Selection, genome-wide fitness effects and evolutionary rates in the model legume Medicago truncatula

Timothy Paape, Thomas Bataillon, Peng Zhou, Tom J.Y. Kono, Roman Briskine, Nevin D. Young, Peter Tiffin

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Sequence data for >20 000 annotated genes from 56 accessions of Medicago truncatula were used to identify potential targets of positive selection, the determinants of evolutionary rate variation and the relative importance of positive and purifying selection in shaping nucleotide diversity. Based upon patterns of intraspecific diversity and interspecific divergence, c. 50-75% of nonsynonymous polymorphisms are subject to strong purifying selection and 1% of the sampled genes harbour a signature of positive selection. Combining polymorphism with expression data, we estimated the distribution of fitness effects and found that the proportion of deleterious mutations is significantly greater for expressed genes than for genes with undetected transcripts (nonexpressed) in a previous RNA-seq experiment and greater for broadly expressed genes than those expressed in only a single tissue. Expression level is the strongest correlate of evolutionary rates at nonsynonymous sites, and despite multiple genomic features being significantly correlated with evolutionary rates, they explain less than 20% of the variation in nonsynonymous rates (dN) and <15% of the variation in either synonymous rates (dS) or dN:dS. Among putative targets of selection were genes involved in defence against pathogens and herbivores, genes with roles in mediating the relationship with rhizobial symbionts and one-third of annotated histone-lysine methyltransferases. Adaptive evolution of the methyltransferases suggests that positive selection in gene expression may have occurred through evolution of enzymes involved in epigenetic modification.

Original languageEnglish (US)
Pages (from-to)3525-3538
Number of pages14
JournalMolecular ecology
Volume22
Issue number13
DOIs
StatePublished - Jul 2013

Keywords

  • adaptive evolution
  • evolutionary rates
  • population genomics
  • purifying selection

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