Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis

Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods. We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity. BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp. hengli@broadinstitute.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.

Tuberculosis is responsible for one in four of all avoidable adult deaths in developing countries. Increased frequency and accelerated fatality of the disease among individuals infected with human immunodeficiency virus has raised worldwide concern that control programmes may be inadequate, and the emergence of multidrug-resistant strains of Mycobacterium tuberculosis has resulted in several recent fatal outbreaks in the United States. Isonicotinic acid hydrazide (isoniazid, INH) forms the core of antituberculosis regimens; however, clinical isolates that are resistant to INH show reduced catalase activity and a relative lack of virulence in guinea-pigs. Here we use mycobacterial genetics to study the molecular basis of INH resistance. A single M. tuberculosis gene, katG, encoding both catalase and peroxidase, restored sensitivity to INH in a resistant mutant of Mycobacterium smegmatis, and conferred INH susceptibility in some strains of Escherichia coli. Deletion of katG from the chromosome was associated with INH resistance in two patient isolates of M. tuberculosis.