

but not using the 5-Mb bracket size: for Churra, positions within

this region appeared within the top 1st percent of –log(p) values for

the smaller bracket size but did not reach the threshold for the top

Figure 1. Genome-wide distribution of FST values for the six analysed breed pairs. The level of genetic differentiation, measured by FST,was estimated within each dairy – non-dairy breed pair1, and averaged in sliding windows of 9 SNPs (FST-9SNPW) across the genome: The horizontalline indicates the top 0.5.th percent threshold considered for the FST-distributions. These raw results were used to identify FST-based candidateregions (FST-CRs) when overlapping significant selection signals (allowing gaps up to 2-Mb) were identified between different pairs. 1Breed pairsanalysed: a) Chios-Sakiz, b) Churra-Ojalada; c) Comisana-Australian Poll Merino; d) East Friesian Brown -Finnsheep, e) Milk Lacaune-Australian PollMerino f) Milk Lacaune-MeatLacune.doi:10.1371/journal.pone.0094623.g001



0.5th percent, whereas for Milk Lacaune, this region was identified

using both bracket sizes. Regarding the five regions (Table 3) that

were identified in two dairy breeds using 5-Mb bracket size but not

10-Mb, four of the regions were in the top 1st percent of –log(p)

values for one or both of the dairy breeds. Two of these regions

(RegBrack5-CR1 and RegBrack5-CR3) were found in Chios and

Churra, however, while these regions were found for Churra using

both the 5- and 10-Mb bracket sizes, for the 10-Mb bracket size,

the top –log(p) values for Chios were dominated by regions on

OAR13 and OAR16, which did not feature in the top –log(p)

values for the other dairy breeds. Thus, these Chios-specific signals

may have overwhelmed the more general dairy signals for the

larger bracket size in this breed. The region labelled as

RegBrack5-CR4, identified at ,75 Mb on OAR3 for Churra

and Milk Lacaune using the 5-Mb bracket size, did not feature in

the top 1st percent of the –log(p) values for the 10-Mb bracket for

either of these breeds. It is worth noting that regions identified

using one bracket size but not a smaller one could reflect more

recent selection events for which the pattern of heterozygosity with

respect to distance from the selected locus appears linear rather

than asymptotic in the smaller bracket.

Convergence Candidate Regions (CCR)Six candidate regions were detected in at least two breed pairs

by the pair-wise FST comparison and in at least two breeds by a

heterozygosity-based analysis (Table 4). One of the regions, CCR3

(OAR6:30.367–41.863 Mb), was identified by all three analysis

methods. The orthologous bovine genomic regions corresponding

to each of the CCR are shown in Table 5. A total of 406 genes

(positional candidate genes) were found in these six core regions

(Table S3). There were three other regions where an FST-CR

signals was less than 1 Mb from an ObsHtz-CR signal

(OAR3:18.648–19.360 Mb, OAR3:167.711–168.959 Mb, and

OAR13:95.801–98.865 Mb) but because they did not overlap,

they were not considered as CCR.

Among the positional candidate genes extracted from the six

CCRs, a search for functional candidates for milk production traits

and mastitis was performed by comparison with the genes

included in the Ogorevc et al. [22] database of cattle candidate

genes for dairy-related traits. A total of 13 genes were common to

these two lists (Table 5). The evidence for relationships with milk

production traits for these genes was based on the different aspects

considered in the Ogorevc et al. [22] database such as gene

expression studies related to mammary gland (TFAP2C, FAM110A,

CD82, ABCG2) or mastitis (BID, MAFF, AHCY), mouse model

studies in which gene knockouts or expression of transgenes

resulted in phenotypes associated with the mammary gland

(FKBP4, MKL1, POFUT1, CHUK) and association studies of milk

production traits (ABCG2, SPP1, SCD).

In order to assess whether there was greater overlap between the

CCRs and candidate genes than expected by chance, we

repeatedly (1 000 000 times) assigned regions of the same length

as the CCR at random positions on the bovine genome and

checked overlap with all candidate genes from the Ogorevc et al.

[22] database that could be positioned on the bovine genome (423

genes). Although we could not do the test with the sheep genome

as the annotation is not as complete, the length of the sheep and

bovine genomes is very similar and so we expect this test would

provide similar results. The number of overlaps between CCR

regions and candidate genes based on a model with random

positioning of CCR regions was very different from the actual

situation: only 8.4% of the replicates contained any overlaps and

the maximum number of overlaps was 4.

Some other positional candidate genes not included in the

Ogorevc et al. [22] database were identified as possible functional

candidates based on their known biological function and an

exhaustive literature review of reported signatures of selection in

dairy cattle (Table 5). There was also correspondence between the

CCR and QTL previously reported in dairy cattle and sheep for

milk production traits or functional traits related to dairy

production (Table 5), which is discussed below.

Discussion

This study reports the first genome-wide analysis of regions

under selection for dairy traits in sheep. For this we have used the

valuable information generated in the International Sheep

HapMap project [14], through the use of the Illumina OvineSNP50

BeadChip, to evaluate a range of European sheep breeds that have

been selected for dairy production. With the aim of identifying the

signatures of selection specifically due to dairy selection and not

related to other traits that may have been selection target in the

studied sheep populations (e.g. coat colour), we also included in

our study other non-dairy European sheep breeds. Furthermore,

because of the difficulties in distinguishing between the effects

caused in the genome by genuine selective sweeps rather than

demographic events such as population expansion or contraction

[16], we used three different analysis methods and only considered

for further exploration those six regions identified by the FST-

based method and at least one of the two heterozygosity-based

methodologies.

Candidate Dairy Selection RegionsBased on the convergence among the three different analysis

methods, six core regions were identified as candidate regions

under positive selection in dairy sheep. Based on the comparison

Table 2. Maximum and minimum of the 0.005 top averaged pair-wise FST values in sliding windows of 9 SNPs (FST-9SNPW)estimated for the pairs considered in the present work to detect selection signals in dairy sheep.

Breed pair Min. FST-9SNPW Max. FST -9SNPW

Chios-Sakiz 0.2799 0.4392

Churra-Ojalada 0.1345 0.2193

Comisana-Australian Poll Merino 0.1781 0.4873

East Friesian Brown-Finnsheep 0.3212 0.7515

Milk Lacaune-Australian Poll Merino 0.1547 0.3071

Milk Lacaune-Meat Lacaune 0.0757 0.1449

doi:10.1371/journal.pone.0094623.t002



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cau

ne

10

4.3

60

10

4.5

60

Me

atLa

cau

ne

10

4.3

60

10

4.5

10

Ch

urr

a1

04

.46

0A

ust

ralia

nP

oll

Me

rin

o1

04

.41

01

04

.46

0

Re

gB

rack

5-C

R3

2C

hu

rra

12

2.3

60

12

2.9

10

Ch

ios

12

3.0

10

12

3.2

10

Re

gB

rack

5-C

R4

3M

ilkLa

cau

ne

75

.19

27

5.2

92

Ch

urr

a7

5.2

92

Re

gB

rack

5-C

R5

3M

ilkLa

cau

ne

16

8.7

42

16

8.8

92

Au

stra

lian

Po

llM

eri

no

16

8.6

92

16

8.9

42

Ch

urr

a1

68

.79

21

68

.89

2M

eat

Laca

un

e1

68

.79

21

68

.89

2

Re

gB

rack

5-C

R6

6M

ilkLa

cau

ne

35

.47

53

6.6

25

Me

atLa

cau

ne

34

.72

53

6.7

75

Co

mis

ana

36

.62

53

7.3

25

Au

stra

lian

Po

llM

eri

no

35

.97

53

7.1

75

Re

gB

rack

5-C

R7

11

Milk

Laca

un

e1

8.3

80

18

.53

0O

jala

da

18

.43

01

8.5

30

Ch

urr

a1

8.4

30

18

.48

0M

eat

Laca

un

e1

8.4

30

18

.48

0

Re

gre

ssio

nto

p0

.5%

bra

cke

t1

0M

bR

eg

Bra

ck1

0-C

R1

2M

ilkLa

cau

ne

10

4.4

10

Oja

lad

a1

04

.41

01

04

.46

0

Ch

urr

a1

04

.46

01

04

.51

0M

eat

Laca

un

e1

04

.41

01

04

.46

0

Fin

nsh

ee

p1

04

.46

01

04

.51

0

Re

gB

rack

10

-CR

26

Milk

Laca

un

e3

4.8

75

38

.87

5M

eat

Laca

un

e3

4.3

74

73

8.1

75

Co

mis

ana

36

.12

53

8.3

25

Au

stra

lian

Po

llM

eri

no

35

.52

53

8.2

25

Re

gB

rack

10

-CR

32

0C

hu

rra

49

.97

15

0.1

71

Milk

Laca

un

e5

0.0

71

Re

gre

ssio

nto

p0

.5%

bra

cke

t2

0M

bR

eg

Bra

ck2

0-C

R1

6M

ilkLa

cau

ne

34

.82

53

8.5

25

Me

atLa

cau

ne

34

.37

53

8.1

75

Co

mis

ana

35

.52

53

8.8

25

Au

stra

lian

Po

llM

eri

no

34

.97

53

8.1

75

We

also

ind

icat

eif

the

sam

esi

gn

atu

reo

fse

lect

ion

was

also

ide

nti

fie

din

the

no

n-d

airy

bre

ed

s.d

oi:1

0.1

37

1/j

ou

rnal

.po

ne

.00

94

62

3.t

00

3



Ta

ble

4.

Co

nve

rge

nce

can

did

ate

reg

ion

s(C

CR

)fo

rse

lect

ion

sig

nal

sid

en

tifi

ed

for

dai

rysh

ee

p.

CC

RC

hr.

Me

tho

dIn

div

idu

al

me

tho

dca

nd

ida

tere

gio

nS

tart

ma

rke

r*S

tart

po

siti

on

(Mb

)E

nd

ma

rke

r*E

nd

po

siti

on

(Mb

)

CC

R1

3F S

TF

ST-C

R7

s51

77

21

52

.68

OA

R3

_1

65

45

08

43

15

4.5

82

Ob

sHtz

Ob

sHtz

-CR

17

s26

17

71

53

.95

OA

R3

_1

65

54

94

68

_X

15

4.6

79

CC

R2

3F S

TF

ST-C

R9

s34

66

82

09

.87

2O

AR

3_

23

43

28

13

4_

X2

15

.81

4

Ob

sHtz

Ob

sHtz

-CR

21

OA

R3

_2

29

87

39

96

21

1.6

24

s35

73

92

15

.40

3

CC

R3

6F S

TF

ST-C

R1

4O

AR

6_

34

08

65

00

30

.36

7O

AR

6_

44

21

00

19

39

.57

7

Re

gre

ssio

nR

eg

Bra

ck1

0-C

R2

OA

R6

_3

89

19

83

13

4.8

75

OA

R6

_3

89

19

83

13

8.8

75

Ob

sHtz

Ob

sHtz

-CR

27

OA

R6

_3

85

85

18

73

4.5

76

s38

25

44

1.8

63

CC

R4

13

Ob

sHtz

Ob

sHtz

-CR

42

OA

R1

3_

60

89

38

51

56

.06

1s6

37

08

63

.78

1

F ST

FS

T-C

R2

4s4

81

33

62

.27

7O

AR

13

_7

10

91

73

86

5.8

11

CC

R5

15

F ST

Fst-

CR

26

s31

34

07

2.7

74

OA

R1

5_

80

44

80

54

74

.55

Ob

sHtz

Ob

sHtz

-CR

44

s02

79

37

2.8

43

s28

87

57

2.9

48

CC

R6

22

Ob

sHtz

Ob

sHtz

-CR

51

OA

R2

2_

23

39

20

99

19

.58

8O

AR

22

_2

47

47

56

52

0.9

91

F ST

FS

T-C

R2

8O

AR

22

_2

46

82

84

52

0.9

25

OA

R2

2_

26

95

15

73

23

.15

7

AC

CR

reg

ion

was

de

fin

ed

wh

en

ove

rlap

pin

gse

lect

ion

reg

ion

sid

en

tifi

ed

by

the

ge

ne

tic

dif

fere

nti

atio

nan

alys

is(i

nat

leas

ttw

ob

ree

dp

airs

),av

era

ge

dfo

ra

9-S

NP

win

do

wsi

ze(F

ST),

and

by

atle

ast

on

eo

fth

etw

oh

ete

rozy

go

sity

-b

ase

dan

alys

ism

eth

od

olo

gie

s(i

nat

leas

ttw

ob

ree

ds)

:o

bse

rve

dh

ete

rozy

go

sity

,av

era

ge

dfo

ra

9-S

NP

win

do

wsi

ze(O

bsH

tz),

and

reg

ress

ion

anal

ysis

,co

nsi

de

rin

ga

10

-Mb

bra

cke

tsi

ze(R

eg

ress

ion

).* Fo

rR

eg

ress

ion

resu

lts,

this

ind

icat

es

the

clo

sest

mar

ker

toth

eSt

art/

End

po

siti

on

.d

oi:1

0.1

37

1/j

ou

rnal

.po

ne

.00

94

62

3.t

00

4



to predicted overlaps for randomly-positioned CCR, these regions

were highly enriched for candidate dairy-related loci. We discuss

further the CCR regions that meet specific criteria.

Region Identified by all the Three Methods– CCR3 (OAR6:30.367–41.863 Mb). The three analysis

methods identified this region of positive selection in the first

half of OAR6, which includes the ABCG2 (ATP-binding

cassette, sub-family G (white), member 2) and SPP1 (osteo-

pontin) genes (at 36.565–36.610 Mb and 36.708–36.720 Mb

respectively), and is orthologous to the region of the bovine

genome on BTA6 where several QTL for milk production

traits have been reported (See Table 5 for QTL identifier

number in the CattleQTLdb). This region also includes the

FAM13A (family with sequence similarity 13, member A) gene,

which has been shown to be associated with mastitis in Jersey

cows [27]. In dairy cattle, strong selection signals have

previously been identified [23,24] in the proximity of the

ABCG2 gene, which harbors one of the few causal mutations or

Quantitative Trait Nucleotide (QTN) described in livestock

species [28]. In sheep, a selection signal in the ABCG2 region

has also been identified in a work focused on Altamurana

sheep, where differences in allele frequencies were compared

for animals with high and low milk yields [29].

The identification of a selection signature in this region of

OAR6 by the pair-wise FST comparison (FST-CR14) was based on

four breed pairs. For the Milk Lacaune-Australian Poll Merino

and the Comisana-Australian Poll Merino pairs, the signal of

genetic differentiation involved the ABCG2 and SPP1 genes,

whereas for the two other pairs, the identified signal was upstream

(Chios-Sakiz; OAR6:30.367–30.380 Mb) or downstream (Churra-

Ojalada; OAR6:39.316–39.577 Mb) of these genes. The ObsHtz

analysis showed a selection signal (ObsHtz-CR27) for Milk

Lacaune, Comisana and Churra dairy breeds, and also for three

non-dairy breeds, Australian Poll Merino, Meat Lacaune and

Ojalada. Both Lacaune breeds showed low values of ObsHtz

extended for long intervals (3.48 and 5.47 Mb for Milk Lacaune

and Meat Lacaune, respectively). With regard to the regression-

based analysis, this region was the only one detected in multiple

breeds for all three bracket sizes (for Milk Lacaune, Comisana,

Meat Lacaune and Australian Poll Merino breeds).

Together these results suggest that CCR3 shows selection for

dairy traits in several sheep breeds, and that this signal may be

related to the documented effects of the ABCG2 [28] or SPP1 [30]

genes on milk production and lactation regulation, respectively.

The selection signal positioned directly at ABCG2 and SPP1 was

only seen in the highly specialized breeds Milk Lacaune and

Comisana (FST, ObsHtz and Regression). In other dairy breeds for

which the selection is more recent and less efficient (e.g. Churra

and Chios), selection may not have substantially altered the

frequencies of favoured alleles at these loci, which could explain

why a strong selection signal directly at these genes was not

observed. A previous study in Churra sheep found suggestive

associations between the ABCG2 gene and milk fat percentage and

milk yield [31] while no studies to date have tested the effects of

these two genes on dairy traits in the Lacaune and Comisana

breeds.

The results reported in the current study also suggest that in this

region of OAR6 there could be a selection signal related to meat

specialized breeds such as Meat Lacaune, Australian Poll Merino

and Ojalada. In this regard, it is worth noting that several QTL for

growth and carcass traits have been described in the orthologous

bovine region [32,33]. Hence, analogous to the observations in the

orthologous bovine region, this region of the sheep genome may

influence both dairy and meat production traits.

