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A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs
GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition...
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/PMC7334201/ https://www.ncbi.nlm.nih.gov/pubmed/32620845 http://dx.doi.org/10.1038/s41467-020-17159-8 |
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author | Zhao, Yihan Wu, Di Jiang, Danli Zhang, Xiaoyu Wu, Ting Cui, Jing Qian, Min Zhao, Jean Oesterreich, Steffi Sun, Wei Finkel, Toren Li, Gang |
author_facet | Zhao, Yihan Wu, Di Jiang, Danli Zhang, Xiaoyu Wu, Ting Cui, Jing Qian, Min Zhao, Jean Oesterreich, Steffi Sun, Wei Finkel, Toren Li, Gang |
author_sort | Zhao, Yihan |
collection | PubMed |
description | GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information. |
format | Online Article Text |
id | pubmed-7334201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73342012020-07-09 A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs Zhao, Yihan Wu, Di Jiang, Danli Zhang, Xiaoyu Wu, Ting Cui, Jing Qian, Min Zhao, Jean Oesterreich, Steffi Sun, Wei Finkel, Toren Li, Gang Nat Commun Article GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information. Nature Publishing Group UK 2020-07-03 /pmc/articles/PMC7334201/ /pubmed/32620845 http://dx.doi.org/10.1038/s41467-020-17159-8 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 Zhao, Yihan Wu, Di Jiang, Danli Zhang, Xiaoyu Wu, Ting Cui, Jing Qian, Min Zhao, Jean Oesterreich, Steffi Sun, Wei Finkel, Toren Li, Gang A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title | A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title_full | A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title_fullStr | A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title_full_unstemmed | A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title_short | A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs |
title_sort | sequential methodology for the rapid identification and characterization of breast cancer-associated functional snps |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334201/ https://www.ncbi.nlm.nih.gov/pubmed/32620845 http://dx.doi.org/10.1038/s41467-020-17159-8 |
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