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Emfinger, C. H.

Publications and source records attributed to Emfinger, C. H..

3 recordsLinked to original sources

Distinct genetic architecture of gene and isoform level QTL in the Diversity Outbred (DO) mouse population

Genetic association studies of mRNA abundance phenotypes link regulatory gene loci to mRNA abundance (quantitative trait loci; QTL). Here, we used liver RNA-seq data from a large cohort of the Diversity Outbred (DO) mouse population to map QTL for gene abundance (eQTL), isoform abundance (isoQTL), isoform ratios (irQTL), and splicing (sQTL). QTL studies using this heterogeneous mouse population have been limited to gene-level abundance of mRNAs and have not focused on mRNA isoforms or splicing. We show for the first time that genetic effects on expression are distinct from splicing in the DO mouse population. Using allele-effect patterns from local QTL for protein-coding gene-isoform pairs, we show that genetic variation drives allele-specific isoform usage, generating isoforms whose genetic signals diverge from their aggregated gene-level effects. We conducted pathway enrichment on distal eQTL and isoQTL hotspots and uncovered pathways not detected with eQTL. We then applied a composite mediation approach at these distal hotspots that compares gene-gene, isoform-isoform, and isoform-gene mediator models. By contrasting these causal models of transcriptional regulation, we identified unique associations between mRNA isoforms. We identified candidate genes at irQTL and sQTL hotspots that regulate mRNAs primarily through isoform usage and splicing, including Alkbh1 and Dicer1. For these driver genes, we nominated novel candidate targets through mediation analysis and pathway associations with known RNA-binding targets. We integrated our QTL data with human genetic data, prioritizing effector genes in loci associated with metabolically relevant traits. Our data also suggest that sex and diet influence eQTL and isoQTL distinctly and primarily through distal-acting gene loci. Overall, our findings highlight distinctive genetic effects on transcriptional and post-transcriptional mechanisms of gene regulation.

genetics↗

Target deconvolution of an insulin hypersecretion-inducer acting through VDAC1 with a distinct transcriptomic signature in beta-cells

Obesity, insulin resistance, and a host of environmental and genetic factors can drive hyperglycemia, causing {beta}-cells to compensate by increasing insulin production and secretion. In type 2 diabetes (T2D), {beta}-cells under these conditions eventually fail. Rare {beta}-cell diseases like congenital hyperinsulinism (HI) also cause inappropriate insulin secretion, and some HI patients develop diabetes. However, the mechanisms of insulin hypersecretion and how it causes {beta}-cell dysfunction are not fully understood. We previously discovered small molecules (e.g. SW016789) that cause insulin hypersecretion and lead to a loss in {beta}-cell function without cell death. Here, we uncover the protein target of SW016789 and provide the first time-course transcriptomic analysis of hypersecretory responses versus thapsigargin-mediated ER stress in {beta}-cells. In mouse MIN6 and human EndoC-{beta}H1 {beta}-cells, we identified and validated VDAC1 as a SW016789 target using photoaffinity proteomics, cellular thermal shift assays, siRNA, and small molecule inhibitors. SW016789 raises membrane potential to enhance Ca2+ influx, potentially through VDAC1. Chronically elevated intracellular Ca2+ appears to underpin the negative impacts of hypersecretion, as nifedipine protected against each small molecule hypersecretion inducer we tested. Using time- course RNAseq, we discovered that hypersecretion induced a distinct transcriptional pattern compared to ER stress. Clustering analyses led us to focus on ER-associated degradation (ERAD) as a potential mediator of the adaptive response. SW016789 reduced the abundance of ERAD substrate OS-9 and pharmacological inhibition of ERAD worsened {beta}-cell survival in response to hypersecretory stress. Changes in other ERAD components in MIN6 and EndoC-{beta}H1 at the protein level were minor with either SW016789 or thapsigargin. However, immunostaining for core ERAD components SEL1L, HRD1, and DERL3 in non-diabetic and T2D human pancreas revealed altered distributions of SEL1L/HRD1 and SEL1L/DERL3 rations in {beta}-cells of T2D islets, in alignment with altered ERAD in stressed {beta}-cells. We conclude that hypersecretory stimuli, including SW016789- mediated VDAC1 activation, cause enhanced Ca2+ influx and insulin release. Subsequent differential gene expression represents a {beta}-cell hypersecretory response signature that is reflected at the protein level for some, but not all genes. A better understanding of how {beta}-cells induce hypersecretion and the mechanisms of negative feedback on secretory rate may lead to the discovery of novel therapeutic targets for T2D and HI.

cell biology↗

Identification of genetic drivers of plasma lipoproteins in the Diversity Outbred mouse population

Despite great progress in understanding lipoprotein physiology, there is still much to be learned about the genetic drivers of lipoprotein abundance, composition, and function. We used ion mobility spectrometry to survey 16 plasma lipoprotein subfractions in 500 Diversity Outbred (DO) mice maintained on a Western-style diet. We identified 21 quantitative trait loci (QTL) affecting lipoprotein abundance. To refine the QTL and link them to disease risk in humans, we asked if the human homologues of genes located at each QTL were associated with lipid traits in human genome-wide association studies (GWAS). Integration of mouse QTL with human GWAS yielded candidate gene drivers for 18 of the 21 QTL. This approach enabled us to nominate the gene encoding the neutral ceramidase, Asah2, as a novel candidate driver at a QTL on chromosome 19 for large HDL particles (HDL-2b). To experimentally validate Asah2, we surveyed lipoproteins in Asah2-/-mice. Compared to wild-type mice, female Asah2-/- mice showed an increase in several lipoproteins, including HDL. Our results provide insights into the genetic regulation of circulating lipoproteins, as well as mechanisms by which lipoprotein subfractions may affect cardiovascular disease risk in humans.

genetics↗