Exome sequencing in families with severe mental illness identifies novel and rare variants in genes implicated in Mendelian neuropsychiatric syndromes.

AIM: Severe mental illnesses (SMI), such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome-wide association studies detect a part of the heritability, which can be attributed to common genetic variation. Examination of rare variants with next-generation sequencing may add to the understanding of the genetic architecture of SMI. METHODS: We analyzed 32 ill subjects from eight multiplex families and 33 healthy individuals using whole-exome sequencing. Prioritized variants were selected by a three-step filtering process, which included: deleteriousness by five in silico algorithms; sharing within families by affected individuals; rarity in South Asian sample estimated using the Exome Aggregation Consortium data; and complete absence of these variants in control individuals from the same gene pool. RESULTS: We identified 42 rare, non-synonymous deleterious variants (~5 per pedigree) in this study. None of the variants were shared across families, indicating a 'private' mutational profile. Twenty (47.6%) of the variant harboring genes were previously reported to contribute to the risk of diverse neuropsychiatric syndromes, nine (21.4%) of which were of Mendelian inheritance. These included genes carrying novel deleterious variants, such as the GRM1 gene implicated in spinocerebellar ataxia 44 and the NIPBL gene implicated in Cornelia de Lange syndrome. CONCLUSION: Next-generation sequencing approaches in family-based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The findings of the study suggest a potential phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of SMI.

In depth analysis of rumen microbial and carbohydrate-active enzymes profile in Indian crossbred cattle.

Rumen houses a plethora of symbiotic microorganisms empowering the host to hydrolyze plant lignocellulose. In this study, NGS based metagenomic approach coupled with bioinformatic analysis was employed to gain an insight into the deconstruction of lignocellulose by carbohydrate-active enzymes (CAZymes) in Indian crossbred Holstein-Friesian cattle. Cattle rumen metagenomic DNA was sequenced using Illumina-MiSeq and 1.9 gigabases of data generated with an average read length of 871 bp. Analysis of the assembled sequences by Pfam-based Carbohydrate-active enzyme Analysis Toolkit identified 17,164 putative protein-encoding CAZymes belonging to different families of glycoside hydrolases (7574), glycosyltransferases (5185), carbohydrate-binding modules (2418), carbohydrate esterases (1516), auxiliary activities (434) and polysaccharide lyases (37). Phylogenetic analysis of putative CAZymes revealed that a significant proportion of CAZymes were contributed by bacteria belonging to the phylum Bacteroidetes (40%), Firmicutes (30%) and Proteobacteria (10%). The comparative analysis of HF cross rumen metagenome with other herbivore metagenomes indicated that Indian crossbred cattle rumen is endowed with a battery of CAZymes that may play a central role in lignocellulose deconstruction. The extensive catalog of enzymes reported in our study that hydrolyzes plant lignocellulose biomass, can be further explored for the better feed utilization in ruminants and also for different industrial applications.

Metagenomic insights into the rumen microbial fibrolytic enzymes in Indian crossbred cattle fed finger millet straw.

The rumen is a unique natural habitat, exhibiting an unparalleled genetic resource of fibrolytic enzymes of microbial origin that degrade plant polysaccharides. The objectives of this study were to identify the principal plant cell wall-degrading enzymes and the taxonomic profile of rumen microbial communities that are associated with it. The cattle rumen microflora and the carbohydrate-active enzymes were functionally classified through a whole metagenomic sequencing approach. Analysis of the assembled sequences by the Carbohydrate-active enzyme analysis Toolkit identified the candidate genes encoding fibrolytic enzymes belonging to different classes of glycoside hydrolases(11,010 contigs), glycosyltransferases (6366 contigs), carbohydrate esterases (4945 contigs), carbohydrate-binding modules (1975 contigs), polysaccharide lyases (480 contigs), and auxiliary activities (115 contigs). Phylogenetic analysis of CAZyme encoding contigs revealed that a significant proportion of CAZymes were contributed by bacteria belonging to genera Prevotella, Bacteroides, Fibrobacter, Clostridium, and Ruminococcus. The results indicated that the cattle rumen microbiome and the CAZymes are highly complex, structurally similar but compositionally distinct from other ruminants. The unique characteristics of rumen microbiota and the enzymes produced by resident microbes provide opportunities to improve the feed conversion efficiency in ruminants and serve as a reservoir of industrially important enzymes for cellulosic biofuel production.

The Identification of Discriminating Patterns from 16S rRNA Gene to Generate Signature for Bacillus Genus.

