Biology subjects

Joshi, E.

Publications and source records attributed to Joshi, E..

3 recordsLinked to original sources

bioRxiv2022

Whole-genome sequencing across 449 samples spanning 47 ethnolinguistic groups provides insights into genetic diversity in Nigeria

African populations have been drastically underrepresented in genomics research and failure to capture the genetic diversity across the numerous ethnolinguistic groups (ELGs) found in the continent has hindered the equity of precision medicine initiatives globally. Here, we describe the whole-genome sequencing of 449 Nigerian individuals across 47 unique self-reported ELGs. Population structure analysis reveals genetic differentiation amongst our ELGs, consistent with previous findings. From the 36 million SNPs and INDELs discovered in our dataset, we provide a high-level catalog of both novel and medically-relevant variation present across the ELGs. These results emphasize the value of this resource for genomics research, with added granularity by representing multiple ELGs from Nigeria. Our results also underscore the potential of using these cohorts with larger sample sizes to improve our understanding of human ancestry and health in Africa.

genomics↗

bioRxiv2022

A survey of proteomic variation across two ethnic groups in Nigeria and its relationship to obesity risk

Proteomic variation between individuals has immense potential for identifying novel drug targets and disease mechanisms. However, with high-throughput proteomic technologies still in their infancy, they have largely been applied in large majority European ancestry cohorts (e.g. the UK Biobank). An open question is the degree to which proteomic signatures seen in European and other groups mirror those seen in diverse populations, such as cohorts from Africa. Coupled with genetic information, we can also gain a better understanding of the role of genetic variants in the regulation of the proteome and subsequent disease mechanisms. To address the gap in our understanding of proteomic variation in individuals of African ancestry, we collected proteomic data from 176 individuals across two ethnic groups (Igbo and Yoruba) in Nigeria. These individuals were also stratified into high BMI (BMI > 30 kg/m2) and normal BMI (20 kg/m2 < BMI < 30 kg/m2) categories. We characterized differences in plasma protein abundance using the Olink Explore 1536 panel between high and normal BMI individuals, finding strong associations consistent with previously known signals in individuals of European descent. We additionally found 73 sentinel cis-pQTL in this dataset, with 21 lead cis-pQTL not observed in catalogs of variation from European-ancestry individuals. In summary, our study highlights the value of leveraging proteomic data in cohorts of diverse ancestry for investigating trait-specific mechanisms and discovering novel genetic regulators of the plasma proteome.

genomics↗

bioRxiv2020

GeneTerpret: a customizable multilayer approach to genomic variant prioritization and interpretation

Variant interpretation is the main bottleneck in medical genomic sequencing efforts. This usually involves genome analysts manually scouring through a multitude of independent databases, often with the aid of several and mostly independent computational tools. To streamline the variant interpretation process, we developed GeneTerpret platform that collates data from current interpretation tools and databases, and applies a phenotype-driven query to categorize the variants identified in a given genome. The platform assigns quantitative validity scores to genes by query and assembly of the current genotype-phenotype data, sequence homology, molecular interactions, expression data, and animal models. The platform uses the American College of Medical Genetics (ACMG) criteria to categorize variants into five tiers (from benign to pathogenic). The platform then outputs a prioritized list of potentially causal variants/genes in a given genome for a specific case. GeneTerpret is a flexible and free platform designed to streamline the variant interpretation process through a unique interface, with improved ease, speed and accuracy. This unique integrated system provides effective validity and pathogenicity modules to assess genetic variant data and allows the user to decide which output and impact level should be considered in this process. The platform can be accessed and used online at https://geneterpret.com.

bioinformatics↗