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10.1371/journal.pgen.1006508 http://scihub22266oqcxt.onion/10.1371/journal.pgen.1006508 C5312804!5312804 !28207813     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28207813 &cmd=llinks): Failed to open stream: HTTP request failed! 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Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis |pdf=|usr=}}{{28207813 }} gab.com Text Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis JO: PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=28207813 #FOAvip 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. Twit Text FOAVip Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis ????PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=28207813 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28207813 #FOAvip English Wikipedia <ref>{{Cite pmid|28207813 }}</ref> Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis #MMPMID28207813 Skwark MJ ; Croucher NJ ; Puranen S ; Chewapreecha C ; Pesonen M ; Xu YY ; Turner P ; Harris SR ; Beres SB ; Musser JM ; Parkhill J ; Bentley SD ; Aurell E ; Corander J PLoS Genet 2017[Feb]; 13 (2 ): e1006508 PMID28207813 show ga 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. |*Epistasis, Genetic [MESH] |Aminoacyltransferases/genetics [MESH] |Anti-Bacterial Agents/therapeutic use [MESH] |Bacterial Proteins/genetics [MESH] |Gene Regulatory Networks/genetics [MESH] |Genetics, Population [MESH] |Genome, Bacterial/genetics [MESH] |Genomics [MESH] |Genotype [MESH] |Humans [MESH] |Microbial Sensitivity Tests [MESH] |Penicillin-Binding Proteins/chemistry/genetics [MESH] |Peptidyl Transferases/genetics [MESH] |Selection, Genetic/*genetics [MESH] |Streptococcus pneumoniae/drug effects/*genetics/pathogenicity [MESH] |Streptococcus pyogenes/drug effects/*genetics/pathogenicity [MESH] |beta-Lactam Resistance/*genetics [MESH]Interacting networks of resistance, virulence and core machinery genes(epmc).pdf DeepDyve Pubget Overpricing