193 23 1836 2 6298 document 1836 AdditionalFile1-TableS1.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 799fab1b2e878ea1fe856bdf67cbbea401def12ec61c6553ed37a1d1e8dd5ace SHA256 57287 2016-04-11 09:56:16 https://datacompass.lshtm.ac.uk/id/eprint/193/1/AdditionalFile1-TableS1.docx 193 1 1 application/vnd.openxmlformats-officedocument.wordprocessingml.document Dataset en public cc_by

AdditionalFile1-TableS1.docx

data indefinite The isolates according to geographic location and phenotypic drug resistance 1837 1 6304 document 1837 indexcodes.txt text/x-c 1f671bd5e6a0de21b03be19dba62bb6bf761a7a9606fd97991fa3c5ebf441361 SHA256 3378 2016-04-11 10:06:19 https://datacompass.lshtm.ac.uk/id/eprint/193/2/indexcodes.txt 193 2 2 text/x-c other en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://datacompass.lshtm.ac.uk/id/document/1836 http://eprints.org/relation/isVolatileVersionOf https://datacompass.lshtm.ac.uk/id/document/1836 http://eprints.org/relation/isIndexCodesVersionOf https://datacompass.lshtm.ac.uk/id/document/1836 indefinite Generate index codes conversion from Dataset to indexcodes archive 3 disk0/00/00/01/93 2016-04-11 09:57:37 2025-06-17 10:40:11 2016-04-11 09:57:37 data_collection show Phelan Jody 0000-0001-8323-7019 TRUE 5192f0191f2538d0166106c24634f7ca Coll Francesc 0000-0002-7882-2325 TRUE 6c2b7e9afcb260630b636d81fd3bfaf0 Mcnerney Ruth TRUE 742e523ff9b133b222c41fb882843cdb Ascher David B. FALSE Pires Douglas E. V. FALSE Furnham Nick 0000-0002-7532-1269 TRUE 0fe896f7be3f2c7db6f8b28e68870c57 Coeck Nele FALSE Hill-Cawthorne Grant A. FALSE Nair Mridul B. FALSE Mallard Kim FALSE Ramsay Andrew FALSE Campino Susana 0000-0003-1403-6138 TRUE b440f47b7ee6c1f6c5e11fc34edf059e Hibberd Martin 0000-0001-8587-1849 TRUE 1f995f1c7e03c1b91784efdf5c246e39 Pain Arnab FALSE Rigouts Leen FALSE Clark Taane 0000-0001-8985-9265 TRUE d6c0a9ae313d576cb0129f8b148489e7 Study consortium EPID ITPM Tuberculosis Drug resistance Genomics Protein structural modelling Association study Convergent evolution Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. 2015-11-04 published European Nucleotide Archive Dataset Study consortium Experiment public Biotechnology and Biological Sciences Research Council National Health and Medical Research Council René Rachou Research Center Medical Research Council Fundação de Amparo à Pesquisa do Estado de Minas Gerais Dataset Quantitative All DNA samples underwent Illumina sequencing on the HiSeq 2000 platform at the KAUST genomic facility, generating paired-end reads of 150 bp (Additional file 1: Table S1, pathogenseq.lshtm.ac.uk/tdr, Additional file 1: Table S2). All raw sequence data can be downloaded from the ENA short read archive (accession number PRJEB11653). For the raw sequence data, trimmomatic (v0.33) software [42] (parameters: LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36) was used to remove or truncate reads of low quality. High quality reads were then mapped to the H37Rv reference genome (Genbank accession: AL123456.3) using the BWA-mem (v0.7.12) algorithm [43] (parameters: -c 100 -M -T 50). From the resulting alignments, SAMtools (v1.3) [44] and GATK (v3.5) [45] software (default parameter settings) were used to call SNPs and small indels, and the interaction of variants between the methods retained. Mappability values were calculated along the reference genome using GEM-Mappability software with a k-mer length of 50 bp and a 0.04 % substitution threshold [46]. Non-unique SNP sites (mappability values greater than one) were removed. Sample genotypes were called using the majority allele (minimum frequency 75 %) in positions supported by at least 20-fold total genome coverage, otherwise they were classified as missing. Isolates or SNPs with in excess of 10 % missing genotype calls were excluded. The final dataset included 144 isolates and 17,952 genome-wide SNPs. en http://www.ebi.ac.uk/ena/data/view/PRJEB11653 dataresource http://pathogenseq.lshtm.ac.uk/tdr/ project http://researchonline.lshtm.ac.uk/id/eprint/2535998 Biotechnology and Biological Sciences Research Council http://dx.doi.org/10.13039/501100000268 National Health and Medical Research Council http://dx.doi.org/10.13039/501100000925 René Rachou Research Center Medical Research Council http://dx.doi.org/10.13039/501100000265 Fundação de Amparo à Pesquisa do Estado de Minas Gerais https://doi.org/10.13039/501100004901 2015-11-04