Genetic diversity in global chicken breeds in relation to their genetic distances to wild populations

Abstract

Abstract

Background Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation.

Methods To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations.

Results Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%.

Conclusions Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations’ needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken.