Population Structure & Genetic
Improvement in Livestock
Heather J. Huson, Ph.D.
Cornell University
Department of Anima...
Overview
Research focus
• Population structure
• Trait association
Research projects
• Thermo-tolerance in tropical c...
THERMO-TOLERANCE IN
TROPICAL CATTLE
Thermo-tolerance in Tropical Cattle
• Importance of thermo-tolerance in cattle
– Milk Production
– Reproduction
• SLIC...
Research Roll
• Identify breed relationship of SLICK- tropical
cattle
• Investigate ancestral origins of SLICK- hair
c...
Research Approach
• Use a variety of analyses to assess trait
association across the genome
– Runs Of Homozygosity
– S...
Ancestry of Senepol cattle
Red Poll
N’Dama
East
African
Zebu
• Composite Breed of the
St. Croix Virgin Island
Sene...
Genomic verification of Senepol ancestry
N’Dama Red Poll Senepol Zebu
K=4
GWAS of SLICK hair-coat
Use ancestral breeds as controls to balance SLICK
cases
Cases= 72 Controls= 61
• Senepol-2
•...
GWAS of SLICK hair-coat
639,663SNPs
Minimal Correction for Relatedness or
Population Structure
-log10p = 5
-log10p = ...
Improved GWAS of SLICK hair-coat
EMMAX Kinship Matrix- Correction for
Relatedness / Population Structure
-log10p = 5
-...
Runs of Homozygosity
Dr. Eui-Soo Kim, Iowa State University
SNP Threshold Approximate distance
100 consecutive SNPs 0.3...
Haplotype Blocks
 24 significantly associated haplotype patterns
 3 haplotype patterns identified only in SLICK
Block...
Multiple Genetic Analyses
BTA 20
37 Mb 40 Mb
SKP2 SPEF2
Keratinocyte
proliferation and skin
homeostasis
Spermatogen...
Outcomes
• Breed relationship and ancestry of SLICK-haired
tropical cattle
• Narrowed SLICK locus to 0.5 Mb on BTA 20
...
Future Directions
• Potentially 2 mutations effecting same gene
– Related to breeds
• Sequencing region to determine ca...
USAID: Feed the Future Initiative
AFRICAN GOAT IMPROVEMENT
NETWORK (AGIN)
Global Food Security
• 90% of global population located in “Hunger Zones”
• Target: African small-holder farmers
GOATS ...
Why Goats?
• Most common livestock species in Africa
– Small-holder farmers (women)
• Diverse & hardy species
– Thrive...
SAMPLING STATUS
Total Sampling Dataset
16 Countries
> 60 Sampling Sites
~ 66 Breeds/Populations
> 2,737 Goats Sampled
Egypt
Ethiopia
Kenya
Tanzania
Malawi
Zimbabwe
South Africa
Mozambique
Nigeria
Cameroon
Uganda
Breeds sampled
w...
Global Comparison
US: Spanish derived
New Zealand: Boer
Turkey: domestication
Brazil: climate, parasite
Italy: dairy ...
PHENOTYPING
Standardized Sampling Protocol
• Geographical information system (GIS) data
– Latitude, longitude, elevation
• Physical...
Variation in
body size
Is there a significance to size variation
of breeds across different countries?
Boer
Country # Goats
Malawi 18
Mozambique 2
Tanzania 13
Uganda 6
Zimbabwe 31
USA 15
Points of Note:
USA- Are indi...
Ethiopia
Gumez
Keffa
Abergelle
Woyito Guji
Breed # Goats
Abergelle 64
Gumez 53
Keffa 50
Woyito Guji 50
Ethiopian Goats
GENOTYPING STATUS
Quality Control Filtering
11 Countries, ~41 breeds/populations
952 individuals
53,347 SNPs
SNP Filtering
51,543 SNPs ...
Quality Control Filtering
11 Countries, ~41 breeds/populations
952 individuals
53,347 SNPs
SNP Filtering
51,543 SNPs ...
Quality Control Filtering
11 Countries, ~41 breeds/populations
952 individuals
53,347 SNPs
SNP Filtering
51,543 SNPs ...
