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De Novo Sequencing of Astyanax mexicanus Surface Fish and Pachón Cavefish Transcriptomes Reveals Enrichment of Mutations in Cavefish Putative Eye Genes

Overview of attention for article published in PLOS ONE, January 2013
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Title
De Novo Sequencing of Astyanax mexicanus Surface Fish and Pachón Cavefish Transcriptomes Reveals Enrichment of Mutations in Cavefish Putative Eye Genes
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0053553
Pubmed ID
Authors

Hélène Hinaux, Julie Poulain, Corinne Da Silva, Céline Noirot, William R. Jeffery, Didier Casane, Sylvie Rétaux

Abstract

Astyanax mexicanus, a teleost species with surface dwelling (surface fish) and cave adapted (cavefish) morphs, is an important model system in evolutionary developmental biology (evodevo). Astyanax cavefish differ from surface fish in numerous traits, including the enhancement of non-visual sensory systems, and the loss of eyes and pigmentation. The genetic bases for these differences are not fully understood as genomic and transcriptomic data are lacking. We here present de novo transcriptome sequencing of embryonic and larval stages of a surface fish population and a cavefish population originating from the Pachón cave using the Sanger method. This effort represents the first large scale sequence and clone resource for the Astyanax research community. The analysis of these sequences show low levels of polymorphism in cavefish compared to surface fish, confirming previous studies on a small number of genes. A high proportion of the genes mutated in cavefish are known to be expressed in the zebrafish visual system. Such a high number of mutations in cavefish putative eye genes may be explained by relaxed selection for vision during the evolution in the absence of light. Based on these sequence differences, we provide a list of 11 genes that are potential candidates for having a role in cavefish visual system degeneration.

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Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 2 2%
Spain 1 <1%
Italy 1 <1%
Unknown 96 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 25%
Researcher 20 20%
Student > Master 13 13%
Professor > Associate Professor 6 6%
Student > Bachelor 6 6%
Other 17 17%
Unknown 14 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 51%
Biochemistry, Genetics and Molecular Biology 16 16%
Environmental Science 5 5%
Neuroscience 4 4%
Arts and Humanities 1 <1%
Other 4 4%
Unknown 20 20%