LncRNA VEAL2 regulates PRKCB2 to modulate endothelial permeability in diabetic retinopathy.

Long non-coding RNAs (lncRNAs) are emerging as key regulators of endothelial cell function. Here, we investigated the role of a novel vascular endothelial-associated lncRNA (VEAL2) in regulating endothelial permeability. Precise editing of veal2 loci in zebrafish (veal2gib005Δ8/+ ) induced cranial hemorrhage. In vitro and in vivo studies revealed that veal2 competes with diacylglycerol for interaction with protein kinase C beta-b (Prkcbb) and regulates its kinase activity. Using PRKCB2 as bait, we identified functional ortholog of veal2 in humans from HUVECs and named it as VEAL2. Overexpression and knockdown of VEAL2 affected tubulogenesis and permeability in HUVECs. VEAL2 was differentially expressed in choroid tissue in eye and blood from patients with diabetic retinopathy, a disease where PRKCB2 is known to be hyperactivated. Further, VEAL2 could rescue the effects of PRKCB2-mediated turnover of endothelial junctional proteins thus reducing hyperpermeability in hyperglycemic HUVEC model of diabetic retinopathy. Based on evidence from zebrafish and hyperglycemic HUVEC models and diabetic retinopathy patients, we report a hitherto unknown VEAL2 lncRNA-mediated regulation of PRKCB2, for modulating junctional dynamics and maintenance of endothelial permeability.

IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes.

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the 'IndiGen' program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as 'IndiGenomes' http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.

WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as variants of uncertain significance as either pathogenic or benign. Here we classify ATP7B genetic variants by employing ML and AI algorithms trained on our well-annotated WilsonGen dataset. METHODS: We have trained and validated two algorithms: TabNet and XGBoost on a high-confidence dataset of manually annotated, ACMG & AMP classified variants of the ATP7B gene associated with Wilson's Disease. RESULTS: Using an independent validation dataset of ACMG & AMP classified variants, as well as a patient set of functionally validated variants, we showed how both algorithms perform and can be used to classify large numbers of variants in clinical as well as research settings. CONCLUSION: We have created a ready to deploy tool, that can classify variants linked with Wilson's disease as pathogenic or benign, which can be utilized by both clinicians and researchers to better understand the disease through the nature of genetic variants associated with it.

Protocols for Characterization of Cdk5 Kinase Activity.

Cyclin-dependent kinases (Cdks) are generally known to be involved in controlling the cell cycle, but Cdk5 is a unique member of this protein family for being most active in post-mitotic neurons. Cdk5 is developmentally important in regulating neuronal migration, neurite outgrowth, and axon guidance. Cdk5 is enriched in synaptic membranes and is known to modulate synaptic activity. Postnatally, Cdk5 can also affect neuronal processes such as dopaminergic signaling and pain sensitivity. Dysregulated Cdk5, in contrast, has been linked to neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). Despite primarily being implicated in neuronal development and activity, Cdk5 has lately been linked to non-neuronal functions including cancer cell growth, immune responses, and diabetes. Since Cdk5 activity is tightly regulated, a method for measuring its kinase activity is needed to fully understand the precise role of Cdk5 in developmental and disease processes. This article includes methods for detecting Cdk5 kinase activity in cultured cells or tissues, identifying new substrates, and screening for new kinase inhibitors. Furthermore, since Cdk5 shares homology and substrate specificity with Cdk1 and Cdk2, the Cdk5 kinase assay can be used, with modification, to measure the activity of other Cdks as well. © 2021 Wiley Periodicals LLC. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Basic Protocol 1: Measuring Cdk5 activity from protein lysates Support Protocol 1: Immunoprecipitation of Cdk5 using Dynabeads Alternate Protocol: Non-radioactive protocols to measure Cdk5 kinase activity Support Protocol 2: Western blot analysis for the detection of Cdk5, p35, and p39 Support Protocol 3: Immunodetection analysis for Cdk5, p35, and p39 Support Protocol 4: Genetically engineered mice (+ and - controls) Basic Protocol 2: Identifying new Cdk5 substrates and kinase inhibitors.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes.

BACKGROUND: Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient's ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India. RESULTS: We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported. CONCLUSION: With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.