6/20/2019 1 S‐1064 Raluca Mateescu | Associate Professor Animal Genomics BIF, June 2019 Improving thermotolerance in beef cattle – a genomic approach Beef cattle in the world • > 50% cattle in the world – maintained in hot and humid environments • including ~ 40% of beef cows in US Global distribution of cattle Bos Indicus cattle • Approximately 80% of global beef production is Bos Indicus based. Bos indicus germplasm: • Critical role in US and worldwide beef production • Particularly when used as part of a well‐structured crossbreeding program • Adapted to heat and humidity • Resistant (or at least tolerant) to internal and external parasites • In crossbreeding systems produce improved cattle: • Fertile • Gain well • Long lived Thermotolerance • Climatic stress ‐ major limiting factor of production efficiency • Genomic tools can help select Animals with superior ability for both thermal adaptation and food production Energy‐efficient, sustainable approach to meet the challenge of global climate change. In response to heat stress, cattle will regulate: Goal: Develop genomic tools to select for superior ability for both thermal adaptation and food production. Goal: Develop genomic tools to select for superior ability for both thermal adaptation and food production. Heat Production Heat Production Modulating basal metabolic rate Changing: feed intake, growth, lactation, activity Heat Exchange Heat Exchange Blood flow to the skin Evaporative heat loss through sweating & panting Research Populations – pilot data • UF Multibreed Angus x Brahman Herd • Summer 2017, 2018 • 335 cows: from 100% Brahman to 100% Angus Breed Group Angus % Brahman % 1 Angus 100 0 2 75%A 75 25 3 Brangus 62.5 37.5 4 50%A 50 50 5 25%A 25 75 6 Brahman 0 100 1 2 3 4 5 6
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
6/20/2019
1
S‐1064
Raluca Mateescu | Associate Professor Animal Genomics
BIF, June 2019
Improving thermotolerance in beef cattle – a genomic approach
Beef cattle in the world•> 50% cattle in the world – maintained in hot and humid environments • including ~ 40% of beef cows in US
Global distribution of cattle
Bos Indicus cattle• Approximately 80% of global beef production is Bos Indicus based.
Bos indicus germplasm:• Critical role in US and worldwide beef production
• Particularly when used as part of a well‐structured crossbreeding program
• Adapted to heat and humidity
• Resistant (or at least tolerant) to internal and external parasites
• In crossbreeding systems produce improved cattle:
• Fertile
• Gain well
• Long lived
Thermotolerance
• Climatic stress ‐ major limiting factor of production efficiency
• Genomic tools can help select
Animals with superior ability for both thermal adaptation and food production Energy‐efficient, sustainable approach to meet the challenge of global climate change.
In response to heat stress, cattle will regulate:
Goal: Develop genomic tools to select for superior ability for both thermal adaptation and food production.
Goal: Develop genomic tools to select for superior ability for both thermal adaptation and food production.
Heat ProductionHeat Production
Modulating basal metabolic rate
Changing: feed intake,
growth, lactation, activity
Heat ExchangeHeat Exchange
Blood flow to the skin
Evaporative heat loss through sweating & panting
Research Populations – pilot data
•UF Multibreed Angus x Brahman Herd• Summer 2017, 2018 •335 cows: from 100% Brahman
to 100% Angus
Breed Group Angus % Brahman %
1 Angus 100 02 75%A 75 253 Brangus 62.5 37.54 50%A 50 505 25%A 25 756 Brahman 0 100
1 2
3 4
5 6
6/20/2019
2
Internal Body Temperature• Vaginal temperature at 15‐min intervals for 5 days
• Air temperature and relative humidity ‐ recorded continuously in the pastures
1 inch
CIDR
iButton
DS1922L iButton Temperature Logger ‐Maxim Integrated Products, 120 San Gabriel Drive, Sunnyvale, CARange: ‐40°C to +85°CResolution: 0.0625°C (11 bit) or 0.5°C (8 bit)
THI = (1.8 * dbt + 32)‐[(0.55‐0.0055*rh)*(1.8*dbt‐26.8)]THI = (1.8 * dbt + 32)‐[(0.55‐0.0055*rh)*(1.8*dbt‐26.8)]
65
67
69
71
73
75
77
79
81
83
85
38
38.2
38.4
38.6
38.8
39
39.2
39.4
39.6
39.8
0 2 4 6 8 10 12 14 16 18 20 22
THI
Body Temp (°C)
Hour
Breed effect on body temperature
vagtmp every 15 min by day ‐ REPEATED with cov structure type = ARH(1)
Critical heat stressMajor heat stressModerate heat stressMinimal heat stress≤ 75
≥ 84
75 ‐ 7879 ‐ 83
Phenotypic Plasticicty• Ability of an individual to alter its phenotype in response to changes in environmental conditions
The ability of one genotype to produce more than one phenotype when exposed to different environments.
Environment
Phenotype
Environment
Phenotype
Environment
Phenotype
No Plasticity Plasticity High Plasticity, strong GxE
Each of the colored lines is a "Reaction Norm"Each of the colored lines is a "Reaction Norm"
Genotype A
Genotype B
Genotype C
72
74
76
78
80
82
84
86
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Representing reaction norms in models
Environment
Phenotype
Intercept
Gi
E0
Pi 0
Slope
Linear reaction norm{Pi0 , s}: intercept and slope are considered as the evolving traits.Pi (E): reaction norm is represented by a flexible function which
can evolve like a trait
Pi (E)
Low THI (74‐76)
High THI (84‐86)
Mean THI (79‐81)
THI over 24 hours
38.6
38.7
38.8
38.9
39.0
39.1
39.2
39.3
39.4
39.5
74‐76 79‐81 84‐86
Body Temperature (C)
AngusBrahman
Breed effect on phenotypic plasticity
Estimate the effect of various % of Brahman genes on phenotypic plasticity Use a reaction norm approach via random regression mixed models.
