NDLI: Automated Reconstruction of Whole-Genome Phylogenies from Short-Sequence Reads

Content Provider	PubMed Central
Author	Bertels, Frederic Silander, Olin K. Mikhail, Pachkov Rainey, Paul B. Van Nimwegen, Erik
Copyright Year	2014
Abstract	Studies of microbial evolutionary dynamics are being transformed by the availability of affordable high-throughput sequencing technologies, which allow whole-genome sequencing of hundreds of related taxa in a single study. Reconstructing a phylogenetic tree of these taxa is generally a crucial step in any evolutionary analysis. Instead of constructing genome assemblies for all taxa, annotating these assemblies, and aligning orthologous genes, many recent studies 1) directly map raw sequencing reads to a single reference sequence, 2) extract single nucleotide polymorphisms (SNPs), and 3) infer the phylogenetic tree using maximum likelihood methods from the aligned SNP positions. However, here we show that, when using such methods to reconstruct phylogenies from sets of simulated sequences, both the exclusion of nonpolymorphic positions and the alignment to a single reference genome, introduce systematic biases and errors in phylogeny reconstruction. To address these problems, we developed a new method that combines alignments from mappings to multiple reference sequences and show that this successfully removes biases from the reconstructed phylogenies. We implemented this method as a web server named REALPHY (Reference sequence Alignment-based Phylogeny builder), which fully automates phylogenetic reconstruction from raw sequencing reads.
Related Links	http://dx.doi.org/10.1093/molbev/msu088
Ending Page	1088
Page Count	12
Starting Page	1077
File Format	PDF
ISSN	07374038
e-ISSN	15371719
Journal	Molecular Biology and Evolution
Issue Number	5
Volume Number	31
Language	English
Publisher	Oxford University Press
Publisher Date	2014-05-01
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Genetics Ecology, Evolution, Behavior and Systematics Molecular Biology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics Molecular Biology Ecology, Evolution, Behavior and Systematics

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