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      Whole-genome sequencing of rifampicin-resistant M. tuberculosis strains identifies compensatory mutations in RNA polymerase

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          Abstract

          Drug-resistant bacteria are emerging worldwide, despite frequently being less fit than drug-susceptible strains 1 . Data from model systems suggest the fitness cost of antimicrobial resistance can be mitigated by compensatory mutations 2 . However, current evidence that compensatory evolution plays any significant role in the success of drug-resistant bacteria in human populations is weak 36 . Here we describe a set of novel compensatory mutations in the RNA polymerase of rifampicin-resistant Mycobacterium tuberculosis, the etiologic agent of human tuberculosis (TB). M. tuberculosis strains harbouring these compensatory mutations exhibited a high competitive fitness in vitro. Moreover, these mutations were associated with high in vivo fitness as determined by their relative clinical frequency across patient populations. Importantly, in countries with the world’s highest incidence of multidrug-resistant (MDR) TB 7 , more than 30% of MDR clinical isolates had such a mutation. Our findings support a role for compensatory evolution in the global epidemics of MDR-TB 8 .

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          Most cited references45

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          Is Open Access

          ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

          High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a ‘variants reduction’ protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/ .
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            SIFT: Predicting amino acid changes that affect protein function.

            P C Ng (2003)
            Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at http://blocks.fhcrc.org/sift/SIFT.html.
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              MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0.

              We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature Genetics
                1061-4036
                1546-1718
                26 November 2011
                18 December 2011
                01 July 2012
                : 44
                : 1
                : 106-110
                Affiliations
                [1 ]Medical Research Council, National Institute for Medical Research, London, UK
                [2 ]Swiss Tropical and Public Health Institute, Basel, Switzerland
                [3 ]University of Basel, Basel, Switzerland
                [4 ]Research Centre Borstel, Molecular Mycobacteriology, Borstel, Germany
                [5 ]University of California San Francisco, San Francisco, USA
                [6 ]Broad Institute, Cambridge, USA
                [7 ]Boston University, Boston, USA
                Author notes
                [* ]Corresponding author: Sebastien GAGNEUX, Ph.D., Department of Medical Parasitology & Infection Biology, Swiss Tropical & Public Health Institute, Socinstrasse 57, 4002 Basel, Switzerland, Phone: +41 -61-284-8369, Fax: +41 -61-284-8101 sebastien.gagneux@ 123456unibas.ch
                [a]

                Current affiliation: Genomics and Health Unit, Centre for Public Health Research, Valencia, Spain

                Article
                nihpa339089
                10.1038/ng.1038
                3246538
                22179134
                3441a1b9-882e-4188-a88b-13e03a9e1418

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: R01 AI090928-03 || AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: R01 AI034238-17 || AI
                Categories
                Article

                Genetics
                Genetics

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