Journal article
Influence of Effective Population Size on Genes under Varying Levels of Selection Pressure
Genome Biology and Evolution, Vol.10(3), pp.756-762
2018
PMCID: PMC5841380
PMID: 29608718
Abstract
The ratio of diversities at amino acid changing (nonsynonymous) and neutral (synonymous) sites (ω = πN/πS) is routinely used to measure the intensity of selection pressure. It is well known that this ratio is influenced by the effective population size (Ne) and selection coefficient (s). Here, we examined the effects of effective population size on ω by comparing protein-coding genes from Mus musculus castaneus and Mus musculus musculus-two mouse subspecies with different Ne. Our results revealed a positive relationship between the magnitude of selection intensity and the ω estimated for genes. For genes under high selective constraints, the ω estimated for the subspecies with small Ne (M. m. musculus) was three times higher than that observed for that with large Ne (M. m. castaneus). However, this difference was only 18% for genes under relaxed selective constraints. We showed that the observed relationship is qualitatively similar to the theoretical predictions. We also showed that, for highly expressed genes, the ω of M. m. musculus was 2.1 times higher than that of M.m. castaneus and this difference was only 27% for genes with low expression levels. These results suggest that the effect of effective population size is more pronounced in genes under high purifying selection. Hence the choice of genes is important when ω is used to infer the effective size of a population.
Details
- Title
- Influence of Effective Population Size on Genes under Varying Levels of Selection Pressure
- Authors
- Sankar Subramanian (Corresponding Author) - University of the Sunshine Coast, Queensland, GeneCology Research Centre - Legacy
- Publication details
- Genome Biology and Evolution, Vol.10(3), pp.756-762
- Publisher
- Oxford University Press
- Date published
- 2018
- DOI
- 10.1093/gbe/evy047
- ISSN
- 1759-6653
- PMID
- 29608718; PMC5841380
- Copyright note
- Copyright © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
- Organisation Unit
- School of Science and Engineering - Legacy; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99451349202621
- Output Type
- Journal article
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