Paper Info
Title
On The Complexity Of Haplotyping A Microbial Community
Abstract
Motivation: Population-level genetic variation enables competitiveness and niche specialization in microbial communities. Despite the difficulty in culturing many microbes from an environment, we can still study these communities by isolating and sequencing DNA directly from an environment (metagenomics). Recovering the genomic sequences of all isoforms of a given gene across all organisms in a metagenomic sample would aid evolutionary and ecological insights into microbial ecosystems with potential benefits for medicine and biotechnology. A significant obstacle to this goal arises from the lack of a computationally tractable solution that can recover these sequences from sequenced read fragments. This poses a problem analogous to reconstructing the two sequences that make up the genome of a diploid organism (i.e. haplotypes) but for an unknown number of individuals and haplotypes.Results: The problem of single individual haplotyping was first formalized by Lancia et al. in 2001. Now, nearly two decades later, we discuss the complexity of 'haplotyping' metagenomic samples, with a new formalization of Lancia et al.'s data structure that allows us to effectively extend the single individual haplotype problem to microbial communities. This work describes and formalizes the problem of recovering genes (and other genomic subsequences) from all individuals within a complex community sample, which we term the metagenomic individual haplotyping problem. We also provide software implementations for a pairwise single nucleotide variant (SNV) co-occurrence matrix and greedy graph traversal algorithm.
Year
DOI
Venue
2021
10.1093/bioinformatics/btaa977
BIOINFORMATICS
DocType
Volume
Issue
Journal
37
10
ISSN
Citations 
PageRank 
1367-4803
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Samuel M. Nicholls100.68
Wayne Aubrey2111.89
Kurt De Grave31096.45
Leander Schietgat437614.30
C. J. Creevey530921.31
Amanda Clare659247.37