Quality Control Filtering
11 Countries, ~41 breeds/populations
952 individuals
53,347 SNPs
SNP Filtering
51,543 SNPs ...
PROJECT ANALYSES
Italy
USA
(Spanish)
Brazil
Turkey
Nigeria
Egypt
Ethiopia
Kenya
Uganda
South Africa
US/NZ
Boer
Principle
Comp...
Population dynamics from the PCA
PC Eigenvalue Factor
1 31.23479 European – African
2 17.93332 Boer breed- South Africa...
PCA of African Countries Only
Principle Component 1
EV = 13.65
By Country By Breed
3 African Countries & NZ Boer
Signature of Selection- FST
Outcomes
• Both body size and genetic investigation show variation among goat
breeds
– Level of significance?
• Genomi...
Research Strategy
• Genome-wide investigation
– Thousands of markers across the genome
• Population Structure
– Relate...
Acknowledgements
Huson Lab, Cornell University
Mary Beth Hannon
Thermo-tolerance in tropical cattle
Dr. EuiSoo Kim...
Questions?
of 45

Population Structure & Genetic Improvement in Livestock

The genetic improvement of livestock has been a hot topic for almost a century, bringing together researchers, industry, and producers to work towards a common goal. Many countries currently employ extensive genetic selection programs in their cattle with pigs, sheep, and chicken close behind. In this webcast, Heather J. Huson, Ph.D. from Cornell University will focus on population dynamics and trait association in cattle and goats using high density SNP datasets. Population structure plays a critical role in understanding the relatedness among livestock, ancestral origins of traits, and identification of unique sub-populations or breeds for production improvement and conservation. This also lays the foundation for understanding and improving species such as the goat which is a vital food source in developing countries but has little recorded production or health data. Understanding population structure is essential for designing complex trait association studies such as those related to production and health characteristics. Here, Huson shows examples of her lab's investigation into population structure in both goats and cattle to identify distinct groups and study traits such as thermo-tolerance.
Published on: Mar 4, 2016
Published in: Science      
Source: www.slideshare.net


Transcripts - Population Structure & Genetic Improvement in Livestock

  • 1. Population Structure & Genetic Improvement in Livestock Heather J. Huson, Ph.D. Cornell University Department of Animal Science Robert & Anne Everett Endowed Professorship in Dairy Cattle Genetics
  • 2. Overview Research focus • Population structure • Trait association Research projects • Thermo-tolerance in tropical cattle • African Goat Improvement Project Research goal • Genetic improvement of livestock
  • 3. THERMO-TOLERANCE IN TROPICAL CATTLE
  • 4. Thermo-tolerance in Tropical Cattle • Importance of thermo-tolerance in cattle – Milk Production – Reproduction • SLICK hair-coat: short, fine, sleek hair-coat found in tropically adapted cattle • Objective: improve diagnostic markers & identify causative mutation Senepol St. Croix Romosinuano Venezuela Carora Venezuela
  • 5. Research Roll • Identify breed relationship of SLICK- tropical cattle • Investigate ancestral origins of SLICK- hair coat • Conduct the Genome-wide association analysis of SLICK phenotype
  • 6. Research Approach • Use a variety of analyses to assess trait association across the genome – Runs Of Homozygosity – Signatures of selection (iHS) – Genome-wide Association Study – Haplotype blocks
  • 7. Ancestry of Senepol cattle Red Poll N’Dama East African Zebu • Composite Breed of the St. Croix Virgin Island Senepol
