Genetic Diversity in Wild and Cultivated Peanut Sameer Khanal B.S. Tribhuvan University, Nepal Advisors: Dr. Steven J. Knapp Committee: Dr. Albert K. Culbreath Dr. E. Charles Brummer In Partial Fulfillment of the Requirements for the Degree Master of Science in Agronomy
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Genetic Diversity in Wild and Cultivated Peanut
Sameer KhanalB.S. Tribhuvan University, Nepal
Advisors: Dr. Steven J. Knapp Committee: Dr. Albert K. Culbreath
Dr. E. Charles Brummer
In Partial Fulfillment of the Requirements for the Degree Master of Science in Agronomy
Topical Breakdown
1. Introduction
3. Discovery and characterization of SSRs from tetraploid EST Database4. SSR Diversity in A- and B-Genome Diploid Peanut Species
2. Mining A- and B-Genome Diploid and AB-Genome Tetraploid GSSs for SSRs
5. Summary
1.2. Economic Importance1.3. Production Constraints1.4. Improvement Gridlocks1.5. Genomics and Molecular Breeding
1.6. Research ObjectivesObjectivesMaterials and MethodsResults and DiscussionConclusion
1.1. Arachis spp.
1.1. Arachis spp.
Belongs to the family of legumes (Fabaceae)
Gene pool includes 80 accepted species assembled into 9 sections1,2
Cultivated peanut (Arachis hypogaea L.) belongs to section Arachis together with 32 other wild diploids and a wild tetraploid species, A. monticola
1. Krapovickas and Gregory 1994 2. Valls and Simson 2005
1.2. Economic Importance
Cultivated in tropical, sub-tropical, and warm-temperate regions of more than 100 countries
Second most important legume after soybean
Third most important source of vegetable protein
Fourth most important source of vegetable oil
Twelfth most important food crop
Source: FOASTAT (http://faostat.fao.org
1.3. Production Constraints
Source: Compiled from plantpathology.tamu.edu
edis.ifas.ufl.edu/IN176
Biotic Constraints
Diseases
Insect-Pests
Abiotic Constraints
Drought
High Temp.
Abiotic Constraints
Drought
High Temp. Source: environmentalgraffiti.com
1.4. Improvement Constraints
2n Gametes Or
Spontaneous
Chromosome Doubling
AA (n=10) BB (n=10)
AABB (n=20)
Parents
Allotetraploid peanut Source: Figure Modified from
Bertioli1. Kochert et al. 1991 2. Burow et al. 2001 3. Halward et al. 1991 4. Knauft and Gorbet 1989 5. Stalker 1997
Low genetic variation and breeding bottlenecks
Reasons:
• Reproductive isolation of an amphidiploid1
• Monophyletic origin2
• Autogamy3
• Narrow genetic base4
• Rearing susceptible genotypes under chemical intensive systems5
1.4. Improvement Constraints
A. cardinasii (AA) A. diogoi (AA)X
AA
TXAG-6
Parents
INTERSPECIFIC HYBRIDIZATION
F1 hybrid
CHROMOSOME DOUBLING
Tetraploid
X
Florunner
AB
INTERSPECIFIC HYBRIDIZATION
X
A. batizocoi (BB)
BC5F3 COAN1
Development of COAN and NemaTAM
NemaTAM2 BC7F3
Introgression of traits of interest from exotic spp. is desirable
Large number of introgression lines
Very few introgression cultivars have been released
Reasons:
1. Complex crosses
2. Resource intensive
3. Linkage drag
4. Lack of molecular tools
1. Simpson and Starr 2. Simpson et al. 2003
1.5. Genomics and Molecular Breeding Lagging in genomic resources to address pertinent problems with
molecular breeding solutions.
