Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Customizable high-throughput platform for profiling cofactor recruitment to DNA to characterize cis-regulatory elements and screen non-coding single-nucleotide polymorphisms

David Bray, Heather Hook, Rose Zhao, Jessica L. Keenan, Ashley Penvose, Yemi Osayame, Nima Mohaghegh, Trevor Siggers
doi: https://doi.org/10.1101/2020.04.21.053710
David Bray
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
3Bioinformatics Program, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Heather Hook
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rose Zhao
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jessica L. Keenan
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
3Bioinformatics Program, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ashley Penvose
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yemi Osayame
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nima Mohaghegh
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Trevor Siggers
1Department of Biology, Boston University, MA, USA
2Biological Design Center, Boston University, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: tsiggers@bu.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

Determining how DNA variants affect the binding of regulatory complexes to cis-regulatory elements (CREs) and non-coding single-nucleotide polymorphisms (ncSNPs) is a challenge in genomics. To address this challenge, we have developed CASCADE (Comprehensive ASsessment of Complex Assembly at DNA Elements), which is a protein-binding microarray (PBM)-based approach that allows for the high-throughput profiling of cofactor (COF) recruitment to DNA sequence variants. The method also enables one to infer the identity of the transcription factor-cofactor (TF-COF) complexes involved in COF recruitment. We use CASCADE to characterize regulatory complexes binding to CREs and SNP quantitative trait loci (SNP-QTLs) in resting and stimulated human macrophages. By profiling the recruitment of the acetyltransferase p300 and MLL methyltransferase component RBBP5, we identify key regulators of the chemokine CXCL10, and by profiling a set of five functionally diverse COFs we identify a prevalence of ETS sites mediating COF recruitment at SNP-QTLs in macrophages. Our results demonstrate that CASCADE is a customizable, high-throughput platform to link DNA variants with the biophysical complexes that mediate functions such as chromatin modification or remodeling in a cell state-specific manner.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148945

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 22, 2020.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Customizable high-throughput platform for profiling cofactor recruitment to DNA to characterize cis-regulatory elements and screen non-coding single-nucleotide polymorphisms
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Customizable high-throughput platform for profiling cofactor recruitment to DNA to characterize cis-regulatory elements and screen non-coding single-nucleotide polymorphisms
David Bray, Heather Hook, Rose Zhao, Jessica L. Keenan, Ashley Penvose, Yemi Osayame, Nima Mohaghegh, Trevor Siggers
bioRxiv 2020.04.21.053710; doi: https://doi.org/10.1101/2020.04.21.053710
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Customizable high-throughput platform for profiling cofactor recruitment to DNA to characterize cis-regulatory elements and screen non-coding single-nucleotide polymorphisms
David Bray, Heather Hook, Rose Zhao, Jessica L. Keenan, Ashley Penvose, Yemi Osayame, Nima Mohaghegh, Trevor Siggers
bioRxiv 2020.04.21.053710; doi: https://doi.org/10.1101/2020.04.21.053710

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4086)
  • Biochemistry (8761)
  • Bioengineering (6479)
  • Bioinformatics (23339)
  • Biophysics (11750)
  • Cancer Biology (9149)
  • Cell Biology (13247)
  • Clinical Trials (138)
  • Developmental Biology (7416)
  • Ecology (11369)
  • Epidemiology (2066)
  • Evolutionary Biology (15087)
  • Genetics (10398)
  • Genomics (14009)
  • Immunology (9121)
  • Microbiology (22040)
  • Molecular Biology (8779)
  • Neuroscience (47366)
  • Paleontology (350)
  • Pathology (1420)
  • Pharmacology and Toxicology (2482)
  • Physiology (3704)
  • Plant Biology (8050)
  • Scientific Communication and Education (1431)
  • Synthetic Biology (2208)
  • Systems Biology (6016)
  • Zoology (1249)