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Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions

Background: Chromatin falls into one of two major subtypes: closed heterochromatin and euchromatin which is accessible, transcriptionally active, and occupied by transcription factors (TFs). The most widely used approach to interrogate differences in the chromatin state landscape is the Assay for Tr...

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Autores principales: Naval-Sanchez, Marina, Deshpande, Nikita, Tran, Minh, Zhang, Jingyu, Alhomrani, Majid, Alsanie, Walaa, Nguyen, Quan, Nefzger, Christian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302965/
https://www.ncbi.nlm.nih.gov/pubmed/35874611
http://dx.doi.org/10.3389/fmolb.2022.900323
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author Naval-Sanchez, Marina
Deshpande, Nikita
Tran, Minh
Zhang, Jingyu
Alhomrani, Majid
Alsanie, Walaa
Nguyen, Quan
Nefzger, Christian M.
author_facet Naval-Sanchez, Marina
Deshpande, Nikita
Tran, Minh
Zhang, Jingyu
Alhomrani, Majid
Alsanie, Walaa
Nguyen, Quan
Nefzger, Christian M.
author_sort Naval-Sanchez, Marina
collection PubMed
description Background: Chromatin falls into one of two major subtypes: closed heterochromatin and euchromatin which is accessible, transcriptionally active, and occupied by transcription factors (TFs). The most widely used approach to interrogate differences in the chromatin state landscape is the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). While library generation is relatively inexpensive, sequencing depth requirements can make this assay cost-prohibitive for some laboratories. Findings: Here, we benchmark data from Beijing Genomics Institute’s (BGI) DNBSEQ-G400 low-cost sequencer against data from a standard Illumina instrument (HiSeqX10). For comparisons, the same bulk ATAC-seq libraries generated from pluripotent stem cells (PSCs) and fibroblasts were sequenced on both platforms. Both instruments generate sequencing reads with comparable mapping rates and genomic context. However, DNBSEQ-G400 data contained a significantly higher number of small, sub-nucleosomal reads (>30% increase) and a reduced number of bi-nucleosomal reads (>75% decrease), which resulted in narrower peak bases and improved peak calling, enabling the identification of 4% more differentially accessible regions between PSCs and fibroblasts. The ability to identify master TFs that underpin the PSC state relative to fibroblasts (via HOMER, HINT-ATAC, TOBIAS), namely, foot-printing capacity, were highly similar between data generated on both platforms. Integrative analysis with transcriptional data equally enabled direct recovery of three published 3-factor combinations that have been shown to induce pluripotency. Conclusion: Other than a small increase in peak calling sensitivity for DNBSEQ-G400 data (BGI), both platforms enable comparable levels of open chromatin identification for ATAC-seq library sequencing, yielding similar analytical outcomes, albeit at low-data generation costs in the case of the BGI instrument.
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spelling pubmed-93029652022-07-22 Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions Naval-Sanchez, Marina Deshpande, Nikita Tran, Minh Zhang, Jingyu Alhomrani, Majid Alsanie, Walaa Nguyen, Quan Nefzger, Christian M. Front Mol Biosci Molecular Biosciences Background: Chromatin falls into one of two major subtypes: closed heterochromatin and euchromatin which is accessible, transcriptionally active, and occupied by transcription factors (TFs). The most widely used approach to interrogate differences in the chromatin state landscape is the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). While library generation is relatively inexpensive, sequencing depth requirements can make this assay cost-prohibitive for some laboratories. Findings: Here, we benchmark data from Beijing Genomics Institute’s (BGI) DNBSEQ-G400 low-cost sequencer against data from a standard Illumina instrument (HiSeqX10). For comparisons, the same bulk ATAC-seq libraries generated from pluripotent stem cells (PSCs) and fibroblasts were sequenced on both platforms. Both instruments generate sequencing reads with comparable mapping rates and genomic context. However, DNBSEQ-G400 data contained a significantly higher number of small, sub-nucleosomal reads (>30% increase) and a reduced number of bi-nucleosomal reads (>75% decrease), which resulted in narrower peak bases and improved peak calling, enabling the identification of 4% more differentially accessible regions between PSCs and fibroblasts. The ability to identify master TFs that underpin the PSC state relative to fibroblasts (via HOMER, HINT-ATAC, TOBIAS), namely, foot-printing capacity, were highly similar between data generated on both platforms. Integrative analysis with transcriptional data equally enabled direct recovery of three published 3-factor combinations that have been shown to induce pluripotency. Conclusion: Other than a small increase in peak calling sensitivity for DNBSEQ-G400 data (BGI), both platforms enable comparable levels of open chromatin identification for ATAC-seq library sequencing, yielding similar analytical outcomes, albeit at low-data generation costs in the case of the BGI instrument. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9302965/ /pubmed/35874611 http://dx.doi.org/10.3389/fmolb.2022.900323 Text en Copyright © 2022 Naval-Sanchez, Deshpande, Tran, Zhang, Alhomrani, Alsanie, Nguyen and Nefzger. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Naval-Sanchez, Marina
Deshpande, Nikita
Tran, Minh
Zhang, Jingyu
Alhomrani, Majid
Alsanie, Walaa
Nguyen, Quan
Nefzger, Christian M.
Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title_full Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title_fullStr Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title_full_unstemmed Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title_short Benchmarking of ATAC Sequencing Data From BGI’s Low-Cost DNBSEQ-G400 Instrument for Identification of Open and Occupied Chromatin Regions
title_sort benchmarking of atac sequencing data from bgi’s low-cost dnbseq-g400 instrument for identification of open and occupied chromatin regions
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302965/
https://www.ncbi.nlm.nih.gov/pubmed/35874611
http://dx.doi.org/10.3389/fmolb.2022.900323
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