Linkage maps
1. Diploid RFLP map produced from an interspecific hybrid1 Mapping population: A. stenosperma x A. cardinasii 117 markers mapped along 11 linkage groups
2. Microsatellite-based map published in Arachis2 Mapping population A. duranensis x A. stenosperma170 SSRs mapped along 11 linkage groups
3. Tetraploid RFLP map produced from a complex hybrid3 A. hypogaea x ‘synthetic’ amphidiploid [A. batizocoi x A. diogoi] 370 RFLP loci mapped on 23 linkage groups
1. Halward et al. 1993 2. Burow et al. 2002 3. Moretzsohn et al. 2005
1.6. Research Objectives
To access the frequency of polymorphic SSRs in the genic and non-genic DNA sequences of Arachis
To access genetic diversity in wild and cultivated peanut
To develop and report additional DNA markers and genomics resources
2. Mining A- and B-Genome Diploid and AB-Genome Tetraploid GSSs for SSRs
2.1. Objectives
To estimate enrichment for genic DNA sequences using methylation-filtration
To develop and characterize genome survey sequence-derived SSRs (GSS-SSRs)
2.2. Materials and Methods
Figure 2.2.1. Number of genome survey sequences (GSSs) from methylation-filtered (MF) and unfiltered (UF) genomic libraries of peanut.
2.2. Materials and Methods Mining tool and criteria: SSRIT1; minimum no. of repeats (n) = 5 Primer design tool: Primer32
PCR amplicons resolved in SSCP gels and haplotypes were scored
1. Temnykh et al. 2001 2. Rozen and Skaletsky 2000
Table 2.2.1. Arachis germplasm screened for SSR marker amplification and length polymorphisms.
2.3. Results and Discussion Methylation filtration
produced enrichment in the range of 4.4 to 14.6 for genic DNA
Gene enrichment suggested a reduction of:
- 1,240 Mb A. duranensis to 279 Mb gene space
- 951 Mb A. batizocoi to 65.14 Mb gene space
- 2,813 Mb A. hypogaea to 478.40 Mb space
500,000 to 10,000,000 MF sequence reads for 1x raw coverage of Arachis genome
Table 2.3.1. Example: Calculation of filter power for A. duranensis.
2.3. Results and Discussion
Table 2.3.2. Annotation statistics of methylation-filtered (MF) and unfiltered (UF) GSSs from Arachis.
MF showed reduced representation of repetitive fraction of the genome in the sequence database
2.3. Results and Discussion
A total of 1,168 SSRs were interspersed in 960 GSSs
Figure 2.3.1. Abundance of di-, tri-, and tetranucleotide repeats among 9,517 genomic survey sequences of Arachis.
Dinucleotide repeats were the predominant repeat type in the GSSs
2.3. Results and Discussion
97 out of 153 SSR markers amplified alleles across species and accessions and produced high-quality genotypes
A. duranensis and A. batizocoi contributed 21 markers each and A. hypogaea contributed 55 markers
93% of the markers were polymorphic among diploids with an average heterozygosity (H) of 0.57
40% of the markers were polymorphic among tetraploids (H = 0.24)
70-80% of A. hypogaea based markers were transferable to the diploids
2.3. Results and Discussion
56.7% of the markers were in genic regions and 43.3% were in non-genic regions
Among tetraploids, frequency of polymorphic markers was higher for the genic (41.8%) than the non-genic ones (38.1%)
Average heterozygosity (H) among tetraploids was equal for the genic and the non-genic SSRs
However, among diploids, H was slightly higher for the non-genic (0.59) than for the genic (0.55) SSRs
2.3. Results and Discussion Dinucleotide repeats were more polymorphic (H=0.62) than
trinucleotide (H=0.55) and tetranucleotide (H=0.51) repeats
Among tetraploids, SSRs longer than 26 bp were nearly fourfold more polymorphic (H=0.44) than SSRs shorter than 26 bp (H=0.12)
Figure 2.3.2. Relationship between the simple sequence repeat length (bp) and heterozygosity for 97 SSR markers among eight peanut germplasm accessions.
