Use of a single-step approach for integrating foreign information into national genomic evaluation in Holstein cattle

Abstract

The use of multi-trait across-country evaluation (MACE) and the exchange of genomic information among countries allows national breeding programs to combine foreign and national data to increase the size of the training populations and potentially increase accuracy of genomic prediction of breeding values. By including genotyped and nongenotyped animals simultaneously in the evaluation, the single-step genomic BLUP (GBLUP) approach has the potential to deliver more accurate and less biased genomic evaluations. A single-step genomic BLUP approach, which enables integration of data from MACE evaluations, can be used to obtain genomic predictions while avoiding doublecounting of information. The objectives of this study were to apply a single-step approach that simultaneously includes domestic and MACE information for genomic evaluation of workability traits in Canadian Holstein cattle, and compare the results obtained with this methodology with those obtained using a multistep approach (msGBLUP). By including MACE bulls in the training population, msGBLUP led to an increase in reliability of genomic predictions of 4.8 and 15.4% for milking temperament and milking speed, respectively, compared with a traditional evaluation using only pedigree and phenotypic information. Integration of MACE data through a single-step approach (ssGBLUP IM ) yielded the highest reliabilities compared with other considered methods. Integration of MACE data also helped reduce bias of genomic predictions. When using ssGBLUP IM , the bias of genomic predictions decreased by half compared with msGBLUP using domestic and MACE information. Therefore, the reliability and bias of genomic predictions for both traits improved substantially when a single-step approach was used for evaluation compared with a multi-step approach. The use of a single-step approach with integration of MACE information provides an alternative to the current method used in Canadian genomic evaluations.

Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups

“…The values of accuracy estimators confirm that the inclusion of genomic information increases the accuracy of the EBV of individuals without daughter records, which is consistent with other studies [ 41 – 44 ].…”

Genomic evaluation of Brown Swiss dairy cattle with limited national genotype data and integrated external information

“…Regression coefficient was the same for the EBV f,r and the GEBV f,r (0.60), indicating similar over-dispersion of breeding values from the reduced evaluation in the pedigreebased as well as in the single-step genomic evaluation. Guarini et al (2019), in contrast to our results, found that integration of MACE information in the singlestep genomic evaluation for milk yield and milking traits reduces inflation of genomic breeding values and genomic breeding value reliabilities in bulls. However, the results are hard to compare as the regression analyses differ among studies.…”

“…They obtained 9.6-point and 19.3-point EBV to GEBV REL increases with domestic ssGBLUP evaluation for their 2 traits, which is in agreement with Colinet et al (2013) for bulls with low EBV REL, and with our results for validation males. Guarini et al (2019) obtained additional 0.2-point and 1.4-point GEBV to GEBVM REL increases, respectively, when they integrated MACE information, which is lower than the rest of the presented and reviewed results in the present study.…”

“…A small training population can negatively affect GEBV REL (e.g., Lund et al, 2011), but that was not the case in the present study. However, the importance of combining national and available foreign information in genomic evaluation has been shown in several publications (Vandenplas et al, 2015;Vandenplas et al, 2017;Andonov et al, 2017;Colinet et al, 2018;Guarini et al, 2019). Combining multiple information sources is especially relevant for small cattle populations with limited national information where all additional information in evaluation is useful.…”

“…Our average GEBV f to GEBVM f REL increase for the youngest individuals was closer to the increase from the recent study (Colinet et al, 2018;19 points) where they included a greater amount of genomic and MACE information. Guarini et al (2019) also used Holstein data with genotype information for 33,000 bulls and obtained higher reliabilities integrating MACE information into ssGBLUP than in multiple-step GB-LUP evaluation for milking temperament and speed. Similar to Colinet et al (2013), they integrated April 2013 MACE information into genomic evaluations for around 1,800 genotyped sires, of which ~100 contributed to integrated MACE evaluation.…”