Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet

Simple item page
dc.article.number11
dc.catalogadorpau
dc.contributor.authorViner, Coby
dc.contributor.authorIshak, Charles A.
dc.contributor.authorJohnson, James
dc.contributor.authorWalker, Nicolas J.
dc.contributor.authorShi, Hui
dc.contributor.authorSjoberg, Marcela K.
dc.contributor.authorShen, Shu Yi
dc.contributor.authorLardo, Santana M.
dc.contributor.authorAdams, David J.
dc.contributor.authorFerguson-Smith, Anne C.
dc.contributor.authorDe Carvalho, Daniel D.
dc.contributor.authorHainer, Sarah J.
dc.contributor.authorBailey, Timothy L.
dc.contributor.authorHoffman, Michael M.
dc.date.accessioned2024-01-29T15:00:28Z
dc.date.available2024-01-29T15:00:28Z
dc.date.issued2024
dc.date.updated2024-01-14T01:02:45Z
dc.description.abstractBackground: Transcription factors bind DNA in specific sequence contexts. In addition to distinguishing one nucleobase from another, some transcription factors can distinguish between unmodified and modified bases. Current models of transcription factor binding tend not to take DNA modifications into account, while the recent few that do often have limitations. This makes a comprehensive and accurate profiling of transcription factor affinities difficult. Results: Here, we develop methods to identify transcription factor binding sites in modified DNA. Our models expand the standard A/C/G/T DNA alphabet to include cytosine modifications. We develop Cytomod to create modified genomic sequences and we also enhance the MEME Suite, adding the capacity to handle custom alphabets. We adapt the well-established position weight matrix (PWM) model of transcription factor binding affinity to this expanded DNA alphabet. Using these methods, we identify modification-sensitive transcription factor binding motifs. We confirm established binding preferences, such as the preference of ZFP57 and C/EBPβ for methylated motifs and the preference of c-Myc for unmethylated E-box motifs. Conclusions: Using known binding preferences to tune model parameters, we discover novel modified motifs for a wide array of transcription factors. Finally, we validate our binding preference predictions for OCT4 using cleavage under targets and release using nuclease (CUT&RUN) experiments across conventional, methylation-, and hydroxymethylation-enriched sequences. Our approach readily extends to other DNA modifications. As more genome-wide single-base resolution modification data becomes available, we expect that our method will yield insights into altered transcription factor binding affinities across many different modifications.
dc.fechaingreso.objetodigital2024-01-29
dc.format.extent46 páginas
dc.identifier.citationGenome Biology. 2024 Jan 08;25(1):11
dc.identifier.urihttps://doi.org/10.1186/s13059-023-03070-0
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/81000
dc.information.autorucFacultad de Ciencias Biológicas; Sjoberg, Marcela K.; 0000-0001-7173-048X; 1040445
dc.language.isoen
dc.language.rfc3066en
dc.nota.accesoContenido completo
dc.revistaGenome Biology
dc.rightsacceso abierto
dc.rights.holderThe Author(s)
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.titleModeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet
dc.typeartículo
dc.volumen25
sipa.codpersvinculados1040445
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
13059_2023_Article_3070.pdf
Size:
6.32 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.98 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Artículos de revistas