2.4. Conclusions
Methylation filtration effectively enriched for the genic DNA sequences
GSSs were abundant in SSRs
93 polymorphic SSRs were developed
Tetraploids showed narrow allelic variation, while diploids were highly polymorphic
3. Discovery and Characterization of SSRs from Tetraploid Peanut EST Database
3.1. Objectives
To describe the abundance and characteristics of simple sequence repeats (SSRs) in peanut expressed sequence tags (ESTs)
To assess polymorphisms offered by a broad spectrum of SSR repeat motifs, repeat lengths, and repeat locations
To decipher population structure of tetraploid peanut
3.2. Materials and Methods
Source of ESTs: PeanutDB; 71,448 long-read (Sanger) ESTs and 304,215 short-read (454) ESTs assembled into 101,132 unigenes
SSR Mining Tool: SSRIT1 with minimum no. of repeats = 5
Representative SSR-EST panel selected based on:SSR Repeat Motif (M): Di-, Tri-, Tetra-, Penta-, and HexanucleotideSSR Length (K) = Motif (M) x Repeat Number (N)SSR Location: Exon and UTRs
Primer Design: Primer32 online tool
Genotypes determined using ABI3730 DNA analyzer and GeneMapper Software Version 4 (Applied Biosystems, Foster City, CA)
1. Temnykh et al. 2001 2. Rozen and Skaletsky 2000
3.2. Materials and Methods
Power Marker V3.251 was used to estimate average heterozygosity (H)
Microsat2 was used to generate pair wise genetic distance matrix based on the proportion of shared bands (D = 1 – ps)
Phylip v3.673 was used for the construction of neighbor-joining tree and TreeDyn 198.34 was used for editing the tree
Principle coordinate analysis (PCoA) was performed using Microsoft excel based software GenAlexEx 6.15
Software package structure 2.26 was used for deciphering population structure
1. Liu and Muse 2005 2. Minch et al. 1997 3. Felsenstein et al. 1989 4. Chevenet et al. 5. Peakall and Smoush 2006
Figure 3.2.1. Arachis germplasm screened for EST-SSR marker amplification and length polymorphisms among 28 tetraploids and 4 diploid peanut accessions
3.3. Results and Discussion
A total of 7,413 SSRs were interspersed in 6,371 uniscripts
Figure 3.3.2. Abundance of di-, tri-, and tetranucleotide repeats ESTs
Dinucleotide repeats were the predominant repeat type in the ESTs
394952%
317643%
521%
491%187
3%
DiTriTetraPentaHexa
Figure 3.3.3. Distribution of di- and trinucleotide repeats
3.3. Results and Discussion
GSSs ESTsSeqs. With SSRs (%) 10% 7.3%SSR Freq. 1/4.7 kb 1/5 kbPolymorphic (n, among diploids) 93% 81%Polymorphic (n, among tetraploids) 40% 32%Heterozygosity (H, among diploids) 0.57 0.50Heterozygosity (H, among tetraploids) 0.24 0.11
Table 3.3.1. Comparing ESTs with GSSs
3.3. Results and Discussion In tetraploids, dinucleotide and trinucleotide SSRs were equally
polymorphic (H=0.14) Polymorphisms of SSRs in exons and UTRs were also equal Among tetraploids, SSRs longer than 26 bp were nearly three-fold
more polymorphic (H=0.18) than SSRs shorter than 26 bp (H=0.08)
Figure 2.3.2. Relationship between the simple sequence repeat length (bp) and heterozygosity for 59 SSR markers among 28 tetraploid peanut accessions.
3.3. Results and Discussion
Figure 3.3.4. Inference on number of populations and population structure of tetraploid peanut.
3.3. Results and Discussion
Figure 3.3.5. Neighbor-joining tree produced from genetic distances estimated from 59 EST-SSR markers among 28 tetraploid peanuts. Runners are shown in red, valencia in blue and Spanish in Green.
