Cited by 287Genomics and Phylogenetic StudiesAlgorithms and Data CompressionFractal and DNA sequence analysis

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Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly

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Chen, Yen-Chun, Liu, Tsunglin, Yu, Chun-Hui, Chiang, Tzen-Yuh, Hwang, Chi-Chuan·2013·PLoS ONE

DOI 10.1371/journal.pone.0062856PMC PMC3639258

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Abstract

Next-generation-sequencing (NGS) has revolutionized the field of genome assembly because of its much higher data throughput and much lower cost compared with traditional Sanger sequencing. However, NGS poses new computational challenges to de novo genome assembly. Among the challenges, GC bias in NGS data is known to aggravate genome assembly. However, it is not clear to what extent GC bias affects genome assembly in general. In this work, we conduct a systematic analysis on the effects of GC bias on genome assembly. Our analyses reveal that GC bias only lowers assembly completeness when the degree of GC bias is above a threshold. At a strong GC bias, the assembly fragmentation due to GC bias can be explained by the low coverage of reads in the GC-poor or GC-rich regions of a genome. This effect is observed for all the assemblers under study. Increasing the total amount of NGS data thus rescues the assembly fragmentation because of GC bias. However, the amount of data needed for a full rescue depends on the distribution of GC contents. Both low and high coverage depths due to GC bias lower the accuracy of assembly. These pieces of information provide guidance toward a better de novo genome assembly in the presence of GC bias.

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Authors: Chen, Y.-C., Liu, T., Yu, C.-H., Chiang, T.-Y., & Hwang, C.-C.
Affiliations: National Cheng Kung University (TW)
Corresponding author: Hwang, Chi-Chuan
ORCID: Chen, Yen-Chun
Liu, Tsunglin
Chiang, Tzen-Yuh
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2013-04-29
Volume: 8
Issue: 4
Pages: e62856
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0062856
PMC: PMC3639258
OpenAlex: W1998330439
Cited by: 285
References: 43
Citations by year: 2026: 7 · 2025: 22 · 2024: 25 · 2023: 20 · 2022: 26 · 2021: 48 · 2020: 30 · 2019: 13 · 2018: 27 · 2017: 23 · 2016: 18 · 2015: 11 · 2014: 12 · 2013: 2
FWCI: 6.42
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS ONE (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, other-oa)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Figshare (submittedVersion, cc-by)
Funders: National Science Council
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
Keywords: GC content bias, de novo genome assembly, next-generation sequencing, assembly completeness, read coverage, assembly accuracy
MeSH terms: Reference Standards, Artifacts, Genome, Bacterial, GC Rich Sequence, Genomics, High-Throughput Nucleotide Sequencing

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Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly

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