Biology subjects

Taylor, H. J.

Publications and source records attributed to Taylor, H. J..

3 recordsLinked to original sources

bioRxiv2023

Functional interrogation of twenty type 2 diabetesassociated genes using isogenic hESC-derived β-like cells

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional role of many loci has remained unexplored. In this study, we engineered isogenic knockout human embryonic stem cell (hESC) lines for 20 genes associated with T2D risk. We systematically examined {beta}-cell differentiation, insulin production and secretion, and survival. We performed RNA-seq and ATAC-seq on hESC-{beta} cells from each knockout line. Analyses of T2D GWAS signals overlapping with HNF4A-dependent ATAC peaks identified a specific SNP as a likely causal variant. In addition, we performed integrative association analyses and identified four genes (CP, RNASE1, PCSK1N and GSTA2) associated with insulin production, and two genes (TAGLN3 and DHRS2) associated with sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental hESC line, to identify a single likely functional variant at each of 23 T2D GWAS signals.

genetics↗

bioRxiv2022

Single-cell gene expression and chromatin accessibility profiling of human pancreatic islets at basal and stimulatory conditions nominates mechanisms of type 1 diabetes genetic risk

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by the loss of pancreatic islet beta cells. The mechanisms of T1D genetic risk remain poorly understood. Here, we present a multi-omic integrative study of single-cell/nucleus molecular profiles of gene expression and chromatin accessibility in the same biological samples from healthy and beta cell autoantibody+ (AAB+) human pancreatic islets to characterize mechanisms of islet-mediated T1D genetic risk. We additionally performed single-cell/nucleus multi-omic profiling of healthy islets under two stimulatory conditions used as in vitro models of T1D (cytokine cocktail and CVB4 infection) to evaluate how environmental exposures recapitulate multi-omic signatures of T1D. In total, we analyzed 121,272 cells/nuclei across 34 libraries, identifying 10 distinct cell types. We identified cell-type-specific and disease-associated cis-regulatory elements and nominated likely target genes. We provide evidence that T1D genetic risk is mediated through multiple pancreatic cell populations, including islet endocrine cells (beta, alpha, gamma, and delta), exocrine acinar and ductal cells, and immune cells. Finally, we identified three independent T1D risk variants acting through pancreatic islet endocrine cells at the TOX, RASGRP1, and DLK1/MEG3 loci. Together, this work improves our understanding of how non-coding genetic variants encode T1D risk through a complex interplay of different cell types in the pancreas.

genomics↗

bioRxiv2022

Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis

Genetic studies have identified [≥]240 loci associated with risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, representing the largest sequencing-based analysis of miRNA expression in human islets to date. We characterize the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression (miRNA-eQTLs). We find (i) 81 heritable miRNAs, primarily regulated by trans-acting genetic effects, and (ii) 5 miRNA-eQTLs. We also use several different strategies to identify T2D-associated miRNAs. First, we colocalize miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersect miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and find 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we perform differential expression analysis and identify 13 miRNAs associated with T2D status--including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p--and 4 miRNAs associated with a polygenic score for HbA1c levels--miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.

genetics↗