bioRxivEvolutionary Biology
Disentangling The Causes For Faster-X Evolution In Aphids
J. Jaquiery, J. Peccoud, T. Ouisse, F. Legeai, N. Prunier-Leterme, A. Gouin, P. Nouhaud, J. Brisson, R. Bickel, S. Purandare, J. Poulain, C. Battail, C. Lemaitre, L. Mieuzet, G. Le Trionnaire, J.-C. Simon, C. Rispe
Abstract
Faster evolution of X chromosomes has been documented in several species and results from the increased efficiency of selection on recessive alleles in hemizygous males and/or from increased drift due to the smaller effective population size of X chromosomes. Aphids are excellent models for evaluating the importance of selection in faster-X evolution, because their peculiar life-cycle and unusual inheritance of sex-chromosomes lead to equal effective population sizes for X and autosomes. Because we lack a high-density genetic map for the pea aphid whose complete genome has been sequenced, we assigned its entire genome to the X and autosomes based on ratios of sequencing depth in males and females. Unexpectedly, we found frequent scaffold misassembly, but we could unambiguously locate 13,726 genes on the X and 19,263 on autosomes. We found higher non-synonymous to synonymous substitutions ratios (dN/dS) for X-linked than for autosomal genes. Our analyses of substitution rates together with polymorphism and expression data showed that relaxed selection is likely to contribute predominantly to faster-X as a large fraction of X-linked genes are expressed at low rates and thus escape selection. Yet, a minor role for positive selection is also suggested by the difference between substitution rates for X and autosomes for male-biased genes (but not for asexual female-biased genes) and by lower Tajimas D for X-linked than for autosomal genes with highly male-biased expression patterns. This study highlights the relevance of organisms displaying alternative inheritance of chromosomes to the understanding of forces shaping genome evolution.
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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