Critical for brain development, neurodevelopmental and network disorders, the GABRA1 gene encodes for the α1 subunit, an abundantly and developmentally expressed subunit of heteropentameric gamma-aminobutyric acid A receptors (GABAARs) mediating primary inhibition in the brain. Mutations of the GABAAR subunit genes including GABRA1 gene are associated with epilepsy, a group of syndromes, characterized by unprovoked seizures and diagnosed by integrative approach, that involves genetic testing. Despite the diagnostic use of genetic testing, a large fraction of the GABAAR subunit gene variants including the variants of GABRA1 gene is not known in terms of their molecular consequence, a challenge for precision and personalized medicine. Addressing this, one hundred thirty-seven GABRA1 gene variants of unknown clinical significance have been extracted from the ClinVar database and computationally analyzed for pathogenicity. Eight variants (L49H, P59L, W97R, D99G, G152S, V270G, T294R, P305L) are predicted as pathogenic and mapped to the α1 subunit\'s extracellular domain (ECD), transmembrane domains (TMDs) and extracellular linker. This is followed by the integration with relevant data for cellular pathology and severity of the epilepsy syndromes retrieved from the literature. Our results suggest that the pathogenic variants in the ECD of GABRA1 (L49H, P59L, W97R, D99G, G152S) will probably manifest decreased surface expression and reduced current with mild epilepsy phenotypes while V270G, T294R in the TMDs and P305L in the linker between the second and the third TMDs will likely cause reduced cell current with severe epilepsy phenotypes. The results presented in this study provides insights for clinical genetics and wet lab experimentation.

Adenosine-to-inosine (A-to-I) RNA editing leads to functional change of neurotransmitter receptor which is essential for neurotransmission and normal neuronal development. As a highly accessible part of central nervous system, retina has been extensively studied, however, it remains largely unknown how RNA editing regulates its development. Here, a genome-wide screening of high-confidence RNA editing events were performed to decipher the dynamic transcriptome regulation by RNA editing during mouse retinal development. 2000 high-confidence editing sites across eight developmental stages of retina were called. Three unique patterns (RNA-editinghigh pattern, RNA-editingmedium pattern and RNA-editinglow pattern) were identified by clustering these editing sites based on their editing level during retinal development. Editing events from RNA-editinghigh pattern were significantly associated with glutamate receptors and regulated synaptic transmission. Interestingly, most non-synonymous high-editing sites were mapped to ion channel genes of glutamatergic synapse which were associated with neurotransmission by controlling ion channel permeability and affecting exocytosis. Meanwhile, these non-synonymous editing sites were evolutionarily conserved and exhibited a consistently increasing editing levels between mouse and human retinal development. Single-cell RNA-seq data analysis revealed that RNA editing events prefer to occur in two main cell types including bipolar and amacrine cells. Genes with non-synonymous high-editing sites were enriched in both bipolar cells and retina ganglion cells, which may mediate retina ganglion cell differentiation by altering channel ion permeability. Together, our results provide novel insights into mechanism of post-transcriptional regulation during retinal development and help to develop novel RNA editing-guided therapeutic strategies for retinal disorders.

In-silico studies on SARS-CoV-2 genome are considered important to identify the significant pattern of variations and its possible effects on the structural and functional characteristics of the virus. The current study determined such genetic variations and their possible impact among SARS-CoV-2 variants isolated in India. A total of 546 SARS-CoV-2 genomic sequences (India) were retrieved from the gene bank (NCBI) and subjected to alignment against the Wuhan variant (NC_045512.2), the corresponding amino acid changes were analyzed using NCBI Protein-BLAST. These 546 variants revealed 841 mutations; most of these were non-synonymous 464/841 (55.1%), there was no identical variant compared to the original strain. All genes; coding and non-coding showed nucleotide changes, most of the structural genes showed frequent nonsynonymous mutations. The most affected genes were ORF1a/b followed by the S gene which showed 515/841 (61.2%) and 120/841 (14.3%) mutations, respectively. The most frequent non-synonymous mutation 486/546 (89.01%) occurred in the S gene (structural gene) at position 23,403 where A changed to G leading to the replacement of aspartic acid by glycine in position (D614G). Interestingly, four variants also showed deletion. The variants MT800923 and MT800925 showed 12 consecutive nucleotide deletion in position 21982-21993 resulting in 4 consecutive amino acid deletions that were leucine, glycine, valine, and tyrosine in positions 141, 142, 143, and 144 respectively. The present study exhibited a higher mutations rate per variant compared to other studies carried out in India.

