GENETIC CONSIDERATIONS FOR HEIFER FERTILITY DR. HEATHER J. HUSON ROBERT & ANNE EVERETT ENDOWED PROFESSORSHIP OF DAIRY CATTLE GENETICS OVERVIEW Genetic merit of the heifer Genetics as a management tool CALF & HEIFER CONGRESS 2017 CALF & HEIFER CONGRESS 2017 What s the value of the individual? GENETIC MERIT OF THE HEIFER How do we select for value? CALF & HEIFER CONGRESS 2017
ESTIMATION OF GENETIC MERIT Phenotype Genotype Pedigree Parent Average: Genetic average of each parent s genetic value Assumes that offspring inherit exactly ½ of each parents genetic merit for all traits Assumes that parents are identified as 100% accurate Genotypic value: value of an individual s genes on their OWN performance Breeding value: value of an individual s genes on their PROGENY s performance (EBV) Progeny difference = Transmitting ability: expectation of what the PROGENY inherits from the parent (PTA) Producing ability: (PA) performance potential of an individual for a repeated trait Economically important traits Predicted Genetic Merit WHAT S INCLUDED IN GENETIC EVALUATIONS ESTIMATING GENETIC MERIT OF THE HEIFER Genomic evaluation of the heifer Sire: genomic evaluations Dam: farm records; potential genomic evaluations Siblings: farm records; potential genomic evaluations
HOW DO YOU ESTIMATE THE VALUE OF TRAITS NOT EXHIBITED? PROGENY TESTING Investment Time (generation interval) Cost (cost of raising animal and progeny til performance evaluated) Milking ability Calving ease Maternal traits Mastitis GENOMIC PREDICTION gebv Investment Genetic research Industry infrastructure Producer buy-in USES FOR GENETIC EVALUATIONS Management tool Provides an objective value for an individual reflecting health, production, and conformation Reproductive management Sire decisions IVF/Embryo transfer (donors versus recipients) Culling decisions Marketing tool Creates economic value for the producer Provides a currency for marketing stock particularly in young and phenotypically unproven animals Ensures utilization and subsequent incorporation of the targeted genetics in the next generation Investigate marketing (research) claims
CONSIDERATIONS FOR USING PERFORMANCE INDEXES RATE OF GENETIC CHANGE Measures the effectiveness of selection CDCB / USDA Economic index Industry objectives Breed association & Company indexes Targeted toward association or company objectives Purebred evaluations Within breed: genetic patterns can be breed specific Holstein, Jersey, Ayrshire, Milking Shorthorn, Brown Swiss, Guernsey Crossbred evaluations International evaluations Selection criteria INTERBULL Supporting research Expected genetic progress per year Genetic variance = variation in the population due to genetics; includes heritability (h 2 ) of the trait We can t change this Genetic variance Selection differential = intensity of selection; how selective we are when making mating decisions Accuracy = how certain we are about our estimate of an animal s genetic merit Generation interval = time between generations Selection differential (intensity) Generation interval Accuracy GENOMIC PREDICTION COMPARISON OF COMMON TOTAL PERFORMANCE INDEXES = OPTIMIZED FOR GENERAL IMPROVEMENT OF PRODUCTION, HEALTH, AND CONFORMATION Net Merit TPI JPI Benefits of Genomics Chapter 8.15.1: Principle of genomic selection; Groen Kennisnet https://wiki.groenkennisnet.nl/display/tab/chapter+8.15.1%3a+principle+of+genomic+selection Improved accuracy of genetic merit and trait selection Merit of young stock Parentage validation Disease assessment (Carrier status for genetic conditions) Conf. 16% Health 40% Production 44% Holstein, Jersey, Ayrshire, Brown Swiss, Guernsey, Milking Shorthorn Conf. 26% Health 28% Holstein Production 46% Health 27% Conf. 15% Jersey Production 58%
INDIVIDUAL TRAITS Milk Fat Protein Fat % Protein % Somatic cell score Productive life Reproduction Daughter pregnancy rate Heifer conception rate Cow conception rate Sire calving ease Daughter calving ease Sire still birth Daughter still birth Type / Conformation Stature Strength (chest width) Body depth (rib cage) Dairy form (rib angle) Rump angle Rump width Rear leg side view Rear leg rear view Foot angle Feet/ leg score Fore udder attachment Rear udder attachment Rear udder height Rear udder width Udder cleft Udder depth Front teat placement Rear teat placement Teat length GENETICS AS A MANAGEMENT TOOL GENETICS MATTER Genetics provide the foundation for potential Set the genetic ceiling of the herd Management and the environment allow animal to reach that potential Some animals will exceed estimated potential while others do not achieve expected potential Farms which don t use genetic information will generally still improve due to overall industry improvement Slower rate of improvement Nutrition Environment Reproduction Genetics Milk Quality Health Establish herd goals
