1. Population Structure & GeneticImprovement in LivestockHeather J. Huson, Ph.D.Cornell UniversityDepartment of Animal ScienceRobert & Anne Everett Endowed Professorship in Dairy Cattle Genetics

2. OverviewResearch focus Population structure Trait associationResearch projects Thermo-tolerance in tropical cattle African Goat Improvement ProjectResearch goal Genetic improvement of livestock 3. THERMO-TOLERANCE INTROPICAL 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 intropically adapted cattle Objective: improve diagnostic markers & identifycausative mutationSenepolSt. CroixRomosinuanoVenezuelaCaroraVenezuela 5. Research Roll Identify breed relationship of SLICK- tropicalcattle Investigate ancestral origins of SLICK- haircoat Conduct the Genome-wide associationanalysis of SLICK phenotype 6. Research Approach Use a variety of analyses to assess traitassociation across the genome Runs Of Homozygosity Signatures of selection (iHS) Genome-wide Association Study Haplotype blocks 7. Ancestry of Senepol cattleRed PollNDamaEastAfricanZebu Composite Breed of theSt. Croix Virgin IslandSenepol 8. Genomic verification of Senepol ancestryNDama Red Poll Senepol ZebuK=4 9. GWAS of SLICK hair-coatUse ancestral breeds as controls to balance SLICKcasesCases= 72 Controls= 61 Senepol-2 Red Pole-10 NDama-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 xAngus-1 Romosinuano x Angus-11 Holstein x Senepol- 7 Carora- 10 10. GWAS of SLICK hair-coat639,663SNPsMinimal Correction for Relatedness orPopulation Structure-log10p = 5-log10p = ~16.5 11. Improved GWAS of SLICK hair-coatEMMAX Kinship Matrix- Correction forRelatedness / Population Structure-log10p = 5-log10p = ~12.8 12. Runs of HomozygosityDr. Eui-Soo Kim, Iowa State UniversitySNP Threshold Approximate distance100 consecutive SNPs 0.3 Mb200 0.6300 1.0500 1.6 13. Haplotype Blocks 24 significantly associated haplotype patterns 3 haplotype patterns identified only in SLICKBlock ID Start bp End bpBlockDistance(bp) HaplotypeFrequencySLICKFrequencyNon-SLICK P Value94 37718791 37721846 3,055 GGG 0.833 0.314 3.58E-12104 37940179 37957238 17,059 GGGGA 0.292 0 4.96E-10112 38224054 38281493 57,439 GGGGAGG 0.278 0 1.44E-09143 39469953 39508807 38,854 GGGAGGGCAGCGGGAGGAGA 0.264 0 4.06E-09 14. Multiple Genetic AnalysesBTA 2037 Mb 40 MbSKP2 SPEF2Keratinocyteproliferation and skinhomeostasisSpermatogenesis defects.Late feathering in male chickens.PRLR Hair cycling andlocalized to skin tissue 15. Outcomes Breed relationship and ancestry of SLICK-hairedtropical cattle Narrowed SLICK locus to 0.5 Mb on BTA 20 Identified new diagnostic markers 3 haplotypes found only in SLICK hairedindividuals Huson et al. Frontiers in Genetics, March2014 16. Future Directions Potentially 2 mutations effecting same gene Related to breeds Sequencing region to determine causative mutation Genotyping additional SLICK breedsSenepolSt. CroixRomosinuanoVenezuelaCaroraVenezuela 17. USAID: Feed the Future InitiativeAFRICAN GOAT IMPROVEMENTNETWORK (AGIN) 18. Global Food Security 90% of global population located in Hunger Zones Target: African small-holder farmersGOATSGOATS 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 Dataset16 Countries> 60 Sampling Sites~ 66 Breeds/Populations> 2,737 Goats Sampled 22. EgyptEthiopiaKenyaTanzaniaMalawiZimbabweSouth AfricaMozambiqueNigeriaCameroonUgandaBreeds sampledwithin Africa 11 African countriessampled 4 new FAO researchprojects being added 23. Global ComparisonUS: Spanish derivedNew Zealand: BoerTurkey: domesticationBrazil: climate, parasiteItaly: dairy breedsItalyNOAA: http://www.ngdc.noaa.gov/mgg/global/global.htmlUnitedStatesTurkeyBrazilNew 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-bonewidth, weight Photo characterization Biological sample (DNA)Shot 5: TeethshotShot 6:FAMACHAshot 26. Variation inbody size 27. Is there a significance to size variationof breeds across different countries? 28. BoerCountry # GoatsMalawi 18Mozambique 2Tanzania 13Uganda 6Zimbabwe 31USA 15Points of Note:USA- Are individualssignificantly heavier?Mozambique- only 2individualsSouth Africa???Develop plan to pursueBoer investigation 29. EthiopiaGumezKeffaAbergelleWoyito GujiBreed # GoatsAbergelle 64Gumez 53Keffa 50Woyito Guji 50 30. Ethiopian Goats 31. GENOTYPING STATUS 32. Quality Control Filtering11 Countries, ~41 breeds/populations952 individuals53,347 SNPsSNP Filtering51,543 SNPsCall rate < 0.9, > 2 alleles, MAF 2 alleles, MAF < 0.02Sample Filtering895 individualsCall rate < 0.9895 individuals51,543 SNPs 34. Quality Control Filtering11 Countries, ~41 breeds/populations952 individuals53,347 SNPsSNP Filtering51,543 SNPsCall rate < 0.9, > 2 alleles, MAF < 0.02Sample Filtering895 individualsCall rate < 0.9895 individuals51,543 SNPs 35. Quality Control Filtering11 Countries, ~41 breeds/populations952 individuals53,347 SNPsSNP Filtering51,543 SNPsCall rate < 0.9, > 2 alleles, MAF