Abstract
Genomic relationships can be computed with dense genome-wide genotypes through different methods, either based on identity-by-state (IBS) or identity-by-descent (IBD). The latter has been shown to increase the accuracy of both estimated relationships and predicted breeding values. However, it is not clear whether an IBD approach would achieve greater heritability (h2$$ {\boldsymbol{h}}<^>{\mathbf{2}} $$) and predictive ability (ry,y$$ {\hat{r}}_{y,\hat{y}} $$) than its IBS counterpart for data with low-depth pedigrees. Here, we compare both approaches in terms of the estimated of h2$$ {\boldsymbol{h}}<^>{\mathbf{2}} $$ and ry,y$$ {\hat{r}}_{y,\hat{y}} $$, using data on meat quality and carcass traits recorded in experimental crossbred pigs, with a pedigree constrained to only three generations. Three animal models were fitted which differed on the relationship matrix: an IBS model (GIBS$$ {\boldsymbol{G}}_{\mathbf{IBS}} $$), an IBD (defined within the known pedigree) model (GIBD$$ {\boldsymbol{G}}_{\mathbf{IBD}} $$), and a pedigree model (A22$$ {\boldsymbol{A}}_{\mathbf{22}} $$). In 9 of 20 traits, the range of increase for the estimates of sigma u2$$ {\sigma}_{\mathrm{u}}<^>2 $$ and h2$$ {\boldsymbol{h}}<^>{\mathbf{2}} $$ was 1.2-2.9 times greater with GIBS$$ {\boldsymbol{G}}_{\mathbf{IBS}} $$ and GIBD$$ {\boldsymbol{G}}_{\mathbf{IBD}} $$ models than with A22$$ {\boldsymbol{A}}_{\mathbf{22}} $$. Whereas for all traits, both parameters were similar between genomic models. The ry,y$$ {\hat{r}}_{y,\hat{y}} $$ of the genomic models was higher compared to A22$$ {\boldsymbol{A}}_{\mathbf{22}} $$. A scarce increment in ry,y$$ {\hat{r}}_{y,\hat{y}} $$ was found with GIBS$$ {\boldsymbol{G}}_{\mathbf{IBS}} $$ when compared to GIBD$$ {\boldsymbol{G}}_{\mathbf{IBD}} $$, most likely due to the former recovering sizeable relationships among founder F-0 animals.
Funding Information
  • Fondo para la Investigación Científica y Tecnológica (PICT‐2018‐04497)
  • National Institute of Food and Agriculture (2021‐67021‐34150)
  • Agencia Nacional de Promoción Científica y Tecnológica
  • Universidad de Buenos Aires
  • Michigan State University