Identify methods to achieve herd goals SETTING GOALS Focused use of genetic information Selection intensity Accuracy Reduced time to achieve gain REPRODUCTIVE MANAGEMENT Total Performance Indexes Net Merit Conf. 16% Health 40% Production 44% Big Picture Targeted Indexes Calving ability (CA$) Fertility Index (FI) Individual Reproductive Traits Daughter pregnancy rate Heifer conception rate Cow conception rate Sire calving ease Daughter calving ease Sire still birth Daughter still birth Genetic Conditions Recessive Fertility Haplotypes Details
REPRODUCTIVE INDEXES HEALTH: REPRODUCTIVE TRAITS Calving ability (CA$): Genetic index that measures the ability of a calf to be born easily and alive. Specific traits used in the CA$ index include sire calving ease, daughter calving ease, sire still birth and daughter still birth Fertility Index (FI): Holstein only; Genetic index combining 18% heifer conception rate + 18% cow conception rate + 64% daughter pregnancy rate. Daughter pregnancy rate (DPR): expected % difference, compared to breed average, that a nonpregnant cow will become pregnant during each 21 day estrous cycle. (~1% DPR increase equals four fewer days open) Heifer conception rate (HCR): heifers ability to conceive defined as the % of inseminated heifers that become pregnant at each service. (an HCR of 1 implies that daughters of this animal would be 1% more likely to become pregnant as a heifer than daughters of an animal with an HCR value of 0) Cow conception rate (CCR): similar to HCR but in regards to cow that has previously calved Sire calving ease (SCE): ability of a calf to be born easily and is expressed as a percentage of difficult births in among first-calf heifer calvings. Lower numbers reflect easier calving. Daughter calving ease (DCE): Measures the genetic ability of a female to calve easily and is expressed as percent difficult births for first-calf heifers. Lower numbers reflect easier calving. Sire still birth (SSB): Measures the genetic tendency of calves from a particular sire to be stillborn or die within 48 hours. Lower numbers are desired. Daughter still birth (DSB): Measures the genetic ability of a cow to produce live calves REPRODUCTIVE / FERTILITY CONDITIONS INBREEDING: RECESSIVE FERTILITY HAPLOTYPES HH1 HH2 HH3 HH4 HH5 JH1 JH2 BH1 BH2 Zoetis C = carrier F = free Geneseek T = tested free C = carrier A = homozygous affected 1. Individuals are documented as Carrier or Free for genetic conditions. 2. An individual s status for a genetic condition does NOT alter it s merit score! Haplotypes traced back to common, popular sires Name Chromoso me Location Carri er Freq Earliest Known Ancestors BTA Mbase % HH1 5 62-68 4.5 Pawnee Farm Arlinda Chief HH2 1 93-98 4.6 Willowholme Mark Anthony HH3 8 92-97 4.7 Glendell Arlinda Chief, Gray View Skyliner JH1 15 11-16 23.4 Observer Chocolate Soldier BH1 7 42-47 14.0 West Lawn Stretch Improver VanRaden, P.M., et al. Reporting of haplotypes with recessive effects on fertility. Proc. Interbull Mtg., Stavanger, Norway, Aug. 26 28, 4 pp. 2011.
INBREEDING Genetic merit. Regression per 1% inbreeding https://queries.uscdcb.com/eval/summary/bmean_bases_het.cfm Milk Fat Protein Productive Life Somatic Cell Score Daughter Pregnancy Rate Heifer Cow Conception Conception Livability Rate Rate -63.3-2.37-1.88-0.26 0.00-0.13-0.08-0.16-0.08 FOCUSED USE OF GENOMIC INFORMATION MANAGEMENT TOOL S M A R T Specific Improved reproductive efficiency within herd Meaningful Actionable Realistic Trackable How will it improve your herd? Economics, health, welfare Net merit Fertility index = (18% Heifer Conception Rate) + (18% Cow conception rate) + (64% Daughter Pregnancy Rate) Individual traits: DPR, HCR, CCR, CA, SCE, DCE, SSB, DSB Genetic conditions: Recessive fertility haplotypes (HH1, HH2 JH1 ) What endpoint is achievable given resources? Who to genotype? Implementation? Cost? Time-frame? Pregnancy rate, conception rate, calf survival Reproductive management Sire decisions IVF/Embryo transfer (donors versus recipients) Culling decisions
