TY - JOUR
T1 - Within-herd heritability estimated with daughter-parent regression for yield and somatic cell score
AU - Dechow, C. D.
AU - Normanf, H. D.
N1 - Funding Information:
The authors appreciate funding from the Agricultural Research Service , USDA. The cooperation of AgriTech Analytics (Visalia, CA), AgSource Cooperative Services (Verona, WI), Dairy Records Management Systems (Raleigh, NC), DHI Computing Services (Provo, UT), and Texas DHIA (College Station, TX) in supplying yield data through the National Genetic Improvement Program was invaluable. The assistance of S. M. Hubbard, Animal Improvement Programs Laboratory (Beltsville, MD), and 2 anonymous reviewers in manuscript preparation is appreciated.
PY - 2007/1
Y1 - 2007/1
N2 - Estimates of heritability within herd (h2wu) that were generated with daughter-dam regression, daughtersire regression, and REML were compared, and effects of adjusting lactation records for within-herd heritability on genetic evaluations were evaluated. Holstein records for milk, fat, and protein yields and somatic cell score (SCS) from the USDA national database represented herds in the US Northeast, Southeast, Midwest, and West. Four data subsets (457 to 499 herds) were randomly selected, and a large-herd subset included the 15 largest herds from the West and 10 largest herds from other regions. Subset heritabilities for yield and SCS were estimated assuming a regression model that included fixed covariates for effects of dam yield or SCS, sire predicted transmitting ability (PTA) for yield or SCS, herd-year-season of calving, and age within parity. Dam records and sire PTA were nested within herd as random covariates to generate within-herd heritability estimates that were regressed toward mean h2WH for the random subset. Heritabilities were estimated with REML using sire models (REMLSIRE), sire-maternal grandsire models (REMLMGS) and animal models (REMLANIM) for each herd individually in the large-herd subset. Phenotypic variance for each herd was estimated from herd residual variance after adjusting for effects of year-season and age within parity. Deviations from herd-year-season mean were standardized to constant genetic variance across herds, and records were weighted according to estimated error variance to accommodate h2wH when estimating breeding values. Mean h2wH tended to be higher with daughter-dam regression (0.35 for milk yield) than with daughter-sire regression (0.24 for milk yield). Heritability estimates varied widely across herds (0.04 to 0.67 for milk yield estimated with daughter-dam regression), and h 2wn deviated from subset means more for large herds than for small herds. Correlation with REMLANIM h2WH was 0.68 for daughter-dam and was 0.45 for daughter-sire h2wH for milk yield. The correlation between daughtersire hwH and REMLMGS was greater than the correlation between daughter-dam h2WH and REMLMGs. Data adjustments had a minimal impact on breeding value bias. Within-herd heritability can be estimated rapidly using regression techniques with moderate accuracy, but adjusting lactation records for h2wH resulted in only a small improvement in the accuracy of genetic evaluations.
AB - Estimates of heritability within herd (h2wu) that were generated with daughter-dam regression, daughtersire regression, and REML were compared, and effects of adjusting lactation records for within-herd heritability on genetic evaluations were evaluated. Holstein records for milk, fat, and protein yields and somatic cell score (SCS) from the USDA national database represented herds in the US Northeast, Southeast, Midwest, and West. Four data subsets (457 to 499 herds) were randomly selected, and a large-herd subset included the 15 largest herds from the West and 10 largest herds from other regions. Subset heritabilities for yield and SCS were estimated assuming a regression model that included fixed covariates for effects of dam yield or SCS, sire predicted transmitting ability (PTA) for yield or SCS, herd-year-season of calving, and age within parity. Dam records and sire PTA were nested within herd as random covariates to generate within-herd heritability estimates that were regressed toward mean h2WH for the random subset. Heritabilities were estimated with REML using sire models (REMLSIRE), sire-maternal grandsire models (REMLMGS) and animal models (REMLANIM) for each herd individually in the large-herd subset. Phenotypic variance for each herd was estimated from herd residual variance after adjusting for effects of year-season and age within parity. Deviations from herd-year-season mean were standardized to constant genetic variance across herds, and records were weighted according to estimated error variance to accommodate h2wH when estimating breeding values. Mean h2wH tended to be higher with daughter-dam regression (0.35 for milk yield) than with daughter-sire regression (0.24 for milk yield). Heritability estimates varied widely across herds (0.04 to 0.67 for milk yield estimated with daughter-dam regression), and h 2wn deviated from subset means more for large herds than for small herds. Correlation with REMLANIM h2WH was 0.68 for daughter-dam and was 0.45 for daughter-sire h2wH for milk yield. The correlation between daughtersire hwH and REMLMGS was greater than the correlation between daughter-dam h2WH and REMLMGs. Data adjustments had a minimal impact on breeding value bias. Within-herd heritability can be estimated rapidly using regression techniques with moderate accuracy, but adjusting lactation records for h2wH resulted in only a small improvement in the accuracy of genetic evaluations.
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U2 - 10.3168/jds.S0022-0302(07)72650-4
DO - 10.3168/jds.S0022-0302(07)72650-4
M3 - Article
C2 - 17183117
AN - SCOPUS:35748985587
SN - 0022-0302
VL - 90
SP - 482
EP - 492
JO - Journal of dairy science
JF - Journal of dairy science
IS - 1
ER -