Genomic analysis of divergently selected experimental lines in rabbit

Resumen

Divergent selection can alter frequencies of genetic markers in opposite directions, leading to intermediate allelic frequencies when both divergent lines are jointly considered in the genetic analyses. Therefore, divergent selection experiments increase the detection power for genome wide association studies (GWAS) and for genomic scan studies through methods of selection signatures. Bayesian GWASs using Bayes B model was used to analyse genomic data of litter size traits of the uterine capacity experiment with 181 does. The associations were tested by computing Bayes factors for each SNP, and by computing percentages of the genomic variance for each 1-Mb non-overlapping window. The GWASs uncovered SNPs associated with total number born and implanted embryos. Moreover, relevant genomic regions were revealed for total number born (1 region), number born alive (1 region), implanted embryos (3 regions), and ovulation rate (5 regions). The percentages of genomic variance that accounted for these litter size traits were 39,48%, 10.36%, 37.21%, and 3.95%, respectively, under a model excluding line effect; and 7.36%, 1.27%, 15.87%, and 3.95%, respectively, under a model with line effect. The genomic region located on the rabbit chromosome (OCU) 17 in 70.0 - 73.3 Mb was deemed as a novel quantitative trait locus (QTL) of reproductive traits in rabbits, since this region was found overlapped for total number born, number born alive and implanted embryos. Bone morphogenetic protein 4 gene, BMP4, is the main promising candidate gene within the novel QTL. A combination of GWASs were performed for analysing the genomic data of the intramuscular fat experiment with 480 rabbits. The GWAS methods included a Bayesian method, Bayes B model; and a frequentist method, single marker regressions with the data adjusted by genomic relatedness. This study revealed four relevant genomic regions in OCU1 (1 region), OCU8 (2 regions) and OCU13 (1 region) associated with intramuscular fat. The most important associated region was on OCU8 in 24.59 - 26.95 Mb, and accounted for 7.34% of the genomic variance. The low percentage explained by the main relevant genomic regions indicates a large polygenic component for intramuscular fat. Functional analyses retrieved genes linked to pathways and function of energy, carbohydrate and lipid metabolisms. In addition, a genome scan study was performed using rabbits from the divergent selection experiment for intramuscular fat, and using three methods of selection signatures: Wright's fixation index (Fst), cross population composite likelihood ratio (XP-CLR) and cross population extended haplotype homozygosity (XP-EHH). The results showed multiple selection signatures across the rabbit genome. None of these selection signatures agreed with the associated genomic regions from GWAS findings. In synthesis, the results of both experiments, GWAS and genome scan study, suggest that the genomic architecture of intramuscular fat in rabbit seems to be highly polygenic and their causative variants would be hardly detectable. This study demonstrates that detection of causative variants and associated genetic markers depends on the hypothetical genomic architectures of traits, regardless of the successful responses attained in the two divergent selection experiments. Hitherto, these findings would not have worthwhile implications for the rabbit breeding programs.