ArticlePloS one2017
Quantitative analysis of correlation between AT and GC biases among bacterial genomes.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
- Article
- Strand asymmetries across genomic processes.Computational and structural biotechnology journal · 2023Review
- Ori-Finder 2022: A Comprehensive Web Server for Prediction and Analysis of Bacterial Replication Origins.Genomics, proteomics & bioinformatics · 2022Article
- Molecular analysis of the replication functions of the bifidobacterial conjugative megaplasmid pMP7017.Microbial biotechnology · 2021Article
- SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes.PLoS computational biology · 2020Article
- gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.Scientific reports · 2020Article
- Article
- Exopolysaccharide ProducingFrontiers in microbiology · 2020Article
- Article
- Comprehensive Analysis of Replication Origins inFrontiers in microbiology · 2019Article
- Genome rearrangements and selection in multi-chromosome bacteria Burkholderia spp.BMC genomics · 2018Article
- Novel metrics for quantifying bacterial genome composition skews.BMC genomics · 2018Article
- Selection for energy efficiency drives strand-biased gene distribution in prokaryotes.Scientific reports · 2017Article
- Bacillus subtilis DNA polymerases, PolC and DnaE, are required for both leading and lagging strand synthesis in SPP1 origin-dependent DNA replication.Nucleic acids research · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Due to different replication mechanisms between the leading and lagging strands, nucleotide composition asymmetries widely exist in bacterial genomes. A general consideration reveals that the leading strand is enriched in Guanine (G) and Thymine (T), and the lagging strand shows richness in Adenine (A) and Cytosine (C). However, some bacteria like Bacillus subtilis have been discovered composing more A than T in the leading strand. To investigate the difference, we analyze the nucleotide asymmetry from the aspect of AT and GC bias correlations. In this study, we propose a windowless method, the Z-curve Correlation Coefficient (ZCC) index, based on the Z-curve method, and analyzed more than 2000 bacterial genomes. We find that the majority of bacteria reveal negative correlations between AT and GC biases, while most genomes in Firmicutes and Tenericutes have positive ZCC indexes. The presence of PolC, purine asymmetry and stronger genes preference in the leading strand are not confined to Firmicutes, but also likely to happen in other phyla dominated by positive ZCC indexes. This method also provides a new insight into other relevant features like aerobism, and can be applied to analyze the correlation between RY (Purine and Pyrimidine) and MK (Amino and Keto) bias and so on.
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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.