Literature DB >> 27939711

Testing cospeciation through large-scale cophylogenetic studies.

Astrid Cruaud1, Jean-Yves Rasplus2.   

Abstract

Insects are involved in a multitude of interactions with other organisms, which make them ideal models for large-scale cophylogenetic studies. Once phylogenies of interacting lineages have been inferred, there are a number of questions we may wish to ask, such as what was the relationship between the partners in the past? Have they co-evolved for thousands or millions of years, or has one of the partners switched among different host species? To answer such questions, researchers may conduct cophylogenetic analysis, to explore the relationships between the phylogenies of interacting lineages and determine whether the match is significant or find explanations for observed differences. When combined with dating analyses, cophylogenetic analyses may support cospeciation of the partners or phylogenetic tracking. As they may reveal dynamics of host-pathogen coevolution, cophylogenetic studies may also help tackle global health issues (e.g. document the spread of disease causing pathogens). Cophylogenetic studies of parasitoids and their insect hosts may also help identify effective biocontrol agents. With the advent of next generation sequencing technologies and keeping in mind that systematic errors may occur, cophylogenetics will benefit from better-resolved trees, allowing more accurate reconciliation. However as trees become larger, current algorithms also become more computationally challenging. Nevertheless, both theoretical and methodological developments are leading to more accurate and powerful tests of cospeciation through cophylogenetic analysis.
Copyright © 2016 Elsevier Inc. All rights reserved.

Mesh:

Year:  2016        PMID: 27939711     DOI: 10.1016/j.cois.2016.10.004

Source DB:  PubMed          Journal:  Curr Opin Insect Sci            Impact factor:   5.186


  4 in total

1.  A Cretaceous peak in family-level insect diversity estimated with mark-recapture methodology.

Authors:  Sandra R Schachat; Conrad C Labandeira; Matthew E Clapham; Jonathan L Payne
Journal:  Proc Biol Sci       Date:  2019-12-18       Impact factor: 5.349

2.  LSX: automated reduction of gene-specific lineage evolutionary rate heterogeneity for multi-gene phylogeny inference.

Authors:  Carlos J Rivera-Rivera; Juan I Montoya-Burgos
Journal:  BMC Bioinformatics       Date:  2019-08-13       Impact factor: 3.169

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Authors:  Allison Q Byrne; Anthony W Waddle; Veronica Saenz; Michel Ohmer; Jef R Jaeger; Corinne L Richards-Zawacki; Jamie Voyles; Erica Bree Rosenblum
Journal:  PLoS One       Date:  2022-03-14       Impact factor: 3.240

4.  Microbial genomes from non-human primate gut metagenomes expand the primate-associated bacterial tree of life with over 1000 novel species.

Authors:  Serena Manara; Francesco Asnicar; Francesco Beghini; Davide Bazzani; Fabio Cumbo; Moreno Zolfo; Eleonora Nigro; Nicolai Karcher; Paolo Manghi; Marisa Isabell Metzger; Edoardo Pasolli; Nicola Segata
Journal:  Genome Biol       Date:  2019-12-28       Impact factor: 13.583

  4 in total

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