ArticleGigaScience2020
GC bias affects genomic and metagenomic reconstructions, underrepresenting GC-poor organisms.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers, 1 of them a synthesis that pooled it.
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Who cites it
116 citing papers in PubMed, 1 synthesis or guideline pooled it, 197 citations in OpenAlex.
- Systematic Review: Long-Read Sequencing in Algal Studies.International journal of molecular sciences · 2026Pooled it
- Long-Term Effects of a Web-Based Low-FODMAP Diet Versus Probiotic Treatment for Irritable Bowel Syndrome, Including Shotgun Analyses of Microbiota: Randomized, Double-Crossover Clinical Trial.Journal of medical Internet research · 2021Trial
- The planktonic microbiome of the Great Barrier Reef.Nature · 2026Article
- Targeted amplicon sequencing for enhanced detection of spiked Shiga toxin-producingMicrobiology spectrum · 2026Article
- Benchmarking next- versus third-generation sequencing in metagenomics: performance metrics and diagnostic efficacy.Microbiology spectrum · 2026Article
- IRCAS: a novel end-to-end approach to identify, rectify, and classify comprehensive alternative splicing events in a transcriptome without genome reference.Briefings in bioinformatics · 2026Article
- Exploring per-base quality scores as a surrogate marker of cell-free DNA fragmentome.Briefings in bioinformatics · 2026Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Article
- Taxonomy bias in metagenome-assembled genome recovery.Microbial genomics · 2026Article
- Quantitative interpretation models for targeted next-generation sequencing in lower respiratory tract infections: a multicenter prospective study.Respiratory research · 2026Article
- Bacterial Siderophore Production in Metal-Rich Environments: Underexplored Sources of Siderophores and Insights into Bioremediation.Journal of natural products · 2026Review
- Decoding the Avian Missing Gene Mystery: Dot Chromosomes Unmask Extensive Gene Loss and Novel Genetic Instability.Genome biology and evolution · 2026Article
- Oligonucleotide Selective Detection by Levitated Optomechanics.ACS nanoscience Au · 2026Article
- Design and computational evaluation of a prophylactic and therapeutic multi-epitope vaccine candidate against cervical cancer.Virology journal · 2026Article
- Unlocking the full potential of nanopore sequencing: tips, tricks, and advanced data analysis techniques.Nucleic acids research · 2026Review
- Benchmarking Illumina and Oxford Nanopore Technologies (ONT) sequencing platforms for whole genome sequencing of bacterial genomes and use in clinical microbiology.BMC medical genomics · 2026Article
- Article
- PCNE: A Tool for Plasmid Copy Number Estimation.Bioinformatics and biology insights · 2026Article
- Genomic GC bias correction improves species abundance estimation from metagenomic data.Nature communications · 2025Article
56 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetagenomic 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.
resultsWe 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 the 45-65% GC range, leading to a falsely low coverage in GC-rich and especially GC-poor sequences, where genomic windows with 30% GC content had >10-fold less coverage than windows close to 50% GC content. We also showed that GC content correlates tightly with coverage biases. The PacBio and HiSeq platforms also evidenced similar profiles of GC biases to each other, which were distinct from those seen in the MiSeq and NextSeq workflows. The Oxford Nanopore workflow was not afflicted by GC bias.
conclusionsThese findings indicate potential sources of difficulty, arising from GC biases, in genome sequencing that could be pre-emptively addressed with methodological optimizations provided that the GC biases inherent to the relevant workflow are understood. Furthermore, it is recommended that a more critical approach be taken in quantitative abundance estimates in metagenomic studies. In the future, metagenomic studies should take steps to account for the effects of GC bias before drawing conclusions, or they should use a demonstrably unbiased workflow.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.