COVID-19 has posed unforeseen circumstances and throttled major economies worldwide. India has witnessed two waves affecting around 31 million people representing 16% of the cases globally. To date, the epidemic waves have not been comprehensively investigated to understand pandemic progress in India.
Here, we aim for pan Indian cross-sectional evolutionary analysis since inception of SARS-CoV-2.
High quality genomes, along with their collection date till 26th July 2021, were downloaded. Whole genome-based phylogeny was obtained. Further, the mutational analysis was performed using SARS-CoV-2 first reported from Wuhan (NC_045512.2) as reference.
Based on reported cases and mutation rates, we could divide the Indian epidemic into seven phases. The average mutation rate for the pre-first wave was <11, which elevated to 17 in the first wave and doubled in the second wave (∼34). In accordance with mutation rate, VOCs and VOIs started appearing in the first wave (1.5%), which dominated the second (∼96%) and post-second wave (100%). Nation-wide mutational analysis depicted >0.5 million mutation events with four major mutations in >19,300 genomes, including two mutations in coding (spike (D614G), and NSP 12b (P314L) of rdrp), one silent mutation (NSP3 F106F) and one extragenic mutation (5\' UTR 241).
Whole genome-based phylogeny could demarcate post-first wave isolates from previous ones by point of diversification leading to incidences of VOCs and VOIs in India. Such analysis is crucial in the timely management of pandemic.

Dietary intervention is effective in human health promotion through modulation of gut microbiota. Diet can cause single-nucleotide polymorphisms (SNPs) to occur in the gut microbiota, and some of these variations may lead to functional changes in human health. In this study, we performed a systematic SNP analysis based on metagenomic data collected from children with Prader-Willi syndrome (PWS, n = 17) and simple obese (SO) children (n = 19), who had better healthy conditions after receiving high-fiber diet intervention. We found that the intervention increased the SNP proportions of Faecalibacterium, Bifidobacterium, and Clostridium and decreased those of Bacteroides in all children. Besides, the PWS children had Collinsella increased and Ruminococcus decreased, whereas the SO had Blautia and Escherichia decreased. There were much more BiasSNPs in PWS than in SO (4,465 vs 303), and only 81 of them appeared in both groups, of which 78 were from Faecalibacterium prausnitzii, and 51 were nonsynonymous mutations. These nonsynonymous variations were mainly related to pathways of environmental adaptation and nutrition metabolism, particularly to carbohydrate and nucleotide metabolism. In addition, dominant strains carrying BiasSNPs in all children shifted from F. prausnitzii AF32-8AC and F. prausnitzii 942/30-2 to F. prausnitzii SSTS Bg7063 and F. prausnitzii JG BgPS064 after the dietary intervention. Furthermore, although the abundance of Bifidobacterium increased significantly by the intervention and became dominant strains responsible for nutrition metabolism, they had less BiasSNPs between the pre- and post-intervention group in comparison with Faecalibacterium. The finding of F. prausnitzii as important functional strains influenced by the intervention highlights the superiority of applying SNP analysis in studies of gut microbiota. This study provided evidence and support for the effect of dietary intervention on gut microbial SNPs, and gave some enlightenments for disease treatment.

Tuberculosis caused by Mycobacterium tuberculosis is one of the main global health concerns. In this study, the entire mitochondrial genome from blood samples of tuberculosis patients was analyzed to understand the possible mtDNA variants. The potential impact of non-synonymous substitutions on protein functions were determined using prediction tools. 28 non- synonymous variants were found of which 2 variants (MT-ND2 g. A > G4824 p.T119A and MT-ND6 g. T > C14180 p.Y165C) were found to be deleterious among the cases only. Majority of the variants lie in the D-loop of the non-protein coding region of the mitochondrial DNA. We propose that mutations in the mitochondrial genome need to be validated further to understand their association with tuberculosis.

Glycoprotein M6A, a stress related gene, plays an important role in synapse and filopodia formation. Filopodia formation is vital for development, immunity, angiogenesis, wound healing and metastasis. In this study, structural and functional analysis of high-risk SNPs associated with Glycoprotein M6-A were evaluated using six different bioinformatics tools. Results classified T210I, T134I, Y153H, I215T, F156L, T160I, I226T, R247W, R178C, W159R, N157S and P151L as deleterious mutants that are crucial for the structure and function of the protein causing malfunction of M6-a and ultimately leads to disease development. The three-dimensional structure of wild-type M6-a and mutant M6-a were also predicted. Furthermore, the effects of high risk substitutions were also analyzed with interaction with valproic acid. Based on structural models obtained, the binding pocket of ligand bound glycoprotein M6-A structure showed few core interacting residues which are different in the mutant models. Among all substitutions, F156L showed complete loss of binding pocket when interacting with valproic acid as compared to the wild type model. Up to the best of our knowledge this is the first comprehensive study where GPM6A mutations were analyzed. The mechanism of action of GPM6A is still not fully defined which limits the understanding of functional details encoding M6-A. Our results may help enlighten some molecular aspects underlying glycoprotein M6-A. Communicated by Ramaswamy H. Sarma.

