Less-is-more: selecting transcription factor binding regions informative for motif inference.
Nucleic Acids Res
; 52(4): e20, 2024 Feb 28.
Article
em En
| MEDLINE
| ID: mdl-38214231
ABSTRACT
Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Fatores de Transcrição
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Genômica
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Motivos de Nucleotídeos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article