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Genomic Evaluations: Past, Present, and Future

Genomic Evaluations: Past, Present, and Future. Genetic Improvement. Driven by genetic evaluation program Yield, fitness, type and calving traits evaluated Widespread use of AI sires Progeny test programs Genomics Increases rate of improvement by reducing generation interval. Past.

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Genomic Evaluations: Past, Present, and Future

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  1. Genomic Evaluations: Past, Present, and Future

  2. Genetic Improvement Driven by genetic evaluation program Yield, fitness, type and calving traits evaluated Widespread use of AI sires Progeny test programs Genomics Increases rate of improvement by reducing generation interval

  3. Past Parentage verification using Blood groups Microsatellites Search for major genes Marker assisted selection Little value

  4. History of genomic evaluations Dec. 2007 BovineSNP50 BeadChip available Apr. 2008 First unofficial evaluation released Jan. 2009 Genomic evaluations official for Holstein and Jersey Aug. 2009 Official for Brown Swiss Sept. 2010 Unofficial evaluations from 3K chip released Dec. 2010 3K genomic evaluations to be official

  5. Bovine Genome Sequence

  6. Background: Genetic Markers • A segment of DNA at a unique physical location in the genome that varies sufficiently between individuals that its inheritance can be tracked through families. • A marker is not required to be part of a gene.

  7. Genetic Markers • Allow inheritance to be followed in a region across generations • Single nucleotide polymorphisms (SNP) are the markers of choice • Need lots! • 3 million in the genome

  8. Cattle SNP Collaboration - iBMAC • Develop 60,000 Bead Illumina iSelect® assay • USDA-ARS Beltsville Agricultural Research Center: Bovine Functional Genomics Laboratory and Animal Improvement Programs Laboratory • University of Missouri • University of Alberta • USDA-ARS US Meat Animal Research Center • Starting 60,800 beads – 54,000 useable SNP

  9. Participants Illumina Marylinn Munson Cindy Lawley Christian Haudenschild BARC Curt Van Tassell Lakshmi Matukumalli Tad Sonstegard Missouri Jerry Taylor Bob Schnabel Stephanie McKay Alberta Steve Moore USMARC – Clay Center Tim Smith Mark Allan iBMAC Consortium Funding Agencies • USDA/NRI/CSREES • 2006-35616-16697 • 2006-35205-16888 • 2006-35205-16701 • USDA/ARS • 1265-31000-081D • 1265-31000-090D • 5438-31000-073D • Merial • Stewart Bauck • NAAB • Godon Doak • ABS Global • Accelerated Genetics • Alta Genetics • CRI/Genex • Select Sires • Semex Alliance • Taurus Service 10

  10. Collaboration Consortium including universities, government and industry contributed to developing chip Full sharing of genotypes with Canada CDN calculates genomic evaluations on Canadian base Trading of Brown Swiss genotypes with Switzerland, Germany, and Austria Collaborations with other countries being negotiated

  11. What’s genomics? Study of the effects of an animal’s genes as a whole Genomic evaluations based on DNA markers Single nucleotide polymorphism (SNP) markers abundant and cheap to read Genotypes from Illumina BovineSNP50, 3K and HD BeadChips 3 possible genotypes across 2 chromosomes at each SNP (AA, AB, BB) or (2, 1, 0)

  12. What’s whole-genome selection? • Many markers used to track inheritance of chromosomal segments • Impact of each segment on each trait is estimated • Estimates combined with traditional predicted transmitting abilities (PTA) to produce genomic PTA • Animals can be selected shortly after birth

  13. What’s a SNP? • Place on chromosome where animals differ in nucleotides (A, C, T, or G) • Usually not part of gene that controls trait (quantitative trait locus; QTL) • With enough SNP, association between SNP and QTL alleles enables useful evaluations • SNP chosen to be distributed evenly and have both alleles well represented in population

  14. Source of genomic evaluations • DNA extracted from blood, hair, semen, nasal swab, or ear punch • 43,382 SNP evaluated • SNP effect is difference in PTA from having 1 more A allele (BB to AB, or AB to AA)

  15. Present

  16. Steps to prepare genotypes Nominate animal for genotyping Collect DNA containing sample Blood may not be suitable for twins Send to laboratory for extraction Transfer DNA to BeadChip for 3-day genotyping process

  17. Steps to prepare genotypes (cont.) • Read red/green intensities from chip • Call genotypes from clusters • Send genotypes to AIPL • Check genotypes for duplicates, parent-progeny conflicts, breed, and wrong sex

  18. Before clustering adjustment 86% call rate

  19. After clustering adjustment 100% call rate

  20. What can go wrong • Sample doesn’t provide adequate DNA quality or quantity • Genotype has many SNP that can’t be determined (90% call rate required) • Parent-progeny conflicts • Pedigree error • Sample ID error • Laboratory error • Unrelated animal qualifies as parent or progeny

  21. Parent-progeny conflict Parent 10212002101201211001020120100 Progeny 10202010100200221001120120220

  22. Parent-Progeny conflicts For animal Pedigree wrong Genotype unreliable (3K) For SNP SNP unreliable Clustering needs adjustment

  23. Parent-Progeny conflict resolution Animal checked against all other genotypes Usually true sire is found when there is a conflict Requester must confirm new parent Conflict declared when parent-progeny relationship detected that is not in pedigree Split embryo duplicate of parent Sample ID error on genomic parent/progeny

