Abstract
BackgroundThe detection of signatures of selection has the potential to elucidate the identities of genes and mutations associated with phenotypic traits important for livestock species. It is also very relevant to investigate the levels of genetic diversity of a population, as genetic diversity represents the raw material essential for breeding and has practical implications for implementation of genomic selection. A total of 1151 animals from nine goat populations selected for different breeding goals and genotyped with the Illumina Goat 50K single nucleotide polymorphisms (SNP) Beadchip were included in this investigation.ResultsThe proportion of polymorphic SNPs ranged from 0.902 (Nubian) to 0.995 (Rangeland). The overall mean HO and HE was 0.374 ± 0.021 and 0.369 ± 0.023, respectively. The average pairwise genetic distance (D) ranged from 0.263 (Toggenburg) to 0.323 (Rangeland). The overall average for the inbreeding measures FEH, FVR, FLEUT, FROH and FPED was 0.129, −0.012, −0.010, 0.038 and 0.030, respectively. Several regions located on 19 chromosomes were potentially under selection in at least one of the goat breeds. The genomic population tree constructed using all SNPs differentiated breeds based on selection purpose, while genomic population tree built using only SNPs in the most significant region showed a great differentiation between LaMancha and the other breeds. We hypothesized that this region is related to ear morphogenesis. Furthermore, we identified genes potentially related to reproduction traits, adult body mass, efficiency of food conversion, abdominal fat deposition, conformation traits, liver fat metabolism, milk fatty acids, somatic cells score, milk protein, thermo-tolerance and ear morphogenesis.ConclusionsIn general, moderate to high levels of genetic variability were observed for all the breeds and a characterization of runs of homozygosity gave insights into the breeds’ development history. The information reported here will be useful for the implementation of genomic selection and other genomic studies in goats. We also identified various genome regions under positive selection using smoothed FST and hapFLK statistics and suggested genes, which are potentially under selection. These results can now provide a foundation to formulate biological hypotheses related to selection processes in goats.
Highlights
The detection of signatures of selection has the potential to elucidate the identities of genes and mutations associated with phenotypic traits important for livestock species
The objectives of this study were: 1) to present a comprehensive genome-wide analysis of genetic diversity of a variety of the worldwide most common goat breeds; 2) to detect signatures of selection using a 50K single nucleotide polymorphisms (SNP) chip using different methodologies and the most common breeds raised for fiber, meat and/or milk production and geographically distinct populations of the same breed (i.e. Boer); 3) to provide, for the first time, a comprehensive characterization of runs of homozygosity (ROH) in the goat genome using a collection of diverse breeds; and 4) to examine potential biological functions and metabolic pathways of the genes in the identified regions of selection signatures
SNPs with minor allele frequency (MAF) lower than 0.01, call rate lower than 95%, SNPs located on the X chromosome or without known position in the genome were excluded from the analysis
Summary
The detection of signatures of selection has the potential to elucidate the identities of genes and mutations associated with phenotypic traits important for livestock species. The detection of signatures of selection is a relevant topic since it has the potential to elucidate the identities of genes and mutations associated with phenotypic traits even if they are no longer segregating within any of the populations of interest and does not necessarily require phenotypes measures. This knowledge is important in order to better understand the evolution process and the mechanisms that underlie traits that have been exposed to intensive natural and artificial selection. We can make use of this information to design and/or update breeding and conservation programs worldwide
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