Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.

Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and mu...

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Main Authors: Kristian Ovaska, Filomena Matarese, Korbinian Grote, Iryna Charapitsa, Alejandra Cervera, Chengyu Liu, George Reid, Martin Seifert, Hendrik G Stunnenberg, Sampsa Hautaniemi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3688481?pdf=render
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spelling doaj-0e84788c4dd94d04b5fec045a77ecd662020-11-24T21:55:35ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582013-01-0196e100310010.1371/journal.pcbi.1003100Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.Kristian OvaskaFilomena MatareseKorbinian GroteIryna CharapitsaAlejandra CerveraChengyu LiuGeorge ReidMartin SeifertHendrik G StunnenbergSampsa HautaniemiIdentification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and multi-level deep sequencing data. To answer this need we introduce here a data-driven algorithm, SPINLONG, which is designed to search for genes that match the user-defined hypotheses or models. SPINLONG is applicable to various experimental setups measuring several molecular markers in parallel. To demonstrate the SPINLONG approach, we analyzed ChIP-seq data reporting PolII, estrogen receptor α (ERα), H3K4me3 and H2A.Z occupancy at five time points in the MCF-7 breast cancer cell line after estradiol stimulus. We obtained 777 ERa early responsive genes and compared the biological functions of the genes having ERα binding within 20 kb of the transcription start site (TSS) to genes without such binding site. Our results show that the non-genomic action of ERα via the MAPK pathway, instead of direct ERa binding, may be responsible for early cell responses to ERα activation. Our results also indicate that the ERα responsive genes triggered by the genomic pathway are transcribed faster than those without ERα binding sites. The survival analysis of the 777 ERα responsive genes with 150 primary breast cancer tumors and in two independent validation cohorts indicated the ATAD3B gene, which does not have ERα binding site within 20 kb of its TSS, to be significantly associated with poor patient survival.http://europepmc.org/articles/PMC3688481?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Kristian Ovaska
Filomena Matarese
Korbinian Grote
Iryna Charapitsa
Alejandra Cervera
Chengyu Liu
George Reid
Martin Seifert
Hendrik G Stunnenberg
Sampsa Hautaniemi
spellingShingle Kristian Ovaska
Filomena Matarese
Korbinian Grote
Iryna Charapitsa
Alejandra Cervera
Chengyu Liu
George Reid
Martin Seifert
Hendrik G Stunnenberg
Sampsa Hautaniemi
Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
PLoS Computational Biology
author_facet Kristian Ovaska
Filomena Matarese
Korbinian Grote
Iryna Charapitsa
Alejandra Cervera
Chengyu Liu
George Reid
Martin Seifert
Hendrik G Stunnenberg
Sampsa Hautaniemi
author_sort Kristian Ovaska
title Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
title_short Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
title_full Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
title_fullStr Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
title_full_unstemmed Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
title_sort integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links atad3b to poor survival in breast cancer.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2013-01-01
description Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and multi-level deep sequencing data. To answer this need we introduce here a data-driven algorithm, SPINLONG, which is designed to search for genes that match the user-defined hypotheses or models. SPINLONG is applicable to various experimental setups measuring several molecular markers in parallel. To demonstrate the SPINLONG approach, we analyzed ChIP-seq data reporting PolII, estrogen receptor α (ERα), H3K4me3 and H2A.Z occupancy at five time points in the MCF-7 breast cancer cell line after estradiol stimulus. We obtained 777 ERa early responsive genes and compared the biological functions of the genes having ERα binding within 20 kb of the transcription start site (TSS) to genes without such binding site. Our results show that the non-genomic action of ERα via the MAPK pathway, instead of direct ERa binding, may be responsible for early cell responses to ERα activation. Our results also indicate that the ERα responsive genes triggered by the genomic pathway are transcribed faster than those without ERα binding sites. The survival analysis of the 777 ERα responsive genes with 150 primary breast cancer tumors and in two independent validation cohorts indicated the ATAD3B gene, which does not have ERα binding site within 20 kb of its TSS, to be significantly associated with poor patient survival.
url http://europepmc.org/articles/PMC3688481?pdf=render
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