Biology subjects

Dey, R.

Publications and source records attributed to Dey, R..

29 records · Page 2Linked to original sources

bioRxiv2021

Active microrheology using pulsed optical tweezers to probe viscoelasticity of Lamin A towards diagnosis of laminopathies

Lamins are nucleoskeletal proteins of mammalian cells that stabilize the structure and maintain the rigidity of the nucleus. These type V intermediate filament proteins which are predominantly of A and B types provide necessary tensile strength to the nucleus. Single amino acid missense mutations occurring all over the lamin A protein form a cluster of human diseases termed as laminopathies, a few of which principally affect the muscle and cardiac tissues responsible for load bearing functionalities of the body. One such mutation is lamin A350P which causes dilated cardiomyopathy in patients. It is likely that a change from alanine to proline in the -helical 2B rod domain of the protein might severely disrupt the propensity of the filaments to polymerise into functional higher order structures required to form a fully functional lamina with its characteristic elasticity. In this study, we validate for the very first time, the application of active microrheology employing oscillating optical tweezers to investigate any alterations in the visco-elastic parameters of the mutant protein meshwork in vitro, which might translate into possible changes in nuclear plasticity. We confirm our findings from this robust yet fast method by imaging both the wild type and mutant lamins using a super resolution microscope, and observe changes in the mesh size which explain our measured changes in the viscoelastic parameters of the lamins. This method could naturally be extended to conduct microrheological measurements on any intermediate filament protein or any protein endowed with elastic behavior, with minor schematic modifications, thus bearing significant implications in laminopathies and other diseases which are associated with changes in structural rigidity of any cellular organelle. SignificanceLamin A mutations produce an array of diseases termed as laminopathies which are primarily characterized by alteration of elastic behavior of the nucleus which in turn leads to defects in mechanotransduction. This is the first report in the lamin arena which shows a fast, accurate and direct quantification of elastic moduli of lamin A using optical tweezers-based microrheology. This has very significant implications and can be registered to be a robust and universal method that could also be suitably used for probing changes in elastic properties of any proteins or surfactants in a disease scenario such as SARS-Cov2 (Covid-19), which is pandemic at this time.

biophysics↗

bioRxiv2020

A versatile toolkit for molecular QTL mapping and meta-analysis at scale

Molecular QTLs (xQTLs) are widely studied to identify functional variation and possible mechanisms underlying genetic associations with diseases. Larger xQTL sample sizes are critical to help identify causal variants, improve predictive models, and increase power to detect rare associations. This will require scalable and accurate methods for analysis of tens of thousands of molecular traits in large cohorts, and/or from summary statistics in meta-analysis, both of which are currently lacking. We developed APEX (All-in-one Package for Efficient Xqtl analysis), an efficient toolkit for xQTL mapping and meta-analysis that provides (a) highly optimized linear mixed models to account for relatedness and shared variation across molecular traits; (b) rapid factor analysis to infer latent technical and biological variables from molecular trait data; (c) fast and accurate trait-level omnibus tests that incorporate prior functional weights to increase statistical power; and (d) compact summary data files for flexible and accurate joint analysis of multiple variants (e.g., joint/conditional regression or Bayesian finemapping) without individual-level data in meta-analysis. We applied the methods to data from three LCL eQTL studies and the UK Biobank. APEX is open source: https://corbinq.github.io/apex.

genetics↗

bioRxiv2020

An efficient and accurate frailty model approach for genome-wide survival association analysis controlling for population structure and relatedness in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We developed an efficient and accurate frailty (random effects) model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes in large biobanks by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrated the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 samples in FinnGen, respectively. We further performed genome-wide association analysis for 871 TTE phenotypes in UK Biobank and presented the genome-wide scale phenome-wide association (PheWAS) results with the PheWeb browser.

genomics↗

bioRxiv2020

A Second Generation Leishmanization Vaccine with a Markerless Attenuated Leishmania major Strain using CRISPR gene editing

