SRG extractor: a skinny reference genome approach for reduced-representation sequencing

Davoud Torkamaneh; Jérôme Laroche; Istvan Rajcan; François Belzile

doi:10.1093/bioinformatics/btz043

SRG extractor: a skinny reference genome approach for reduced-representation sequencing

Bioinformatics. 2019 Sep 1;35(17):3160-3162. doi: 10.1093/bioinformatics/btz043.

Authors

Davoud Torkamaneh^{1

2

3}, Jérôme Laroche², Istvan Rajcan³, François Belzile^{1

2}

Affiliations

¹ Département de Phytologie, Université Laval, Québec City, Canada.
² Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, Canada.
³ Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada.

PMID: 30668828
DOI: 10.1093/bioinformatics/btz043

Abstract

Motivation: Reduced-representation sequencing is a genome-wide scanning method for simultaneous discovery and genotyping of thousands to millions of single nucleotide polymorphisms that is used across a wide range of species. However, in this method a reproducible but very small fraction of the genome is captured for sequencing, while the resulting reads are typically aligned against the entire reference genome.

Results: Here we present a skinny reference genome approach in which a simplified reference genome is used to decrease computing time for data processing and to increase single nucleotide polymorphism counts and accuracy. A skinny reference genome can be integrated into any reduced-representation sequencing analytical pipeline.

Availability and implementation: https://bitbucket.org/jerlar73/SRG-Extractor.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Genome*
Genotyping Techniques
High-Throughput Nucleotide Sequencing
Polymorphism, Single Nucleotide
Sequence Analysis, DNA
Software