REPRODUCTIVE TECHNOLOGIES BULL SELECTION Bulls Artificial insemination Sexed semen Considerations for use Cost Animal transport requirements Expertise and facility availability Cows Egg collection: traditional flushing, ovum pickup (OPU) or transvaginal oocyte retrieval (TVOR) In vitro fertilization (IVF) Cryopreservation / Recipient cows Proven Bulls Increased reliability in estimation of genetic merit Phenotypic and genomic data 85-90% reliability (B. Cassell, 2010 https://pubs.ext.vt.edu/404/404-090/404-090_pdf.pdf ) Higher probability of progeny having expected genetic merit Young Bulls Reduces generation interval- increasing rate of genetic change Genomic estimation of merit slightly less than proven estimates 70% reliability (B. Cassell, 2010 https://pubs.ext.vt.edu/404/404-090/404-090_pdf.pdf ) (~30% reliability phenotype only) Popularity and acceptance of technology Impact Reduce generation interval Increased # of offspring from elite stock Increase selection intensity The use of a variety of bulls buffers the impact of any bull decreasing in genetic merit over time. BULL SELECTION TAKE HOME: GENOMIC & REPRODUCTIVE TECHNOLOGIES Who selects the bull(s)? How diverse is your bull selection? How specific is the mating choice? Individual mating Group mating- how are groups identified? Overall merit, specific traits, random? Herd Sexed semen Reduce generation interval Increase selection intensity Beef semen Increase rate of genetic change
ELITE ANIMALS DRIVE GENETIC CHANGE CURRENT & FUTURE STATUS OF GENETICS & GENOMICS Table 1. Mean predicted transmitting abilities (PTAs) for milk, fat, protein, productive life (PL), somatic cell score (SCS), and net merit (NM) for registered 1 cows passing first-stage screening. Breed Cows 2 (no.) NM ($) PTA milk PTA fat PTA protein PTA PTA PL PTA SCS DPR (lb) (lb) (lb) (mo) Ayrshire 6,470 60 156 7.1 5.3 2.97 0.3 0.07 Brown Swiss 21,396 85 108 4.9 4.5 2.98 1.5 0.15 Guernsey 7,050 56 83 5.2 3.1 2.97 0.6 0.09 Holstein 927,335 190 303 16 11.3 2.93 1.8 0.31 Jersey 151,465 113 64 10.9 6.2 3 1.7-0.16 Milking Shorthorn 2,771-23 -226-5.7-5.7 3.01 0 0.69 Red and White 296-67 -511-13 -11.8 3 0.5 0.62 August 2017 Elite Cow and Heifer Statistics https://queries.uscdcb.com/eval/summary/elitestat.cfm Table 3. Percentiles and corresponding NM for a cow to be designated as elite or a high-ranking grade and numbers by breed. Evaluation Minimum Minimum Elite cows Highranking Breed percentile NM ($) (no.) grade cows (no.) Ayrshire 98 320 410 11,641 Brown Swiss 98 386 482 1,768 Guernsey 98 331 145 409 Holstein 99 589 61,931 35,109 Jersey 99 402 3,725 24,565 Milking Shorthorn 97 355 40 271 Red and White 97 250 192 173 GENETIC VERSUS GENOMIC PTA Reliability (%) Trait Genomic Traditional Difference 1 Standard deviation Genomic Traditional Difference 1 average average average average Net merit ($) 629 508 121 82 75 33 42 Milk (pounds) 1091 982 110 339 78 36 42 Fat (pounds) 57.7 50.2 7.5 12.1 78 36 42 Protein (pounds) 42.2 37.6 4.6 7.8 79 37 42 Somatic cell score 2.8 2.86-0.06 0.1 76 32 44 Productive life (months) 5.6 3.8 1.8 1.2 73 28 45 Livability 0.8-0.2 0.9 1.2 60 19 41 Daughter pregnancy rate (%) 1.5 0.8 0.7 1.1 72 27 45 Cow conception rate 2.7 1.9 0.9 1.3 71 27 44 Heifer conception rate 2 1.5 0.5 0.9 66 29 37 Sire calving ease 7.2 7.3-0.1 0.6 71 51 20 Daughter calving ease 5.1 5.4-0.3 0.8 62 36 26 Final score 1.77 1.67 0.1 0.42 77 34 44
COMMERCIAL MARKETING WHY DO WE NEED NEW TRAITS? Changes in production economics Technology produces new phenotypes Better understanding of biology Recent review by Egger-Danner et al. Immunity + Sires Offering dairymen a genetic option for natural disease resistance -- Semex http://www.semex.com/tsa/i?viewnews=1354799991 Creating wellness trait genomic predictions http://news.zoetis.com/press-release/clarifideplus/zoetis-launches-clarifide-plus J. Cole, USDA 2016 CHALLENGES TO GENETIC IMPROVEMENT THERE ARE NO GUARANTEES GENETIC CHANGE ISN T FAST... Research is being done on new traits Often not turned into new products It s a collective action problem Disagreement on objectives Lack of commercial incentives Infrastructure is not in place This provides an opportunity for new players to enter the market Independent validation lacking New technologies often require considerable capital investment They sometimes fail to work or do not deliver the promised gain Data are most useful when combined with observations from many farms This inevitably involves risk J. Cole, USDA 2016 J. Cole, USDA 2016
FRANKENSCIENTISTS ANNOUNCE MUTANT GMO COWS TO PRODUCE HORMONE-INDUCED ENGINEERED MILK http://americathecorrupt.blogspo t.com/2013/06/frankenscientistsannounce-mutant-gmo.html RESOURCES GMOs??? Gene editing? What s the future of GMO technology in the dairy industry? https://youtu.be/-qks_lmmodw Council on Dairy Cattle Breeding https://www.uscdcb.com/ Heifer/Cow Fertility Traits: Genetic evaluation https://queries.uscdcb.com/reference/form_ge_ffertility_1412.pdf CALF & HEIFER CONGRESS 2017
QUESTIONS TOPICS TO CONSIDER http://www.thebullvine.com/dairy-cattle-reproduction/sire-vsdam-greater-impact-herds-genetic-improvement/ CALF & HEIFER CONGRESS 2017