Identification of Hot and Cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts

Das, Sarbashis; Duggal, Priyanka; Roy, Roshni; Myneedu, Vithal Prasad; Behera, Digamber; Prasad, H. K.; Bhattacharya, Alok

doi:10.1038/srep00297

Cited by 13 publications

(20 citation statements)

References 33 publications

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“…A control chart approach has been recently used to identify sites of preferential location of genetic variation in Mycobacterium tuberculosis (Das et al . ). In the present study, smoothed F st values were plotted against their position along the chromosome.…”

Section: Methodsmentioning

confidence: 97%

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures inPiedmontese andItalianBrown cattle breeds

Pintus

Sorbolini

Albera³

et al. 2013

Animal Genetics

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Selection is the major force affecting local levels of genetic variation in species. The availability of dense marker maps offers new opportunities for a detailed understanding of genetic diversity distribution across the animal genome. Over the last 50 years, cattle breeds have been subjected to intense artificial selection. Consequently, regions controlling traits of economic importance are expected to exhibit selection signatures. The fixation index (Fst ) is an estimate of population differentiation, based on genetic polymorphism data, and it is calculated using the relationship between inbreeding and heterozygosity. In the present study, locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach were used to investigate selection signatures in two cattle breeds with different production aptitudes (dairy and beef). Fst was calculated for 42 514 SNP marker loci distributed across the genome in 749 Italian Brown and 364 Piedmontese bulls. The statistical significance of Fst values was assessed using a control chart. The LOWESS technique was efficient in removing noise from the raw data and was able to highlight selection signatures in chromosomes known to harbour genes affecting dairy and beef traits. Examples include the peaks detected for BTA2 in the region where the myostatin gene is located and for BTA6 in the region harbouring the ABCG2 locus. Moreover, several loci not previously reported in cattle studies were detected.

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Section: Methodsmentioning

confidence: 97%

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures inPiedmontese andItalianBrown cattle breeds

Pintus

Sorbolini

Albera³

et al. 2013

Animal Genetics

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show abstract

“…It has previously been reported that mutational hotspots in Mtb, expressed as SNVs per 434 genome size (Mb), cluster in certain genomic regions (Das et al 2012). We provide data 435 that the number of mutational hotspots is significantly higher for the 19 Mma strains 436 compared to other mycobacteria (Mtb, MAP, Mbo and Mph; Fig 4c).…”

Section: Phylogenetic Analysis 331mentioning

confidence: 64%

“…A similar analysis of 20 Mtb isolates suggested only 45 mutational hotspots corresponding 314 to 10/Mb (Das et al 2012;Fig 5c). We therefore determined the hotspot frequencies for 315 three other mycobacteria, M. avium subsp.…”

Section: Identification Of Snvs and Mutational Hotspots In M Marinummentioning

confidence: 66%

“…Single nucleotide insertions/deletions were filtered out, and only SNVs 560 were used for further analysis. Mutational hotspots were identified using Shewhart Control 561 Chart, as described by Das et al (2012). Briefly, the genome of the M strain was divided 562 into non-overlapping windows of 2000 bases and the average number of SNVs in each of 563 the windows was determined.…”

Section: Identification Of Snvs and Mutational Hotspots 557mentioning

confidence: 99%

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Extensive genomic diversity among Mycobacterium marinum strains revealed by whole genome sequencing

Das¹,

Pettersson²,

Behra³

et al. 2018

Preprint

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33Mycobacterium marinum is the causative agent for the tuberculosis-like disease 34 mycobacteriosis in fish and skin lesions in humans. Ubiquitous in its geographical 35 distribution, M. marinum is known to occupy diverse fish as hosts. However, information 36 about its genomic diversity is limited. Here, we provide the genome sequences for 15 M. 37 marinum strains isolated from infected humans and fish. Comparative genomic analysis of 38 these and four available genomes of the M. marinum strains M, E11, MB2 and Europe 39 reveal high genomic diversity among the strains, leading to the conclusion that M. 40 marinum should be divided into two different clusters, the "M"-and the "Aronson"-type. 41We suggest that these two clusters should be considered, if not two separate species, at 42 least two M. marinum subspecies. Our data also show that the M. marinum pan-genome for

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“…It has also become possible to identify evolving patterns in genomes. For example, “hotspot” and “coldspot” regions have been identified using statistical methods and sequence information from large number of isolates [14]. However, most of the genome data available are from M. tuberculosis isolates derived from pulmonary tuberculosis patients.…”

Section: Introductionmentioning

confidence: 99%

Genetic heterogeneity revealed by sequence analysis of Mycobacterium tuberculosis isolates from extra-pulmonary tuberculosis patients

et al. 2013

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BackgroundTuberculosis remains a major public health problem. Clinical tuberculosis manifests often as pulmonary and occasionally as extra-pulmonary tuberculosis. The emergence of drug resistant tubercle bacilli and its association with HIV is a formidable challenge to curb the spread of tuberculosis. There have been concerted efforts by whole genome sequencing and bioinformatics analysis to identify genomic patterns and to establish a relationship between the genotype of the organism and clinical manifestation of tuberculosis. Extra-pulmonary TB constitutes 15–20 percent of the total clinical cases of tuberculosis reported among immunocompetent patients, whereas among HIV patients the incidence is more than 50 percent. Genomic analysis of M. tuberculosis isolates from extra pulmonary patients has not been explored.ResultsThe genomic DNA of 5 extra-pulmonary clinical isolates of M. tuberculosis derived from cerebrospinal fluid, lymph node fine needle aspirates (FNAC) / biopsies, were sequenced. Next generation sequencing approach (NGS) was employed to identify Single Nucleotide Variations (SNVs) and computational methods used to predict their consequence on functional genes. Analysis of distribution of SNVs led to the finding that there are mixed genotypes in patient isolates and that many SNVs are likely to influence either gene function or their expression. Phylogenetic relationship between the isolates correlated with the origin of the isolates. In addition, insertion sites of IS elements were identified and their distribution revealed a variation in number and position of the element in the 5 extra-pulmonary isolates compared to the reference M. tuberculosis H37Rv strain.ConclusionsThe results suggest that NGS sequencing is able to identify small variations in genomes of M. tuberculosis isolates including changes in IS element insertion sites. Moreover, variations in isolates of M. tuberculosis from non-pulmonary sites were documented. The analysis of our results indicates genomic heterogeneity in the clinical isolates.

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Identification of Hot and Cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts

Cited by 13 publications

References 33 publications

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures inPiedmontese andItalianBrown cattle breeds

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures inPiedmontese andItalianBrown cattle breeds

Extensive genomic diversity among Mycobacterium marinum strains revealed by whole genome sequencing

Genetic heterogeneity revealed by sequence analysis of Mycobacterium tuberculosis isolates from extra-pulmonary tuberculosis patients

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