Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs.

Autor:	Kuronen J; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway., Horsfield ST; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W12 0BZ, United Kingdom.; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom., Pöntinen AK; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway.; Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, 9019 Tromsø, Norway., Mallawaarachchi S; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway.; Peter MacCallum Cancer Centre, Melbourne, Victoria 3052, Australia.; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria 3052, Australia., Arredondo-Alonso S; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway., Thorpe H; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway., Gladstone RA; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway., Willems RJL; Department of Medical Microbiology, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands., Bentley SD; Parasites and Microbes, Wellcome Sanger Institute, Cambridge CB10 1RQ, United Kingdom., Croucher NJ; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W12 0BZ, United Kingdom., Pensar J; Department of Mathematics, University of Oslo, 0372 Blindern, Norway., Lees JA; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom; gerryt@uio.no jlees@ebi.ac.uk., Tonkin-Hill G; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway; gerryt@uio.no jlees@ebi.ac.uk.; Peter MacCallum Cancer Centre, Melbourne, Victoria 3052, Australia.; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria 3052, Australia.; Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria 3052, Australia., Corander J; Department of Biostatistics, University of Oslo, 0372 Blindern, Norway.; Department of Medical Microbiology, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.; Helsinki Institute of Information Technology, Department of Mathematics and Statistics, University of Helsinki, 00014 Helsinki, Finland.
Jazyk:	angličtina
Zdroj:	Genome research [Genome Res] 2024 Aug 20; Vol. 34 (7), pp. 1081-1088. Date of Electronic Publication: 2024 Aug 20.
DOI:	10.1101/gr.278485.123
Abstrakt:	Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance, and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis . (© 2024 Kuronen et al.; Published by Cold Spring Harbor Laboratory Press.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu