Autoregressive single-step test-day model for genomic evaluations of Portuguese Holstein cattle

Abstract

The multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (autocorrelations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set were 0.52 (0.16) and 0.72 (0.62) for genotyped bulls with no daughters and bulls with 1 to 9 daughters, respectively. These results showed an increase in EBV reliabilities of 0.10 to 0.36 when genomic information was included, corresponding to a reduction of up to 43% in prediction error variance. Considering the 3 validation scenarios, the inclusion of genomic information improved the average EBV reliability in the reduced data set, which ranged, on average, from 0.16 to 0.26, indicating an increase in the predictive ability. Similarly, empirical reliability increased by up to 0.08 between validation tests. The H-AR outperformed A-AR in terms of genetic trends when unproven genotyped bulls were included. The results suggest that the single-step GBLUP AR model is feasible and may be applied to national Portuguese genetic evaluations for milk yield.

Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle

“…Silva et al . (2019 a ) reported a drop in the genetic tendencies for productive traits for this period. Therefore, the response observed in the genetic trends for reproductive traits could be actually a correlated response from the selection on the productive traits.…”

“…This suggests that the genetic trends observed along those years were a result of indirect selection on production traits. In fact, the trends here observed are almost the opposite of those of milk production for the same period (Silva et al ., 2019 a ). As in other countries, the Portuguese dairy breeding program has as its main goal, the increase of milk production and its components.…”

“…Starting in the year 2008-2010, Portugal underwent a strong economic recession, affecting all sectors of the economy, including the importation of genetics (frozen semen and heifers). Silva et al (2019a) reported a drop in the genetic tendencies for productive traits for this period. Therefore, the response observed in the genetic trends for reproductive traits could be actually a correlated response from the selection on the productive traits.…”

Autoregressive and random regression test‐day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle

“…As a future implication, given the current relevance of genomic selection for dairy breeding programs, both RR (Oliveira, Brito, et al, ) and AR (Silva, Silva, et al, ) models have been tailored to handle SNP marker data. In this context, further comparisons should be carried out in order to evaluate possible major differences between these models.…”

Autoregressive single‐step model for genomic evaluation of longitudinal reproductive traits in portuguese holstein cattle

“…The next step for the Portuguese dairy cattle breeding programme will be the inclusion of genomic data in their genetic evaluations. Recently, Silva et al (2019) demonstrated the feasibility of using the ssGBLUP methodology under the AR-Model for genomic evaluation of milk production traits in the Portuguese Holstein cattle. They reported higher EBV reliabilities for young bulls when compared with the traditional autoregressive model (using pedigree-based relationship matrix).…”