Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution
- McGill University, Canada
- McGill University and Genome Quebec Innovation Centre, Canada
- McGill University and Génome Québec Innovation Centre, Canada
Abstract
Myofibers are the main components of skeletal muscle, which is the largest tissue in the body. Myofibers are highly adaptive and can be altered under different biological and disease conditions. Therefore, transcriptional and epigenetic studies on myofibers are crucial to discover how chromatin alterations occur in the skeletal muscle under different conditions. However, due to the heterogenous nature of skeletal muscle, studying myofibers in isolation proves to be a challenging task. Single cell sequencing has permitted the study of the epigenome of isolated myonuclei. While this provides sequencing with high dimensionality, the sequencing depth is lacking, which makes comparisons between different biological conditions difficult. Here we report the first implementation of single myofiber ATAC-Seq, which allows for the sequencing of an individual myofiber at a depth sufficient for peak calling and for comparative analysis of chromatin accessibility under various physiological and disease conditions. Application of this technique revealed significant differences in chromatin accessibility between resting and regenerating myofibers, as well as between myofibers from a mouse model of Duchenne Muscular Dystrophy (mdx) and wild type (WT) counterparts. This technique can lead to a wide application in the identification of chromatin regulatory elements and epigenetic mechanisms in muscle fibers during development and in muscle-wasting diseases.
Data availability
The data discussed in this study have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession numbers GSE173676 and GSE171534
-
ATAC-Seq of single myofibersNCBI Gene Expression Omnibus, GSE173676.
-
ATAC-Seq of young and aged satellite cellsNCBI Gene Expression Omnibus, GSE171534.
Article and author information
Author details
Funding
Natural Sciences and Engineering Research Council of Canada
- Vahab D Soleimani
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- YM Dennis Lo, The Chinese University of Hong Kong, Hong Kong
Ethics
Animal experimentation: All procedures that were performed on animals were approved by the McGill University Animal Care Committee (UACC), protocol #7512
Version history
- Preprint posted: June 15, 2021 (view preprint)
- Received: August 4, 2021
- Accepted: February 9, 2022
- Accepted Manuscript published: February 21, 2022 (version 1)
- Version of Record published: March 7, 2022 (version 2)
Copyright
© 2022, Sahinyan et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,842
- views
-
- 509
- downloads
-
- 13
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution
eLife 11:e72792.
https://doi.org/10.7554/eLife.72792
Further reading
-
- Genetics and Genomics
LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.
-
- Evolutionary Biology
- Genetics and Genomics
Copy number variation in large gene families is well characterized for plant resistance genes, but similar studies are rare in animals. The zebrafish (Danio rerio) has hundreds of NLR immune genes, making this species ideal for studying this phenomenon. By sequencing 93 zebrafish from multiple wild and laboratory populations, we identified a total of 1513 NLRs, many more than the previously known 400. Approximately half of those are present in all wild populations, but only 4% were found in 80% or more of the individual fish. Wild fish have up to two times as many NLRs per individual and up to four times as many NLRs per population than laboratory strains. In contrast to the massive variability of gene copies, nucleotide diversity in zebrafish NLR genes is very low: around half of the copies are monomorphic and the remaining ones have very few polymorphisms, likely a signature of purifying selection.
