Improving genetic evaluation using a multitrait single-step genomic model for ability to resume cycling after calving, measured by activity tags in Holstein cows.

The objective of this study was to evaluate the improvement of the accuracy of estimated breeding values for ability to recycle after calving by using information of genomic markers and phenotypic information of correlated traits. The traits in this study were the interval from calving to first insemination (CFI), based on artificial insemination data, and the interval from calving to first high activity (CFHA), recorded from activity tags, which could better measure ability to recycle after caving. The phenotypic data set included 1,472,313 records from 820,218 cows for CFI, and 36,504 records from 25,733 cows for CFHA. The genomic information was available for 3,159 progeny-tested sires, which were genotyped using Illumina Bovine SNP50 BeadChip (Illumina, San Diego, CA). Heritability estimates were 0.06 for the interval from calving to first insemination and 0.14 for the interval from calving to first high activity, and the genetic correlation between both traits was strong (0.87). Breeding values were obtained using 4 models: conventional single-trait BLUP; conventional multitrait BLUP with pedigree-based relationship matrix; single-trait single-step genomic BLUP; and multitrait single-step genomic BLUP model with joint relationship matrix combining pedigree and genomic information. The results showed that reliabilities of estimated breeding values (EBV) from single-step genomic BLUP models were about 40% higher than those from conventional BLUP models for both traits. Furthermore, using a multitrait model doubled the reliability of breeding values for CFHA, whereas no gain was observed for CFI. The best model was the multitrait single-step genomic BLUP, which resulted in a reliability of EBV 0.19 for CFHA and 0.14 for CFI. The results indicate that even though a relatively small number of records for CFHA were available, with genomic information and using multitrait model, the reliability of EBV for CFHA is acceptable. Thus, it is feasible to include CFHA in Nordic Holstein breeding evaluations to improve fertility performance.

Ismael A ，Løvendahl P ，Fogh A ，Lund MS ，Su G ... -  《-》

Application of multivariate single-step SNP best linear unbiased predictor model and revised SNP list for genomic evaluation of dairy cattle in Australia.

The objectives of this study were (1) to evaluate the computational feasibility of the multitrait test-day single-step SNP-BLUP (ssSNP-BLUP) model using phenotypic records of genotyped and nongenotyped animals, and (2) to compare accuracies (coefficient of determination; R2) and bias of genomic estimated breeding values (GEBV) and de-regressed proofs as response variables in 3 Australian dairy cattle breeds (i.e., Holstein, Jersey, and Red breeds). Additive genomic random regression coefficients for milk, fat, protein yield and somatic cell score were predicted in the first, second, and third lactation. The predicted coefficients were used to derive 305-d GEBV and were compared with the traditional parent averages obtained from a BLUP model without genomic information. Cow fertility traits were evaluated from the 5-trait repeatability model (i.e., calving interval, days from calving to first service, pregnancy diagnosis, first service nonreturn rate, and lactation length). The de-regressed proofs were only for calving interval. Our results showed that ssSNP-BLUP using multitrait test-day model increased reliability and reduced bias of breeding values of young animals when compared with parent average from traditional BLUP in Australian Holsten, Jersey, and Red breeds. The use of a custom selection of approximately 46,000 SNP (custom XT SNP list) increased the reliability of GEBV compared with the results obtained using the commercial Illumina 50K chip (Illumina, San Diego, CA). The use of the second preconditioner substantially improved the convergence rate of the preconditioned conjugate gradient method, but further work is needed to improve the efficiency of the computation of the Kronecker matrix product by vector. Application of ssSNP-BLUP to multitrait random regression models is computationally feasible.

Konstantinov KV ，Goddard ME 《-》

Estrus traits derived from activity measurements are heritable and closely related to the time from calving to first insemination.

The aim of this study was to estimate genetic parameters for estrus-related traits that could improve selection for increased fertility due to improved ability of the cow to return to cycling and go into heat after calving. We compared the time from calving to first insemination (CFI) to 3 physical activity traits: the interval from calving to first high activity (CFHA), estrus duration (ED), and estrus strength (ES). We calculated CFI based on data from commercial Holstein herds that included the insemination dates for 11,363 cows. The CFHA, ED, and ES traits were derived from electronic activity tags for 3,533 Holstein cows. Estimates of heritability were 0.07 for CFI, 0.16 for CFHA, 0.02 for ED, and 0.05 for ES. We found a strong genetic correlation between CFI and CFHA (0.96). Genetic correlations between ED and CFI and CFHA were -0.37 and -0.68, respectively. Genetic correlations between ES and CFI and CFHA were -0.50 and -0.58, respectively. The heritability of CFHA and its strong genetic correlation with CFI suggest that including CFHA in the genetic evaluation of female cow fertility could improve the effectiveness of selection, because CFHA reflects the ability to return to cyclicity and go into heat after calving.