  • 8. Genomic verification of Senepol ancestry N’Dama Red Poll Senepol Zebu K=4
  • 9. GWAS of SLICK hair-coat Use ancestral breeds as controls to balance SLICK cases Cases= 72 Controls= 61 • Senepol-2 • Red Pole-10 • N’Dama-10 • Zebu- 10 • Senepol x Angus-1 • Senepol/Angus x Angus-1 • Angus-10 • Holstein- 7 • Brown Swiss- 10 • Senepol- 36 • Senepol x Angus-3 • Senepol/Angus x Angus-1 • Romosinuano- 2 • Romosinuano/Angus x Angus-1 • Romosinuano x Angus-11 • Holstein x Senepol- 7 • Carora- 10
  • 10. GWAS of SLICK hair-coat 639,663SNPs Minimal Correction for Relatedness or Population Structure -log10p = 5 -log10p = ~16.5
  • 11. Improved GWAS of SLICK hair-coat EMMAX Kinship Matrix- Correction for Relatedness / Population Structure -log10p = 5 -log10p = ~12.8
  • 12. Runs of Homozygosity Dr. Eui-Soo Kim, Iowa State University SNP Threshold Approximate distance 100 consecutive SNPs 0.3 Mb 200 0.6 300 1.0 500 1.6
  • 13. Haplotype Blocks  24 significantly associated haplotype patterns  3 haplotype patterns identified only in SLICK Block ID Start bp End bp Block Distance (bp) Haplotype Frequency SLICK Frequency Non-SLICK P Value 94 37718791 37721846 3,055 GGG 0.833 0.314 3.58E-12 104 37940179 37957238 17,059 GGGGA 0.292 0 4.96E-10 112 38224054 38281493 57,439 GGGGAGG 0.278 0 1.44E-09 143 39469953 39508807 38,854 GGGAGGGCAGCGGGAGGAGA 0.264 0 4.06E-09
  • 14. Multiple Genetic Analyses BTA 20 37 Mb 40 Mb SKP2 SPEF2 Keratinocyte proliferation and skin homeostasis Spermatogenesis defects. Late feathering in male chickens. PRLR Hair cycling and localized to skin tissue
  • 15. Outcomes • Breed relationship and ancestry of SLICK-haired tropical cattle • Narrowed SLICK locus to 0.5 Mb on BTA 20 • Identified new diagnostic markers – 3 haplotypes found only in SLICK haired individuals • Huson et al. Frontiers in Genetics, March 2014
  • 16. Future Directions • Potentially 2 mutations effecting same gene – Related to breeds • Sequencing region to determine causative mutation • Genotyping additional SLICK breeds Senepol St. Croix Romosinuano Venezuela Carora Venezuela
  • 17. USAID: Feed the Future Initiative AFRICAN GOAT IMPROVEMENT NETWORK (AGIN)
  • 18. Global Food Security • 90% of global population located in “Hunger Zones” • Target: African small-holder farmers GOATS GOATS
  • 19. Why Goats? • Most common livestock species in Africa – Small-holder farmers (women) • Diverse & hardy species – Thrive in harsh climates with sparse forage • Large potential growth with selection • Economically efficient
  • 20. SAMPLING STATUS
  • 21. Total Sampling Dataset 16 Countries > 60 Sampling Sites ~ 66 Breeds/Populations > 2,737 Goats Sampled
  • 22. Egypt Ethiopia Kenya Tanzania Malawi Zimbabwe South Africa Mozambique Nigeria Cameroon Uganda Breeds sampled within Africa • 11 African countries sampled • 4 new FAO research projects being added
  • 23. Global Comparison US: Spanish derived New Zealand: Boer Turkey: domestication Brazil: climate, parasite Italy: dairy breeds Italy NOAA: http://www.ngdc.noaa.gov/mgg/global/global.html United States Turkey Brazil New Zealand
  • 24. PHENOTYPING
  • 25. Standardized Sampling Protocol • Geographical information system (GIS) data – Latitude, longitude, elevation • Physical body measurements – Chest girth, height, length, shoulder width, pin-bone width, weight • Photo characterization • Biological sample (DNA) Shot 5: Teeth shot Shot 6: FAMACHA shot
  • 26. Variation in body size
  • 27. Is there a significance to size variation of breeds across different countries?