The 16S ribosomal RNA (16S rRNA) gene has been widely used for the taxonomic classification of bacteria. A molecular signature is a set of nucleotide patterns, which constitute a regular expression that is specific to each particular taxon. Our main goal was to identify discriminating nucleotide patterns in 16S rRNA gene and then to generate signatures for taxonomic classification. To demonstrate our approach, we used the phylum Firmicutes as a model using representative taxa Bacilli (class), Bacillales (order), Bacillaceae (family), and Bacillus (genus), according to their dominance at each hierarchical taxonomic level. We applied combined composite vector and multiple sequence alignment approaches to generate gene-specific signatures. Further, we mapped all the patterns into the different hypervariable regions of 16S rRNA gene and confirmed the most appropriate distinguishing region as V3-V4 for targeted taxa. We also examined the evolution in discriminating patterns of signatures across taxonomic levels. We assessed the comparative classification accuracy of signatures with other methods (i.e., RDP Classifier, KNN, and SINA). Results revealed that the signatures for taxa Bacilli, Bacillales, Bacillaceae, and Bacillus could correctly classify isolate sequences with sensitivity of 0.99, 0.97, 0.94, and 0.89, respectively, and specificity close to 0.99. We developed signature-based software DNA Barcode Identification (DNA BarID) for taxonomic classification that is available at website http://www.neeri.res.in/DNA_BarID.htm . This pattern-based study provides a deeper understanding of taxon-specific discriminating patterns in 16S rRNA gene with respect to taxonomic classification.

Morphological and Molecular Characterization of Reared Parasitoid Wasps of the Genus Glyptapanteles Ashmead 1904 (Insecta: Hymenoptera: Braconidae: Microgastrinae) Associated with Lepidoptera in India.

Glyptapanteles Ashmead (Hymenoptera: Braconidae: Microgastrinae) is a cosmopolitan group of hyperdiverse parasitic wasps. The genus remains taxonomically challenging in India due to its highly speciose nature, morphological similarity amongst species and negligible host records. The Indian fauna is one of the most diverse and also the least studied. The present study is based on 60 populations reared from 35 host species, 100+ individual caterpillar rearings (1100 wasp specimens pinned and 2000 in alcohol) and from 12 different geographical locations of the country (11 states and one Union territory) that represent 26 provisional Glyptapanteles species within 8 species-groups. Out of 60 populations, phylogenetic analyses were performed on 38 based on mitochondrial cytochrome oxidase subunit I (COI) nucleotide sequences. Maximum likelihood and Bayesian inference methods displayed three and four major discrete Glyptapanteles clades, respectively. In clade A very few Indian species were grouped along with Neotropical and Thailand species. The other clades B and C grouped the majority of the Indian species and showed considerable host specificity in both the trees. All parasitic wasp species were gregarious in nature, except for two populations. Three different sets of data (morphology, host records, and COI) were integrated in order to generate accurate boundaries between species/species-groups. Illustrations of all parasitized caterpillars/cocoons and 42 habitus views of Glyptapanteles spp., distributional information, and GenBank accession numbers, are presented. The present study, perhaps the most comprehensive done to date in India, suggests the presence of several additional Glyptapanteles species, which were previously unrecognized.

Genome Sequence of Mycobacterium tuberculosis C2, a Cerebrospinal Fluid Clinical Isolate from Central India.

We report the annotated genome sequence of a Mycobacterium tuberculosis clinical isolate from the cerebrospinal fluid of a tuberculous meningitis patient admitted to the Central India Institute of Medical Sciences, Nagpur, India.

Metagenomic analysis of oxygenases from activated sludge.

Oxygenases play a key role in degradation of the aromatic compounds in the wastewater. This study explores the oxygenase coding gene sequences from the metagenome of activated biomass. Based on these results, the catabolic capacity of the activated sludge was assessed towards degradation of naphthalene, anthracene, phenol, biphenyl and o-toluidine. Oxygenases found in this study were compared with oxygenases from three other metagenome datasets. Results demonstrate that despite different geographical locations and source, many genes coding for oxygenases were common between treatment plants. 1, 2 Homogentisate dioxygenase and phenylacetate CoA oxygenases were present in all four metagenomes. Metagenomics provides a vast amount of data that needs to be mined with specific targets to harness the potential of the microbial world.

Mining and assessment of catabolic pathways in the metagenome of a common effluent treatment plant to induce the degradative capacity of biomass.

Metagenome analysis was used to understand the microbial community in activated sludge treating industrial wastewaters at a Common Effluent Treatment Plant (CETP) in South India. The taxonomic profile mapped onto National Center for Biotechnology Information (NCBI) taxonomy using MEtaGenome ANalyzer (MEGAN), demonstrated that the most abundant domain belonged to prokaryotes, dominated by bacteria. Bacteria representing nine phyla were identified from the sequence data including representatives from two new phyla, Synergistetes and Elusimicrobia. Functional analysis of the metagenome, with specific reference to the metabolism of aromatic compounds, revealed the dominance of genes of the central meta-cleavage pathway. This information was used to improve the degradative efficiency in the wastewater treatment plant. A pilot scale plant was set up with 200L of activated sludge using salicylate induced sludge and results demonstrated 52% removal in chemical oxygen demand (COD) against non-induced biomass.