Regions with High FST in more than Two Breed PairsThis criterion was used to highlight the CCR regions where the

genetic differentiation analysis showed a particularly strong

indication of a dairy selection signature, as this is possibly the

most effective analysis performed in this study to detect regions

specifically affected by dairy selection rather than selection acting

on non-dairy-related traits. With the aim of establishing stringent

criteria we consider in this section only those regions where more

than two breed pairs (none sharing a common breed, as explained

above) showed the selection signal. In addition to CCR3 discussed

above, this category also includes the following two regions:

– CCR1 (OAR3:152.680 to 154.679 Mb). This core region,

for which the FST-selection signals were identified for the

Churra-Ojalada, Comisana-Australian Poll Merino and East

Friesian Brown-Finnsheep pairs, includes HMGA2 (high

mobility group AT-hook 2), a gene associated with human

stature [34]. The identification of this gene as a selection target

was also found in an analysis of dogs with divergent stature

[10]. The bovine region orthologous to CCR1 includes QTL

related to stature (with the HMGA2 gene suggested as a possible

causative locus [35]) and rump length (see Table 5). Hence, the

CCR1 signal identified in the present study might indicate

selection targeting sheep body conformation traits. This

hypothesis would agree with the differences in body size

between some of the pairs involved in this selection signal. For

example, the adult weight of Australian Poll Merino is

significantly higher than that of Lacaune and Comisana;

Churra and East Friesian Brown are also generally heavier

than their comparison breeds. HGMA2 has also been suggested

as a candidate gene related to ear size and shape in both pigs

and dogs [36,37], thus further investigation is required to assess

whether there are differences in ear morphology between the

sheep breeds showing this selection signal. Although the

confidence interval of a QTL for protein percentage reported

in Churra sheep [38] (Table 5) overlaps with CCR1, the causal

mutation for that QTL was later found in the LALBA gene

[39], which maps outside of this core region.

– CCR2 (OAR3:209.872–215.814 Mb). Four candidate

genes in the orthologous bovine region to this CCR (distal

end of BTA5) were identified from the Ogorevc et al. [22]

database. Two of them were related to mastitis in a disease-

induced mouse-model study [40]: BID (BH3 interacting

domain death agonist), which is a pro-apoptotic induced gene,

and MAFF (v-maf avian musculoaponeurotic fibrosarcoma

oncogene homolog F), which is related to cell proliferation. The

identification of two other genes as candidates for dairy traits in

this regions, FKBP4 (FK506 binding protein 4) and MLK1

(mixed lineage protein kinase), was also based on mouse model

studies (http://www.informatics.jax.org/). Furthermore,

FKBP4 is expressed in breast cancer tissue (Genes-to-Systems

Breast Cancer database, G2SBC, http://www.itb.cnr.it/

breastcancer//index.html) and MLK1 is expressed in epithelial

tumor cell lines of colonic, breast and esophageal origin [41].

QTL effects described in the bovine region orthologous to

CCR2 (on BTA5) influence milk production and some

conformation traits (Table 5). A previous study in dairy cows

found a selection signature in this region [23]. In that case, the

gene displaying the strongest evidence of selection was CD163,

which is involved in the innate immune response and clearance

of plasma hemoglobin [42]. This region also includes the gene

coding for CSNK1e (casein-kinase epsilon), which is related to



http://www.informatics.jax.org/

http://www.itb.cnr.it/breastcancer//index.html

http://www.itb.cnr.it/breastcancer//index.html

Ta

ble

5.

Co

nve

rge

nce

can

did

ate

reg

ion

s(C

CR

)fo

ro

vin

ed

airy

sele

ctio

nsw

ee

ps

ide

nti

fie

din

this

stu

dy.

Co

nv

erg

en

ceca

nd

ida

tere

gio

ns

Sh

ee

pg

en

om

era

ng

e(M

b)

(Oa

rv

2.0

)

Bo

vin

eg

en

om

era

ng

e(M

b)

(UM

D3

.1)

Fu

nct

ion

al

can

did

ate

ge

ne

sb

ase

do

nO

go

rev

ce

ta

l.[2

2]

Oth

er

can

did

ate

ge

ne

s1Q

TL

de

scri

be

din

she

ep

QT

Ld

esc

rib

ed

inca

ttle

inre

lati

on

tom

ilk

pro

du

ctio

na

nd

fun

ctio

na

ld

air

ytr

ait

s(C

att

leQ

TL

db

ide

nti

fie

r2)

Nb

.o

fp

osi

tio

na

lca

nd

ida

tes3

CC

R1

OA

R3

:15

2.6

80

–1

54

.67

9B

TA

5:4

6.7

20

–4

9.0

09

HM

GA

2M

ilkp

rote

inp

erc

en

tag

e[3

8]

Som

atic

cell

sco

re(2

65

9),

Milk

fat

yie

ld(4

49

5),

Milk

yie

ld(2

42

9),

Ru

mp

len

gth

(34

22

),St

atu

re(1

62

77

,1

62

78

),C

linic

alm

asti

tis

(49

73

)1

1

CC

R2

OA

R3

:20

9.8

72

–2

15

.81

4B

TA

5:1

06

.97

6–

11

2.6

36

BID

,M

AFF

,FK

BP

4,M

KL1

CSN

K1E

Milk

fat

yie

ld(d

aug

hte

rd

evi

atio

n)

(99

95

),M

ilkp

rote

inyi

eld

(dau

gh

ter

de

viat

ion

)(9

99

4),

Milk

fat

pe

rce

nta

ge

(27

17

),C

he

stw

idth

(46

23

),H

iph

eig

ht

(34

20

)

10

0

CC

R3

OA

R6

:30

.36

7–

41

.86

3B

TA

6:3

1.7

10

–4

3.0

22

AB

CG

2,SP

P1

FAM

13A

Milk

pro

tein

pe

rce

nta

ge

(EB

V)

(15

00

2,

15

00

3),

Milk

fat

pe

rce

nta

ge

(17

53

,1

60

57

),M

ilkp

rote

inp

erc

en

tag

e(1

75

5,

99

13

,1

60

58

,1

60

59

),M

ilkp

rote

inyi

eld

(dau

gh

ter

de

viat

ion

)(1

01

45

),M

ilkfa

tyi

eld

(EB

V)

(11

30

3,

12

03

1),

Milk

pro

tein

yie

ld(E

BV

)(1

13

04

),M

ilkyi

eld

(EB

V)

(11

30

2),

Som

atic

cell

sco

re(E

BV

)(6

16

5,

61

64

),M

ilkfa

tty

acid

un

satu

rate

din

de

x(1

15

06

,1

15

08

,1

15

09

,1

15

10

),M

ilkm

yris

tole

icac

idp

erc

en

tag

e(1

15

07

),M

ilkp

alm

ito

leic

acid

pe

rce

nta

ge

(11

50

5),

Te

atp

lace

me

nt

(10

28

5),

Ud

de

rat

tach

me

nt

(10

28

4)

32

CC

R4

OA

R1

3:5

6.0

61

–6

5.8

11

BT

A1

3:5

7.5

72

–6

7.0

05

PO

FUT1

,TF

AP

2C,

FAM

110A

,A

HC

YG

HR

H,

ASI

PM

ilkp

rote

inp

erc

en

tag

e(2

67

2),

Milk

pro

tein

yie

ld(E

BV

)(6

09

0),

Milk

fat

yie

ld(2

55

5),

Milk

pro

tein

yie

ld(d

aug

hte

rd

evi

atio

n)

(10

15

6),

Milk

pro

tein

yie

ld(2

67

1),

Milk

yie

ld(2

67

0),

Ud

de

rat

tach

me

nt

(15

84

),U

dd

er

com

po

site

ind

ex

(15

89

),U

dd

er

de

pth

(15

88

),U

dd

er

he

igh

t(1

58

6),

Ud

de

rw

idth

(15

87

),R

um

pan

gle

(34

29

),Fo

ot

ang

le(1

58

3)

17

2

CC

R5

OA

R1

5:7

2.7

74

–7

4.5

50

BT

A1

5:7

5.1

54

–7

6.8

79

CD

82T

eat

pla

cem

en

t(1

59

5),

Ud

de

rcl

eft

(16

00

),U

dd

er

com

po

site

ind

ex

(16

02

),M

ilkfa

tyi

eld

(45

03

),M

ilkp

rote

inyi

eld

(45

02

),M

ilkp

rote

inyi

eld

(EB

V),

(61

03

),M

ilkfa

tp

erc

en

tag

e(3

45

2),

Milk

pro

tein

pe

rce

nta

ge

(EB

V)

(11

34

5),

Milk

yie

ld(E

BV

)(1

13

46

)

17

CC

R6

OA

R2

2:1

9.5

87

–2

3.1

57

BT

A2

6:2

0.2

86

–2

4.2

26

CH

UK

,SC

DM

ilkfa

tty

acid

com

po

siti

on

[57

,58

],So

mat

icce

llsc

ore

[60

]

Milk

yie

ld(1

04

52

),M

ilkp

rote

inyi

eld

(10

45

4),

Milk

fat

yie

ld(3

63

6),

Milk

pro

tein

yie

ld(3

63

8),

Milk

pro

tein

yie

ld(1

17

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www.biomart.org

circadian rhythms. In a study of the human milk fat globule

transcriptome, CSNK1e was identified as one of the nine core

‘‘clock’’ genes that showed differential expression over a 24-

hour period time in lactating women [43]. Of particular

interest is the finding that this OAR3 region was labelled as a

CCR based on the overlap of candidate regions detected by

pair-wise-FST in the pairs including the most highly specialized

dairy breeds (Milk Lacaune, Comisana and East Friesian

Brown), which may have been under selection for circadian-

related adaptation of milk production to intensive milking.

Other Regions– CCR4 (OAR13:56.061 to 65.811 Mb). Several genes

included in this core candidate region were also found in the

Ogorevc et al. [22] database. The POFUT1 (protein O-

fucosyltransferase 1) gene plays a crucial role in Notch

signaling, which regulates mammary stem cell function and

luminal cell-fate commitment [44]. TFAP2C (transcription

factor AP-2 gamma; activating enhancer binding protein 2

gamma) is involved in mammary development, differentiation,

and oncogenesis playing a critical role in gene regulation in

hormone responsive breast cancer [45], and AHCY (adeno-

sylhomocysteinase) has been suggested as potentially involved

in mastitis defense based on its disease-associated expression

[46]. Another positional candidate gene for this core region is

the GHRH (growth hormone-releasing hormone) gene. Al-

though the direct relationship of this gene and milk production

traits is still not clear [47,48], its link to the somatotropic axis

and other functional candidate genes included in the Ogorevc

et al. [22] database (GH, GHR, GHRHR) suggest a possible

influence, directly or indirectly, on dairy traits. In addition to

these candidate dairy-related genes, the ASIP (Agoutı signaling

protein) gene is also located in this region (OAR13:63.028–

63.033 Mb). This gene has a major role in metabolic processes

[49] and coat colour pigmentation in mammalian species [50].

Based on the known associations between polymorphisms at

this gene and coat colour patterns in sheep [51] it is possible

that the identified selection signal results from coat colour

selection. In their analysis of the complete HapMap dataset,

Kijas et al. [14] also identified a selection signal near ASIP.

– CCR5 (OAR15:72.774–74.550 Mb). This region included

the CD82 (CD82 molecule) gene, which is included in the

Ogorevc et al. [22] database based on its expression in the

mammary gland. This gene is included in the group of genes

that regulate breast cancer metastasis, as a metastasis

suppressor [52]. Whereas no studies have reported an

association of this gene with dairy related traits, there is a

functional relationship between CD82 and ERBB3 (Receptor

tyrosine-protein kinase erbB-3) [53], which is related to normal

mammary development [54].

– CCR6: (OAR22:19.588–23.157 Mb). Two functional can-

didate genes [22] were found in this region: SCD (Stearoyl-CoA

desaturase) and CHUK (conserved helix-loop-helix ubiquitous

kinase). The SCD gene encodes a multifunctional complex

enzyme important in the cellular biosynthesis of fatty acids.

Several studies in different populations of dairy cattle have

reported associations between polymorphisms at this gene with

milk production traits [55] and milk fatty acid composition

[56]. In sheep, the SCD gene has been suggested as positional

and functional candidate gene for a QTL identified on OAR22

in a Sarda 6 Lacaune back-cross population for the ratio of

conjugated linoleic acid to vaccenic acid in sheep milk [57]. A

later study in Churra sheep also identified a QTL on OAR22

for the same trait close to the SCD position, although various

analyses questioned this gene as responsible for the identified

effect [58]. The CHUK gene is listed in the Ogorevc et al. [22]

database because it is expressed in breast cancer tumors and is

a regulator of mammary epithelial proliferation [59]. Accord-

ing to the SheepQTL database, this region includes a QTL for

somatic cell score described in an Awassi x Merino cross

population [60] and it has also been identified as a selection

signal by the analysis of allele frequency differences between

animals with divergent milk yields reported in Altamurana

sheep [29].

The bovine region orthologous to CCR6 (on BTA26), overlaps

with a region showing a selection signature in dairy cattle [23],

where the C10ORF76 (chromosome 10 open reading frame 76)

gene was associated with the strongest selection signal. Although

there is not a reported association of this gene with milk

production traits, it is expressed in the mammary gland and it is

altered in breast cancer cells, based on the G2SBC database.

Inconsistencies between this Study and Previous QTLand Selection Mapping Studies of Cattle and Sheep

Although all six CCR overlapped with QTL for dairy traits in

sheep or cattle (Table 4 and discussed above), our study did not

identify a selection signal close to several genes previously

associated with dairy traits in sheep and cattle. For example,

there were no CCR near the LALBA (alpha-lactalbumin) gene

(OAR3:137 Mb), where a particular variant has been recently

been proposed to explain a QTL for milk protein percentage

identified in Churra sheep [39]. The lack of signal near this QTL

in the FST analysis of Churra vs Ojalada is consistent with the fact

that the causative mutation is still segregating in Churra, which

allowed its identification as QTL.

In addition, in their analysis of the complete Sheep HapMap

dataset, Kijas et al. [14] reported positive selection surrounding

the PRLR gene, which is associated with milk traits in dairy cattle

[61]. In our study, although none of the CCRs map to OAR16,

where this gene is located (39.250–39.284 Mb), it is worth

mentioning that this gene is included in the interval of FST-

CR27 (OAR16:37.347–40.850 Mb), which was identified based

on the signals detected in three breed pairs involving the most

specialized dairy breeds in this study (East Friesian Brown-

Finnsheep, Milk Lacaune-Australian Poll Merino and Comisana-

Australian Poll Merino) but was not classified a CCR due to the

lack of selection signals from the heterozygosity-based methods.

Other regions that were detected by the FST-pairwise comparison

for many breed pairs but that were not supported by the

heterozygosity-based methods were found on OAR2 (FST-

CR2:52.346–53.409 Mb) and OAR9 (57.363–60.849 Mb).

Whereas the first region does not include any functional candidate

gene for dairy traits, the region in OAR9 included three genes

related to the metabolism of fatty acids (FABP4, FABP5 and

FABP9). FABP4 and FABP5 have been shown to be highly

expressed in the mammary gland during lactation [62] and

significant associations have been found between FABP4 and fatty

acid composition of bovine milk [63]. We acknowledge that one or

more of these regions may represent false negatives that were

missed by our stringent selection signal criteria. However, because

of the difficulty in linking a sweep signal to a given phenotype, we

suggest that application of stringent criteria in this type of study is

an appropriate option to avoid reporting long lists of candidate

regions based on spurious results.

We also did not find evidence of selection on some major

candidate genes for milk production for which selection signatures

have been observed in cattle (e.g. DGAT1: OAR9:13.534–

13,543 Mb; GHR: OAR16:32.068–32.231). In contrast to our



results, the GHR gene (BTA20) showed the largest difference in

sliding window average allele frequencies in a study of divergent

selection between dairy and beef cattle [24], and also showed

significant extended haplotype homozygosity [25]. With regard to

DGAT1, evidence of selection has also been identified when

comparing dairy and beef cattle breeds [24].

In their study, Kijas et al. [14] also identified a strong selection

signal on OAR10, associated to the presence or absence of horns

and close to the gene responsible of the polled phenotype, RXFP2

(relaxin/insulin-like family peptide receptor 2) gene

(OAR10:27.602–27.646 Mb). In our study, a selection signal was

identified in this region based on the ObsHtz-based method

(ObsHtz-CR33:24.856–27.897 Mb, for the dairy breeds Comi-

sana, Churra and Milk Lacaune) and the FST-based method

(OAR10:25.540–28.983 Mb). However because the FST signal

was due only to the two breed pairs involving the Australian Poll

Merino, this was not labelled as FST-CR.

Apart from the overlap between two CCRs (CCR3 on OAR6

and CCR6 on OAR22) with the selection signals identified in

Altamurana sheep for milk yield [29], we did not find evidence of

selection near the signals reported for this Italian breed. This lack

of correspondence may derive from breed-specific signals reported

for Altamurana.

