Understanding the coevolutionary dynamics of mutualism with population genomics. Issue 10 (18th October 2016)

• Record Type: Journal Article
• Authors: Yoder, Jeremy B.
• Is Part Of: American journal of botany. Volume 103:Issue 10(2016)
• Page Start: 1742
• Page End: 1752
• Publication Date: 2016-10-18
• Subjects: coevolution -- Fabaceae -- Medicago truncatula -- mutualism -- population genomics -- symbiosis; Botany -- Periodicals; Botany; Electronic journals; Periodicals; 580
• DOI: 10.3732/ajb.1600154
• Languages: English
• ISSNs: 0002-9122

Abstract

Abstract : Decades of research on the evolution of mutualism has generated a wealth of possible ways whereby mutually beneficial interactions between species persist in spite of the apparent advantages to individuals that accept the benefits of mutualism without reciprocating — but identifying how any particular empirical system is stabilized against cheating remains challenging. Different hypothesized models of mutualism stability predict different forms of coevolutionary selection, and emerging high‐throughput sequencing methods allow examination of the selective histories of mutualism genes and, thereby, the form of selection acting on those genes. Here, I review the evolutionary theory of mutualism stability and identify how differing models make contrasting predictions for the population genomic diversity and geographic differentiation of mutualism‐related genes. As an example of the possibilities offered by genomic data, I analyze genes with roles in the symbiosis of Medicago truncatula and nitrogen‐fixing rhizobial bacteria, the first classic mutualism in which extensive genomic resources have been developed for both partners. Medicago truncatula symbiosis genes, as a group, differ from the rest of the genome, but they vary in the form of selection indicated by their diversity and differentiation — some show signs of selection expected from roles in sanctioning noncooperative symbionts, while others show evidence of balancing selection expected from coevolution with symbiont signaling factors. I then assess the current state of development for similar resources in other mutualistic interactions and look ahead to identify ways in which modern sequencing technology can best inform our understanding of mutualists and mutualism.