Identifying rare genetic variants in 21 highly multiplex autism families: the role of diagnosis and autistic traits.

Autism is a highly heritable, heterogeneous, neurodevelopmental condition. Large-scale genetic studies, predominantly focussing on simplex families and clinical diagnoses of autism have identified hundreds of genes associated with autism. Yet, the contribution of these classes of genes to multiplex families and autistic traits still warrants investigation. Here, we conducted whole-genome sequencing of 21 highly multiplex autism families, with at least three autistic individuals in each family, to prioritise genes associated with autism. Using a combination of both autistic traits and clinical diagnosis of autism, we identify rare variants in genes associated with autism, and related neurodevelopmental conditions in multiple families. We identify a modest excess of these variants in autistic individuals compared to individuals without an autism diagnosis. Finally, we identify a convergence of the genes identified in molecular pathways related to development and neurogenesis. In sum, our analysis provides initial evidence to demonstrate the value of integrating autism diagnosis and autistic traits to prioritise genes.

Identification and functional characterization of two novel mutations in KCNJ10 and PI4KB in SeSAME syndrome without electrolyte imbalance.

BACKGROUND: Dysfunction in inwardly rectifying potassium channel Kir4.1 has been implicated in SeSAME syndrome, an autosomal-recessive (AR), rare, multi-systemic disorder. However, not all neurological, intellectual disability, and comorbid phenotypes in SeSAME syndrome can be mechanistically linked solely to Kir4.1 dysfunction. METHODS: We therefore performed whole-exome sequencing and identified additional genetic risk-elements that might exert causative effects either alone or in concert with Kir4.1 in a family diagnosed with SeSAME syndrome. RESULTS: Two variant prioritization pipelines based on AR inheritance and runs of homozygosity (ROH), identified two novel homozygous variants in KCNJ10 and PI4KB and five rare homozygous variants in PVRL4, RORC, FLG2, FCRL1, NIT1 and one common homozygous variant in HSPA6 segregating in all four patients. The novel mutation in KCNJ10 resides in the cytoplasmic domain of Kir4.1, a seat of phosphatidylinositol bisphosphate (PIP2) binding. The mutation altered the subcellular localization and stability of Kir4.1 in patient-specific lymphoblastoid cells (LCLs) compared to parental controls. Barium-sensitive endogenous K+ currents in patient-specific LCLs using whole-cell patch-clamp electrophysiology revealed membrane depolarization and defects in inward K+ ion conductance across the membrane, thereby suggesting a loss-of-function effect of KCNJ10 variant. CONCLUSION: Altogether, our findings implicate the role of new genes in SeSAME syndrome without electrolyte imbalance and thereby speculate the regulation of Kir4.1 channel activity by PIP2 and integrin-mediated adhesion signaling mechanisms.

Metagenomic approach to characterize soil microbial diversity of Phumdi at Loktak Lake.

Loktak, one of the largest freshwater lakes of India, is known for floating islands (Phumdi), being made up of a heterogeneous biomass of vegetation and soil. This ecological site represents an exclusive environmental habitat wherein the rhizospheric microbial community of Phumdi plays a key role in biogeochemical cycling of nutrients. A culture-independent whole genome shotgun sequencing based metagenomic approach was employed to unravel the composition of the microbial community and its corresponding functional potential at this environmental habitat. Proteobacteria (51%) was found to be the most dominant bacterial phylum followed by Acidobacteria (10%), Actinobacteria (9%) and Bacteroidetes (7%). Furthermore, Loktak metagenome data were compared with available metagenomes from four other aquatic habitats, varying from pristine to highly polluted eutrophic habitats. The comparative metagenomics approach aided by statistical analysis revealed that Candidatus Solibacter, Bradyrhizobium, Candidatus Koribacter, Pedosphaera, Methylobacterium, Anaeromyxobacter, Sorangium, Opitutus and Acidobacterium genera are selectively dominant at this habitat. Correspondingly, 12 different functional categories were found to be exclusively prevalent at Phumdi compared to other freshwater habitats. These differential features have been attributed to the unique habitat at Phumdi and correlated to the phenomenon of bioremediation at Loktak Lake.

INDEX-db: The Indian Exome Reference Database (Phase I).

Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map. In this study, we report the development of phase I of a new database of genetic variations called INDian EXome database (INDEX-db), from the Indian population, with an aim to establish a centralized database of integrated information. This could be useful for researchers involved in studying disease mechanisms at clinical, genetic, and cellular levels.

matK-QR classifier: a patterns based approach for plant species identification.

BACKGROUND: DNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK (matK) and ribulose-1, 5-bisphosphate carboxylase (rbcL) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification. METHODS: In order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset. RESULTS: Due to the higher discrimination success obtained with the matK as compared to the rbcL, we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK-QR Classifier (http://www.neeri.res.in/matk_classifier/index.htm), which search signatures in the query matK gene sequences and predict corresponding plant species. CONCLUSIONS: This novel approach of employing pattern-based signatures opens new avenues for the classification of species. In addition to existing methods, we believe that matK-QR Classifier would be a valuable tool for molecular taxonomists enabling precise identification of plant species.