The variants reported for mitochondrial DNA (mtDNA) and type 2 diabetes (T2D) may not be accountable for the disease in certain other populations and the risk depends upon numerous factors which may include genetics, environment as well as ethnicity. This leads to a challenge in identifying, exploring and comparing the variants between diabetic cases and healthy controls in a remote unexplored tribal population. To study the possible contribution of mtDNA variants, we sequenced the entire mitochondrial genomes and the frequencies of mtSNPs, their association with familial T2D and the potential impact of non-synonymous substitutions on protein functions were determined. The mtSNP 8584 G > A (ATP6: A20T) was detected in 14.28% of the diabetic patients and none in the control groups. The mitochondrial ND3 variant 10398A > G was found to be significantly associated with the risk of T2D (OR = 9.489, 95% CI = 1.161-77.54, P value = 0.036). A novel Frame-shift substitution ND5: 81_81ins A at position 12,417 was observed in 53.57% of diabetic individuals. Majority of the variants lie in tRNA-Phe in the non-protein coding region of mtDNA for both diabetic cases and common cases. We concluded that mutations in the coding (synonymous or non-synonymous) and noncoding regions of the mitochondria might have contribution towards the development of T2D. Our study is the first to report the distinct mitochondrial variants which may be attributed to the susceptibility as well as development of type 2 diabetes in an ethnic tribe from northeast India.

Characterizing how variation at the level of individual nucleotides contributes to traits and diseases has been an area of growing interest since the completion of sequencing the first human genome. Our understanding of how a single nucleotide polymorphism (SNP) leads to a pathogenic phenotype on a genome-wide scale is a fruitful endeavor for anyone interested in developing diagnostic tests, therapeutics, or simply wanting to understand the etiology of a disease or trait. To this end, many datasets and algorithms have been developed as resources/tools to annotate SNPs. One of the most common practices is to annotate coding SNPs that affect the protein sequence. Synonymous variants are often grouped as one type of variant, however there are in fact many tools available to dissect their effects on gene expression. More recently, large consortiums like ENCODE and GTEx have made it possible to annotate non-coding regions. Although annotating variants is a common technique among human geneticists, the constant advances in tools and biology surrounding SNPs requires an updated summary of what is known and the trajectory of the field. This review will discuss the history behind SNP annotation, commonly used tools, and newer strategies for SNP annotation. Additionally, we will comment on the caveats that distinguish approaches from one another, along with gaps in the current state of knowledge, and potential future directions. We do not intend for this to be a comprehensive review for any specific area of SNP annotation, but rather it will be an excellent resource for those unfamiliar with computational tools used to functionally characterize SNPs. In summary, this review will help illustrate how each SNP annotation method impacts the way in which the genetic and molecular etiology of a disease is explored in-silico.

Commercial vaccines based on recombinant forms of the Bm86 tick gut antigen are used to control the southern cattle tick, Rhipicephalus microplus, a 1-host species, in Australia and Latin America. We describe herein sequence polymorphism in genes encoding Ra86 homologues of Bm86 in the brown ear tick, Rhipicephalus appendiculatus, isolated from four Kenyan field populations and one laboratory colony. Sequencing of 19 Ra86 sequences defined two alleles differentiated by indels, encoding 693 amino acids (aa) and 654 aa respectively, from the Muguga laboratory reference strain. Ra86 sequences were also determined from gut cDNA from four field populations of R. appendiculatus collected in different livestock production systems in Kenya. Analysis of approximately 20 Ra86 sequences from each of the four field sites in central and Western Kenya; Makuyu, Kiambu, Kakamega and Uasin Gishu, revealed three additional size types differentiated by 39-49 amino acid indels resulting in a total of 5 indel-defined genotypes. The 693 aa type 5 was isolated only from the laboratory tick stock; genotypes 1, 2 and 3 were identified in ticks from the four Kenyan field sites and appeared to be derivatives of the shorter RA86 genotype found in Muguga laboratory stock genotype 4. By contrast no large indels have yet been observed between R. microplus sequences from Australia, South America or Africa. Evidence that selection contributes to the observed sequence variation was provided by analysis of ratio of synonymous and non-synonymous substitutions and application of the selective neutrality and neutral evolution tests to the primary data. Phylogenetic analysis clustered sequences from all Ra86 size types and Bm86, into four major clades based on amino acid substitutions, but there was no evidence that these groupings correlated with geographical separation of R. appendiculatus populations.