Leishmaniasis is a debilitating and often fatal neglected tropical disease caused by Leishmania protozoa transmitted by infected sand flies. Vaccination through leishmanization with live Leishmania major has been used successfully but is no longer practiced because it resulted in unacceptable skin lesions. A second generation leishmanization is described here using a CRISPR genome edited L. major strain (LmCen-/-). Notably, LmCen-/- is the first genetically engineered gene deleted Leishmania strain that is antibiotic resistant marker free and does not have any off-target mutations. Mice immunized with LmCen-/- had virtually no visible lesions following challenge with L. major-infected sand flies while non-immunized animals developed large and progressive lesions with a 2-log fold higher parasite burden. LmCen-/- immunization showed protection and an immune response comparable to leishmanization. LmCen-/- is safe since it was unable to cause disease even in immunocompromised mice, induces robust host protection against vector sand fly challenge and because it is marker free, can be advanced to human vaccine trials.

microbiology↗

bioRxiv2020

Mutational spectra of SARS-CoV-2 orf1ab polyprotein and Signature mutations in the United States of America

Pandemic COVID-19 outbreak has been caused due to SARS-COV2 pathogen, resulting millions of infection and death worldwide, USA being on top at the present moment. The long, complex orf1ab polyproteins of SARS-COV2 play an important role in viral RNA synthesis. To assess the impact of mutations in this important domain, we analyzed 1134 complete protein sequences of orf1ab polyprotein from NCBI Virus database from affected patients across various states of USA from December 2019 to 25th April, 2020. Multiple sequence alignment using Clustal Omega followed by statistical significance was calculated. Four significant mutations T265I (nsp 2), P4715L (nsp 12) and P5828L and Y5865C (both at nsp 13) were identified in important non-structural proteins, which function either as replicase or helicase. A comparative analysis shows 265T>I, 5828P>L and 5865Y>C are unique to USA and not reported from Europe or Asia; while one, 4715P>L is predominant in both Europe and USA. Mutational changes in amino acids are predicted to alter structure and function of corresponding proteins, thereby it is imperative to consider the mutational spectra while designing new antiviral therapeutics targeting viral orf1ab.

bioinformatics↗

bioRxiv2019

Fast and robust ancestry prediction using principal component analysis

Population stratification (PS) is a major confounder in genome-wide association studies (GWAS) and can lead to false positive associations. To adjust for PS, principal component analysis (PCA)-based ancestry prediction has been widely used. Simple projection (SP) based on principal component loading and recently developed data augmentation-decomposition-transformation (ADP), such as LASER and TRACE, are popular methods for predicting PC scores. However, they are either biased or computationally expensive. The predicted PC scores from SP can be biased toward NULL. On the other hand, since ADP requires running PCA separately for each study sample on the augmented data set, its computational cost is high. To address these problems, we develop and propose two alternative approaches, bias-adjusted projection (AP) and online ADP (OADP). Using random matrix theory, AP asymptotically estimates and adjusts for the bias of SP. OADP uses computationally efficient online singular value decomposition, which can greatly reduce the computation cost of ADP. We carried out extensive simulation studies to show that these alternative approaches are unbiased and the computation times can be 10-100 times faster than ADP. We applied our approaches to UK-Biobank data of 488,366 study samples with 2,492 samples from the 1000 Genomes data as the reference. AP and OADP required 7 and 75 CPU hours, respectively, while the projected computation time of ADP is 2,534 CPU hours. Furthermore, when we only used the European reference samples in the 1000 Genomes to infer sub-European ancestry, SP clearly showed bias, unlike the proposed approaches. By using AP and OADP, we can infer ancestry and adjust for PS robustly and efficiently.

genetics↗

bioRxiv2019

Technical Note: Efficient and accurate estimation of genotype odds ratios in biobank-based unbalanced case-control studies

In genome-wide association studies (GWASs), genotype log-odds ratios (LORs) quantify the effects of the variants on the binary phenotypes, and calculating the genotype LORs for all of the markers is required for several downstream analyses. Calculating genotype LORs at a genome-wide scale is computationally challenging, especially when analyzing large-scale biobank data, which involves performing thousands of GWASs phenome-wide. Since most of the binary phenotypes in biobank-based studies have unbalanced (case : control = 1 : 10) or often extremely unbalanced (case : control = 1 : 100) case-control ratios, the existing methods cannot provide a scalable and accurate way to estimate the genotype LORs. The traditional logistic regression provides biased LOR estimates in such situations. Although the Firth bias correction method can provide unbiased LOR estimates, it is not scalable for genome-wide or phenome-wide scale association analyses typically used in biobank-based studies, especially when the number of non-genetic covariates is large. On the other hand, the saddlepoint approximation-based test (fastSPA), which can provide accurate p values and is scalable to analyse large-scale biobank data, does not provide the genotype LOR estimates as it is a score-based test. Here, we propose a scalable method based on score statistics, to accurately estimate the genotype LORs, adjusting for non-genetic covariates. Comparing to the Firth method, our proposed method reduces the computational complexity from O(nK2 + K3) to O(n), where n is the sample-size, and K is the number of non-genetic covariates. Our method is ~ 10x faster than the Firth method when 15 covariates are being adjusted for. Through extensive numerical simulations, we show that the proposed method is both scalable and accurate in estimating the genotype ORs in genome-wide or phenome-wide scale.