Comparison of the Three Selection Mapping MethodsFrom our point of view, the analysis method that involved the

estimation of pair-wise FST for pairs of related breeds showing

divergent specialization (one for milk production, one not) should

be the most powerful analysis in terms of identifying selection

specifically related to dairy production. Four out of the 28

candidate regions showing multiple pair-wise FST signals were

detected in four out of the six breed pairs (FST-CR3, FST-CR9,

FST-CR14 and FST-CR18). Of these, FST-CR3 (OAR2:52.346–

53.409 Mb) was not included as a CCR due to the lack of

consistency with the ObsHtz or 10-Mb Regression analysis results,

although the same region was identified by the 5-Mb Regression

analysis (RegBrack5-CR1 in Table 3) in two dairy breeds (Churra

and Chios) and one non-dairy breed (Ojalada). Given that no

functional candidate genes from the Ogorevc et al. [22] database

were found in the orthologous bovine region, it is possible that this

region underlies breed differentiation not directly related to dairy

traits.

Among the 55 candidate regions identified based on the

ObsHtz analysis (ObsHtz-CRs, Table S2), there were only twelve

regions showing a signal in dairy but not in non-dairy breeds

(ObsHtz-CR3, 7, 8, 10, 12, 25, 28, 29, 31, 41, 45 and 55).

Considering that the background genome has been previously

selected for meat, maternal characteristics, and other traits,

whereas the development of dairy breeds is much more recent,

it would be expected that the selection signals specifically related to

dairy traits would not be seen in the other breeds (although Meat

Lacaune could be an exception). However, as none of these

regions showing a reduction of heterozygosity exclusively in dairy

breeds were identified by the FST-based method, they were not

identified as final core CCRs (and thus are not present in Table 4).

Although the evidence linking these regions to dairy-related

selection is weaker than for the CCRs, we performed an additional

search for functional candidate genes and dairy-related QTL

mapping within these regions, similar to that performed in the

eight identified CCRs (see Table S4). A total of 118 genes were

extracted from the orthologous bovine regions of these eleven

dairy-breed-limited regions of reduced heterozygosity (data not

shown). Among them, only the HSPD1 (Heat shock 60 kDa

protein 1; chaperonin) gene is included in the Ogorevc et al. [22]

database, due to its expression in the mammary gland. This gene is

also included in the G2SBC database although no studies have

reported so far its association with milk production traits.

Interestingly, among the dairy QTL detected in these regions

there is greater overlap with ovine QTL for milk production traits

(Table S4) than for the list of core CCRs. Hence, these regions

identified exclusively by ObsHtz could include gene variants

occurring in individual dairy breeds, as it is the case for many of

the QTL described in sheep.

There were eight regions that overlapped between those

identified by FST (including a full set of regions, including those

that contained pairs with the same breeds that were removed from

Table S1) and ObsHtz (out of 35 and 55, respectively). The

explanation for the higher number of regions identified by ObsHz

is that the regions identified using FST were slightly larger

(incorporated more windows) than those identified using ObsHtz.

There were far fewer signals identified using the Regression

approach than either FST or ObsHtz. Although the top (or bottom)

0.5th percent results were considered as signals of selection for all

methods, the Regression method first filtered out the intervals with

non-significant and non-asymptotic regression patterns, and thus

the total number of eligible intervals was substantially reduced

compared to the other approaches in which the distribution of

FST/ObsHtz values for all markers (with the exception of those on

the very ends of the chromosomes) was considered. Thus the

implementation of Regression in this study was more stringent

than the other methods.

The regions identified by the Regression method showed

greater overlap with ObsHtz than FST, which is not surprising

since both Regression and ObsHtz are designed to detect regions

with a reduction in diversity. For the 10-Mb bracket size (results

considered for the identification of CCR), all three regions

identified with the Regression approach overlapped with those

identified with ObsHtz while one out of the three, RegBrack10-

CR2, overlapped with the regions identified with FST, and was

therefore considered as CCR (CCR3).

Conclusions

The results reported here provide a genome-wide map of

selection signatures in the dairy sheep genome. The six core

candidate regions identified are likely to influence traits of

economic interest in dairy sheep production and can be

considered as starting points for future studies aimed at the

identification of the causal genetic variation underlying these

signals. For some of these regions, strong candidate genes have

been proposed (e.g. ABCG2, SPP1), whereas some other genes

designated as candidates based on their association with sheep and

cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a

detectable sweep signal. Discrepancies between selection signals in

dairy sheep and cattle may be explained either by statistical or

biological factors, such as the limited statistical power of the

analyses to identify effects of small magnitude or the fact that the

genetic architecture of milk production and dairy-related traits

substantially differs from sheep to cattle and also between the

different breeds of dairy sheep, which have been subjected to

different levels of selection pressure. Many of the identified regions

corresponded to orthologous regions in cattle where QTL for

dairy traits have been identified. Due to the limited number of

QTL studies reported in sheep compared with cattle, the results

illustrate the potential value of the study of selection signatures to

uncover mutations with potential effects on quantitative dairy

sheep traits. Additional studies are needed to confirm and refine

the results reported here. To this end, the recent availability of the



high-density ovine chip (700 K) will provide a valuable tool to

perform more powerful and precise selection mapping studies.

Supporting Information

Table S1 Candidate regions for signatures of selection identified

on the basis of the pair-wise FST analysis.

(PDF)

Table S2 Candidate regions identified based on reduced

heterozygosity signals identified in at least two of the dairy breeds.

(PDF)

Table S3 List of all genes from the orthologous bovine genome

regions corresponding to the six convergence candidate regions

(CCR) for dairy selection sweeps identified in this study, extracted

using the Biomart tool (http://www.biomart.org/).

(XLSX)

Table S4 Candidate regions identified by the analysis based on

observed heterozygosity (ObsHtz-CR), averaged in sliding win-

dows of 9 SNPs (ObsHtz-9SNPW), that were exclusively detected

in dairy breeds.

(PDF)

File S1 Summary of the criteria for selection of breedsto be included in the study, including the results of aPrincipal Component Analysis (PCA) performed with theinitial set of breeds considered.

(PDF)

File S2 Summary of the results of the analysis per-formed in this work in relation to the myostatin (GDF-8)gene region. These results were evaluated to establish criteria for

the analyses performed to detect dairy selection signatures in the

dairy breeds.

(PDF)

Acknowledgments

We thank Samantha Wilkinson for providing R scripts.

Author Contributions

Conceived and designed the experiments: BGG PW JJA. Analyzed the

data: BGG PW. Contributed reagents/materials/analysis tools: RPW JJA

EGG JK. Wrote the paper: BGG PW JJA RPW JK. Conceived the study:

BGG PW.

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1

File S1 for Application of selection mapping to identify genomic regions

associated with dairy production in sheep

Authors: Beatriz Gutiérrez-Gil1*, Juan Jose Arranz1, Ricardo Pong-Wong2, Elsa García-

Gámez1, James Kijas3, Pamela Wiener2

File S1. Summary of the criteria for selection of breeds to be included in the study,

including the results of a Principal component analysis (PCA) performed with the initial set

of breeds considered.

Selection of breeds for analysis

From the breeds analysed in the SheepHapMap project [1], a group of five European breeds

was selected to be analysed as “dairy group” in the present study: Chios, Chura, Comisana,

East Friesian Brown and Milk Lacaune (Table 1). This group included breeds showing

different levels of dairy specialization (See Supporting Table 1 for additional breed

information) with some highly-specialized dairy breeds such as East Friesian Brown and

Milk Lacaune, and some others for which official dairy breeding improvement is more

recent.

With the aim of providing an appropriate comparison set that could help identify the

selection signals specifically related to dairy selection, we selected another group of non-

dairy breeds to be included in the study. The initial selection of the non-dairy breeds was

2

based on the estimated divergence time between ovine breeds reported by Kijas et al. [1]

from the extent of haplotype sharing that persists at increasing physical distances between

SNP pairs (Supporting Information Figure S10 and Figure 3 of Kijas et al. [1]), choosing,

for each dairy breed, the most closely related non-dairy breed to which it could be

compared. Based on this, a group of six non-dairy breeds were selected, including both

meat-specialized breeds and also breeds that have not been under specific selection pressure

(i.e. traditional triple purpose breeds). For one of the dairy breeds, EastFriesianBrown, two

potential comparison non-dairy breeds (Finnsheep and Scottish Texel) were initially

investigated (Table 1). For the Milk Lacaune, in addition to a meat-specialized breed, the

Australian Poll Merino, the Meat Lacaune variety was also considered for comparison. The

Australian Poll Merino was also selected as comparative breed for the (dairy) Italian

Comisana breed. The estimated divergence times between the initially selected pairs ranged

from 80-160 generations (Milk Lacaune vs Meat Lacaune pair) and 480-560 (East Friesian

Brown vs Finnsheep pair) [1].

The initial selection of non-dairy breeds was refined based on the results of a Principal

Component Analysis (PCA) of allele sharing performed using smartpca implemented in

Eigensoft [2] for the total list of breeds included in Table 1. Due to differences in the

number of samples available for each breed, we selected 22 samples for each breed (the

maximum number available for all selected breeds) to performed an N-balanced PCA

analysis. This analysis helped to determine the clustering pattern within the initial selected

dataset and, in conjunction with the haplotype similarities previously described [1], was

used to choose related dairy and non-dairy breed pairs for subsequent genetic

differentiation analysis.

3

This PCA analysis also included the Galway and Border Leicester breeds for comparison

with the Scottish Texel breed in the pair-wise FST analysis of the myostatin gene region as a

test case of a gene known to be under selection. According to Kijas et al. [1], these two

breeds showed the closest phylogenetic relationship with Scottish Texel based on the extent

of haplotype sharing (80-160 generations of divergence) and neither is known to carry the

allele associated with muscle hypertrophy.

From this analysis, the proportion of variance explained by each component was obtained

by dividing the eigenvalue corresponding to each component by the sum of all eigenvalues

identified (for a total of 20 PC estimated).

Population structure analysis and selection of dairy and non-dairy breed pairs

The results of the PCA of allele sharing were plotted to show direct comparison of

Principal Component 1 (PC1) against PC2 to PC5 (Supporting Figure S1). The two largest

principal components (A) separated four differentiated clusters related to the geographical

groups represented in the initial selected dataset: the mainland Mediterranean breeds

(Lacaunes, Churra, Ojalada, Australian Poll Merino and Comisana), the island

Mediterranean breeds (Chios, Sakiz and Cyprus Fat Tail), the mainland NorthEuropean

breeds (Finnsheep and East Frisian Brown) and the island NorthEuropean breeds (Scottish

Texel, Galway and Border Leicester). Based on this clustering, the Finnsheep was selected

as the comparison breed for East Friesian Brown for subsequent analyses, rather than

Scottish Texel.

The Australian Poll Merino showed a close relationship with all the other mainland

Mediterranean breeds, and therefore was considered as the non-dairy breed to compare with

4

Milk Lacaune and Comisana, while the two Spanish breeds, Churra (dairy) - Ojalada (non-

dairy), and the Mediterranean island breeds, Chios (dairy) - Sakiz (non-dairy), were

considered as pairs. Also based on the PCA analysis, the Scottish Texel-Galway pair was

selected for the pair-wise FST comparison for test-case control region selected in this study

(myostatin), as these two breeds showed a closer relationship than that observed between

the Scottish Texel and Border Leicester.

Based on this analysis, PC1 explained 18.93% of the genotypic variance, PC2 and PC3

explained 11.79% and 10.36% respectively, and PC4 and PC5 explained from 7.89% and

6.06% of the variance.

5

Figure S1: Clustering of animals based on principal component analysis of allele

sharing for the initial selected breed dataset.

Individual animals from the initial selected breeds to include in the study are plotted for

principal component (PC) 1 vs PC2 (A), for PC1 vs PC3 (B), for PC1 vs PC4 (C) and for te

PCA1 vs PC5 (D). Individuals from different breeds are shown using different colored

symbols as indicated in the legend.

6

References

1. Kijas JW, Lenstra JA, Hayes B, Boitard S, Porto Neto LR, et al. (2012) Genome-

wide analysis of the world's sheep breeds reveals high levels of historic mixture and

strong recent selection. PLoS Biol 10: e1001258.

2. Patterson N, Price AL, Reich D. (2006) Population structure and eigenanalysis.

PLoS Genet 2: e190.

1

File S2 for Application of selection mapping to identify genomic regions




File S2: Summary of the results of the analysis performed in this work in relation to the

myostatin (GDF-8) gene region. These results were evaluated to establish criteria for the

analyses performed to detect dairy selection signatures in the dairy breeds analysed.

Methods: Test Case Analysis: Myostatin (GDF-8) Gene Region The myostatin gene (GDF-8), variation at which is associated with muscle hypertrophy in the

Belgian Texel breed [1] and other related sheep breeds [2], was considered as a test case to

assess the ability of the different analyses to detect genomic regions that have been subject to

selection pressure. This region was also used to evaluate the influence of parameters used for

the analyses implemented in this study. Kijas et al. [3] showed that a selection signature in

the GDF-8 gene region could be identified in three geographically distinct populations of

Texel, including the Scottish Texel, which was considered as the reference breed for this test

case assessment.

Based on the PCA analysis described in Supporting Information File 1, the Scottish Texel

breed was compared to the Galway breed in the pair-wise FST analysis. Regions of low

observed heterozygosity were also assessed for the Scottish Texel breed following the

2

methods described for the dairy and non-dairy breeds in the Selection sweep mapping

analysis methods section of the main text of the manuscript. These analyses were

implemented across the whole genome using sliding windows of 9-, 13- and 17- SNPs and

the results obtained near the GDF-8 gene (OAR2: 118.573 – 118.579 Mb) were evaluated to

establish criteria for the analyses performed to detect dairy selection signatures. The results

of the regression analysis for detection of regions with asymptotic heterozygosity patterns

performed in the Scottish Texel breed, which was performed as described in the Selection

sweep mapping analysis methods section of the main text of the manuscript, for the three

tested bracket sizes (5, 10 and 20 Mbp) were also assessed for chromosome OAR2, in

relation to the position of the GDF-8 gene.

Results: Mapping accuracy of GDF-8 and setting of criteria for further analyses

Differentiation: For two of the window sizes (9- and 17-SNP) used to obtain the averaged FST

for the Scottish Texel-Galway pair, the top result genome-wide was found in the OAR2

region carrying the GDF-8 gene, whereas for the 13-SNP window the top position was found

on OAR7 (33.45 Mb). The top location for the 9-SNP window size (at 115.28 Mb) was much

closer to the actual position of GDF-8 (118.57 Mb) than seen for the case of the 17-SNP

window size (top position at 113.25 Mb). Based on these results, a 9-SNP window size was

selected to calculate the average pair-wise FST values for the dairy vs non-dairy breed pairs.

Furthermore, the distribution of identified positions near GDF-8 was considered to determine

the criteria to define a single selection signal. Among positions on OAR2 that were in the top

0.5 percent of the 9-SNP window FST (FST-9SNPW) values for the Scottish-Texel-Galway

pair, 55 of 68 of them were found between 109.62 Mb and 122.62 Mb, with inter-marker

distances less than or equal to 1.97 Mb (Supporting Figure S2a). The gaps flanking the

3

upstream and downstream positions to this interval of extreme genetic differentiation were

42.49 and 5.04 Mb respectively. Between the positions identified at 116.21 and 118.12 Mb,

there was a gap of 1.91 Mb where no highly differentiated markers were detected. Based on

these observations, the distance of 2 Mb was considered as the maximum interval between

markers defining a single FST-based selection signal.

Reduced heterozygosity: In the Scottish Texel breed there was a region of decreased

heterozygosity near the GDF-8 gene detected with the three SNP window sizes tested. This

region showed the lowest values of ObsHtz for 13 and 17-SNP window sizes, whereas the

lowest value for the 9-SNP window size was found on OAR19, (0.047) followed by the

signal around the myostatin region (0.056). For the three tested window sizes, decreased

heterozygosity regions encompassed continuous markers positions on OAR2. The following

regions included gaps up to 2.00 Mb: 108.88-119.51 Mb for Htz-9SNPW, 108.89-123.64 for

Htz-13SNPW and 108.96-123.66 for Htz-13SNPW, all of which included GDF-8 (118.573-

118.579 Mb), such that the length of the low heterozogosity region increased with the

window size. As the region of continuous low heterozygosity was smallest, the 9-SNP

window size was selected to calculate the reduced diversity in the dairy and non-dairy breeds

included in our study. The continuous region identified by Htz-9SNPW values near GDF-8

(108.88-119.51 Mb) was flanked by gaps of 4.37 and 2.92 Mb long. Within that continuous

region the maximum intermarker distance was 1.99 Mb upstream and 1.94 Mb downstream

of the positions 111.39 and 113.77 Mb, respectively (Supporting Figure S2b). Hence, for this

method up to a 2 Mb interval was again allowed within a region defined on the basis of the

reduced heterozygosity values.

