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J Exp Zool B Mol Dev Evol. 2015 Jun;324(4):372-82. doi: 10.1002/jez.b.22618. Epub 2015 Apr 10.

What to compare and how: Comparative transcriptomics for Evo-Devo.

Author information

1
Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
2
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
3
Department of Human Genetics, University of Chicago, Chicago, Illinois.

Abstract

Evolutionary developmental biology has grown historically from the capacity to relate patterns of evolution in anatomy to patterns of evolution of expression of specific genes, whether between very distantly related species, or very closely related species or populations. Scaling up such studies by taking advantage of modern transcriptomics brings promising improvements, allowing us to estimate the overall impact and molecular mechanisms of convergence, constraint or innovation in anatomy and development. But it also presents major challenges, including the computational definitions of anatomical homology and of organ function, the criteria for the comparison of developmental stages, the annotation of transcriptomics data to proper anatomical and developmental terms, and the statistical methods to compare transcriptomic data between species to highlight significant conservation or changes. In this article, we review these challenges, and the ongoing efforts to address them, which are emerging from bioinformatics work on ontologies, evolutionary statistics, and data curation, with a focus on their implementation in the context of the development of our database Bgee (http://bgee.org).

PMID:
25864439
PMCID:
PMC4949521
DOI:
10.1002/jez.b.22618
[Indexed for MEDLINE]
Free PMC Article

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