สืบค้นงานวิจัย
Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
Skwark M.J. - ไม่ระบุหน่วยงาน
ชื่อเรื่อง (EN): Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
ผู้แต่ง / หัวหน้าโครงการ (EN): Skwark M.J.
บทคัดย่อ (EN): 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. © 2017 Skwark et al.
บทคัดย่อ: ไม่พบข้อมูลจากหน่วยงานต้นทาง
ภาษา (EN): en
เอกสารแนบ (EN): https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014119857&doi=10.1371%2fjournal.pgen.1006508&partnerID=40&md5=50169ed68a9a27f45eaf0900c5f77d11
เผยแพร่โดย (EN): มหาวิทยาลัยมหิดล
คำสำคัญ (EN): Streptococcus pyogenes
เจ้าของลิขสิทธิ์ (EN): มหาวิทยาลัยมหิดล
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Skwark M.J.. "Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis". ไม่ระบุหน่วยงาน. ม.ป.ป.

Skwark M.J.. "Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis". ไม่ระบุหน่วยงาน. ม.ป.ป.. Print.



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Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
Skwark M.J.
มหาวิทยาลัยมหิดล
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