1
|
Salignon J, Millan-Ariño L, Garcia MU, Riedel CG. Cactus: A user-friendly and reproducible ATAC-Seq and mRNA-Seq analysis pipeline for data preprocessing, differential analysis, and enrichment analysis. Genomics 2024; 116:110858. [PMID: 38735595 DOI: 10.1016/j.ygeno.2024.110858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/14/2024]
Abstract
The ever decreasing cost of Next-Generation Sequencing coupled with the emergence of efficient and reproducible analysis pipelines has rendered genomic methods more accessible. However, downstream analyses are basic or missing in most workflows, creating a significant barrier for non-bioinformaticians. To help close this gap, we developed Cactus, an end-to-end pipeline for analyzing ATAC-Seq and mRNA-Seq data, either separately or jointly. Its Nextflow-, container-, and virtual environment-based architecture ensures efficient and reproducible analyses. Cactus preprocesses raw reads, conducts differential analyses between conditions, and performs enrichment analyses in various databases, including DNA-binding motifs, ChIP-Seq binding sites, chromatin states, and ontologies. We demonstrate the utility of Cactus in a multi-modal and multi-species case study as well as by showcasing its unique capabilities as compared to other ATAC-Seq pipelines. In conclusion, Cactus can assist researchers in gaining comprehensive insights from chromatin accessibility and gene expression data in a quick, user-friendly, and reproducible manner.
Collapse
Affiliation(s)
- Jérôme Salignon
- Department of Bioscience and Nutrition, Karolinska Institute, Blickagången 16, Huddinge SE-141 83, Sweden.
| | - Lluís Millan-Ariño
- Department of Bioscience and Nutrition, Karolinska Institute, Blickagången 16, Huddinge SE-141 83, Sweden
| | - Maxime U Garcia
- National Genomics Infrastructure, Science for Life Laboratory, Tomtebodavägen 23A, Solna SE-171 65, Sweden; Department of Oncology-Pathology, Karolinska Institute, Visionsgatan 4, Solna SE-171 64, Sweden
| | - Christian G Riedel
- Department of Bioscience and Nutrition, Karolinska Institute, Blickagången 16, Huddinge SE-141 83, Sweden.
| |
Collapse
|
2
|
Nair VD, Pincas H, Smith GR, Zaslavsky E, Ge Y, Amper MAS, Vasoya M, Chikina M, Sun Y, Raja AN, Mao W, Gay NR, Esser KA, Smith KS, Zhao B, Wiel L, Singh A, Lindholm ME, Amar D, Montgomery S, Snyder MP, Walsh MJ, Sealfon SC. Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures. CELL GENOMICS 2024:100421. [PMID: 38697122 DOI: 10.1016/j.xgen.2023.100421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/07/2023] [Accepted: 09/12/2023] [Indexed: 05/04/2024]
Abstract
Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.
Collapse
Affiliation(s)
- Venugopalan D Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hanna Pincas
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gregory R Smith
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Anne S Amper
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mital Vasoya
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maria Chikina
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yifei Sun
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Weiguang Mao
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicole R Gay
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Karyn A Esser
- Department of Physiology and Aging, University of Florida, Gainesville, FL 32610, USA
| | - Kevin S Smith
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Bingqing Zhao
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Laurens Wiel
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Aditya Singh
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Malene E Lindholm
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - David Amar
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Stephen Montgomery
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Martin J Walsh
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| |
Collapse
|
3
|
Smith GR, Zhao B, Lindholm ME, Raja A, Viggars M, Pincas H, Gay NR, Sun Y, Ge Y, Nair VD, Sanford JA, Amper MAS, Vasoya M, Smith KS, Montgomery S, Zaslavsky E, Bodine SC, Esser KA, Walsh MJ, Snyder MP. Multi-omic identification of key transcriptional regulatory programs during endurance exercise training. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.10.523450. [PMID: 36711841 PMCID: PMC9882056 DOI: 10.1101/2023.01.10.523450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Transcription factors (TFs) play a key role in regulating gene expression and responses to stimuli. We conducted an integrated analysis of chromatin accessibility, DNA methylation, and RNA expression across eight rat tissues following endurance exercise training (EET) to map epigenomic changes to transcriptional changes and determine key TFs involved. We uncovered tissue-specific changes and TF motif enrichment across all omic layers, differentially accessible regions (DARs), differentially methylated regions (DMRs), and differentially expressed genes (DEGs). We discovered distinct routes of EET-induced regulation through either epigenomic alterations providing better access for TFs to affect target genes, or via changes in TF expression or activity enabling target gene response. We identified TF motifs enriched among correlated epigenomic and transcriptomic alterations, DEGs correlated with exercise-related phenotypic changes, and EET-induced activity changes of TFs enriched for DEGs among their gene targets. This analysis elucidates the unique transcriptional regulatory mechanisms mediating diverse organ effects of EET.
