Author
Chaitanya G. Joshi
Other affiliations: College of Veterinary Science and Animal Husbandry, Indian Institute of Technology Gandhinagar, Sardarkrushinagar Dantiwada Agricultural University ...read more
Bio: Chaitanya G. Joshi is an academic researcher from Anand Agricultural University. The author has contributed to research in topics: Genome & Population. The author has an hindex of 30, co-authored 334 publications receiving 3794 citations. Previous affiliations of Chaitanya G. Joshi include College of Veterinary Science and Animal Husbandry & Indian Institute of Technology Gandhinagar.
Topics: Genome, Population, Metagenomics, Transcriptome, Biology
Papers published on a yearly basis
Papers
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TL;DR: The first ever successful effort in India to detect the genetic material of SARS-CoV-2 viruses to understand the capability and application of wastewater-based epidemiology (WBE) surveillance in India makes a strong case for the environmental surveillance of the COVID-19 pandemic.
371 citations
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TL;DR: This study suggests an association between HLA-B*1502 and carbamazepine-induced SJS in Indian patients.
Abstract: Background: Stevens-Johnson Syndrome (SJS) and toxic epidermal necrolysis are severe cutaneous reactions caused by certain drugs, including antiepileptic carbamazepine. A strong association has been reported between human leucocyte antigen (HLA)-B*1502 and carbamazepine-induced SJS in Han Chinese patients. European studies suggested that HLA-B*1502 is not a universal marker but is ethnicity-specific for Asians. Aim: To study the association between HLA-B*1502 and carbamazepine-induced SJS in Indian patients. Methods: Eight individuals who fulfilled the diagnostic criteria of SJS induced by carbamazepine were identified and HLA-B molecular typing was performed. HLA-B genotyping was carried out by polymerase chain reaction using sequence-specific primers. Results: Out of eight patients studied for genotype, six patients were found to have the HLA-B*1502 allele. Conclusion: This study suggests an association between HLA-B*1502 and carbamazepine-induced SJS in Indian patients.
274 citations
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TL;DR: The metagenomic profile of fecal bacteria in birds with high and low feed conversion ratio (FCR) was investigated to identify microbial community linked to low and high FCR by employing high throughput pyrosequencing of 16S rRNA genomic targets.
Abstract: The performance of birds appears to vary among the flock of growing broilers which may in part be due to variation in their gut microbiota. In the view of poultry industry, it is desirable to minimise such variation. We investigated metagenomic profile of fecal bacteria in birds with high and low feed conversion ratio (FCR) to identify microbial community linked to low and high FCR by employing high throughput pyrosequencing of 16S rRNA genomic targets. Therefore feeding trial was investigated in order to identify fecal bacteria consistently linked with better feed conversion ratio in bird performance as measured by body weight gain. High-throughput 16S rRNA gene based pyrosequencing was used to provide a comparative analysis of fecal microbial diversity. The fecal microbial community of birds was predominated by Proteobacteria (48.04 % in high FCR and 49.98 % in low FCR), Firmicutes (26.17 % in high FCR and 36.23 % in low FCR), Bacteroidetes (18.62 % in high FCR and 11.66 % in low FCR), as well as unclassified bacteria (15.77 % in high FCR and 14.29 % in low FCR), suggesting that a large portion of fecal microbiota is novel and could be involved in currently unknown functions. The most prevalent bacterial classes in high FCR and low FCR were Gammaproteobacteria, Clostridia and Bacteroidia. However in low FCR birds Phascolarctobacterium, Faecalibacterium and Clostridium predominated among the Clostridia. In FCR comparison of fecal bacteria, about 36 genera were differentially abundant between high and low FCR birds. This information could be used to formulate effective strategies to improve feed efficiency and feed formulation for optimal gut health.
154 citations
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TL;DR: Chicken breed-specific variation in bacterial occurrence, correlation between genera and clustering of operational taxonomic units indicate scope for quantitative genetic analysis and the possibility of selective breeding of chickens for defined enteric microbiota.
Abstract: The caecal microbiota plays a key role in chicken health and performance, influencing digestion and absorption of nutrients, and contributing to defence against colonisation by invading pathogens. Measures of productivity and resistance to pathogen colonisation are directly influenced by chicken genotype, but host driven variation in microbiome structure is also likely to exert a considerable indirect influence. Here, we define the caecal microbiome of indigenous Indian Aseel and Kadaknath chicken breeds and compare them with the global commercial broiler Cobb400 and Ross 308 lines using 16S rDNA V3-V4 hypervariable amplicon sequencing. Each caecal microbiome was dominated by the genera Bacteroides, unclassified bacteria, unclassified Clostridiales, Clostridium, Alistipes, Faecalibacterium, Eubacterium and Blautia. Geographic location (a measure recognised to include variation in environmental and climatic factors, but also likely to feature varied management practices) and chicken line/breed were both found to exert significant impacts (p < 0.05) on caecal microbiome composition. Linear discriminant analysis effect size (LEfSe) revealed 42 breed-specific biomarkers in the chicken lines reared under controlled conditions at two different locations. Chicken breed-specific variation in bacterial occurrence, correlation between genera and clustering of operational taxonomic units indicate scope for quantitative genetic analysis and the possibility of selective breeding of chickens for defined enteric microbiota.
121 citations
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TL;DR: Previous hypothesis that mastitis women have lower microbial diversity, increased abundance of opportunistic pathogens and depletion of commensal obligate anaerobes is confirmed.
Abstract: Breastfeeding undoubtedly provides important benefits to the mother-infant dyad and should be encouraged. Mastitis, one of the common but major cause of premature weaning among lactating women, is an inflammation of connective tissue within the mammary gland. This study reports the influence of mastitis on human milk microbiota by utilizing 16 S rRNA gene sequencing approach. We sampled and sequenced microbiome from 50 human milk samples, including 16 subacute mastitis (SAM), 16 acute mastitis (AM) and 18 healthy-controls. Compared to controls, SAM and AM microbiota were quite distinct and drastically reduced. Genera including, Aeromonas, Staphylococcus, Ralstonia, Klebsiella, Serratia, Enterococcus and Pseudomonas were significantly enriched in SAM and AM samples, while Acinetobacter, Ruminococcus, Clostridium, Faecalibacterium and Eubacterium were consistently depleted. Further analysis of our samples revealed positive aerotolerant odds ratio, indicating dramatic depletion of obligate anaerobes and enrichment of aerotolerant bacteria during the course of mastitis. In addition, predicted functional metagenomics identified several gene pathways related to bacterial proliferation and colonization (e.g. two-component system, bacterial secretion system and motility proteins) in SAM and AM samples. In conclusion, our study confirmed previous hypothesis that mastitis women have lower microbial diversity, increased abundance of opportunistic pathogens and depletion of commensal obligate anaerobes.
110 citations
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01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
10,124 citations
01 Jan 2000
3,536 citations
01 Jan 2010
TL;DR: In this paper, the authors show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait, revealing patterns with important implications for genetic studies of common human diseases and traits.
Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
1,751 citations