Usando o RNA-Seq para aumentar a profundidade genômica da árvore da vida

Leveraging skewed transcript abundance by RNA-Seq to increase the genomic depth of the tree of life

Chris Todd Hittinger a,b, Mark Johnston a,b, John T. Tossberg c and Antonis Rokas c,1

- Author Affiliations

aDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver Health Sciences Center, Aurora, CO 80045

bCenter for Genome Sciences, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108

cDepartment of Biological Sciences, Vanderbilt University, Nashville, TN 37235

Edited by Sean B. Carroll, University of Wisconsin, Madison, WI, and approved December 10, 2009 (received for review September 13, 2009)

Abstract

Assembling the tree of life is a major goal of biology, but progress has been hindered by the difficulty and expense of obtaining the orthologous DNA required for accurate and fully resolved phylogenies. Next-generation DNA sequencing technologies promise to accelerate progress, but sequencing the genomes of hundreds of thousands of eukaryotic species remains impractical. Eukaryotic transcriptomes, which are smaller than genomes and biased toward highly expressed genes that tend to be conserved, could potentially provide a rich set of phylogenetic characters. We sampled the transcriptomes of 10 mosquito species by assembling 36-bp sequence reads into phylogenomic data matrices containing hundreds of thousands of orthologous nucleotides from hundreds of genes. Analysis of these data matrices yielded robust phylogenetic inferences, even with data matrices constructed from surprisingly few sequence reads. This approach is more efficient, data-rich, and economical than traditional PCR-based and EST-based methods and provides a scalable strategy for generating phylogenomic data matrices to infer the branches and twigs of the tree of life.

next-generation DNA sequencing phylogenetics transcriptome Anopheles orthology

Footnotes

1To whom correspondence should be addressed at: Vanderbilt University, VU Station B 35-1634, Nashville, TN 37235. E-mail: antonis.rokas@vanderbilt.edu.

Author contributions: C.T.H., M.J., and A.R. designed research; C.T.H., J.T.T., and A.R. performed research; C.T.H., M.J., and A.R. contributed new reagents/analytic tools; C.T.H. and A.R. analyzed data; and C.T.H., M.J., and A.R. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: All sequence data have been deposited at the National Center for Biotechnology Information short read archive (www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi) as study no. SRP001532 of submission no. SRA010237.

This article contains supporting information online at www.pnas.org/cgi/content/full/0910449107/DCSupplemental.

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