Asymptotic heterozygosity pattern: In the regression analysis for detection of regions with

asymptotic heterozygosity patterns performed in the Scottish Texel breed, the GDF-8 region

had the highest –log(p) values across the whole genome for the two larger brackets, 10 and

4

20 Mbp, whereas for the 5 Mb-bracket, a region on OAR4 yielded the highest –log(p) value.

The top position in the 10 Mb-bracket analysis (118.0598 Mb) was closest to the location of

the GDF-8 gene (Supporting Figure S2c). Based on this, results obtained with the 10 Mb-

bracket for the dairy breeds were used for comparison with those obtained using genetic

differentiation and observed heterozygosity. Although the gaps between identified positions

within continuous regions were smaller than for the other methods, for consistency with the

other two analyses, the same criterion was used (maximum distance between identified

positions of 2 Mb) to determine candidate regions based on the asymptotic heterozygosity

pattern.

Figure S2: Identification of the selection signature related to the GDF-8 gene in OAR2

through the analysis of the Scottish Texel sheep breed following the three methodologies

used in this work. I) Across-genome signals. a) Genome-wide distribution of FST values

averaged in sliding windows of 9 SNPs (FST-9SNPW) obtained for the Scottish Texel-

Galway breed pair. b) Genome-wide distribution of observed heterozygosity (ObsHtz) values

averaged in sliding windows of 9 SNPs (ObsHtz-9SNPW) estimated for the Scottish Texel

breed. c) Genome-wide distribution of –log(p) values resulting from the regression analysis

for detection of regions with asymptotic heterozygosity patterns performed in the Scottish

Texel breed and considering all markers within 10 Mb of this position (10 Mb-bracket size).

II) Plots of the 75-150 Mb region of OAR2 with details of the selection signature

identified in the region of the GDF-8 gene by the three considered methodologies: d)

ObsHtz-9SNPW; e) ObsHtz-9SNPW; f) Regression_10Mb-bracket size. The position of the

GDF-8 gene (OAR2: 118.573 – 118.579 Mb; v2.0) is indicated with a green arrow in the x-

axis. The maker or position associated with the top or bottom value of the distribution is

indicated in brown colour, whereas other markers are indicated in blue colour.

5

I)

6

II) d)

e)

f)

7

REFERENCES

1. Clop A, Marcq F, Takeda H, Pirottin D, Tordoir X, et al. (2006) A mutation creating a

potential illegitimate microRNA target site in the myostatin gene affects muscularity

in sheep. Nat Genet 38: 813-818.

2. Bignell CW, Malau-Aduli AE, Nichols PD, McCulloch R, Kijas JW (2010) East

Friesian sheep carry a Myostatin allele known to cause muscle hypertrophy in other

breeds. Anim Genet 41: 445-446.

3. Kijas JW, Lenstra JA, Hayes B, Boitard S, Porto Neto LR, et al. (2012). Genome-

wide analysis of the world's sheep breeds reveals high levels of historic mixture and

strong recent selection. PLoS Biol 10: e1001258.

Table S1 for

Application of selection mapping to identify genomic regions




Table S1. Candidate regions for signatures of selection identified on the basis of the

pairwise FST analysis performed on six dairy–non-dairy breed pairs. For each dairy-non-

dairy breed pair, the results contain the top 0.5th percent of the distributions of FST values,

averaged in sliding windows of 9 SNPs. Only the regions that were found in at least two

pairs of breeds (that did not have a breed in common) were labeled as FST-based

candidate regions (FST-CRs). Gaps up to 2 Mb were allowed between positions identified

within the same breed pair and between different breed pairs to consider a single selection

signal. Positions of the markers (Mb) are referred to the Sheep Genome Assembly v2.0

(update September 2011).

Fst‐Candidate region

(Fst‐CR) Chr Breed Pair Start marker Start position (Mb) End marker End position (Mb)

Fst‐CR1 1 Churra‐Ojalada OAR1_110170625 102.467714 s70081 102.594066

Comisana‐Australian Poll Merino OAR1_112076929 104.214069 OAR1_112239116 104.372893

Chios‐Sakiz s11941 105.338083 OAR1_113402761 105.563436

Fst‐CR2 1 Milk Lacaune‐Meat Lacaune OAR1_245302998 228.057561 OAR1_247070566 229.569756

East Friesian Brown‐Finnsheep OAR1_245583569 228.280721 OAR1_249572898 231.993714

Fst‐CR3 2 Churra‐Ojalada s60207 52.34599 OAR2_55861669 52.563013

Milk Lacaune‐Meat Lacaune OAR2_55752685 52.4461

Comisana‐Australian Poll Merino OAR2_56432170 52.885699

Chios‐Sakiz OAR2_56768579 53.239006 s23499 53.409079

Fst‐CR4 2 Comisana‐Australian Poll Merino OAR2_87854424 83.150938 OAR2_90110357 85.329228

Chios‐Sakiz OAR2_87942973 83.248507

Fst‐CR5 3 East Friesian Brown‐Finnsheep s65219 18.951292 s05622 19.360373

Milk Lacaune‐Australian Poll Merino s13092 19.188714 s05622 19.360373

Fst‐CR6 3 East Friesian Brown‐Finnsheep OAR3_84348827 79.410427

Chios‐Sakiz s63332 79.545868 OAR3_84689579 79.728228




Fst‐CR8 3 East Friesian Brown‐Finnsheep OAR3_180416904 167.711074 OAR3_180484085 167.782385

Milk Lacaune‐Australian Poll Merino OAR3_180416904 167.711074 OAR3_180647061 167.92624

Fst‐CR9 3 Milk Lacaune‐Meat Lacaune s34668 209.872091 s08021 210.525298

Milk Lacaune‐Australian Poll Merino s14713 211.970434 s36662 212.063962

Comisana‐Australian Poll Merino s26777 213.468361 s38745 213.645308

East Friesian Brown‐Finnsheep s68727 215.304893 OAR3_234328134_X 215.814066

Fst‐CR10 4 Chios‐Sakiz OAR4_59113372 55.121399

Milk Lacaune‐Meat Lacaune s04516 55.485954 s32998 55.645159

Fst‐CR11 4 Chios‐Sakiz s64477 72.568414 OAR4_79957476 74.701765

East Friesian Brown‐Finnsheep s12823 74.234142

Fst‐CR12 4 Milk Lacaune‐Meat Lacaune OAR4_85593968 80.007532 OAR4_90286613_X 84.344311


Fst‐CR13 4 Milk Lacaune‐Australian Poll Merino OAR4_102186070 95.801069 OAR4_102504729 96.11515

Milk Lacaune‐Meat Lacaune OAR4_102230122 95.85043 OAR4_102402825 96.019593

Churra‐Ojalada s44110 97.181846

Fst‐CR14 6 Chios‐Sakiz OAR6_34086500 30.366856 OAR6_34099005 30.37978

Milk Lacaune‐Australian Poll Merino OAR6_34609120 30.760292 OAR6_43064935 38.243473


Churra‐Ojalada OAR6_43842580 39.316435 OAR6_44210019 39.577446

Fst‐CR15 6 Comisana‐Australian Poll Merino OAR6_76284920 69.987431 s13781 70.599139

Chios‐Sakiz OAR6_78103269 71.885158


East Friesian Brown‐Finnsheep OAR7_57594015 52.07214

Fst‐CR17 8 East Friesian Brown‐Finnsheep OAR8_34133754 31.505215 s50528 32.978156

Churra‐Ojalada s50528 32.978156 OAR8_35827974 33.178871

Fst‐CR18 9 Milk Lacaune‐Meat Lacaune OAR9_60243687 57.362506

Chios‐Sakiz s71892 59.029356

Milk Lacaune‐Australian Poll Merino s13022 60.567978 OAR9_63903278 60.821175

Comisana‐Australian Poll Merino s57864 60.609845 OAR9_63720685 60.628768

Churra‐Ojalada OAR9_63928272 60.846404

Fst‐CR19 9 Chios‐Sakiz OAR9_72753560 68.819131


Churra‐Ojalada OAR9_73519625 69.587011 s46550 69.830122

Fst‐CR20 10 Churra‐Ojalada OAR10_38873282 36.309562 OAR10_39526423_X 36.868674


Fst‐CR21 11 Milk Lacaune‐Meat Lacaune s43916 33.918454 s37019 36.506595

Milk Lacaune‐Australian Poll Merino OAR11_36358079 34.118663 s33971 34.163747

Chios‐Sakiz OAR11_37440114 35.253844

Fst‐CR22 12 Milk Lacaune‐Australian Poll Merino OAR12_8518601 6.113085 s02824 6.314395

Churra‐Ojalada OAR12_10315606 7.84721 OAR12_10373193 7.894632

Fst‐CR23 13 Milk Lacaune‐Meat Lacaune s27419 48.971612 OAR13_56607666 52.062577


Milk Lacaune‐Australian Poll Merino s67173 52.777853 OAR13_57596022 52.946055

Fst‐CR24 13 Comisana‐Australian Poll Merino s48133 62.276683 OAR13_71091738 65.811237

Churra‐Ojalada OAR13_69221369_X 63.911086 s17594 64.053077


East Friesian Brown‐Finnsheep s28843 21.72601

Fst‐CR26 15 Comisana.vs.AustralianPollMerino s31340 72.774077 s73092 72.88226

Chios.vs.Sakiz OAR15_80448054 74.499334 s72518 74.550363

Fst‐CR27 16 East Friesian Brown‐Finnsheep OAR16_40313142 37.347459 OAR16_44102697 40.850203

Milk Lacaune‐Australian Poll Merino OAR16_42131900 39.068289 s15191 39.263122



East Friesian Brown‐Finnsheep OAR22_26951573 22.959209 s67752 23.157094

Table S2 for





Table S2. Candidate regions identified based on reduced heterozygosity signals identified

in at least two of the analyzed dairy breeds. Non-dairy breeds showing a coincident

reduced heterozygosity signal are also indicated. For each breed, the results contain the

bottom 0.5th percent of the distributions of observed heterozygosity values, averaged in

sliding windows of 9 SNPs. Only the regions that were found in at least two dairy breeds

were labeled as candidate regions based on the reduction of observed heterozygosity

(ObsHtz-CRs). Gaps up to 2 Mb were allowed between positions identified within the same

breed and between different breeds to consider a single selection signal. Positions of the

markers (Mb) are referred to the Sheep Genome Assembly v2.0 (update September

2011).

ObsHtz‐Candidate region Chr Dairy breeds Non‐dairy breeds

(ObsHtz‐CR) Breeds Start marker Start position (Mb) End marker End position (Mb) Breeds Start marker Start position (Mb) End marker End position (Mb)

Obs_Htz1 1 Milk Lacaune OAR1_137761966 127.147272 OAR1_137785444 127.181978 Finnsheep OAR1_138135147 127.487148 s13122 127.757038

Churra OAR1_138170073 127.525829 OAR1_138302052 127.655271

Obs_Htz2 1 Comisana s43775 191.715311 s28201 191.726576 Australian Poll Merino s03519 191.732813

Chios s73989 191.896602 OAR1_207015625_X 191.993294

Obs_Htz3 2 Comisana OAR2_20411070 20.132217 OAR2_20557855 20.27409

Churra OAR2_20494849 20.200641

Obs_Htz4 2 Comisana OAR2_76331680 72.044265 OAR2_79499240 75.030746 Finnsheep OAR2_75832730 71.577808 OAR2_75908169 71.612583

East Frisian Brown OAR2_77962229 73.59807 OAR2_78106813 73.747233 Meat Lacaune OAR2_77568893 73.183462 OAR2_77690140 73.288963

Australian Poll Merino OAR2_77705450 73.305483 s59857 73.888851

Obs_Htz5 2 Milk Lacaune s41033 104.332992 OAR2_111932274 104.586592 Meat Lacaune s41033 104.332992 OAR2_111932274 104.586592

Churra s22902 104.395536 s67874 104.642351 Finnsheep s22902 104.395536 s67874 104.642351

Ojalada s22902 104.395536 s29891 104.501488

Australian Poll Merino s29891 104.501488

Obs_Htz6 2 Churra OAR2_130265015 122.212699 OAR2_130817865 122.86725 Ojalada OAR2_130413374 122.472584 OAR2_130656808 122.697031

Milk Lacaune OAR2_130413374 122.472584 OAR2_130656808 122.697031

Comisana s18930 122.622313 s46322 123.095079

Chios OAR2_130656808 122.697031 OAR2_131507986 123.721808

Obs_Htz7 2 East Frisian Brown OAR2_190455427 180.309886 OAR2_192112657 181.952078

Churra OAR2_193567149 183.403726

Obs_Htz8 2 Chios OAR2_210373144 199.479344 OAR2_210391244 199.493856

Milk Lacaune s70318 199.813655

Obs_Htz9 2 Chios OAR2_222355235 211.20491 Ojalada OAR2_222327692 211.177754

Comisana OAR2_222355235 211.20491 Australian Poll Merino OAR2_222518452 211.36389

Obs_Htz10 2 Milk Lacaune OAR2_244597797 232.586994 OAR2_244925652 232.809436

Churra s01478 234.42203 OAR2_246577997 234.454459

Obs_Htz11 2 Churra OAR2_252085914 239.683321 s04809 241.810875 Meat Lacaune OAR2_252367108 239.948483 s00772 241.977125

Comisana s68726 241.681223 s72745 241.755749 Australian Poll Merino s58181 240.928078 s04809 241.810875

Milk Lacaune s68726 241.681223 s64586 241.79047 Finnsheep s10651 241.717335

Ojalada s10651 241.717335 s43939 241.929821

Obs_Htz12 3 Churra s46658 18.647955

Milk Lacaune s46658 18.647955 s00385 18.858614

Obs_Htz13 3 Milk Lacaune OAR3_34159096 31.475728 s67270 32.053944 Meat Lacaune OAR3_34159096 31.475728 OAR3_34470839 31.786813

East Frisian Brown OAR3_34209284 31.520076 s67270 32.053944 Ojalada OAR3_34209284 31.520076

Comisana OAR3_34470839 31.786813 s67270 32.053944 Finnsheep OAR3_35192406 32.520276

Obs_Htz14 3 Milk Lacaune OAR3_79812234 75.12407 s52383 75.334539 Finnsheep s40967 75.200035

Chios s40967 75.200035 OAR3_79936157 75.239426

Churra s40967 75.200035 OAR3_80038014_X 75.340524

Obs_Htz15 3 Comisana OAR3_127437500 119.375297 OAR3_127719431 119.73187 Ojalada OAR3_128558246 120.420761

Chios s70128 119.623504 s70128 119.623504

East Frisian Brown OAR3_127924329_X 119.921829 OAR3_127956387_X 119.9636

Obs_Htz16 3 East Frisian Brown OAR3_134591031 125.994367 OAR3_134708445 126.116303 Ojalada OAR3_132722549 124.350223 OAR3_132876525 124.473799

Chios OAR3_134841132 126.252978

Obs_Htz17 3 Comisana s26177 153.950444 OAR3_165549468_X 154.679398 Meat Lacaune OAR3_165050963 154.197278 OAR3_165060142 154.207199

Milk Lacaune OAR3_165060142 154.207199 OAR3_165200988 154.347363 Sakiz OAR3_165050963 154.197278 OAR3_166244306 155.291702

Obs_Htz18 3 Churra s75549 163.340446 s28012 163.447575 Sakiz s35593 162.838475 s03123 163.200412

Milk Lacaune OAR3_175355785 163.685017 Finnsheep OAR3_174446873 163.148256

Meat Lacaune OAR3_175355785 163.685017

Obs_Htz19 3 Churra OAR3_181499831 168.655327 OAR3_181815353 168.958984 Australian Poll Merino OAR3_181535066 168.688319 OAR3_181815353 168.958984

Milk Lacaune OAR3_181499831 168.655327 OAR3_181815353 168.958984 Meat Lacaune OAR3_181535066 168.688319 OAR3_181714610 168.866473

East Frisian Brown OAR3_181535066 168.688319 OAR3_182492456 169.636983 Finnsheep OAR3_181576673 168.751495 OAR3_181714610 168.866473

Comisana OAR3_181576673 168.751495 OAR3_181714610 168.866473 Ojalada OAR3_181576673 168.751495 s36931 170.561972

Sakiz OAR3_181688249 168.83807 OAR3_181815353 168.958984

Obs_Htz20 3 Churra OAR3_196791000 182.497709 Meat Lacaune OAR3_196913312 182.643043


Obs_Htz21 3 Chios OAR3_229873996 211.624402 s22341 211.87793 Australian Poll Merino s41320 211.806587

Churra s17644 212.763057 s66905 213.048035 Ojalada DU384041_287 212.622841 s23020 212.887492