Collapse
Affiliation(s)
- Gregory R Smith
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- These authors contributed equally
| | - Bingqing Zhao
- Department of Genetics, Stanford University, Stanford, CA 94305
- These authors contributed equally
| | - Malene E Lindholm
- Division of Cardiovascular Medicine, Stanford University, Stanford, CA 94305
| | - Archana Raja
- Division of Cardiovascular Medicine, Stanford University, Stanford, CA 94305
| | - Mark Viggars
- Department of Physiology and Aging, University of Florida, Gainesville, Florida 32610
| | - Hanna Pincas
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Nicole R Gay
- Department of Genetics, Stanford University, Stanford, CA 94305
| | - Yifei Sun
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Yongchao Ge
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Venugopalan D Nair
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - James A Sanford
- Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Mary Anne S Amper
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Mital Vasoya
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Kevin S Smith
- Department of Genetics, Stanford University, Stanford, CA 94305
- Department of Pathology, Stanford University, Stanford, CA 94305
| | - Stephen Montgomery
- Department of Genetics, Stanford University, Stanford, CA 94305
- Department of Pathology, Stanford University, Stanford, CA 94305
| | - Elena Zaslavsky
- Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Sue C Bodine
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Karyn A Esser
- Department of Physiology and Aging, University of Florida, Gainesville, Florida 32610
| | - Martin J Walsh
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | | |
Collapse
|
4
|
Fan H, Wang F, Zeng A, Murison A, Tomczak K, Hao D, Jelloul FZ, Wang B, Barrodia P, Liang S, Chen K, Wang L, Zhao Z, Rai K, Jain AK, Dick J, Daver N, Futreal A, Abbas HA. Single-cell chromatin accessibility profiling of acute myeloid leukemia reveals heterogeneous lineage composition upon therapy-resistance. Commun Biol 2023; 6:765. [PMID: 37479893 PMCID: PMC10362028 DOI: 10.1038/s42003-023-05120-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 07/07/2023] [Indexed: 07/23/2023] Open
Abstract
Acute myeloid leukemia (AML) is a heterogeneous disease characterized by high rate of therapy resistance. Since the cell of origin can impact response to therapy, it is crucial to understand the lineage composition of AML cells at time of therapy resistance. Here we leverage single-cell chromatin accessibility profiling of 22 AML bone marrow aspirates from eight patients at time of therapy resistance and following subsequent therapy to characterize their lineage landscape. Our findings reveal a complex lineage architecture of therapy-resistant AML cells that are primed for stem and progenitor lineages and spanning quiescent, activated and late stem cell/progenitor states. Remarkably, therapy-resistant AML cells are also composed of cells primed for differentiated myeloid, erythroid and even lymphoid lineages. The heterogeneous lineage composition persists following subsequent therapy, with early progenitor-driven features marking unfavorable prognosis in The Cancer Genome Atlas AML cohort. Pseudotime analysis further confirms the vast degree of heterogeneity driven by the dynamic changes in chromatin accessibility. Our findings suggest that therapy-resistant AML cells are characterized not only by stem and progenitor states, but also by a continuum of differentiated cellular lineages. The heterogeneity in lineages likely contributes to their therapy resistance by harboring different degrees of lineage-specific susceptibilities to therapy.
Collapse
Affiliation(s)
- Huihui Fan
- Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Feng Wang
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andy Zeng
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Alex Murison
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Katarzyna Tomczak
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dapeng Hao
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fatima Zahra Jelloul
- Department of Hematopathology, University of Texas M D Anderson Cancer Center, Houston, TX, USA
| | - Bofei Wang
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Praveen Barrodia
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shaoheng Liang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linghua Wang
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kunal Rai
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Abhinav K Jain
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - John Dick
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Naval Daver
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andy Futreal
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Hussein A Abbas
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
5
|
Xu Z, Wu J, Zhou J, Zhang Y, Qiao M, Sun H, Li Z, Li L, Chen N, Oyelami FO, Peng X, Mei S. Integration of ATAC-seq and RNA-seq analysis identifies key genes affecting intramuscular fat content in pigs. Front Nutr 2022; 9:1016956. [PMID: 36276837 PMCID: PMC9581296 DOI: 10.3389/fnut.2022.1016956] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/14/2022] [Indexed: 11/17/2022] Open
Abstract
Meat quality is one of the most important economic traits in pig breeding and production, and intramuscular fat (IMF) content is the major factor in improving meat quality. The IMF deposition in pigs is influenced by transcriptional regulation, which is dependent on chromatin accessibility. However, how chromatin accessibility plays a regulatory role in IMF deposition in pigs has not been reported. Xidu black is a composite pig breed with excellent meat quality, which is an ideal research object of this study. In this study, we used the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing (RNA-seq) analysis to identify the accessible chromatin regions and key genes affecting IMF content in Xidu black pig breed with extremely high and low IMF content. First, we identified 21,960 differential accessible chromatin peaks and 297 differentially expressed genes. The motif analysis of differential peaks revealed several potential cis-regulatory elements containing binding sites for transcription factors with potential roles in fat deposition, including Mef2c, CEBP, Fra1, and AP-1. Then, by integrating the ATAC-seq and RNA-seq analysis results, we found 47 genes in the extremely high IMF (IMF_H) group compared with the extremely low IMF (IMF_L) group. For these genes, we observed a significant positive correlation between the differential gene expression and differential ATAC-seq signal (r2 = 0.42). This suggests a causative relationship between chromatin remodeling and the resulting gene expression. We identified several candidate genes (PVALB, THRSP, HOXA9, EEPD1, HOXA10, and PDE4B) that might be associated with fat deposition. Through the PPI analysis, we found that PVALB gene was the top hub gene. In addition, some pathways that might regulate fat cell differentiation and lipid metabolism, such as the PI3K-Akt signaling pathway, MAPK signaling pathway, and calcium signaling pathway, were significantly enriched in the ATAC-seq and RNA-seq analysis. To the best of our knowledge, our study is the first to use ATAC-seq and RNA-seq to examine the mechanism of IMF deposition from a new perspective. Our results provide valuable information for understanding the regulation mechanism of IMF deposition and an important foundation for improving the quality of pork.
