A composite genome approach to identify phylogenetically informative data from next-generation sequencing

BMC Bioinformatics

Rachel S. Schwartz²  Kelly M. Harkins⁴  Anne C. Stone³  Reed A. Cartwright¹ 

[1] School of Life Sciences, Arizona State University, Tempe, AZ, USA

[2] The Biodesign Institute, Arizona State University, Tempe, AZ, USA

[3] School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA

[4] Department of Anthropology, University of California – Santa Cruz, Santa Cruz, CA, USA

关键词: Mammals;    Apes;    Next-generation sequencing;    Phylogenetics;   

Others  :  1232174
DOI  :  10.1186/s12859-015-0632-y

 received in 2014-12-09, accepted in 2015-05-29,  发布年份 2015

【 摘 要 】

Background

Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.

Results

For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.

Conclusions

SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases webcite.

【 授权许可】

   
2015 Schwartz et al.

【 图 表 】

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