East Frisian Brown OAR3_233491871 214.981744 s35739 215.4033

Obs_Htz22 4 Churra OAR4_11306223 10.518307 OAR4_12079184 11.293408 Meat Lacaune OAR4_12079184 11.293408

Comisana OAR4_12000546 11.218811 Ojalada OAR4_12079184 11.293408

Obs_Htz23 4 Comisana s28608 97.763212 OAR4_105812413 98.865276 Australian Poll Merino s16828 97.812402 s37018 97.871965

Churra s16828 97.812402 s37018 97.871965 Ojalada s37018 97.871965

Obs_Htz24 4 Milk Lacaune s06803 112.216316 OAR4_120520710 112.268889 Finnsheep s56814 113.730938

Churra OAR4_121859278 113.688324

Obs_Htz25 5 Chios OAR5_43897574 40.407364 s72060 41.107358

Milk Lacaune s74709 40.894605

Obs_Htz26 6 Milk Lacaune OAR6_26894928 23.623375 Meat Lacaune OAR6_26396811 23.210527 OAR6_26894928 23.623375

Chios s17623 25.885521 OAR6_29577816 25.949127 Ojalada OAR6_26396811 23.210527 OAR6_31567469 27.819055

Australian Poll Merino OAR6_31621001 27.872898

Sakiz OAR6_33453920 29.69792

Obs_Htz27 6 Milk Lacaune OAR6_38585187 34.57594 OAR6_42834740 38.054381 Australian Poll Merino OAR6_36395028 32.401102 OAR6_46589899 41.873949

Comisana OAR6_41044118 36.436857 OAR6_42317192 37.632679 Meat Lacaune OAR6_38383335 34.365051 OAR6_44473865 39.833644

Churra s16069 41.629024 s38254 41.862923 Ojalada s43499 36.056663 OAR6_48259046 43.363614

Obs_Htz28 7 Churra OAR7_19866890_X 19.072325 s68550 19.257574

Milk Lacaune OAR7_19928730 19.134616

Obs_Htz29 7 Comisana OAR7_46818598 42.026482

Chios OAR7_47960594 43.116197 s68972 43.570232

Obs_Htz30 7 Milk Lacaune OAR7_60354601 54.41476 s30690 58.162605 Ojalada OAR7_60354601 54.41476 OAR7_66685731 60.560526

Chios OAR7_65038832 59.047277 OAR7_65338086 59.341935 Meat Lacaune OAR7_62610703 56.372667 OAR7_65264623 59.275972

Churra OAR7_65120201 59.12761 Australian Poll Merino s00240 58.138119 s51528 60.408964

Comisana OAR7_66489587 60.45256 OAR7_66685731 60.560526 Finnsheep s30690 58.162605 OAR7_64371135 58.364778

Australian Poll Merino OAR7_64280352 58.272169 s51528 60.408964

Sakiz OAR7_64854028 58.864481 OAR7_66229320 60.192716

Obs_Htz31 8 Milk Lacaune OAR8_83750883 78.04147

East Frisian Brown s34293 78.728134 s66278 78.759335

Obs_Htz32 9 Milk Lacaune s09014 74.560664 s39785 74.609642 Australian Poll Merino s09014 74.560664

Chios OAR9_80693962 76.140824 OAR9_80804089 76.242733 Meat Lacaune s09014 74.560664

Ojalada s22340 74.659349

Sakiz OAR9_80534807_X 75.985327 OAR9_81054740_X 76.651847

Obs_Htz33 10 Comisana OAR10_26652355 24.855758 s38815 28.800676 Finnsheep OAR10_27085156 25.261864 OAR10_29546872 27.557292

Churra OAR10_28646479 26.67809 OAR10_29737372 27.837794 Meat Lacaune OAR10_29448537 27.460172 OAR10_29737372 27.837794

Milk Lacaune OAR10_29389966_X 27.398222 OAR10_29793750 27.896977 Ojalada OAR10_29538398 27.547387 OAR10_30790959 28.876748

Obs_Htz34 10 Comisana OAR10_44470993 42.082634 OAR10_44655795 42.272772 Finnsheep OAR10_43391432 40.671337 OAR10_45065959 42.682521

Chios OAR10_44655795 42.272772 OAR10_44834335 42.474049 Ojalada OAR10_44470993 42.082634 OAR10_44834335 42.474049

Milk Lacaune OAR10_44655795 42.272772 OAR10_44834335 42.474049 Sakiz OAR10_44470993 42.082634 OAR10_44615697 42.230982

Meat Lacaune OAR10_44509259 42.123799 OAR10_44834335 42.474049

Obs_Htz35 11 Churra OAR11_18701428 18.346557 s69909 18.602308 Meat Lacaune s13840 16.449218 s27474 18.671334

Milk Lacaune OAR11_18701428 18.346557 s27474 18.671334 Ojalada OAR11_18701428 18.346557 s69909 18.602308

Comisana OAR11_18815864 18.454208 OAR11_18909056 18.544951 Australian Poll Merino OAR11_18815864 18.454208 OAR11_19810690 19.403144

Sakiz OAR11_19810690 19.403144

Obs_Htz36 11 East Frisian Brown s59074 22.135921 OAR11_23034869 22.199593 Meat Lacaune s51197 22.183054 s43495 22.368448

Churra s51197 22.183054

Milk Lacaune s51197 22.183054 s43495 22.368448

Obs_Htz37 12 Comisana s13858 24.480926 Sakiz OAR11_26873926 25.777153 s31301 26.612875

Churra s14394 24.545136 s43122 24.803153 Australian Poll Merino s51636 26.318526 s23362 29.221714

Chios s10340 24.60133 s62452 29.530127

Milk Lacaune OAR11_27752920 26.50247

Obs_Htz38 12 Churra OAR12_61804737 55.672814 s66802 55.842304 Australian Poll Merino s66802 55.842304 OAR12_61974786 55.848797

Milk Lacaune OAR12_61874204 55.74348 OAR12_61974786 55.848797 Meat Lacaune s66802 55.842304 OAR12_61974786 55.848797

Comisana s66802 55.842304 Australian Poll Merino

Obs_Htz39 12 Churra s30614 58.136309 OAR12_64628319 58.302665 Meat Lacaune s30614 58.136309

East Frisian Brown s26801 58.576013 OAR12_64944672 58.61688

Obs_Htz40 13 Churra OAR13_33752762 30.635254 OAR13_33955992 30.85995 Ojalada OAR13_33752762 30.635254 OAR13_33896421 30.786161

Milk Lacaune OAR13_33896421 30.786161 OAR13_33955992 30.85995 Australian Poll Merino OAR13_34032007 30.939655 OAR13_34176651 31.065051

Obs_Htz41 13 Milk Lacaune s08503 39.88509

Comisana OAR13_54016379 41.65332 s20479 41.694042

Obs_Htz42 13 Chios OAR13_60893851 56.060654 OAR13_68535533 63.227469 Sakiz s31558 56.277903 s13874 63.323127

Comisana s31201 56.339588 s63708 63.78132 Finnsheep OAR13_67067820 61.900545 s19346 62.210378

Australian Poll Merino s48133 62.276683 OAR13_67425309 62.371867

Obs_Htz43 15 Churra OAR15_37160581 35.602806 OAR15_37380344 35.789479 Finnsheep s65735 31.027264

Comisana OAR15_37160581 35.602806 OAR15_37443121 35.84624

Obs_Htz44 15 Chios s02793 72.842543 Finnsheep OAR15_77074005 71.384913 OAR15_77122668 71.432136

Milk Lacaune s28875 72.948461 Australian Poll Merino s28875 72.948461 s52687 72.988365

Meat Lacaune s28875 72.948461

Ojalada s28875 72.948461

Obs_Htz45 16 Comisana OAR16_51977009 48.03606

East Frisian Brown OAR16_52089645 48.143409


Milk Lacaune OAR17_64889221 59.812538 s37924 60.05064


Milk Lacaune OAR20_44626939 40.652715 s37017 40.920512 Australian Poll Merino s64274 41.01732

Obs_Htz48 20 Churra OAR20_54497778 49.766895 s35415 49.979989 Meat Lacaune s61798 49.816123 s35415 49.979989

Comisana OAR20_54497778 49.766895 s35415 49.979989 Finnsheep s35415 49.979989

Chios s61798 49.816123 s35415 49.979989

Milk Lacaune s61798 49.816123 s35415 49.979989

Obs_Htz49 21 Chios s52830 27.451792 OAR21_30678813 27.471775 Meat Lacaune s75804 29.587175 s75804 29.587175

Milk Lacaune s41284 29.40318 s75804 29.587175 Australian Poll Merino s38134 29.447881 s44540 29.507008

Ojalada s38134 29.447881 s44540 29.507008

Obs_Htz50 21 Churra s72899 38.858968 s59728 38.91103 Australian Poll Merino OAR21_46682445 40.738496 OAR21_46936641 40.874274

Comisana OAR21_46682445 40.738496


Obs_Htz51 22 Milk Lacaune OAR22_23392099 19.587631 OAR22_23417873 19.610393 Meat Lacaune OAR22_23392099 19.587631 OAR22_23446812 19.639123

East Frisian Brown OAR22_24747565 20.99124 Australian Poll Merino OAR22_26275112 22.366773

Obs_Htz52 22 Comisana OAR22_36492428 31.879508 OAR22_40197865 35.61184 Ojalada OAR22_36492428 31.879508 OAR22_36576021 31.963576

Milk Lacaune OAR22_36492428 31.879508 s73065 34.30344 Australian Poll Merino OAR22_38946909 34.273821 OAR22_41042892 36.462598

Meat Lacaune OAR22_38946909 34.273821 s13462 38.550647

Finnsheep OAR22_42931135 38.322102 OAR22_43010940 38.403606

Obs_Htz53 24 Comisana s08130 26.375802 Finnsheep OAR24_28445680 26.035068 s63355 27.096216

Milk Lacaune s08130 26.375802 OAR24_29399883 26.984286 Ojalada s08130 26.375802 s48918 26.58114

Obs_Htz54 25 Comisana s12019 5.095615 Australian Poll Merino s25195 6.235402 s67158 6.571187

East Frisian Brown s25195 6.235402 s21107 6.461437 Meat Lacaune s44881 6.451855 s21107 6.461437

Milk Lacaune s03686 6.359903 s67158 6.571187

Obs_Htz55 25 East Frisian Brown OAR25_19926183 18.148995 OAR25_20142347 18.354065

Milk Lacaune OAR25_20106030 18.316414

Table S3 for "Application of selection mapping to identify genomic regions associated with Authors: Beatriz Gutiérrez-Gil1*, Juan Jose Arranz1, Ricardo Pong-Wong2, Elsa García-Gámez1, Table S3. List of all genes from the orthologous bovine genome regions corresponding to the 9 conNumber PositCCR-gene nu Candidate converg Chr: position (Mb; oar v2.0) Ensembl Gen1 1 CCR1 OAR3: 152.68‐154.679 ENSBTAG0002 2 CCR1 OAR3: 152.68‐154.679 ENSBTAG0003 3 CCR1 OAR3: 152.68‐154.679 ENSBTAG0004 4 CCR1 OAR3: 152.68‐154.679 ENSBTAG0005 5 CCR1 OAR3: 152.68‐154.679 ENSBTAG0006 6 CCR1 OAR3: 152.68‐154.679 ENSBTAG0007 7 CCR1 OAR3: 152.68‐154.679 ENSBTAG0008 8 CCR1 OAR3: 152.68‐154.679 ENSBTAG0009 9 CCR1 OAR3: 152.68‐154.679 ENSBTAG00010 10 CCR1 OAR3: 152.68‐154.679 ENSBTAG00011 11 CCR1 OAR3: 152.68‐154.679 ENSBTAG00012 1 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00013 2 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00014 3 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00015 4 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00016 5 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00017 6 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00018 7 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00019 8 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00020 9 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00021 10 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00022 11 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00023 12 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00024 13 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00025 14 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00026 15 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00027 16 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00028 17 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00029 18 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00030 19 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00031 20 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00032 21 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00033 22 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00034 23 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00035 24 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00036 25 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00037 26 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00038 27 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00039 28 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00040 29 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00041 30 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00042 31 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00043 32 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00044 33 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00045 34 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00046 35 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00047 36 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00048 37 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000

49 38 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00050 39 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00051 40 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00052 41 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00053 42 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00054 43 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00055 44 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00056 45 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00057 46 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00058 47 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00059 48 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00060 49 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00061 50 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00062 51 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00063 52 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00064 53 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00065 54 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00066 55 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00067 56 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00068 57 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00069 58 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00070 59 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00071 60 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00072 61 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00073 62 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00074 63 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00075 64 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00076 65 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00077 66 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00078 67 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00079 68 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00080 69 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00081 70 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00082 71 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00083 72 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00084 73 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00085 74 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00086 75 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00087 76 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00088 77 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00089 78 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00090 79 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00091 80 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00092 81 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00093 82 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00094 83 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00095 84 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00096 85 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00097 86 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00098 87 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG00099 88 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000100 89 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000

101 90 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000102 91 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000103 92 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000104 93 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000105 94 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000106 95 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000107 96 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000108 97 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000109 98 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000110 99 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000111 100 CCR2 OAR3: 209.872 ‐ 215.814 ENSBTAG000112 1 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000113 2 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000114 3 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000115 4 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000116 5 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000117 6 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000118 7 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000119 8 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000120 9 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000121 10 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000122 11 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000123 12 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000124 13 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000125 14 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000126 15 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000127 16 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000128 17 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000129 18 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000130 19 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000131 20 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000132 21 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000133 22 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000134 23 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000135 24 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000136 25 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000137 26 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000138 27 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000139 28 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000140 29 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000141 30 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000142 31 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000143 32 CCR3 OAR6: 30.367 ‐ 41.863 ENSBTAG000144 1 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000145 2 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000146 3 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000147 4 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000148 5 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000149 6 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000150 7 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000151 8 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000152 9 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000

153 10 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000154 11 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000155 12 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000156 13 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000157 14 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000158 15 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000159 16 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000160 17 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000161 18 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000162 19 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000163 20 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000164 21 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000165 22 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000166 23 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000167 24 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000168 25 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000169 26 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000170 27 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000171 28 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000172 29 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000173 30 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000174 31 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000175 32 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000176 33 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000177 34 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000178 35 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000179 36 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000180 37 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000181 38 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000182 39 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000183 40 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000184 41 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000185 42 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000186 43 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000187 44 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000188 45 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000189 46 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000190 47 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000191 48 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000192 49 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000193 50 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000194 51 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000195 52 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000196 53 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000197 54 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000198 55 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000199 56 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000200 57 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000201 58 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000202 59 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000



303 160 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000304 161 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000305 162 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000306 163 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000307 164 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000308 165 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000309 166 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000310 167 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000311 168 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000312 169 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000313 170 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000314 171 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000315 172 CCR4 OAR13: 56.061‐ 65.811 ENSBTAG000316 1 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000317 2 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000318 3 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000319 4 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000320 5 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000321 6 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000322 7 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000323 8 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000324 9 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000325 10 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000326 11 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000327 12 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000328 13 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000329 14 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000330 15 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000331 16 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000332 17 CCR5 OAR15:72.774 ‐74.550 ENSBTAG000333 1 CCR6 OAR22: 19.587‐23.157 ENSBTAG000334 2 CCR6 OAR22: 19.587‐23.157 ENSBTAG000335 3 CCR6 OAR22: 19.587‐23.157 ENSBTAG000336 4 CCR6 OAR22: 19.587‐23.157 ENSBTAG000337 5 CCR6 OAR22: 19.587‐23.157 ENSBTAG000338 6 CCR6 OAR22: 19.587‐23.157 ENSBTAG000339 7 CCR6 OAR22: 19.587‐23.157 ENSBTAG000340 8 CCR6 OAR22: 19.587‐23.157 ENSBTAG000341 9 CCR6 OAR22: 19.587‐23.157 ENSBTAG000342 10 CCR6 OAR22: 19.587‐23.157 ENSBTAG000343 11 CCR6 OAR22: 19.587‐23.157 ENSBTAG000344 12 CCR6 OAR22: 19.587‐23.157 ENSBTAG000345 13 CCR6 OAR22: 19.587‐23.157 ENSBTAG000346 14 CCR6 OAR22: 19.587‐23.157 ENSBTAG000347 15 CCR6 OAR22: 19.587‐23.157 ENSBTAG000348 16 CCR6 OAR22: 19.587‐23.157 ENSBTAG000349 17 CCR6 OAR22: 19.587‐23.157 ENSBTAG000350 18 CCR6 OAR22: 19.587‐23.157 ENSBTAG000351 19 CCR6 OAR22: 19.587‐23.157 ENSBTAG000352 20 CCR6 OAR22: 19.587‐23.157 ENSBTAG000