3.3. Results and Discussion
Figure 3.3.6. Principal coordinate analysis of mean genetic distance matrix. The first two principle coordinates explained 36.39% and 20.23% of the total variance.
3.4. Conclusion
Expressed sequence tags were developed, mined, and characterized for SSRs
19 polymorphic markers were developed
Polymorphic EST-SSRs were shown to be sufficient for developing a critical mass of DNA markers for genetic mapping and downstream application
4. SSR Diversity in A- and B-Genome Diploid Peanut Species
4.1. Objectives
To estimate SSR diversity in A- and B-genome diploid peanut species
To decipher population structure of A- and B-genome diploid peanut species
To develop a large number of polymorphic SSR markers in A- and B-genome mapping populations
4.2. Materials and Methods
32 previously mapped SSR markers from Moretzsohn et al. (2005) were used for the analysis
A total of 60 genotypes belonging to A. duranensis, A. batizocoi and A. stenosperma were used
Two of the genotypes (designated as BAT3 and DUR38) were not included in the statistical analysis
Final panel of 58 genotypes included 36 A. duranensis, 8 A. batizocoi, and 14 A. stenosperma
4.2. Materials and Methods
Power Marker V3.25 was used to estimate average heterozygosity (H)
Microsat2 was used to generate pair wise genetic distance matrix based on the proportion of shared bands (D = 1 – ps)
Phylip v3.67 was used for the construction of neighbor-joining tree
Principle coordinate analysis (PCoA) was performed using Microsoft excel based software GenAlexEx 6.1
Software package structure 2.2 was used for deciphering population structure
4.3. Results and Discussion 27 out of 32 markers showed amplification
Almost all the markers amplified single band in all the accessions
Average H was 0.72
Table 4.3.1. Polymorphisms of the 27 SSR markers screened among 36 A. duranensis, 8 A. batizocoi, and 14 A. stenosperma accessions..
4.3. Results and Discussion
Figure 4.3.1. Inference on number of populations and population structure of diploid peanut.
4.3. Results and Discussion
Figure 4.3.2. Population structure of diploid peanut accessions.
4.3. Results and Discussion
For accessions with location information, sites were tagged in google map
Most of the accessions shown to form a separate population group were collected at altitudes above 900 masl
Most other accessions (26) were collected at altitudes below 600 masl Figure 4.3.3. Addressing sub-Population
structure in A. duranensis accessions
4.3. Results and Discussion
D1D2D3 D4
D5
D6
D7
D9
D10
D11
D12D13 D14
D15D16
D17
D18
D19
D20
D21
D22
D23D24
D25
D26
D27D28
D29
D30 D31
D32
D33
D34
D35
D36 D37
B1
B2
B5
B7
B8B9B10B11
S1
S2S4S5
S7 S8
S9
S10S11
S12
S13
S14S15
S16
Coord. 1
Coo
rd. 2
DURBATSTP
Figure 4.3.4. Principal coordinate analysis of mean genetic distance matrix. The first two principle coordinates explained 33.71% and 21.14% of the total variance.
4.3. Results and Discussion
Figure 4.3.5. Neighbor-joining tree produced from the genetic distances estimated from 27 SSR markers screened among 58 diploid Arachis accessions including 36 A. duranensis (DUR), 8 A. batizocoi (BAT), and 14 A. stenosperma (STP).
4.3. Results and Discussion A total of 612 previously reported and 97 GSS-SSRs were screened
among 12 diploids.
Table 4.3.2. Polymorphisms of 556 SSR markers among A. duranensis, A. batizocoi, A. kuhlmanii, and A. diogoi germplasm accessions
4.4. Conclusion
We observed large genetic diversity among the diploid accessions
It is feasible to develop a critical mass of polymorphic SSR markers for the construction of high-density A- and B-genome intraspecific maps of Arachis species
AcknowledgementGraduate committee members
Institute of Plant Breeding, Genetics and Genomics