Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits.

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.

Effects of tRNA modification on translational accuracy depend on intrinsic codon-anticodon strength.

Cellular health and growth requires protein synthesis to be both efficient to ensure sufficient production, and accurate to avoid producing defective or unstable proteins. The background of misreading error frequency by individual tRNAs is as low as 2 × 10(-6) per codon but is codon-specific with some error frequencies above 10(-3) per codon. Here we test the effect on error frequency of blocking post-transcriptional modifications of the anticodon loops of four tRNAs in Escherichia coli. We find two types of responses to removing modification. Blocking modification of tRNA(UUC)(Glu) and tRNA(QUC)(Asp) increases errors, suggesting that the modifications act at least in part to maintain accuracy. Blocking even identical modifications of tRNA(UUU)(Lys) and tRNA(QUA)(Tyr) has the opposite effect of decreasing errors. One explanation could be that the modifications play opposite roles in modulating misreading by the two classes of tRNAs. Given available evidence that modifications help preorder the anticodon to allow it to recognize the codons, however, the simpler explanation is that unmodified 'weak' tRNAs decode too inefficiently to compete against cognate tRNAs that normally decode target codons, which would reduce the frequency of misreading.

Studies of translational misreading in vivo show that the ribosome very efficiently discriminates against most potential errors.

Protein synthesis must rapidly and repeatedly discriminate between a single correct and many incorrect aminoacyl-tRNAs. We have attempted to measure the frequencies of all possible missense errors by tRNA , tRNA and tRNA . The most frequent errors involve three types of mismatched nucleotide pairs, U•U, U•C, or U•G, all of which can form a noncanonical base pair with geometry similar to that of the canonical U•A or C•G Watson-Crick pairs. Our system is sensitive enough to measure errors at other potential mismatches that occur at frequencies as low as 1 in 500,000 codons. The ribosome appears to discriminate this efficiently against any pair with non-Watson-Crick geometry. This extreme accuracy may be necessary to allow discrimination against the errors involving near Watson-Crick pairing.

An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals.

Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased ß cell apoptosis. Additionally, pancreatic ß cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased ß cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- ß-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived ß-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.

Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation.

Skeletal muscle, the largest human organ by weight, is relevant to several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing the relevant cell types, regulatory elements, target genes, and causal variants. Here, we used genetic multiplexing to generate population-scale single nucleus (sn) chromatin accessibility (snATAC-seq) and transcriptome (snRNA-seq) maps across 287 frozen human skeletal muscle biopsies representing 456,880 nuclei. We identified 13 cell types that collectively represented 983,155 ATAC summits. We integrated genetic variation to discover 6,866 expression quantitative trait loci (eQTL) and 100,928 chromatin accessibility QTL (caQTL) (5% FDR) across the five most abundant cell types, cataloging caQTL peaks that atlas-level snATAC maps often miss. We identified 1,973 eGenes colocalized with caQTL and used mediation analyses to construct causal directional maps for chromatin accessibility and gene expression. 3,378 genome-wide association study (GWAS) signals across 43 relevant traits colocalized with sn-e/caQTL, 52% in a cell-specific manner. 77% of GWAS signals colocalized with caQTL and not eQTL, highlighting the critical importance of population-scale chromatin profiling for GWAS functional studies. GWAS-caQTL colocalization showed distinct cell-specific regulatory paradigms. For example, a C2CD4A/B T2D GWAS signal colocalized with caQTL in muscle fibers and multiple chromatin loop models nominated VPS13C, a glucose uptake gene. Sequence of the caQTL peak overlapping caSNP rs7163757 showed allelic regulatory activity differences in a human myocyte cell line massively parallel reporter assay. These results illuminate the genetic regulatory architecture of human skeletal muscle at high-resolution epigenomic, transcriptomic, and cell state scales and serve as a template for population-scale multi-omic mapping in complex tissues and traits.

Disulfide Mispairing During Proinsulin Folding in the Endoplasmic Reticulum.

Proinsulin folding within the endoplasmic reticulum (ER) remains incompletely understood, but it is clear that in mutant INS gene-induced diabetes of youth (MIDY), progression of the (three) native disulfide bonds of proinsulin becomes derailed, causing insulin deficiency, ß-cell ER stress, and onset of diabetes. Herein, we have undertaken a molecular dissection of proinsulin disulfide bond formation, using bioengineered proinsulins that can form only two (or even only one) of the native proinsulin disulfide bonds. In the absence of preexisting proinsulin disulfide pairing, Cys(B19)-Cys(A20) (a major determinant of ER stress response activation and proinsulin stability) preferentially initiates B-A chain disulfide bond formation, whereas Cys(B7)-Cys(A7) can initiate only under oxidizing conditions beyond that existing within the ER of ß-cells. Interestingly, formation of these two "interchain" disulfide bonds demonstrates cooperativity, and together, they are sufficient to confer intracellular transport competence to proinsulin. The three most common proinsulin disulfide mispairings in the ER appear to involve Cys(A11)-Cys(A20), Cys(A7)-Cys(A20), and Cys(B19)-Cys(A11), each disrupting the critical Cys(B19)-Cys(A20) pairing. MIDY mutations inhibit Cys(B19)-Cys(A20) formation, but treatment to force oxidation of this disulfide bond improves folding and results in a small but detectable increase of proinsulin export. These data suggest possible therapeutic avenues to ameliorate ER stress and diabetes.

PDI reductase acts on Akita mutant proinsulin to initiate retrotranslocation along the Hrd1/Sel1L-p97 axis.

In mutant INS gene-induced diabetes of youth (MIDY), characterized by insulin deficiency, MIDY proinsulin mutants misfold and fail to exit the endoplasmic reticulum (ER). Moreover, these mutants bind and block ER exit of wild-type (WT) proinsulin, inhibiting insulin production. The ultimate fate of ER-entrapped MIDY mutants is unclear, but previous studies implicated ER-associated degradation (ERAD), a pathway that retrotranslocates misfolded ER proteins to the cytosol for proteasomal degradation. Here we establish key ERAD machinery components used to triage the Akita proinsulin mutant, including the Hrd1-Sel1L membrane complex, which conducts Akita proinsulin from the ER lumen to the cytosol, and the p97 ATPase, which couples the cytosolic arrival of proinsulin with its proteasomal degradation. Surprisingly, we find that protein disulfide isomerase (PDI), the major protein oxidase of the ER lumen, engages Akita proinsulin in a novel way, reducing proinsulin disulfide bonds and priming the Akita protein for ERAD. Efficient PDI engagement of Akita proinsulin appears linked to the availability of Hrd1, suggesting that retrotranslocation is coordinated on the lumenal side of the ER membrane. We believe that, in principle, this form of diabetes could be alleviated by enhancing the targeting of MIDY mutants for ERAD to restore WT insulin production.