GC bias affects genomic and metagenomic reconstructions, underrepresenting GC-poor organisms.

ABSTRACT:

Background

Metagenomic sequencing is a well-established tool in the modern biosciences. While it promises unparalleled insights into the genetic content of the biological samples studied, conclusions drawn are at risk from biases inherent to the DNA sequencing methods, including inaccurate abundance estimates as a function of genomic guanine-cytosine (GC) contents.

Results

We explored such GC biases across many commonly used platforms in experiments sequencing multiple genomes (with mean GC contents ranging from 28.9% to 62.4%) and metagenomes. GC bias profiles varied among different library preparation protocols and sequencing platforms. We found that our workflows using MiSeq and NextSeq were hindered by major GC biases, with problems becoming increasingly severe outside t

SUBMITTER: Browne PD 

PROVIDER: S-EPMC7016772 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature