EchinoDB, an application for comparative transcriptomics of deeply-sampled clades of echinoderms.


BACKGROUND: One of our goals for the echinoderm tree of life project ( is to identify orthologs suitable for phylogenetic analysis from next-generation transcriptome data. The current dataset is the largest assembled for echinoderm phylogeny and transcriptomics. We used RNA-Seq to profile adult tissues from 42 echinoderm specimens from 24 orders and 37 families. In order to achieve sampling members of clades that span key evolutionary divergence, many of our exemplars were collected from deep and polar seas. DESCRIPTION: A small fraction of the transcriptome data we produced is being used for phylogenetic reconstruction. Thus to make a larger dataset available to researchers with a wide variety of interests, we made a web-based application, EchinoDB ( EchinoDB is a repository of orthologous transcripts from echinoderms that is searchable via keywords and sequence similarity. CONCLUSIONS: From transcripts we identified 749,397 clusters of orthologous loci. We have developed the information technology to manage and search the loci their annotations with respect to the Sea Urchin (Strongylocentrotus purpuratus) genome. Several users have already taken advantage of these data for spin-off projects in developmental biology, gene family studies, and neuroscience. We hope others will search EchinoDB to discover datasets relevant to a variety of additional questions in comparative biology.





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Publication Info

Janies, Daniel A, Zach Witter, Gregorio V Linchangco, David W Foltz, Allison K Miller, Alexander M Kerr, Jeremy Jay, Robert W Reid, et al. (2016). EchinoDB, an application for comparative transcriptomics of deeply-sampled clades of echinoderms. BMC Bioinformatics, 17. p. 48. 10.1186/s12859-016-0883-2 Retrieved from

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Gregory Allan Wray

Professor of Biology

I study the evolution of genes and genomes with the broad aim of understanding the origins of biological diversity. My approach focuses on changes in the expression of genes using both empirical and computational approaches and spans scales of biological organization from single nucleotides through gene networks to entire genomes. At the finer end of this spectrum of scale, I am focusing on understanding the functional consequences and fitness components of specific genetic variants within regulatory sequences of several genes associated with ecologically relevant traits. At the other end of the scale, I am developing molecular and analytical methods to detect changes in gene function throughout entire genomes, including statistical frameworks for detecting natural selection on regulatory elements and empirical approaches to identify functional variation in transcriptional regulation. At intermediate scales, I am investigating functional variation within a dense gene network in the context of wild populations and natural perturbations. My research leverages the advantages of several different model systems, but primarily focuses on sea urchins and primates (including humans).

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