Ismael A ，Strandberg E ，Kargo M ，Fogh A ，Løvendahl P ... -  《-》

Single step genomic evaluation for female fertility in Nordic Red dairy cattle.

Joint Nordic (Denmark, Finland, Sweden) genetic evaluation of female fertility is currently based on the multiple trait multilactation animal model (BLUP). Here, single step genomic model (ssGBLUP) was applied for the Nordic Red dairy cattle fertility evaluation. The 11 traits comprised of nonreturn rate and days from first to last insemination in heifers and first three parities, and days from calving to first insemination in the first three parities. Traits had low heritabilities (0.015-0.04), but moderately high genetic correlations between the parities (0.60-0.88). Phenotypic data included 4,226,715 animals with records and pedigree 5,445,392 animals. Unknown parents were assigned into 332 phantom parent groups (PPG). In mixed model equations animals were associated with PPG effects through the pedigree or both the pedigree and genomic information. Genotype information of 46,914 SNPs was available for 33,969 animals in the pedigree. When PPG used pedigree information only, BLUP converged after 2,420 iterations whereas the ssGBLUP evaluation needed over ten thousand iterations. When the PPG effects were solved accounting both the pedigree and the genomic information, the ssGBLUP model converged after 2,406 iterations. Also, with the latter model breeding values by ssGBLUP and BLUP became more consistent and genetic trends followed each other well. Models were validated using forward prediction of the young bulls. Reliabilities and variance inflation of predicted genomic breeding values (values for parent averages in brackets) for the 11 traits ranged 0.22-0.31 (0.10-0.27) and 0.81-0.95 (0.83-1.06), respectively. The ssGBLUP model gave always higher validation reliabilities than BLUP, but largest increases were for the cow fertility traits.

Matilainen K ，Strandén I ，Aamand GP ，Mäntysaari EA ... -  《-》

Seasonality of fertility measured by physical activity traits in Holstein cows.

Seasonality of female fertility traits, including the interval from calving to first high activity (CFHA), duration of high activity episode (DHA), and strength of high activity episode (SHA) of first estrus, were studied. The physical activity traits were derived from electronic activity tags for 20,794 Holstein cows in 135 commercial Holstein herds in Denmark. Data were categorized in 3 ways: (1) into 4 seasons of calving: winter (January-March), spring (April-June), summer (July-September), and fall (October-December); (2) into 2 seasons: a cold season (October-March) and a warm season (April-September); and (3) into an increasing light season (IL; January-June), where daylight hours gradually increased, and a decreasing light season (DL; July-December), where daylight hours gradually decreased. At the phenotypic level, least squares means of CFHA were highest at 55d for cows calving in December and lowest at 31d for cows calving in September. The highest least squares means of DHA and SHA were recorded for cows calving in November and lowest for cows calving in May and June. Genetic parameters for all traits were estimated using average information-REML in a bivariate animal model that treated the same trait in different calving seasons as different traits. Heritability estimates for CFHA were highest for the winter season (0.13) and low for the other seasons (0.03-0.04), whereas heritability estimates for DHA and SHA were lowest for winter and highest for fall. Heritability estimates for CFHA for the cold season (0.17) was higher than that for the warm season (0.10). Heritability estimates of CFHA for the IL season (0.12) was higher than for the DL season (0.07), but the opposite pattern was found for DHA and SHA. Genetic correlations (rA) of CFHA between winter and summer (rA=0.34 ± 0.27), and winter and fall (rA=0.65 ± 0.20) were significantly lower than unity. The corresponding correlations of DHA and SHA between seasons were all close to unity, except for the correlation of SHA between winter and fall (rA=0.36 ± 0.34). When the year was split into only 2 seasons, the genetic correlation of CFHA between cold and warm seasons was only moderate (rA=0.46 ± 0.15) but was slightly stronger between IL and DL seasons (rA=0.63 ± 0.16); both significantly deviated from unity. These results indicate the existence of a genotype by environment interaction for CFHA regardless of calving season classification.

Ismael A ，Strandberg E ，Berglund B ，Fogh A ，Løvendahl P ... -  《-》