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Orchard P, Manickam N, Ventresca C, et al. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021;doi: 10.1101/gr.268482.120.
Orchard, P., Manickam, N., Ventresca, C., Vadlamudi, S., Varshney, A., Rai, V., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., Burant, C. F., & Parker, S. C. J. (2021). Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome research, . https://doi.org/10.1101/gr.268482.120
Orchard, Peter, et al. "Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits." Genome research vol. (2021). doi: https://doi.org/10.1101/gr.268482.120
Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23. PMID: 34815310; PMCID: PMC8647829.
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Genome Res. 2021 Nov 23; doi: 10.1101/gr.268482.120. Epub 2021 Nov 23.

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

Genome research

Peter Orchard, Nandini Manickam, Christa Ventresca, Swarooparani Vadlamudi, Arushi Varshney, Vivek Rai, Jeremy Kaplan, Claudia Lalancette, Karen L Mohlke, Katherine Gallagher, Charles F Burant, Stephen C J Parker

Affiliations

  1. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA.
  2. Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA.
  3. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.
  4. Epigenomics Core, University of Michigan, Ann Arbor, Michigan 48109, USA.
  5. Department of Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA.
  6. Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA.
  7. Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA.
  8. Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.

PMID: 34815310 PMCID: PMC8647829 DOI: 10.1101/gr.268482.120

Abstract

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.

© 2021 Orchard et al.; Published by Cold Spring Harbor Laboratory Press.

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