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John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD 2016 AGIL Report.

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Presentation on theme: "John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD 2016 AGIL Report."— Presentation transcript:

1 John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD john.cole@ars.usda.gov 2016 AGIL Report

2 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole 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

3 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole AIP scientists l Paul VanRaden (project leader) w Genomic evaluation methods, haplotypes l George Wiggans (CDCB liaison) w SNP selection, genotype exchange, goats l John Cole (acting research leader) w Fertility, health, heat stress resistance, indices l Derek Bickhart w Sequence data analysis, genome assembly correction and gene annotation l Kristen Parker Gaddis (UFL postdoctoral associate) w Fertility, health, use of sequence data

4 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Recent research and changes l Genomic evaluations for Guernseys l Breed composition and GPTAs for crossbreds l Increase to 77,531 SNPs used for evaluations (includes 30 gene tests provided by GeneSeek) l New GeneSeek 7K chip l New Affymetrix 44K chip

5 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Recent research and changes cont’d l Imputed dams now used for parent-progeny checks l Goats (separate management groups for miniature and standard) l Developed an efficient procedure for syncing the AIP and CDCB databases l Additional traits (cow livability, age at first calving, persistency) l Changes to calving traits models

6 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole l Reasons for disposal have been reported and stored in DHI records since 1970 l About 20% of cows die instead of being sold across all lactations l Death loss per lactation averages 7%, higher in later, lower in earlier lactation Cow livability - Background

7 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole l PL measures cow’s ability to avoid dying or being culled l LIV measures cow’s ability to stay alive l LIV is a subset of PL Productive life (PL) vs. Livability (LIV)

8 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Definition l Reverse of mortality: w 0 = died this lactation w 100 = lived this lactation l Multiply by average lactations/cow (2.8) to put on a lifetime scale LIV model

9 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole l Data w 92 million records on 32 million cows l Methodology w Multi-trait 1-step model with PL (by lactation) using similar edits as other traits l Heritability of 1.3 (Miller et al., 2008), genetic correlation with lactation PL of 0.50 LIV model cont’d

10 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole TraitHOJE Milk0.09-0.08 Fat0.210.01 Protein0.16-0.01 Productive Life0.700.54 SCS-0.28-0.07 Daughter Pregnancy Rate0.400.54 Cow Conception Rate0.400.33 Heifer Conception Rate0.280.32 Number of bulls45,8403,893 Correlation of PTA LIV with other trait PTA Bulls born 1990 or later, minimum 50 daughters, 0.50 rel for PTALIV.

11 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole LIV genetic trends 1970-2013

12 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Genetic improvement of cow health l Compute breeding values for 6 common health events l Reflects economic importance, heritability, and reporting consistency based on analyses of field data DRMS Annual Meeting, New Orleans, LA, November 10-11, 2015 TraitIncidence rate (%)Heritability Displaced abomasum2.20 ± 0.420.32 ± 0.04 Ketosis5.15 ± 0.780.14 ± 0.03 Mastitis12.32 ± 1.060.10 ± 0.01 Metritis6.86 ± 0.470.07 ± 0.01 Milk fever2.40 ± 1.060.10 ± 0.01 Retained placenta4.60 ± 0.630.36 ± 0.08 Sources: Parker Gaddis et al. 2015. J. Dairy Sci. 97:3190-3199; Uribet el al. 1995. J. Dairy Sci. 78:421-430.

13 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Health Merit $ and NM$ l HM$ will provide a single value that farmers can use to make selection decisions w Change in lifetime income due to reductions in health care costs (e.g., $50) w Preferred to selection on individual traits l Can be added into NM$ similarly to CA$ l Similar concept to Zoetis’s new Wellness Trait Index (WT$)

14 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole VERY Rough Draft of HM$ l Correlations assembled from several sources – need to re-estimate! l Economic values from Liang (2013) l HM$ = (0.35 x DSAB) + (0.17 x KETO) + (0.14 x MAST) + (0.08 x METR) + (0.08 x CALC) + (0.18 x RETP) w Rough numbers, more work needed! w Does not yet account for any other traits!

15 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Genetic correlations TraitDPRPLMilk yieldSCSNM$ Displaced abomasum-0.47 0.020.19-0.35 Ketosis-0.48 0.020.25-0.40 Mastitis-0.19-0.270.090.56-0.21 Metritis-0.35-0.18-0.210.01-0.37 Retained placenta-0.44-0.34-0.050.24-0.30 Source: Parker Gaddis et al. 2015. J. Dairy Sci. 97:3190-3199. l Health traits are correlated with other traits already included in NM$ l Easy to over-state gain from new traits if correlations not well-estimated

16 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole CorrelationCANDFSFRA USA SCS, foreign MAST0.87 0.86 USA SCS, foreign SCS0.940.880.90 Correlations of SCS with mastitis Genetic correlations estimated by Interbull, Dec 2015 Genetic correlation estimated by Zoetis = 0.45

17 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole YearTraitsAddedDataCorrGain 19773ProteinDHIA 19945Productive life, SCSDHIA0.8419% 200018Size, udder, feet / legsBreeds0.946% 200321Pregnancy rate, calving ease (sire, dtr) DHIA / NAAB 0.982% 200623Stillbirth (sire, dtr)NAAB0.982% 201425Heifer, cow conceptionDHIA0.973% 2016Cow deathDHIA> 0.99 < 1% 2016316 more health traitsZoetis0.92 ?? 21% ?? Added value from more traits

18 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Use in Selection Programs l Avoid using bulls with undesirable PTA w Not all bulls with high rates of daughter illness have low NM$ l Select on an index w This ensures that you don’t overemphasize one trait or another w Results in optimal rates of genetic gain

19 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Acknowledgments l Council on Dairy Cattle Breeding l National DHIA l Binational Agricultural Research and Development (BARD) l National Institute of Food and Agriculture (NIFA), USDA l Washington State University & University of Missouri (NIFA grant) l CNPq “Science Without Borders” Program

20 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Disclaimer Mention of trade names or commercial products in this presentation is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture.

21 2016 National DHIA Annual Meeting, Orlando, FL, March 8, 2016 (‹#›) Cole Questions?

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