  24. Genotype extraction For animals with > 1 genotype, missing values filled in from other genotypes For split embryos and clones, all assigned the same genotype SNP level parent-progeny conflicts resolved by setting SNP with fewest confirmations to missing

  25. Chips BovineSNP50 Version 1 54,001 SNP Version 2 54,609 SNP 43,382 used in evaluations 3K 2900 SNP 2706 used in evaluations HD 777,963 SNP Not yet in use, > 300 in database

  26. 3K chip 2900 SNP mostly from SNP50 chip 14 Y Chr SNP included for sex validation Evenly spaced across 30 Chr Developed to reduce cost of genotyping 2706 SNP used after removing poor performers Rapid adoption, 3,807 animal genotypes submitted for Nov. genomic evaluation

  27. Imputation Based on splitting the genotype into individual chromosomes (maternal & paternal contributions) Missing SNP approximated by tracking inheritance from ancestors and descendents Imputed Dams increase predictor population 3K & 50K genotypes merged by imputing SNP not on 3K

  28. Genotyped Holsteins *Traditional evaluation **No traditional evaluation

  29. Genotype for Elevation • Chromosome 1 10001112200200121110111121111011110011211000201220022201111202101200211122110021112001111001011011010220011002201101120020110102022212112210201001110001122022122211202112012020100202202000021100011202011221112111022011110000212202000221012020002211220111012100111211102112110020102100022000220100020110000220221102211210112111012222001211212220020002002020201222110022222220022121111210021111200110111011200202220001112011010211121211102022100211201211001111102111211021112200010110111020220022111010201112111101120210210212110110221220012110112110120220110022200210021100011100211021101110002220020221212110002220102002222121221121112002011020200122222211221202121121011001211011020022000200100200011110110012110212121112010101212022101010111110211021122111111212111210110120011111021111011111220121012121101022202021211222120222002121210121210201100111222121101

  30. Double grandson of Aerostar Genotype for inbred bull (Megastar) • Chromosome 24 102122210102102101110211011211221121100220200022202000202022000002200202222022020000200202222220000202222000002202000020022002000000222200022220000000000020222022002000222020222220002202222222220000200220202220200020002200000000220222000000220020200022220020200200202022202222222202220200020220220222202022202020202200022002220220022200000220200002002002000200222220002222020200222002220200002020000002222202020000200200222200020220222200220002222022002222020200022022022220022200220002002202000002200220222000022000022000222202002222000220020020202202000222000222002220220220000022022002002002022000200022220220022200202202002222022200000202200020200202020002200220000022022200202220200022002000200022002002000200220222220022022000200002000200002022002022020020000222000022200200020022200002202200200220022022020202020202000222020002202002022022202200002020200002020200022222200222200020022022220000020220020200202022022020200002000200220220002200

  31. X Chromosome Bull 202220200002022220002020222020202 Cow 1201201212222010111022210210212022

  32. Data and evaluation flow AI organizations, breed associations nominations samples evaluations Animal Improvement Programs Laboratory, USDA Dairy producers samples samples genotypes DNA laboratories

  33. Adjustment of Cow Evaluations • Traditional cow evaluations inflated compared to bull evaluations • US industry wanted cow’s own performance to influence genomic evaluations. Most countries use only bull evaluations for SNP effect estimation • Information from genotyped cows did not increasing reliability of yield traits • Cow contributions adjusted to be comparable to those from bulls

  34. Holstein prediction accuracy a CE = calving ease and SB = stillbirth. b 2010 deregressed value – 2006 genomic evaluation.

  35. Reliabilities for young bulls Traditional PA GPTA

  36. Holstein Protein SNP Effects

  37. Use of genomic evaluations • Determine which young bulls to bring into AI service • Use to select mating sires • Pick bull dams • Market semen from 2-year-old bulls

  38. Use of 3K genomic evaluations • Sort heifers for breeding • Flush • Sexed semen • Beef bull • Confirm parentage to avoid inbreeding • Predict inbreeding depression better • Precision mating considering genomics (future)

  39. Updates between trad. evaluations • Genomic evaluations calculated every month • Evaluations not released for animals that already have an official evaluation • Evaluations of new animals distributed to owners • Females by breed associations • Males by NAAB

  40. Impact on producers • Young-bull evaluations with accuracy of early 1st­crop evaluations • AI organizations marketing genomically evaluated 2-year-olds • Bull dams likely to be required to be genotyped • Rate of genetic improvement likely to increase by up to 50% • Progeny-test programs changing

  41. International implications All major dairy countries investigating genomic selection Interbull working on how genomic evaluations should be integrated European collaboration to share genotypes Large number of predictor animals increases prediction accuracy Importing countries changing rules to allow for genomically evaluated young bulls

  42. Future

  43. Increase in accuracy • Genotyped bulls get traditional evaluation when 5 years old • Possible genotyping of 10,000 bulls with semen in CDDR • Collaboration with more countries • Use of more SNP from HD chips • Full sequencing

  44. Application to more traits Animal’s genotype is good for all traits Traditional evaluations required for accurate estimates of SNP effects Traditional evaluations not currently available for heat tolerance or feed efficiency Research populations could provide data for traits that are expensive to measure Will resulting evaluations work in target population?

  45. Summary • Extraordinarily rapid implementation of genomic evaluations • Young-bull acquisition and marketing now based on genomic evaluations • Genotyping of many females because of 3K chip

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