genomics↗

bioRxiv2019

Extracellular Caspase-1 regulates migration of hair follicle stem cells upon wounding

The wound-healing process is a paradigm of the directed migration of various pools of stem cells from their niche to the site of injury where they replenish damaged cells. Two decades have elapsed since the observation that wounding activates multipotent hair follicle stem cells to infiltrate the epidermis, but the cues that coax these cells out of their niche remains unknown. Using an excisional wound and genetic mouse models of wound healing, we discovered that Caspase-1, a protein classically known as an integral component of the cytosolic inflammasome, is secreted and has a non-canonical role in the extracellular milieu. Through its Caspase Activation Recruitment Domain (CARD), Caspase-1 is sufficient to initiate chemotaxis of hair follicle stem cells into the epidermis. Uncovering this novel function of Caspase-1 also facilitates a deeper understanding of the mechanistic basis of the epithelial hyperplasia found to accompany numerous inflammatory skin diseases.

cell biology↗

bioRxiv2018

Genome-wide association study of 1 million people identifies 111 loci for atrial fibrillation

To understand the genetic variation underlying atrial fibrillation (AF), the most common cardiac arrhythmia, we performed a genome-wide association study (GWAS) of > 1 million people, including 60,620 AF cases and 970,216 controls. We identified 163 independent risk variants at 111 loci and prioritized 165 candidate genes likely to be involved in AF. Many of the identified risk variants fall near genes where more deleterious mutations have been reported to cause serious heart defects in humans or mice (MYH6, NKX2-5, PITX2, TBC1D32, TBX5),1,2 or near genes important for striated muscle function and integrity (e.g. MYH7, PKP2, SSPN, SGCA). Experiments in rabbits with heart failure and left atrial dilation identified a heterogeneous distributed molecular switch from MYH6 to MYH7 in the left atrium, which resulted in contractile and functional heterogeneity and may predispose to initiation and maintenance of atrial arrhythmia.

genetics↗

bioRxiv2017

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies

In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly - producing large type I error rates - in the analysis of phenotypes with unbalanced case-control ratios. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation (SPA) to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational time and memory cost of generalized mixed model. The computation cost linearly depends on sample size, and hence can be applicable to GWAS for thousands of phenotypes by large biobanks. Through the analysis of UK Biobank data of 408,961 white British European-ancestry samples for >1400 binary phenotypes, we show that SAIGE can efficiently analyze large sample data, controlling for unbalanced case-control ratios and sample relatedness.

genomics↗

bioRxiv2017

A fast and accurate algorithm to test for binary phenotypes and its application to PheWAS

The availability of electronic health record (EHR)-based phenotypes allows for genome-wide association analyses in thousands of traits, and has great potential to identify novel genetic variants associated with clinical phenotypes. We can interpret the phenome-wide association study (PheWAS) result for a single genetic variant by observing its association across a landscape of phenotypes. Since PheWAS can test 1000s of binary phenotypes, and most of them have unbalanced (case:control = 1:10) or often extremely unbalanced (case:control = 1:600) case-control ratios, existing methods cannot provide an accurate and scalable way to test for associations. Here we propose a computationally fast score test-based method that estimates the distribution of the test statistic using the saddlepoint approximation. Our method is much faster than the state of the art Firths test ([~] 100 times). It can also adjust for covariates and control type I error rates even when the case-control ratio is extremely unbalanced. Through application to PheWAS data from the Michigan Genomics Initiative, we show that the proposed method can control type I error rates while replicating previously known association signals even for traits with a very small number of cases and a large number of controls.

genomics↗