353 21 CCR6 OAR22: 19.587‐23.157 ENSBTAG000354 22 CCR6 OAR22: 19.587‐23.157 ENSBTAG000355 23 CCR6 OAR22: 19.587‐23.157 ENSBTAG000356 24 CCR6 OAR22: 19.587‐23.157 ENSBTAG000357 25 CCR6 OAR22: 19.587‐23.157 ENSBTAG000358 26 CCR6 OAR22: 19.587‐23.157 ENSBTAG000359 27 CCR6 OAR22: 19.587‐23.157 ENSBTAG000360 28 CCR6 OAR22: 19.587‐23.157 ENSBTAG000361 29 CCR6 OAR22: 19.587‐23.157 ENSBTAG000362 30 CCR6 OAR22: 19.587‐23.157 ENSBTAG000363 31 CCR6 OAR22: 19.587‐23.157 ENSBTAG000364 32 CCR6 OAR22: 19.587‐23.157 ENSBTAG000365 33 CCR6 OAR22: 19.587‐23.157 ENSBTAG000366 34 CCR6 OAR22: 19.587‐23.157 ENSBTAG000367 35 CCR6 OAR22: 19.587‐23.157 ENSBTAG000368 36 CCR6 OAR22: 19.587‐23.157 ENSBTAG000369 37 CCR6 OAR22: 19.587‐23.157 ENSBTAG000370 38 CCR6 OAR22: 19.587‐23.157 ENSBTAG000371 39 CCR6 OAR22: 19.587‐23.157 ENSBTAG000372 40 CCR6 OAR22: 19.587‐23.157 ENSBTAG000373 41 CCR6 OAR22: 19.587‐23.157 ENSBTAG000374 42 CCR6 OAR22: 19.587‐23.157 ENSBTAG000375 43 CCR6 OAR22: 19.587‐23.157 ENSBTAG000376 44 CCR6 OAR22: 19.587‐23.157 ENSBTAG000377 45 CCR6 OAR22: 19.587‐23.157 ENSBTAG000378 46 CCR6 OAR22: 19.587‐23.157 ENSBTAG000379 47 CCR6 OAR22: 19.587‐23.157 ENSBTAG000380 48 CCR6 OAR22: 19.587‐23.157 ENSBTAG000381 49 CCR6 OAR22: 19.587‐23.157 ENSBTAG000382 50 CCR6 OAR22: 19.587‐23.157 ENSBTAG000383 51 CCR6 OAR22: 19.587‐23.157 ENSBTAG000384 52 CCR6 OAR22: 19.587‐23.157 ENSBTAG000385 53 CCR6 OAR22: 19.587‐23.157 ENSBTAG000386 54 CCR6 OAR22: 19.587‐23.157 ENSBTAG000387 55 CCR6 OAR22: 19.587‐23.157 ENSBTAG000388 56 CCR6 OAR22: 19.587‐23.157 ENSBTAG000389 57 CCR6 OAR22: 19.587‐23.157 ENSBTAG000390 58 CCR6 OAR22: 19.587‐23.157 ENSBTAG000391 59 CCR6 OAR22: 19.587‐23.157 ENSBTAG000392 60 CCR6 OAR22: 19.587‐23.157 ENSBTAG000393 61 CCR6 OAR22: 19.587‐23.157 ENSBTAG000394 62 CCR6 OAR22: 19.587‐23.157 ENSBTAG000395 63 CCR6 OAR22: 19.587‐23.157 ENSBTAG000396 64 CCR6 OAR22: 19.587‐23.157 ENSBTAG000397 65 CCR6 OAR22: 19.587‐23.157 ENSBTAG000398 66 CCR6 OAR22: 19.587‐23.157 ENSBTAG000399 67 CCR6 OAR22: 19.587‐23.157 ENSBTAG000400 68 CCR6 OAR22: 19.587‐23.157 ENSBTAG000401 69 CCR6 OAR22: 19.587‐23.157 ENSBTAG000402 70 CCR6 OAR22: 19.587‐23.157 ENSBTAG000

403 71 CCR6 OAR22: 19.587‐23.157 ENSBTAG000404 72 CCR6 OAR22: 19.587‐23.157 ENSBTAG000405 73 CCR6 OAR22: 19.587‐23.157 ENSBTAG000406 74 CCR6 OAR22: 19.587‐23.157 ENSBTAG000

dairy production in sheep"James Kijas3, Pamela Wiener2nvergence candidate regions (CCR) for dairy selection sweeps identified in this study, extrHGNC symbol WikiGene NamWikiGene Description00009939 CAND1 cullin‐associated and neddylation‐dissociated 1

00033726 GRIP1

00020806 HELB helicase (DNA) B

00007636 IRAK3 interleukin‐1 receptor‐associated kinase 3

00026993 TMBIM4 transmembrane BAX inhibitor motif containing 4

LLPH LLPH LLP homolog, long‐term synaptic facilitation (Aplysia

HMGA2 HMGA2 high mobility group AT‐hook 2

MSRB3 MSRB3

00039435 LEMD3 LEM domain containing 3

00014758 WIF1 WNT inhibitory factor 1

00031786 FAU Finkel‐Biskis‐Reilly murine sarcoma virus (FBR‐MuSV

00020699 TSPAN11 tetraspanin 11

TSPAN9 TSPAN9 tetraspanin 9

00019788 TEAD4 TEA domain family member 4

TULP3 TULP3 tubby like protein 3

00015878 RHNO1 chromosome 5 open reading frame, human C12orf3

FOXM1 FOXM1 forkhead box M1

00030325 LOC782076 uncharacterized protein ENSP00000372125‐like

NRIP2 NRIP2 nuclear receptor interacting protein 2

ITFG2 ITFG2 integrin alpha FG‐GAP repeat containing 2

00007605 FKBP4 FK506 binding protein 4, 59kDa

DDX11 DDX11

00011902 WASH1 WAS protein family homolog 1

IQSEC3 IQSEC3 IQ motif and Sec7 domain 3

SLC6A12 SLC6A12 solute carrier family 6 (neurotransmitter transporter

00014525 SLC6A13 solute carrier family 6 (neurotransmitter transporter

00020472 KDM5A lysine (K)‐specific demethylase 5A

00000049 CCDC77 coiled‐coil domain containing 77

00008553 B4GALNT3 beta‐1,4‐N‐acetyl‐galactosaminyl transferase 3

00008554 NINJ2 ninjurin 2

WNK1 WNK1 WNK lysine deficient protein kinase 1

00005225 RAD52 RAD52 homolog (S. cerevisiae)

ERC1 ERC1 ELKS/RAB6‐interacting/CAST family member 1

00001341 WNT5B wingless‐type MMTV integration site family, membe

00009050 ADIPOR2 adiponectin receptor 2

CACNA2D4 CACNA2D4 calcium channel, voltage‐dependent, alpha 2/delta s

LRTM2 LRTM2 leucine‐rich repeats and transmembrane domains 2

DCP1B DCP1B DCP1 decapping enzyme homolog B (S. cerevisiae)

CACNA1C CACNA1C calcium channel, voltage‐dependent, L type, alpha 1

IL17RA IL17RA interleukin 17 receptor A

00016995 CECR5 cat eye syndrome chromosome region, candidate 5

CECR1 CECR1 cat eye syndrome chromosome region, candidate 1

CECR2 CECR2

00014238 ATP6V1E1 ATPase, H+ transporting, lysosomal 31kDa, V1 subun

BCL2L13 BCL2L13 BCL2‐like 13 (apoptosis facilitator)

00013988 BID BH3 interacting domain death agonist

00048271 MICAL3 microtubule associated monoxygenase, calponin and

00011826 PEX26 peroxisomal biogenesis factor 26

00018530 TUBA8 tubulin, alpha 8

00030258 CDC42EP1 CDC42 effector protein (Rho GTPase binding) 1

00021615 LGALS2 lectin, galactoside‐binding, soluble, 2

00006464 GGA1 golgi‐associated, gamma adaptin ear containing, ARF

SH3BP1 SH3BP1 SH3‐domain binding protein 1

00030255 PDXP pyridoxal (pyridoxine, vitamin B6) phosphatase

00015089 LGALS1 lectin, galactoside‐binding, soluble, 1

00015092 NOL12 nucleolar protein 12

00002539 TRIOBP TRIO and F‐actin binding protein

00008434 GCAT glycine C‐acetyltransferase

GALR3 GALR3 galanin receptor 3

00010789 ANKRD54 ankyrin repeat domain 54

00010790 EIF3L eukaryotic translation initiation factor 3, subunit L

MICALL1 MICALL1 MICAL‐like 1

C22orf23 C5H22orf23 chromosome 5 open reading frame, human C22orf23

00004820 POLR2F polymerase (RNA) II (DNA directed) polypeptide F

00004822 SOX10 SRY (sex determining region Y)‐box 10

00015268 PICK1 protein interacting with PRKCA 1

00015275 SLC16A8 solute carrier family 16, member 8 (monocarboxylic

00015290 BAIAP2L2 BAI1‐associated protein 2‐like 2

PLA2G6 PLA2G6 phospholipase A2, group VI (cytosolic, calcium‐indep

00021435 MAFF v‐maf musculoaponeurotic fibrosarcoma oncogene h

00009668 TMEM184B transmembrane protein 184B

00007546 CSNK1E casein kinase 1, epsilon

00047582 CSNK1D casein kinase 1, delta

KDELR3 KDELR3 KDEL (Lys‐Asp‐Glu‐Leu) endoplasmic reticulum prote

00009887 DDX17 DEAD (Asp‐Glu‐Ala‐Asp) box polypeptide 17

00005936 DMC1 DMC1 dosage suppressor of mck1 homolog, meiosis

FAM227A FAM227A

00006588 CBY1 chibby homolog 1 (Drosophila)

00010157 TOMM22 translocase of outer mitochondrial membrane 22 ho

00010171 JOSD1 Josephin domain containing 1

00010324 GTPBP1 GTP binding protein 1

00003693 SUN2 Sad1 and UNC84 domain containing 2

00026495 DNAL4 dynein, axonemal, light chain 4

NPTXR NPTXR neuronal pentraxin receptor

00046724 CBX6 chromobox homolog 6

00037800 APOBEC3A apolipoprotein B mRNA editing enzyme, catalytic po

00007755 APOBEC3B apolipoprotein B mRNA editing enzyme, catalytic po

00007228 CBX7 chromobox homolog 7

00021697 PDGFB platelet‐derived growth factor beta polypeptide

00003228 RPL3 ribosomal protein L3

00005765 SYNGR1 synaptogyrin 1

00019828 TAB1 TGF‐beta activated kinase 1/MAP3K7 binding protein

MIEF1 SMCR7L Smith‐Magenis syndrome chromosome region, cand

00017462 ATF4 activating transcription factor 4 (tax‐responsive enha

00017463 RPS19BP1 ribosomal protein S19 binding protein 1

CACNA1I CACNA1I

00000326 ENTHD1 ENTH domain containing 1

GRAP2 GRAP2 GRB2‐related adaptor protein 2

FAM83F FAM83F family with sequence similarity 83, member F

TNRC6B TNRC6B trinucleotide repeat containing 6B

00000077 ADSL adenylosuccinate lyase

00009624 SGSM3 small G protein signaling modulator 3

MKL1 MKL1 megakaryoblastic leukemia (translocation) 1

00004048 MCHR1 melanin‐concentrating hormone receptor 1

00006200 SLC25A17 solute carrier family 25 (mitochondrial carrier; perox

00006202 ST13 suppression of tumorigenicity 13 (colon carcinoma) (

XPNPEP3 XPNPEP3 X‐prolyl aminopeptidase (aminopeptidase P) 3, putat

00007786 FBXL14 F‐box and leucine‐rich repeat protein 14

00038439 H1F0 H1 histone family, member 0

MGAT3 MGAT3 mannosyl (beta‐1,4‐)‐glycoprotein beta‐1,4‐N‐acetyl

00006205 DNAJB7 DnaJ (Hsp40) homolog, subfamily B, member 7

HPGDS HPGDS hematopoietic prostaglandin D synthase

00017061 SMARCAD1 SWI/SNF‐related, matrix‐associated actin‐dependent

GRID2 GRID2 glutamate receptor, ionotropic, delta 2

CCSER1 CCSER1 family with sequence similarity 190, member A

00010285 MMRN1 multimerin 1

00024957 SNCA synuclein, alpha (non A4 component of amyloid prec

00033346 FAM13A family with sequence similarity 13, member A

00010120 HERC3 HECT and RLD domain containing E3 ubiquitin protei

00020541 PIGY phosphatidylinositol glycan anchor biosynthesis, clas

00020541 PYURF PIGY upstream reading frame

00020538 HERC5 hect domain and RLD 5

00020536 HERC6 hect domain and RLD 6

00005754 PPM1K protein phosphatase, Mg2+/Mn2+ dependent, 1K

00017704 ABCG2 ATP‐binding cassette, sub‐family G (WHITE), membe

00020031 PKD2 polycystic kidney disease 2 (autosomal dominant)

00005260 SPP1 secreted phosphoprotein 1

MEPE MEPE matrix extracellular phosphoglycoprotein

00000470 IBSP integrin‐binding sialoprotein

00005989 LAP3 leucine aminopeptidase 3

00019441 MED28 mediator complex subunit 28

FAM184B FAM184B family with sequence similarity 184, member B

00021582 NCAPG non‐SMC condensin I complex, subunit G

00046561 LCORL ligand dependent nuclear receptor corepressor‐like

SLIT2 SLIT2 slit homolog 2 (Drosophila)

PACRGL PACRGL PARK2 co‐regulated‐like

00047743 KCNIP4 Kv channel interacting protein 4

00002895 ATOH1 atonal homolog 1 (Drosophila)

00047821 LOC10033662 glutamate receptor ionotropic, delta‐2‐like

GPRIN3 GPRIN3 GPRIN family member 3

TIGD2 TIGD2 tigger transposable element derived 2

00010128 NAP1L5 nucleosome assembly protein 1‐like 5

00011973 DCAF16 DDB1 and CUL4 associated factor 16

EDN3 EDN3

ZNF831 LOC10014085 zinc finger protein 831‐like

00004402 SLMO2 slowmo homolog 2 (Drosophila)

00039208 LOC100852024ATP synthase subunit epsilon, mitochondrial‐like

00039208 LOC10033546 ATP synthase subunit epsilon, mitochondrial‐like

00039208 LOC782270 aTP synthase, H+ transporting, mitochondrial F1 com

00039208 ATP5E ATP synthase, H+ transporting, mitochondrial F1 com

00018785 TUBB1 tubulin, beta 1 class VI

CTSZ CTSZ cathepsin Z

NELFCD LOC514958 negative elongation factor D‐like

00017475 GNAS GNAS complex locus

00016724 NPEPL1 aminopeptidase‐like 1

STX16 STX16 syntaxin 16

APCDD1L APCDD1L adenomatosis polyposis coli down‐regulated 1‐like

00017424 VAPB VAMP (vesicle‐associated membrane protein)‐associ

RAB22A RAB22A RAB22A, member RAS oncogene family

ANKRD60 ANKRD60 ankyrin repeat domain 60

00016926 LOC100851784uncharacterized LOC100851784

00016926 C13H20orf85 chromosome 13 open reading frame, human C20orf8

PMEPA1 PMEPA1 prostate transmembrane protein, androgen induced

ZBP1 ZBP1 Z‐DNA binding protein 1

00001936 PCK1 phosphoenolpyruvate carboxykinase 1 (soluble)

00013079 CTCFL CCCTC‐binding factor (zinc finger protein)‐like

RBM38 RBM38 RNA binding motif protein 38

00010934 RAE1 RAE1 RNA export 1 homolog (S. pombe)

SPO11 SPO11 SPO11 meiotic protein covalently bound to DSB hom

00015362 BMP7 bone morphogenetic protein 7

00002065 TFAP2C transcription factor AP‐2 gamma (activating enhance

00031462 FAM209B family with sequence similarity 209, member B

RTFDC1 RTFDC1 replication termination factor 2 domain containing 1

GCNT7 GCNT7 glucosaminyl (N‐acetyl) transferase family member 7

CASS4 CASS4

00006639 CSTF1 cleavage stimulation factor, 3' pre‐RNA, subunit 1, 50

00013009 AURKA aurora kinase A

00013007 FAM210B family with sequence similarity 210, member B

00033397 LOC526613 signal‐regulatory protein delta‐like

00033397 LOC786289 tyrosine‐protein phosphatase non‐receptor type sub

SIRPB2 SIRPB2

00006533 NSFL1C NSFL1 (p97) cofactor (p47)

00008303 FKBP1A FK506 binding protein 1A, 12kDa

SDCBP2 SDCBP2 syndecan binding protein (syntenin) 2

SNPH SNPH syntaphilin

RAD21L1 RAD21L1 RAD21‐like 1 (S. pombe)

