A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package

Victor Levitsky, Elena Zemlyanskaya, Dmitry Oshchepkov, Olga Podkolodnaya, Elena Ignatieva, Ivo Grosse, Victoria Mironova, Tatyana Merkulova

Результат исследования: Научные публикации в периодических изданияхстатья

5 Цитирования (Scopus)

Аннотация

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'.

Язык оригиналаанглийский
Страницы (с-по)e139
Число страниц14
ЖурналNucleic Acids Research
Том47
Номер выпуска21
DOI
СостояниеОпубликовано - 2 дек 2019

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