Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
文献类型：期刊论文
| 作者 | Skwark, MJ; Croucher, NJ; Puranen, S; Chewapreecha, C; Pesonen, M; Xu, YY; Turner, P; Harris, SR; Beres, SB; Musser, JM |
| 刊名 | PLOS GENETICS
 |
| 出版日期 | 2017 |
| 卷号 | 13期号:2页码:e1006508 |
| DOI | http://dx.doi.org/10.1371/journal.pgen.1006508 |
| 英文摘要 | Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work. |
| 学科主题 | Genetics & Heredity |
| 语种 | 英语 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/22136]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 通讯作者 | Corander, J (reprint author), Wellcome Trust Sanger Inst, Pathogen Gen, Cambridge, England.; Aurell, E (reprint author), KTH Royal Inst Technol, Dept Computat Biol, Stockholm, Sweden.; Aurell, E (reprint author), Aalto Univ, Dept Appl Phys & Comp Sci, Espoo, Finland.; Aurell, E (reprint author), Chinese Acad Sci, Inst Theoret Phys, Beijing, Peoples R China.; Corander, J (reprint author), Univ Helsinki, Dept Math & Stat, Helsinki, Finland.; Corander, J (reprint author), Univ Oslo, Dept Biostat, Oslo, Norway.; Corander, J (reprint author), Univ Cambridge, Dept Vet Med, Cambridge, England. |
| 推荐引用方式 GB/T 7714 | Skwark, MJ,Croucher, NJ,Puranen, S,et al. Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis[J]. PLOS GENETICS,2017,13(2):e1006508. |
| APA | Skwark, MJ.,Croucher, NJ.,Puranen, S.,Chewapreecha, C.,Pesonen, M.,...&Corander, J .(2017).Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis.PLOS GENETICS,13(2),e1006508. |
| MLA | Skwark, MJ,et al."Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis".PLOS GENETICS 13.2(2017):e1006508. |
入库方式： OAI收割
来源：理论物理研究所
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