WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (1) George R. Wiggans Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD Animal Improvement Program (AIP) A “big data” project of the Animal Genomics and Improvement Laboratory (AGIL)

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (2) AGIL mission l Discover and develop improved methods for the genetic and genomic evaluation of economically important traits of dairy animals and small ruminants l Conduct fundamental genomics-based research aimed at improving their health and productive efficiency

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (3) l Dr. Erin E. Connor, Research Leader l 10 senior scientists l 2 postdoctoral associates l 9 support scientists l 2 chemists l 5 laboratory technicians l 3 information technology specialists l 2 administrative assistants l Visiting scientists and students AGIL staff

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (4) l Enhancing genetic merit of ruminants through genome selection and analysis l Understanding genetic and physiological factors affecting nutrient use efficiency of dairy cattle l Development of genomic tools to study ruminant resistance to gastrointestinal nematodes l Improving genetic predictions in dairy animals using phenotypic and genomic information “Animal Improvement Program” (AIP) AGIL appropriated projects

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (5) l 4 senior scientists l 6 support scientists l 3 information technology specialists l 1 administrative assistant l 2 visiting scientists AIP staff Dr. George WiggansDr. Paul VanRadenDr. John ColeDr. Derek Bickhart

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (6) AIP objectives l Expand national and international collection of phenotypic and genotypic data l Develop a more accurate genomic evaluation system with advanced, efficient methods to combine pedigrees, genotypes, and phenotypes l Use economic analysis to maximize genetic progress and financial benefits from collected data

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (7) Genetic evaluation l Improve future performance through selection l Possible data w Animal’s own measurable traits w Pedigrees and phenotypes of relatives w Genomic information

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (8) Phenotypic data l Records for milk yield, fat percentage, protein percentage, and somatic cell count (1/month) l Appraiser-assigned scores for  16 body and udder characteristics related to conformation (e.g., stature) l Breeding records that include indicator for conception success l Calving difficulty scores and stillbirth occurrences

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (9) Primary traits evaluated l Yield (milk, fat, and protein) l Conformation (overall and individual traits) l Longevity (productive life) l Fertility (conception and pregnancy rates) l Calving (dystocia and stillbirth) l Disease resistance (somatic cell score)

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (10) Data amounts (as of July 2015) l Pedigree records71,974,045 l Animal genotypes1,035,590 l Lactation records (since 1960)132,629,200 l Daily yield records (since 1990)641,864,015 l Reproduction event records176,559,035 l Calving difficulty scores29,528,607 l Stillbirth scores19,567,198

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (11) Value of incoming data DataAnnual value Phenotypes (2014) 4 million cows×$1.25/cow/month$60 million Genotypes (2014) 15,000 medium-density×$125$2 million 258,000 low-density×$45$12 million Whole-genome sequence (2015) 200+ bulls×$1,000$0.2 million 1,000+ bulls×$3,000$3 million Total$77.2 million

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (12) Genomics and SNP l Genomics – Applies DNA technology and bioinformatics to sequence, assemble and analyze the function and structure of genomes l SNP – Single nucleotide polymorphisms; serve as markers to track inheritance of chromosomal segments l Genomic selection – Selection using genomic predictions of economic merit early in life

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (13) Benefit of genomics l Determine value of bull at birth l Increase accuracy of selection l Reduce generation interval l Increase selection intensity l Increase rate of genetic gain

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (14) Why genomics works for dairy cattle l Extensive historical data available l Well-developed genetic evaluation program l Widespread use of artificial-insemination (AI) sires l Progeny-test programs l High-value animals worth the cost of genotyping l Long generation interval that can be reduced substantially by genomics

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (15) Evaluation transition to dairy industry l Council on Dairy Cattle Breeding (CDCB) w Database maintenance w Calculation and distribution of genetic  merit  estimates w Interface with evaluation users and data suppliers l AGIL w Research and development using data  made  available by CDCB

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (16) Genomic data flow DNA samples genotypes genomic evaluations nominations, pedigree data genotype quality reports genomic evaluations DNA samples genotypes DNA samples Dairy Herd Information (DHI) producer CDCB DNA laboratory AI organization, breed association AI organization, breed association

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (17) Evaluation flow l Animal nominated for genomic evaluation by approved nominator l DNA source sent to genotyping lab (2014) SourceSamples (no.)Samples (%) Blood 10,7274 Hair113,45539 Nasal swab2,9541 Semen3,4321 Tissue149,30151 Unknown12,3014

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (18) Evaluation flow (continued) l DNA extracted and placed on chip w Marker panels that range from 2,900 to 777,962 SNPs w 3-day genotyping process l Genotypes sent from genotyping lab for accuracy review

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (19) Animals genotyped (cumulative totals)

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (20) Laboratory quality control l Each SNP evaluated for w Call rate w Portion heterozygous w Parent-progeny conflicts l Clustering investigated if SNP exceeds limits l Number of failing SNPs indicates genotype quality l Target of <10 SNPs in each category