TMEM74B TMEM74B transmembrane protein 74B

00018417 PSMF1 proteasome (prosome, macropain) inhibitor subunit

RSPO4 RSPO4 R‐spondin 4

00021811 ANGPT4 angiopoietin 4


00003977 SLC52A3 solute carrier family 52, riboflavin transporter, mem

00010913 SRXN1 sulfiredoxin 1

00005750 TCF15 transcription factor 15 (basic helix‐loop‐helix)

00012341 CSNK2A1 casein kinase 2, alpha 1 polypeptide

00013330 TBC1D20 TBC1 domain family, member 20

00017002 RBCK1 RanBP‐type and C3HC4‐type zinc finger containing 1

00017007 TRIB3 tribbles homolog 3 (Drosophila)

00027387 NRSN2 neurensin 2

C20orf96 C13H20orf96 chromosome 13 open reading frame, human C20orf9

DEFB129 BBD129 beta‐defensin 129

00003364 DEFB119 defensin, beta 119

00027384 DEFB122A beta‐defensin 122a

00027383 DEFB122 beta‐defensin 122



00014176 REM1 RAS (RAD and GEM)‐like GTP‐binding 1

00008840 HM13 histocompatibility (minor) 13

00016169 ID1 inhibitor of DNA binding 1, dominant negative helix‐

COX4I2 COX4I2 cytochrome c oxidase subunit IV isoform 2 (lung)

00006526 BCL2L1 BCL2‐like 1

TPX2 TPX2 TPX2, microtubule‐associated, homolog (Xenopus lae

00014930 MYLK2 myosin light chain kinase 2

DUSP15 DUSP15 dual specificity phosphatase 15

00005937 TTLL9 tubulin tyrosine ligase‐like family, member 9

00009743 PDRG1 p53 and DNA‐damage regulated 1

00016348 XKR7 XK, Kell blood group complex subunit‐related family,

CCM2L CCM2L

HCK HCK hemopoietic cell kinase

00001015 TM9SF4 transmembrane 9 superfamily protein member 4

PLAGL2 PLAGL2 pleiomorphic adenoma gene‐like 2

00016231 POFUT1 protein O‐fucosyltransferase 1

KIF3B KIF3B kinesin family member 3B

ASXL1 ASXL1 additional sex combs like 1 (Drosophila)

C20orf112 C13H20orf112chromosome 13 open reading frame, human C20orf1

00016427 COMMD7 COMM domain containing 7

00003901 LOC10084841 DNA (cytosine‐5)‐methyltransferase 3B‐like

00003901 DNMT3B DNA (cytosine‐5‐)‐methyltransferase 3 beta

MAPRE1 LOC10084808 microtubule‐associated protein RP/EB family membe

MAPRE1 MAPRE1 microtubule‐associated protein, RP/EB family, memb

00013056 SUN5 Sad1 and UNC84 domain containing 5

00013056 LOC10085158 SUN domain‐containing protein 5‐like

00019200 LOC10085162 BPI fold‐containing family B member 2‐like

00019200 BPIFB2 BPI fold containing family B, member 2

BPIFB6 BPIFB6

BPIFB3 BPIFB3 BPI fold containing family B, member 3


00009144 BPIFA2A BPI fold containing family A, member 2A

00031376 BPIFA2C BPI fold containing family A, member 2C

00031375 BPIFA2D BPI fold containing family A, member 2D

00019752 BPIFA2B BPI fold containing family A, member 2B

00006802 BPIFA3 BPI fold containing family A, member 3

00017098 BPIFA1 BPI fold containing family A, member 1


00031361 BPIFB5 BPI fold containing family B, member 5

00031354 LOC10190805 vomeromodulin‐like

00018535 CDK5RAP1 CDK5 regulatory subunit associated protein 1

00000512 SNTA1 syntrophin, alpha 1 (dystrophin‐associated protein A

CBFA2T2 CBFA2T2 core‐binding factor, runt domain, alpha subunit 2; tr

NECAB3 NECAB3 N‐terminal EF‐hand calcium binding protein 3

C20orf144 C13H20orf144chromosome 13 open reading frame, human C20orf1

00003971 E2F1 E2F transcription factor 1

00038738 PXMP4 peroxisomal membrane protein 4, 24kDa

00039313 ZNF341 zinc finger protein 341

00013387 CHMP4B charged multivesicular body protein 4B

00016524 RALY RNA binding protein, autoantigenic (hnRNP‐associat

00005969 EIF2S2 eukaryotic translation initiation factor 2, subunit 2 b

00034077 LOC10084911 agouti‐signaling protein‐like

00034077 ASIP agouti signaling protein

00018101 AHCY adenosylhomocysteinase

00000308 ITCH itchy E3 ubiquitin protein ligase homolog (mouse)

00006134 DYNLRB1 dynein, light chain, roadblock‐type 1

00006135 MAP1LC3A microtubule‐associated protein 1 light chain 3 alpha

PIGU PIGU phosphatidylinositol glycan anchor biosynthesis, clas

TP53INP2 TP53INP2 tumor protein p53 inducible nuclear protein 2

NCOA6 NCOA6 nuclear receptor coactivator 6

00013301 GGT7 gamma‐glutamyltransferase 7

00013303 ACSS2 acyl‐CoA synthetase short‐chain family member 2

00003504 GSS glutathione synthetase

MYH7B MYH7B myosin, heavy chain 7B, cardiac muscle, beta

TRPC4AP TRPC4AP transient receptor potential cation channel, subfami

TRPC4AP LOC787940 TRPC4‐associated protein‐like

00003815 EDEM2 ER degradation enhancer, mannosidase alpha‐like 2

00008291 PROCR protein C receptor, endothelial

MMP24 MMP24 matrix metallopeptidase 24 (membrane‐inserted)

00011263 EIF6 eukaryotic translation initiation factor 6

FAM83C FAM83C family with sequence similarity 83, member C

00030990 UQCC ubiquinol‐cytochrome c reductase complex chapero

00004429 GDF5 growth differentiation factor 5

CEP250 CEP250 centrosomal protein 250kDa

C20orf173 C20orf173

00006670 ERGIC3 ERGIC and golgi 3

SPAG4 SPAG4 sperm associated antigen 4

00006955 CPNE1 copine I

RBM12 LOC10014107 RNA‐binding protein 12‐like


00006962 NFS1 NFS1 nitrogen fixation 1 homolog (S. cerevisiae)

00027361 ROMO1 reactive oxygen species modulator 1


PHF20 PHF20 PHD finger protein 20

CNBD2 CNMPD1 cyclic nucleotide (cNMP) binding domain containing

EPB41L1 EPB41L1 erythrocyte membrane protein band 4.1‐like 1

00001645 AAR2 AAR2 splicing factor homolog (S. cerevisiae)

00001741 DLGAP4 discs, large (Drosophila) homolog‐associated protein

00011473 MYL9 myosin, light chain 9, regulatory

TGIF2 TGIF2 TGFB‐induced factor homeobox 2

00021805 C13H20orf24 RAB5‐interacting protein

00040607 SLA2 Src‐like‐adaptor 2

00019621 NDRG3 NDRG family member 3

00022005 TLDC2 TBC/LysM‐associated domain containing 2

00022007 SAMHD1 SAM domain and HD domain 1

00011541 RBL1 retinoblastoma‐like 1 (p107)

00013915 DSN1 DSN1, MIND kinetochore complex component, homo

SOGA1 SOGA1 suppressor of glucose, autophagy associated 1

MROH8 MROH8 maestro heat‐like repeat family member 8

00014648 RPN2 ribophorin II

00012710 GHRH growth hormone releasing hormone

00000528 MANBAL mannosidase, beta A, lysosomal‐like

SRC SRC v‐src sarcoma (Schmidt‐Ruppin A‐2) viral oncogene h

00004712 MC3R melanocortin 3 receptor

00002116 ZCCHC3 zinc finger, CCHC domain containing 3

00048009 LOC10190617 beta‐defensin 118‐like

00009206 FOXS1 forkhead box S1

ACTL10 ACTL10 actin‐like 10

00005573 SCAND1 SCAN domain containing 1

00019644 EXT2 exostosin 200027563 ALX4 ALX homeobox 400031252 LOC10033528CD82 antigen-like00031252 CD82 CD82 moleculeTSPAN18 TSPAN18 tetraspanin 18TP53I11 TP53I11 Tumor Protein P53-Inducible Protein 11PRDM11 PRDM11 PR domain containing 1100001703 SYT13 synaptotagmin XIII00003721 CHST1 carbohydrate (keratan sulfate Gal-6) sulfotransferase 00003199 SLC35C1 solute carrier family 35, member C1CRY2 LOC10190226cryptochrome-2-likeCRY2 LOC509058 cryptochrome-2-likeMAPK8IP1 MAPK8IP1 mitogen-activated protein kinase 8 interacting protein00027562 C15H11orf94 uncharacterized protein C11orf94 homolog00003126 PEX16 peroxisomal biogenesis factor 16GYLTL1B GYLTL1B glycosyltransferase-like 1BPHF21A PHF21A PHD finger protein 21A00011960 GOT1 glutamic‐oxaloacetic transaminase 1, soluble (aspart

00021397 NKX2‐3 NK2 homeobox 3

00012107 SLC25A28 solute carrier family 25, member 28

ENTPD7 ENTPD7 ectonucleoside triphosphate diphosphohydrolase 7‐

00045703 COX15 COX15 homolog, cytochrome c oxidase assembly pro

CUTC CUTC cutC copper transporter homolog (E. coli)

CUTC LOC10085126 copper homeostasis protein cutC homolog

ABCC2 ABCC2 ATP‐binding cassette, sub‐family C (CFTR/MRP), mem

DNMBP DNMBP dynamin binding protein

CPN1 CPN1 carboxypeptidase N, polypeptide 1

00023939 LOC511498 cytochrome P450, family 2, subfamily c

00007588 ERLIN1 ER lipid raft associated 1

00007591 CHUK conserved helix‐loop‐helix ubiquitous kinase

00007594 CWF19L1 CWF19‐like 1, cell cycle control (S. pombe)

00010739 LOC519172 biogenesis of lysosome‐related organelles complex‐1

PKD2L1 PKD2L1 polycystic kidney disease 2‐like 1

PKD2L1 LOC10190960 polycystic kidney disease 2‐like 1 protein‐like

00047957 LOC10190605 acyl‐CoA desaturase‐like

00045728 SCD stearoyl‐CoA desaturase (delta‐9‐desaturase)

WNT8B WNT8B wingless‐type MMTV integration site family, membe

SEC31B SEC31B SEC31 homolog B (S. cerevisiae)

00000091 NDUFB8 NADH dehydrogenase (ubiquinone) 1 beta subcomp

00000092 HIF1AN hypoxia inducible factor 1, alpha subunit inhibitor

PAX2 PAX2 paired box 2

PAX2 LOC789450 paired box protein Pax‐2‐like


00018604 SEMA4G sema domain, immunoglobulin domain (Ig), transme

00003294 MRPL43 mitochondrial ribosomal protein L43

00003296 C26H10orf2 chromosome 26 open reading frame, human C10orf

LZTS2 LZTS2 leucine zipper, putative tumor suppressor 2

00039834 LOC511930 uncharacterized LOC511930

00005015 SFXN3 sideroflexin 3

KAZALD1 KAZALD1 Kazal‐type serine peptidase inhibitor domain 1

00011080 TLX1 T‐cell leukemia homeobox 1

LBX1 LBX1 ladybird homeobox 1

BTRC BTRC beta‐transducin repeat containing

POLL POLL polymerase (DNA directed), lambda

00003578 DPCD deleted in primary ciliary dyskinesia homolog (mous

00003579 FBXW4 F‐box and WD repeat domain containing 4

00001530 FGF8 fibroblast growth factor 8 (androgen‐induced)

00016335 NPM3 nucleophosmin/nucleoplasmin 3

MGEA5 MGEA5 meningioma expressed antigen 5 (hyaluronidase)

KCNIP2 KCNIP2 Kv channel interacting protein 2

C10orf76 C26H10orf76 chromosome 26 open reading frame, human C10orf

LDB1 LDB1 LIM domain binding 1

PPRC1 PPRC1 peroxisome proliferator‐activated receptor gamma,

00007435 NOLC1 nucleolar and coiled‐body phosphoprotein 1

00015700 ELOVL3 ELOVL fatty acid elongase 3

PITX3 PITX3 paired‐like homeodomain 3

00006014 GBF1 golgi brefeldin A resistant guanine nucleotide exchan

NFKB2 NFKB2 nuclear factor of kappa light polypeptide gene enhan

00021065 TMEM180 transmembrane protein 180

00021067 ACTR1A ARP1 actin‐related protein 1 homolog A, centractin a

00021067 ACTR1B ARP1 actin‐related protein 1 homolog B, centractin b

SUFU SUFU suppressor of fused homolog (Drosophila)

00021071 TRIM8 tripartite motif containing 8

00004318 ARL3 ADP‐ribosylation factor‐like 3

00004321 SFXN2 sideroflexin 2

WBP1L WBP1L WW domain binding protein 1‐like

WBP1L C26H10orf26 chromosome 26 open reading frame, human C10orf2

00014335 CYP17A1 cytochrome P450, family 17, subfamily A, polypeptid

00014335 LOC10190842 steroid 17‐alpha‐hydroxylase/17,20 lyase‐like




00021246 C26H10orf32 chromosome 26 open reading frame, human C10orf3

00021246 LOC10190848 UPF0693 protein C10orf32 homolog

00036127 AS3MT arsenic (+3 oxidation state) methyltransferase

CNNM2 CNNM2 cyclin M2

00012858 NT5C2 5'‐nucleotidase, cytosolic II

00002717 INA internexin neuronal intermediate filament protein, a

PCGF6 PCGF6 polycomb group ring finger 6

00009709 TAF5 TAF5 RNA polymerase II, TATA box binding protein (T

00021942 HPS6 Hermansky‐Pudlak syndrome 6

racted using the Biomart tool (http://www.biomart.org/). GO Term Name GO Term AccSCF complex assembly GO:0010265protein localization GO:0008104DNA‐dependent DNA replication GO:0006261negative regulation of innate immune response GO:0045824integral to membrane GO:0016021)

positive regulation of stem cell proliferation GO:2000648oxidation‐reduction process GO:0055114negative regulation of transforming growth factor beta receptor signaling pathway GO:0030512positive regulation of fat cell differentiation GO:0045600translation GO:0006412integral to membrane GO:0016021integral to membrane GO:0016021hippo signaling cascade GO:0035329embryonic neurocranium morphogenesis GO:0048702positive regulation of G0 to G1 transition GO:0070318regulation of cell cycle arrest GO:0071156

negative regulation of transcription from RNA polymerase II promoter GO:0000122protein binding GO:0005515protein complex localization GO:0031503sister chromatid cohesion GO:0007062Arp2/3 complex‐mediated actin nucleation GO:0034314regulation of ARF protein signal transduction GO:0032012neurotransmitter transport GO:0006836neurotransmitter transport GO:0006836oxidation‐reduction process GO:0055114centrosome GO:0005813Golgi cisterna membrane GO:0032580tissue regeneration GO:0042246intracellular protein kinase cascade GO:0007243DNA repair GO:0006281I‐kappaB phosphorylation GO:0007252chondrocyte differentiation GO:0002062integral to membrane GO:0016021ubunit 4

protein binding GO:0005515intracellular membrane‐bounded organelle GO:0043231regulation of ion transmembrane transport GO:0034765positive regulation of cytokine production involved in inflammatory response GO:1900017

purine ribonucleoside monophosphate biosynthetic process GO:0009168execution phase of apoptosis GO:0097194ATP hydrolysis coupled proton transport GO:0015991regulation of apoptotic process GO:0042981release of cytochrome c from mitochondria GO:0001836actin filament depolymerization GO:0030042protein import into peroxisome membrane GO:0045046

protein polymerization GO:0051258regulation of cell shape GO:0008360carbohydrate binding GO:0030246intracellular protein transport GO:0006886signal transduction GO:0007165cellular response to ATP GO:0071318T cell costimulation GO:0031295nucleolus GO:0005730positive regulation of substrate adhesion‐dependent cell spreading GO:1900026biosynthetic process GO:0009058negative regulation of adenylate cyclase activity GO:0007194nucleocytoplasmic transport GO:0006913regulation of translational initiation GO:0006446protein binding GO:00055153

transcription from RNA polymerase I promoter GO:0006360oligodendrocyte differentiation GO:0048709protein kinase C‐activating G‐protein coupled receptor signaling pathway GO:0007205organic anion transport GO:0015711filopodium assembly GO:0046847cardiolipin biosynthetic process GO:0032049regulation of epidermal cell differentiation GO:0045604integral to membrane GO:0016021positive regulation of proteasomal ubiquitin‐dependent protein catabolic process GO:0032436positive regulation of proteasomal ubiquitin‐dependent protein catabolic process GO:0032436protein retention in ER lumen GO:0006621post‐embryonic development GO:0009791synapsis GO:0007129

