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AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq
Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to profile protein-DNA interactions genome-wide. Restriction Enzyme-based Labeling of Chromatin in Situ (RELACS) is a recently developed ChIP-seq protocol that deploys a chromatin barcoding strategy to enable standardiz...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381599/ https://www.ncbi.nlm.nih.gov/pubmed/32709929 http://dx.doi.org/10.1038/s41598-020-69443-8 |
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author | Arrigoni, L. Ferrari, F. Weller, J. Bella, C. Bönisch, U. Manke, T. |
author_facet | Arrigoni, L. Ferrari, F. Weller, J. Bella, C. Bönisch, U. Manke, T. |
author_sort | Arrigoni, L. |
collection | PubMed |
description | Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to profile protein-DNA interactions genome-wide. Restriction Enzyme-based Labeling of Chromatin in Situ (RELACS) is a recently developed ChIP-seq protocol that deploys a chromatin barcoding strategy to enable standardized and high-throughput generation of ChIP-seq data. The manual implementation of RELACS is constrained by human processivity in both data generation and data analysis. To overcome these limitations, we have developed AutoRELACS, an automated implementation of the RELACS protocol using the liquid handler Biomek i7 workstation. We match the unprecedented processivity in data generation allowed by AutoRELACS with the automated computation pipelines offered by snakePipes. In doing so, we build a continuous workflow that streamlines epigenetic profiling, from sample collection to biological interpretation. Here, we show that AutoRELACS successfully automates chromatin barcode integration, and is able to generate high-quality ChIP-seq data comparable with the standards of the manual protocol, also for limited amounts of biological samples. |
format | Online Article Text |
id | pubmed-7381599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73815992020-07-28 AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq Arrigoni, L. Ferrari, F. Weller, J. Bella, C. Bönisch, U. Manke, T. Sci Rep Article Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to profile protein-DNA interactions genome-wide. Restriction Enzyme-based Labeling of Chromatin in Situ (RELACS) is a recently developed ChIP-seq protocol that deploys a chromatin barcoding strategy to enable standardized and high-throughput generation of ChIP-seq data. The manual implementation of RELACS is constrained by human processivity in both data generation and data analysis. To overcome these limitations, we have developed AutoRELACS, an automated implementation of the RELACS protocol using the liquid handler Biomek i7 workstation. We match the unprecedented processivity in data generation allowed by AutoRELACS with the automated computation pipelines offered by snakePipes. In doing so, we build a continuous workflow that streamlines epigenetic profiling, from sample collection to biological interpretation. Here, we show that AutoRELACS successfully automates chromatin barcode integration, and is able to generate high-quality ChIP-seq data comparable with the standards of the manual protocol, also for limited amounts of biological samples. Nature Publishing Group UK 2020-07-24 /pmc/articles/PMC7381599/ /pubmed/32709929 http://dx.doi.org/10.1038/s41598-020-69443-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Arrigoni, L. Ferrari, F. Weller, J. Bella, C. Bönisch, U. Manke, T. AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title | AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title_full | AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title_fullStr | AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title_full_unstemmed | AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title_short | AutoRELACS: automated generation and analysis of ultra-parallel ChIP-seq |
title_sort | autorelacs: automated generation and analysis of ultra-parallel chip-seq |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381599/ https://www.ncbi.nlm.nih.gov/pubmed/32709929 http://dx.doi.org/10.1038/s41598-020-69443-8 |
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