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You are here: Home / Teams / Comparative and Integrative Genomics of Organ Development - S.Pantalacci/M. Semon / RESEARCH PROJECTS / Multispecies detection of convergent genomic evolution

Multispecies detection of convergent genomic evolution

Convergent evolution is widespread in the history of animals. In several case-studies, the same iconic gene was shown to be repeatedly recruited in two lineages. Yet we still lack a broader perspective on convergent evolution, encompassing the genome scale and many instances of convergence.

How much of the evolution of convergent phenotypes is due to the appearance of multiple genomic changes that are convergent themselves? How far are convergent phenotypes underlaid by convergent genome expression? We are involved in a collaborative integrative study of convergent genomic evolution across three animal groups (see more on the website of the project).

We develop bioinformatic methods to integrate RNA-seq data in phylogenies, to measure convergent evolution in genomic sequences as well as in expression level and timing. We study convergent adaptation of rodents to aridity, as well as convergent evolution of tooth morphology (see also here).

  • “Amalgam”, a method for transcriptome assembly and family delimitation

When the sequence of the genome of the species of interest in not available, genes must be assembled de novo from RNA-seq data. Many methods have been proposed but it is common that genes assembled from RNA-seq data are incomplete and present as multiple isoforms. The nature of the input data imposes some alterations of classical pipelines. Amalgam is an automated method which allows to obtain gene family datasets with non-model many species. Amalgam can annotate RNA-Seq data from non-model organisms (one or several species at the time), with the help of known reference sequences of related organisms, and incorporate them with genomic data provided by the user.

  • Detection of convergence in genome sequences

We detect convergent events with a method based on substitution mapping: Because they are based on the raw signal, i.e. events of substitution, they can be corrected for many confounding factors using appropriate substitution models, and be used to search for more complicated events of convergent evolution (Coll. Bastien Boussau, Philippe Veber, Univ Lyon1). This method will be applied to a dataset with 7 transitions to aridity in rodents.

  • Detection of convergence in expression levels and timing

We will detect convergent events in expression levels with methods based on the phylogeny. We will also develop methods to detect convergent changes in expression timing in transcriptome timeseries, within a phylogenetical framework (Coll. Laurent Guéguen, Univ Lyon1). This will be applied to a developmental dataset, asking how far convergent expression changes during development underlie the convergent molar morphology of mice and spiny mice (see more here).

  • What is the level of convergent genomic evolution in arid rodents?

The methods developed above will be applied to a dataset with 7 transitions to aridity in rodents. Adaptation to arid environments occurred several times independently during rodent history in various groups and different places of the world, the most extreme case being adaptation to life in deserts (e.g. gerbils in Africa or the kangaroo rats in the Americas). Rodents inhabiting these environments present a whole range of morphological, physiological and behavioral adaptations in order to cope with limited water and food availability. Hence, adaptation to arid environments involves a number of different traits justifying to study convergence in coding sequences, and expression in kidney is highly relevant to study convergence in expression levels. We will study the proportion of convergent events in relation to adaptation to aridity in the rodent genomes and quantify convergence in kidney expression and in sequences.

People involved in the team: Carine Rey, Domitille Chalopin, Marion Mouginot, Lucas Michon (M2, Past member)

Collaborations: Bastien Boussau, Laurent Guéguen, and Philippe Veber, LBBE, Université Lyon1