Collapse
Affiliation(s)
- Zhong Xu
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Junjing Wu
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Jiawei Zhou
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Yu Zhang
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Mu Qiao
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Hua Sun
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Zipeng Li
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Lianghua Li
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Nanqi Chen
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | | | - Xianwen Peng
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China,*Correspondence: Xianwen Peng,
| | - Shuqi Mei
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China,Shuqi Mei,
| |
Collapse
|
6
|
Kiani K, Sanford EM, Goyal Y, Raj A. Changes in chromatin accessibility are not concordant with transcriptional changes for single-factor perturbations. Mol Syst Biol 2022; 18:e10979. [PMID: 36069349 PMCID: PMC9450098 DOI: 10.15252/msb.202210979] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 08/11/2022] [Accepted: 08/19/2022] [Indexed: 11/23/2022] Open
Abstract
A major goal in the field of transcriptional regulation is the mapping of changes in the binding of transcription factors to the resultant changes in gene expression. Recently, methods for measuring chromatin accessibility have enabled us to measure changes in accessibility across the genome, which are thought to correspond to transcription factor‐binding events. In concert with RNA‐sequencing, these data in principle enable such mappings; however, few studies have looked at their concordance over short‐duration treatments with specific perturbations. Here, we used tandem, bulk ATAC‐seq, and RNA‐seq measurements from MCF‐7 breast carcinoma cells to systematically evaluate the concordance between changes in accessibility and changes in expression in response to retinoic acid and TGF‐β. We found two classes of genes whose expression showed a significant change: those that showed some changes in the accessibility of nearby chromatin, and those that showed virtually no change despite strong changes in expression. The peaks associated with genes in the former group had lower baseline accessibility prior to exposure to signal. Focusing the analysis specifically on peaks with motifs for transcription factors associated with retinoic acid and TGF‐β signaling did not reduce the lack of correspondence. Analysis of paired chromatin accessibility and gene expression data from distinct paths along the hematopoietic differentiation trajectory showed a much stronger correspondence, suggesting that the multifactorial biological processes associated with differentiation may lead to changes in chromatin accessibility that reflect rather than driving altered transcriptional status. Together, these results show many gene expression changes can happen independently of changes in the accessibility of local chromatin in the context of a single‐factor perturbation.
Collapse
Affiliation(s)
- Karun Kiani
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Eric M Sanford
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yogesh Goyal
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.,Center for Synthetic Biology, Northwestern University, Chicago, Illinois, USA
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| |
Collapse
|
7
|
Optimization of the Omni-ATAC protocol to chromatin accessibility profiling in snap-frozen rat adipose and muscle tissues. MethodsX 2022; 9:101681. [PMID: 35464805 PMCID: PMC9027329 DOI: 10.1016/j.mex.2022.101681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 03/22/2022] [Indexed: 01/11/2023] Open
Abstract
ATAC-seq is a fast and sensitive method for the epigenomic profiling of open chromatin and for mapping of transcription factor binding sites [1]. Despite the development of the Omni-ATAC protocol for the profiling of chromatin accessibility in frozen tissues [2], studies in adipose tissue have been restricted due to technical challenges including the high lipid content of adipocytes and reproducibility issues between replicates. Here, we provide a modified Omni-ATAC protocol that achieves high data reproducibility in various tissue types from rat, including adipose and muscle tissues [3].•This protocol describes a methodology that enables chromatin accessibility profiling from snap-frozen rat adipose and muscle tissues.•The technique comprises an optimized bead-based tissue homogenization process that substitutes to Dounce homogenization, reduces variability in the experimental procedure, and is adaptable to various tissue types.•In comparison with the Omni-ATAC protocol, the method described here results in improved ATAC-seq data quality that complies with ENCODE quality standards.
Collapse
|