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (21) Evaluation flow (continued) l Genotype calls modified as necessary l Genotypes loaded into database l Nominators receive reports of parentage and other conflicts l Pedigree or animal assignments corrected l Genotypes extracted and imputed to 61K l SNP effects estimated l Final evaluations calculated

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (22) Parentage validation and discovery l Parent-progeny conflicts detected w Animal checked against all other genotypes w Reported to breeds and requesters w Correct sire usually detected l Maternal grandsire checking w SNP at a time checking w Haplotype checking more accurate

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (23) Evaluation flow (continued) l Evaluations released to dairy industry w Download from FTP site with separate files for each nominator w Weekly release of evaluations of new animals w Monthly release for females and bulls not marketed w All genomic evaluations updated 3 times each year with traditional evaluations

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (24) Parent ages for marketed Holstein bulls

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (25) Genetic merit of marketed Holstein bulls Average gain: $19.42/year Average gain: $47.95/year Average gain: $87.49/year

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (26) Improving accuracy l Increase size of predictor population w Share genotypes across country w Young bulls receive progeny test l Use more or better SNPs l Account for effect of genomic selection on traditional evaluations l Reduce cost to reach more selection candidates

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (27) Growth in bull predictor population BreedJan mo gain Ayrshire71129 Brown Swiss6, Holstein26,7592,174 Jersey4,448245

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (28) Haplotypes affecting fertility l Rapid discovery of new recessive defects w Large numbers of genotyped animals w Affordable DNA sequencing l Determination of haplotype location w Significant number of homozygous animals expected, but none observed w Narrow suspect region with fine mapping w Use sequence data to find causative mutation

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (29) Current research areas l Improve evaluation methodology l Develop applications for sequence data l Acquire data for additional traits l Develop evaluations for new traits

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (30) Mating programs l Genomic relationships of genotyped females with available bulls provided l Determination of best mate possible l Dominance effects could be considered

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (31) Working with sequence data l Sequence data available from 1000 Bull Genomes Project hosted in Australia l Project funded by industry to sequence over 200 bulls to create a haplotype library l A posteriori granddaughter design to locate chromosomal segments of interest from 71 bulls each with over 100 genotyped and progeny-tested sons

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (32) Granddaughter design l Sires with many progeny-tested sons genotyped for genetic markers l Sons of heterozygous sire divided into 2 groups based on paternal allele received l Significant difference in genetic evaluations for 2 son groups indicates sire is segregating for quantitative trait locus (QTL) for trait M ? + – m ? + – M m + –

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (33) Alignment of sequence data l Alignment – determining location of chromosomal segments provided by sequencer l Findmap – matches segment against library of haplotypes l Preserves low-frequency variants l Does not identify new variants l Uses a hash table to find variant enabling  rapid  processing

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (34) Further use of sequence data l Discovery of causative genetic variants l Refinement of SNPs used in genomic evaluation w Add discovered causative variants w Use some SNPs for imputation but not for estimation of SNP effects l Create genotypes for genomic evaluation from sequence data to enable immediate use through imputation of any new SNPs

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (35) Additional traits requiring data l Clinical mastitis l Displaced abomasum l Ketosis l Hoof health l Immune response l Other health traits l Feed efficiency l Methane production l Milk fatty acid composition from mid‐infrared  spectroscopy

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (36) Evaluation of new traits l Mortality l Days to first breeding l Gestation length l Persistency l Resistance to heat stress (predicting genotype × environment interactions)

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (37) Benefits to dairy industry l Low-cost genotyping tools for genomic predictions of genetic merit l Identification of gene mutations for cow fertility l Genetic evaluations for more than 30 traits of U.S. dairy cows l Genetic-economic indexes to help dairy farmers choose parents of future generations l Genomic mating programs for dairy cattle

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (38) Impact on breeders l Haplotype and gene tests in selection and mating programs l Trend towards a small number of elite breeders that are investing heavily in genomics l About 30% of young males genotyped directly by breeders since April 2013 l Prices for top genomic heifers can be very high (e.g., $265,000 )

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (39) Impact on dairy producers l General w Reduced generation interval w Increased rate of genetic gain w More inbreeding/homozygosity? l Sires w Higher average genetic merit of available bulls w More rapid increase in genetic merit for all traits w Larger choice of bulls for traits and semen price w Greater use of young bulls

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (40) Summary l Highly successful program leading to annual increases in genetic merit for production efficiency l Large database of phenotypic and genomic data provided by industry l Research projects to determine mechanism of genetic control of economically important traits l Data processing techniques developed so that rapid turnaround could be realized

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (41) Funding acknowledgments l U.S. taxpayers (USDA appropriated project) l Council on Dairy Cattle Breeding l Binational Agricultural Research & Development l National Institute of Food and Agriculture l Washington State University (NIFA grant)

WiggansARPAS-DC meeting, Beltsville, MD – Dec. 9, 2015 (42) Questions? Holstein and Jersey crossbreds graze on American Farm Land Trust’s Cove Mountain Farm in south-central Pennsylvania Source: ARS Image Gallery, image #K ; photo by Bob Nichols