protein localization GO:0008104protein import into mitochondrial outer membrane GO:0045040proteolysis GO:0006508positive regulation of mRNA catabolic process GO:0061014centrosome localization GO:0051642microtubule‐based process GO:0007017

negative regulation of transcription from RNA polymerase II promoter GO:0000122metabolic process GO:0008152DNA cytosine deamination GO:0070383negative regulation of transcription from RNA polymerase II promoter GO:0000122positive regulation of DNA biosynthetic process GO:2000573translation GO:0006412regulation of long‐term neuronal synaptic plasticity GO:0048169heart morphogenesis GO:0003007mitochondrial fusion GO:0008053gluconeogenesis GO:0006094nucleoplasm GO:0005654regulation of ion transmembrane transport GO:0034765

endosome GO:0005768

positive regulation of nuclear‐transcribed mRNA catabolic process, deadenylation‐dGO:1900153

purine ribonucleotide biosynthetic process GO:0009152positive regulation of protein catabolic process GO:0045732smooth muscle cell differentiation GO:0051145G‐protein coupled receptor signaling pathway GO:0007186AMP transport GO:0080121response to stress GO:0006950glomerular filtration GO:0003094protein ubiquitination involved in ubiquitin‐dependent protein catabolic process GO:0042787nucleosome assembly GO:0006334protein N‐linked glycosylation GO:0006487

prostaglandin metabolic process GO:0006693histone H4 deacetylation GO:0070933cellular protein localization GO:0034613

vesicle‐mediated transport GO:0016192cellular response to copper ion GO:0071280signal transduction GO:0007165protein ubiquitination involved in ubiquitin‐dependent protein catabolic process GO:0042787GPI anchor biosynthetic process GO:0006506GPI anchor biosynthetic process GO:0006506regulation of defense response to virus GO:0050688protein ubiquitination GO:0016567protein dephosphorylation GO:0006470urate metabolic process GO:0046415negative regulation of G1/S transition of mitotic cell cycle GO:2000134response to vitamin D GO:0033280negative regulation of bone mineralization GO:0030502biomineral tissue development GO:0031214proteolysis GO:0006508negative regulation of smooth muscle cell differentiation GO:0051151

mitotic chromosome condensation GO:0007076regulation of transcription from RNA polymerase II promoter GO:0006357axon extension involved in axon guidance GO:0048846binding GO:0005488regulation of ion transmembrane transport GO:0034765positive regulation of inner ear receptor cell differentiation GO:2000982

DNA binding GO:0003677nucleosome assembly GO:0006334protein ubiquitination GO:0016567inositol phosphate‐mediated signaling GO:0048016metal ion binding GO:0046872mitochondrion GO:0005739proton transport GO:0015992proton transport GO:0015992proton transport GO:0015992proton transport GO:0015992protein polymerization GO:0051258epithelial tube branching involved in lung morphogenesis GO:0060441

negative regulation of transcription, DNA‐dependent GO:0045892energy reserve metabolic process GO:0006112proteolysis GO:0006508retrograde transport, endosome to Golgi GO:0042147

positive regulation of viral genome replication GO:0045070nucleocytoplasmic transport GO:0006913protein binding GO:0005515

85

WW domain binding GO:0050699positive regulation of type I interferon‐mediated signaling pathway GO:0060340gluconeogenesis GO:0006094histone methylation GO:0016571regulation of RNA splicing GO:0043484cellular response to organic cyclic compound GO:0071407synapsis GO:0007129positive regulation of hyaluranon cable assembly GO:1900106male gonad development GO:0008584

1

membrane GO:0016020phosphorelay signal transduction system GO:0000160protein binding GO:0005515mitotic cell cycle GO:0000278

protein binding GO:0005515protein binding GO:0005515protein binding GO:0005515Golgi stack GO:0005795regulation of ryanodine‐sensitive calcium‐release channel activity GO:0060314cytoplasm GO:0005737cytoplasmic microtubule GO:0005881double‐strand break repair GO:0006302

proteasome complex GO:0000502

positive regulation of endothelial cell migration GO:0010595spindle pole GO:0000922cellular response to heat GO:0034605response to oxidative stress GO:0006979neuromuscular process controlling posture GO:0050884protein phosphorylation GO:0006468positive regulation of Rab GTPase activity GO:0032851protein linear polyubiquitination GO:0097039regulation of glucose transport GO:0010827neuronal cell body GO:004302596

defense response GO:0006952defense response to bacterium GO:0042742

defense response to bacterium GO:0042742defense response to bacterium GO:0042742defense response to bacterium GO:0042742defense response to bacterium GO:0042742GTP catabolic process GO:0006184membrane protein proteolysis GO:0033619negative regulation of sequence‐specific DNA binding transcription factor activity GO:0043433mitochondrial membrane GO:0031966negative regulation of intrinsic apoptotic signaling pathway GO:2001243regulation of mitotic spindle organization GO:0060236cardiac muscle tissue morphogenesis GO:0055008dephosphorylation GO:0016311cellular protein modification process GO:0006464protein folding GO:0006457 member 7

protein phosphorylation GO:0006468integral to membrane GO:0016021regulation of transcription from RNA polymerase II promoter GO:0006357somitogenesis GO:0001756spindle assembly involved in mitosis GO:0090307negative regulation of retinoic acid receptor signaling pathway GO:0048387112

tumor necrosis factor‐mediated signaling pathway GO:0033209negative regulation of histone H3‐K9 methylation GO:0051573negative regulation of histone H3‐K9 methylation GO:0051573negative regulation of microtubule polymerization GO:0031115negative regulation of microtubule polymerization GO:0031115spermatogenesis GO:0007283spermatogenesis GO:0007283lipid binding GO:0008289lipid binding GO:0008289lipid binding GO:0008289cytoplasm GO:0005737lipid binding GO:0008289lipid binding GO:0008289lipid binding GO:0008289lipid binding GO:0008289lipid binding GO:0008289lipid binding GO:0008289extracellular region GO:0005576extracellular space GO:0005615lipid binding GO:0008289

RNA modification GO:0009451regulation of sodium ion transmembrane transport GO:1902305positive regulation of neuron projection development GO:0010976regulation of amyloid precursor protein biosynthetic process GO:0042984144

negative regulation of transcription involved in G1/S transition of mitotic cell cycle GO:0071930

peroxisomal membrane GO:0005778

protein transport GO:0015031catalytic step 2 spliceosome GO:0071013translational initiation GO:0006413hormone‐mediated signaling pathway GO:0009755hormone‐mediated signaling pathway GO:0009755one‐carbon metabolic process GO:0006730positive regulation of protein catabolic process GO:0045732transport GO:0006810autophagic vacuole assembly GO:0000045regulation of JAK‐STAT cascade GO:0046425autophagic vacuole assembly GO:0000045DNA‐dependent transcription, initiation GO:0006352glutathione biosynthetic process GO:0006750metabolic process GO:0008152glutathione biosynthetic process GO:0006750myosin complex GO:0016459ubiquitin‐dependent protein catabolic process GO:0006511ubiquitin‐dependent protein catabolic process GO:0006511membrane GO:0016020hemostasis GO:0007599proteolysis GO:0006508mature ribosome assembly GO:0042256

cytoplasmic membrane‐bounded vesicle GO:0016023hindlimb morphogenesis GO:0035137centriole‐centriole cohesion GO:0010457protein glycosylation GO:0006486

nucleus GO:0005634nucleus GO:0005634nucleus GO:0005634iron incorporation into metallo‐sulfur cluster GO:0018283cellular response to reactive oxygen species GO:0034614mRNA processing GO:0006397histone H4‐K16 acetylation GO:00439841

cortical actin cytoskeleton organization GO:0030866

cell‐cell signaling GO:0007267myosin II complex GO:0016460negative regulation of transcription from RNA polymerase II promoter GO:0000122negative regulation of transcription from RNA polymerase II promoter GO:0000122negative regulation of calcium‐mediated signaling GO:0050849cytoplasm GO:0005737

regulation of innate immune response GO:0045088regulation of lipid kinase activity GO:0043550

chromosome segregation GO:0007059regulation of autophagy GO:0010506binding GO:0005488protein N‐linked glycosylation via asparagine GO:0018279positive regulation of hormone secretion GO:0046887integral to membrane GO:0016021negative regulation of intrinsic apoptotic signaling pathway GO:2001243positive regulation of cAMP biosynthetic process GO:0030819metal ion binding GO:0046872defense response to bacterium GO:0042742lymphangiogenesis GO:0001946

regulation of transcription from RNA polymerase II promoter GO:0006357cellular polysaccharide biosynthetic process GO:0033692embryonic hindlimb morphogenesis GO:0035116integral to membrane GO:0016021integral to membrane GO:0016021integral to membrane GO:0016021

protein binding GO:0005515vesicle-mediated transport GO:0016192keratan sulfate metabolic process GO:0042339carbohydrate transport GO:0008643circadian rhythm GO:0007623circadian rhythm GO:0007623JUN phosphorylation GO:0007258extracellular region GO:0005576protein import into peroxisome membrane GO:0045046transferase activity, transferring glycosyl groups GO:0016757negative regulation of transcription from RNA polymerase II promoter GO:0000122response to glucocorticoid stimulus GO:0051384macrophage differentiation GO:0030225transport GO:0006810hydrolase activity GO:0016787heme a biosynthetic process GO:0006784protein tetramerization GO:0051262protein tetramerization GO:0051262ATP catabolic process GO:0006200regulation of Rho protein signal transduction GO:0035023proteolysis GO:0006508oxidation‐reduction process GO:0055114ER‐associated protein catabolic process GO:0030433I‐kappaB phosphorylation GO:0007252metabolic process GO:0008152extrinsic apoptotic signaling pathway via death domain receptors GO:0008625detection of mechanical stimulus GO:0050982detection of mechanical stimulus GO:0050982oxidation‐reduction process GO:0055114fatty acid biosynthetic process GO:0006633cell fate commitment GO:0045165

vesicle coat GO:0030120mitochondrial electron transport, NADH to ubiquinone GO:0006120negative regulation of Notch signaling pathway GO:0045746negative regulation of reactive oxygen species metabolic process GO:2000378negative regulation of reactive oxygen species metabolic process GO:2000378

multicellular organismal development GO:0007275mitochondrion GO:0005739transcription from mitochondrial promoter GO:0006390protein binding GO:0005515protein binding GO:0005515iron ion homeostasis GO:0055072regulation of cell growth GO:0001558regulation of transcription, DNA‐dependent GO:0006355neuron fate determination GO:0048664mammary gland epithelial cell proliferation GO:0033598nucleotide‐excision repair GO:0006289ventricular system development GO:0021591cartilage development GO:0051216outflow tract septum morphogenesis GO:0003148rRNA transcription GO:0009303

clustering of voltage‐gated potassium channels GO:0045163binding GO:0005488epithelial structure maintenance GO:0010669nucleus GO:0005634nucleolus organization GO:0007000fatty acid elongation, monounsaturated fatty acid GO:0034625lens development in camera‐type eye GO:0002088regulation of ARF protein signal transduction GO:0032012follicular dendritic cell differentiation GO:0002268integral to membrane GO:0016021centrosome GO:0005813centrosome GO:0005813negative regulation of transcription from RNA polymerase II promoter GO:0000122PML body GO:0016605cilium morphogenesis GO:0060271iron ion homeostasis GO:0055072

26

hormone biosynthetic process GO:0042446hormone biosynthetic process GO:0042446hormone biosynthetic process GO:0042446hormone biosynthetic process GO:0042446hormone biosynthetic process GO:004244632

cellular protein modification process GO:0006464magnesium ion homeostasis GO:0010960nucleotide metabolic process GO:0009117

nervous system development GO:0007399negative regulation of transcription, DNA‐dependent GO:0045892transcription initiation from RNA polymerase II promoter GO:0006367pigmentation GO:0043473

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Table S4 for





Table S4. Candidate regions identified by the analysis based on observed heterozygosity

(ObsHtz-CR), averaged in sliding windows of 9 SNPs (ObsHtz-9SNPW), that were

exclusively detected in dairy breeds. The interval of each region is referred (in bp) to the

sheep genome reference sequence v2.0 (http://www.livestockgenomics.csiro.au/cgi-

bin/gbrowse/oarv2.0/). The corresponding orthologous bovine genomic intervals are given

based on the bovine genome reference sequence UMD 3.1

(http://www.ensembl.org/Bos_taurus/Info/Index). The positional candidate genes that map

within the bovine candidate range and that are included as candidate genes for milk

production and mastitis traits in the database provided by Ogorevc et al. [1] are indicated

as functional candidate genes. The affected trait and reference in the SheepQTL and

CattleQTL databases (at http://www.animalgenome.org/cgi-bin/QTLdb/index) for

previously reported ovine and bovine QTL that map within the corresponding genomic

regions and that influence milk production traits and some other functional traits related to

dairy production are also indicated.

REFERENCES

[1] Ogorevc J, Kunej T, Razpet A, Dovc P (2009) Database of cattle candidate genes and genetic markers for milk production and mastitis. Anim Genet 40: 832-851.

http://www.animalgenome.org/cgi-bin/QTLdb/index

ObsHtz-Candidate region only detected in dairy breeds

Sheep genome range (Mb) (Oar v2.0)

Bovine genome range (Mb) (UMD 3.1)

Functional candidate genes based on Ogorevc et al. [1]

QTL described in sheep (SheepQTLdb identifier1)

QTL described in cattle in relation to milk production and functional dairy traits (CattleQTLdb identifier2)

Nb. of positional candidates3

ObsHtz-CR3 OAR2: 20.132 – 20.274

BTA8: 94.200 – 94.210 Milk fat percentage (DYD) (13913)

Foot angle (3599), Stature (16279, 16280, 16281)

1

ObsHtz-CR7 OAR2: 180.309 – 183.404

BTA2: 67.936 – 70.143

Milk yield (14147), Milk lactose yield (13991)

Milk fat percentage (2650), Milk fat yield (2737), Milk protein yield (4494)

5

ObsHtz-CR8 OAR2: 199.479 – 199.814

BTA2: 86.439 – 86.694

HSPD1 Milk lactose yield (13991)

Palmitoleic acid content (5812), Milk protein yield (EBV) (6045, 9985), Milk fat percentage (daughter deviation) (9983), Milk protein percentage (daughter deviation) (9984)

6

ObsHtz-CR10 OAR2: 232.587 – 234.454

BTA2: 119.341 – 121.226

Somatic cell score (EBV) (6152)

28

ObsHtz-CR12 OAR3: 18.648 – 18.859

BTA11: 87.474 – 87.566

Milk fat yield (2669) 3

ObsHtz-CR25 OAR5: 40.407 – 41.107

BTA7: 43.939 – 44.939

Foot angle (14181) Somatic cell score (2667)

29

ObsHtz-CR28 OAR7: 19.072 – 19.258

BTA10: 19.198 –19.317 Milk fat yield (10295). Milk protein yield (10297), Teat length (10296), Udder attachment (10294), Milk protein percentage (EBV) (10015)

2

ObsHtz-CR29 OAR7: 42.026 – 43.570

BTA10: 45.205 – 46.769

Milk protein percentage (13998)

Milk fat yield (daughter deviation) (10219), Milk yield (2554)

19

ObsHtz-CR31 OAR8: 78.041 – 78.759

BTA9: 92.429 –93.241 Milk fat yield QTL (1520), Clinical mastitis (10087), Milk protein percentage (2534), Milk protein yield (daughter deviation) (3752, 3755), Milk yield (daughter deviation) (3736, 3739)

6

ObsHtz-CR41 OAR13: 39.885 – 41.694

BTA13: 41.248 – 42.894

Milk protein percentage (2672), Rump angle (3429), Milk fat yield (2555)

17

ObsHtz-CR45 OAR16: 48.036 – 48.143

BTA20: 46.768 – 49.061

Milk fat percentage (EBV) (11329), Milk fat yield (EBV) (11328), Milk protein percentage (EBV) (11330), Udder attachment (10323), Udder depth (10322), Milk protein percentage (4805), Somatic cell score (13244)

0

ObsHtz-CR55 OAR25: 18.149 – 18.354

BTA28: 19.393 – 19.807

Milk Fat percentage (14010)

Milk protein percentage (EBV) (10017) Milk yield QTL (2691) Udder composite index (1663) Udder height (1661)

2

1Search QTL identifier number at http://www.animalgenome.org/cgi-bin/QTLdb/index to find complete details about the QTL reported in the sheep genomic region

(SheepQTL database) and its corresponding orthologous bovine region (CattleQTL database) for the candidate region identified in this study.

http://www.animalgenome.org/cgi-bin/QTLdb/index

Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

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