Research output: Contribution to journal › Article › peer-review
A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package. / Levitsky, Victor; Zemlyanskaya, Elena; Oshchepkov, Dmitry et al.
In: Nucleic Acids Research, Vol. 47, No. 21, 02.12.2019, p. e139.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package
AU - Levitsky, Victor
AU - Zemlyanskaya, Elena
AU - Oshchepkov, Dmitry
AU - Podkolodnaya, Olga
AU - Ignatieva, Elena
AU - Grosse, Ivo
AU - Mironova, Victoria
AU - Merkulova, Tatyana
N1 - Publisher Copyright: © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. Copyright: This record is sourced from MEDLINE/PubMed, a database of the U.S. National Library of Medicine © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2019/12/2
Y1 - 2019/12/2
N2 - Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.
AB - Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.
KW - Algorithms
KW - Animals
KW - Binding Sites
KW - Chromatin Immunoprecipitation Sequencing/methods
KW - Computational Biology/methods
KW - Datasets as Topic
KW - Humans
KW - Mice
KW - Nucleotide Motifs/genetics
KW - Regulatory Elements, Transcriptional/genetics
KW - Sequence Analysis, DNA/methods
KW - Transcription Factors/genetics
KW - TRANSCRIPTION FACTORS
KW - ACTIVATION
KW - DNA-BINDING
KW - CHROMATIN
KW - COMPLEXES
KW - COMPOSITE REGULATORY ELEMENTS
KW - ENHANCERS
KW - DISCOVERY
KW - REGIONS
KW - NF-KAPPA-B
UR - http://www.scopus.com/inward/record.url?scp=85075326742&partnerID=8YFLogxK
U2 - 10.1093/nar/gkz800
DO - 10.1093/nar/gkz800
M3 - Article
C2 - 31750523
AN - SCOPUS:85075326742
VL - 47
SP - e139
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - 21
ER -
ID: 26207675