38.6638.63
Intercept
Breed effect on phenotypic plasticity
• Estimate the effect of various % of Brahman genes on phenotypic plasticity
• Use a reaction norm approach via random regression mixed models.
THI
Breed Intercept SlopeAngus 38.66 0.4275%A 38.56 0.33Brangus 38.58 0.3050%A 38.60 0.2825%A 38.57 0.23
Brahman 38.63 0.20
THI THI
38.5
38.6
38.7
38.8
38.9
39.0
39.1
39.2
39.3
39.4
39.5
74‐76 79‐81 84‐86
Body Temperature (C)
Angus75%ABrangus50%A25%ABrahman
7 8
9 10
11 12
6/20/2019
3
Response to different heat loads
65
67
69
71
73
75
77
79
81
83
85
38.2
38.4
38.6
38.8
39
39.2
39.4
39.6
39.8
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48
THI
Body Temp (C)
Low THI‐load day High THI‐load day
2 4 6 8 10 12 14 16 18 20 22 240 2 4 6 8 10 12 14 16 18 20 22 24
∑ 𝑖𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦 𝑥 𝑑𝑢𝑟𝑎𝑡𝑖𝑜𝑛 Heat load = ∑ 𝑖𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦 𝑥 𝑑𝑢𝑟𝑎𝑡𝑖𝑜𝑛
Factors important in thermotolerance
Coat Hair
Sweat Glands
Other Skin Prop.
Long Hair LengthLong Hair DiameterShort Hair LengthShort Hair Diameter
Factors important in thermotolerance
Coat Hair
Sweat Glands
Other Skin Prop.
Long Hair Length Short Hair Length
Factors important in thermotolerance
Coat Score
Sweat Glands
Other Skin Prop.
Angus
Brahman
Sweat Glands
0 0.25 0.5 0.75 1
Fraction of Brahman genes
Significant linear effect of percentage Brahman composition
Factors important in thermotolerance
Coat Score
Sweat Glands
Other Skin Prop.
100%A 75%A Brangus 50%A 25%A 0%A
Factors important in thermotolerance
Coat Score
Sweat Glands
Other Skin Prop.
Skin Histology
13 14
15 16
17 18
6/20/2019
4
Research (Training) Population
•Brangus heifers, Seminole Tribe of Florida
• Summer 2016, 2017, 2018
•2,300 two‐year old heifers
Thermotolerance measurements• Vaginal temperature 15 min over 5 days
• Environmental data: temperature, humidity, THI• Sweating rate
• Coat: color, coat score, hair length & diameter
• Temperament: chute and exit score
• Body condition score
• Skin biopsies: for histology & gene expression
• Weight gain over the summer/fall
• Rump fat and rib fat ultrasound
• Subsequent pregnancy status• 250K genotypes
GWAS – genomic regions individual traits
• SVS (SNP & Variation Suite) v8.8.1 (Golden Helix)
• Mixed Model GWAS using a single locus (EMMAX)
• Genomic relationship matrix• Temperature under High and Low THI, Sweat gland area, Hair length 140,467 SNPs
• Heritability estimates:• Temp Low THI = 0.24• Temp High THI = 0.36• Hair length = 0.21• Sweat gland area = 0.23
Skin Thickness
0 1 2 3 4 5
‐log1
0 P‐value
Sweat Gland Area
0 2 4 6 8 10
‐log1
0 P‐value
Long Hair Length
0 1 2 3 4 5 6 7
‐log1
0 P‐value
Short Hair Length
0 1 2 3 4 5 6 7 8
‐log1
0 P‐value
Future work•Gene networks for individual thermoregulation and production traits
• Transcriptomics analysis of skin tissues
•eQTL analysis to reveal genetic pathways for thermotolerance which are independent or positively associated with production performance
Conclusions
•Cattle with different Brahman percentage vary in their phenotypic plasticity of core body temperature in response to environmental heat stress.
• The thermoregulation associated traits have a genetic component (h2 ~ 0.2 ‐ 0.3)
•Multi‐omics approach can identify genetic pathways for thermotolerance which are independent or positively associated with production performance
Increase tolerance to heat stress, while simultaneously allowing for increased efficiency of production.
Increase tolerance to heat stress, while simultaneously allowing for increased efficiency of production.
Financial SupportFinancial Support
•USDA‐NIFA Grant 2017‐67007‐26143•UF Agricultural Experim. Station
•UF ANS Hatch Project
• Seminole Tribe of Florida•Brangus Breeders Association
•Florida Beef Council• Florida Cattlemen’s Association
AcknowledgmentsUniversity of FloridaUniversity of Florida
• Dr. Pete Hansen• Dr. Mauricio Elzo
• Dr. Dwain Johnson• Dr. Tracy Scheffler• Dr. Jason Schaffler
• Dr. Serdal Dikmen• Danny Driver• Michelle Driver
• Joel Leal, Heather Hamblen, Sarah Flowers, Kaitlyn Sarlo, Mesfin Gobena, Eduardo Rodriquez, Zaira Estrada
•Adriana Zolini, William Ortiz, Samantha Eifert, Lauren Peacock, Alexa Chiroussot
Seminole Tribe of Florida
Seminole Tribe of Florida
• Alex Johns• Phillip Clark
• Sheri Holmes
• Bobby Yates• Mike Ciorocco
• Dayne Johns, etc.
19 20
21 22
23 24
Related Documents
