The effect of divergent selection for intramuscular fat on the domestic rabbit genome

Abstract

An experiment of divergent selection for intramuscular fat was carried out at Universitat Politècnica de València. The high response of selection in intramuscular fat content, after nine generations of selection, and a multidimensional scaling analysis showed a high degree of genomic differentiation between the two divergent populations. Therefore, local genomic differences could link genomic regions, encompassing selective sweeps, to the trait used as selection criterion. In this sense, the aim of this study was to identify genomic regions related to intramuscular fat through three methods for detection of selection signatures and to generate a list of candidate genes. The methods implemented in this study were Wright’s fixation index, cross population composite likelihood ratio and cross population – extended haplotype homozygosity. Genomic data came from the 9th generation of the two populations divergently selected, 237 from Low line and 240 from High line. A high single nucleotide polymorphism (SNP) density array, Affymetrix Axiom OrcunSNP Array (around 200k SNPs), was used for genotyping samples. Several genomic regions distributed along rabbit chromosomes (OCU) were identified as signatures of selection (SNPs having a value above cut-off of 1%) within each method. In contrast, 8 genomic regions, harbouring 80 SNPs (OCU1, OCU3, OCU6, OCU7, OCU16 and OCU17), were identified by at least 2 methods and none by the 3 methods. In general, our results suggest that intramuscular fat selection influenced multiple genomic regions which can be a consequence of either only selection effect or the combined effect of selection and genetic drift. In addition, 73 genes were retrieved from the 8 selection signatures. After functional and enrichment analyses, the main genes into the selection signatures linked to energy, fatty acids, carbohydrates and lipid metabolic processes were ACER2, PLIN2, DENND4C, RPS6, RRAGA (OCU1), ST8SIA6, VIM (OCU16), RORA, GANC and PLA2G4B (OCU17). This genomic scan is the first study using rabbits from a divergent selection experiment. Our results pointed out a large polygenic component of the intramuscular fat content. Besides, promising positional candidate genes would be analysed in further studies in order to bear out their contributions to this trait and their feasible implications for rabbit breeding programmes.

Rabbits Divergently Selected for Total Body Fat Content: Changes in Proximate Composition and Fatty Acids of Different Meat Portions

“…Considering other muscles, selection for intramuscular fat content generated correlated responses also in the biceps femoris , supraspinatus and semimembranosus proprius [ 22 ]. Recent findings have also highlighted that a ten-generation divergent selection for intramuscular fat content produced rabbit populations characterized by a high degree of genomic differentiation, with ten main genes involved and a large polygenic component [ 24 ].…”

Selection for environmental variance of litter size in rabbits involves genes in pathways controlling animal resilience

“…Divergent lines provide good biological material for genomic studies since they are selected for a unique trait and share the same environment. Previous studies on intramuscular fat (IMF) in rabbits and pigs [ 16 , 29 ], and on antibody response and feather pecking behaviour in chickens [ 30 , 31 ], using divergently selected lines, successfully detected signatures of selection, and identified associated genomic regions. The principal component analysis based on genotype data in our study showed a clear separation between the two divergent rabbit lines (Fig.…”

“…Indeed, as each method is based on different assumptions (Fig. 1 ), correlations between results are low [ 15 , 16 ], which makes it difficult to detect overlaps between the identified signatures of selection. The methods used to detect signatures of selection should be considered independently of the sources of QTL detection.…”

“…Previous studies in divergent populations showed that some overlapping occurred between the signatures of selection obtained by F ST analysis and a few QTL identified by GWAS [ 16 , 29 – 31 ]. In contrast to our study, those studies used populations from a long-term divergent selection (during 40 generations) [ 30 , 31 ], or from a selection for a highly heritable trait (intramuscular fat; IMF) [ 16 , 29 ]. The fact that V E of LS has a low heritability and accuracy [ 12 ] could hinder the identification of the genomic regions under selection in GWAS.…”

“…Several methods for the detection of signatures of selection have been proposed and are based on different assumptions according to the pattern of positive selection to be detected [ 14 ]: (1) reduction of the local genomic variability, (2) modification of the spectrums of allele frequency, or (3) variation of the linkage disequilibrium (LD). However, because of these different assumptions, the three methods are not strongly correlated [ 15 , 16 ] and, thus, have to be used in conjunction to identify the largest possible number of signatures of selection.…”