  • 28. Boer Country # Goats Malawi 18 Mozambique 2 Tanzania 13 Uganda 6 Zimbabwe 31 USA 15 Points of Note: USA- Are individuals significantly heavier? Mozambique- only 2 individuals South Africa??? Develop plan to pursue Boer investigation…
  • 29. Ethiopia Gumez Keffa Abergelle Woyito Guji Breed # Goats Abergelle 64 Gumez 53 Keffa 50 Woyito Guji 50
  • 30. Ethiopian Goats
  • 31. GENOTYPING STATUS
  • 32. Quality Control Filtering 11 Countries, ~41 breeds/populations 952 individuals 53,347 SNPs SNP Filtering 51,543 SNPs Call rate < 0.9, > 2 alleles, MAF < 0.02 Sample Filtering 895 individuals Call rate < 0.9 895 individuals 51,543 SNPs
  • 33. Quality Control Filtering 11 Countries, ~41 breeds/populations 952 individuals 53,347 SNPs SNP Filtering 51,543 SNPs Call rate < 0.9, > 2 alleles, MAF < 0.02 Sample Filtering 895 individuals Call rate < 0.9 895 individuals 51,543 SNPs
  • 34. Quality Control Filtering 11 Countries, ~41 breeds/populations 952 individuals 53,347 SNPs SNP Filtering 51,543 SNPs Call rate < 0.9, > 2 alleles, MAF < 0.02 Sample Filtering 895 individuals Call rate < 0.9 895 individuals 51,543 SNPs
  • 35. Quality Control Filtering 11 Countries, ~41 breeds/populations 952 individuals 53,347 SNPs SNP Filtering 51,543 SNPs Call rate < 0.9, > 2 alleles, MAF < 0.02 Sample Filtering 895 individuals Call rate < 0.9 895 individuals 51,543 SNPs
  • 36. PROJECT ANALYSES
  • 37. Italy USA (Spanish) Brazil Turkey Nigeria Egypt Ethiopia Kenya Uganda South Africa US/NZ Boer Principle Component Analysis: PC1 vs PC2
  • 38. Population dynamics from the PCA PC Eigenvalue Factor 1 31.23479 European – African 2 17.93332 Boer breed- South Africa 3 8.407324 Turkish breeds 4 8.021972 Nigerian breeds 5 5.329341 South African breeds Eigenvalue: provides a measure of variation within the dataset for that component PC 3 PC 4 PC 5
  • 39. PCA of African Countries Only Principle Component 1 EV = 13.65 By Country By Breed
  • 40. 3 African Countries & NZ Boer
  • 41. Signature of Selection- FST
  • 42. Outcomes • Both body size and genetic investigation show variation among goat breeds – Level of significance? • Genomic analysis of population structure through PCA shows both country and breed divergence – Further investigation into development of breeds and migration may provide insight into divergence patterns • Genomic analysis demonstrates potential regions of the genome under selective pressure distinguishing African and European ancestry
  • 43. Research Strategy • Genome-wide investigation – Thousands of markers across the genome • Population Structure – Relatedness of individuals, breeds, ancestry • Inbreeding measures • Uniqueness of genetic signatures • Selection for conservation / improvement • Genome-wide Association Studies – Identify regions of the genome in association with a trait (performance/production, morphology, health, adaptation) • Identify genetic regulation of trait • Identify diagnostic markers
  • 44. Acknowledgements Huson Lab, Cornell University Mary Beth Hannon Thermo-tolerance in tropical cattle Dr. EuiSoo Kim, Iowa State University Dr. Robert Godfrey, Univ. of Virgin Islands Dr. Timothy Olson, Univ. of Florida Dr. Matt McClure, Irish Cattle Breeding Federation Dr. Chad Chase, USDA-ARS, MARC Dr. Rita Rizzi, Dept. of Veterinary Services, Italy Dr. Ana O’Brien, BOKU, Austria Dr. Curt Van Tassell, USDA Dr. Jose Fernando Garcia, UNESP, Brazil Dr. Antonio Landaeta-Hernandez, Univ. Venezuela Dr. Tad Sonstegard, USDA African Goat Improvement Network USAID USDA International Livestock Research Institute Association for Strengthening Agricultural Research in Eastern & Central Africa BOKU- University of Vienna Agricultural Research Council AgResearch- New Zealand FAO
  • 45. Questions?

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