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Biology subjects

Pazos, F.

Publications and source records attributed to Pazos, F..

2 recordsLinked to original sources

DIDO3 acts at the interface of RNAPII transcription and chromatin structure regulation

While chromatin structure influences gene expression, how chromatin readers exert transcriptional control is still not fully understood. DIDO3, an isoform of the Death Inducer Obliterator protein, has been implicated in cell differentiation and cancer, yet its precise genomic functions are unclear. Here we integrated ChIP-seq, RNA-seq and Hi-C analyses in mouse embryonic stem cells to reveal that DIDO3 predominantly binds to RNA polymerase II at topological domain boundaries and chromatin loops. We demonstrate that DIDO3 interacts with the architectural protein CTCF and that the N-terminal region of DIDO3 (DIDO31-528) also co-localizes with the histone marks H3K4me3 and H3K36me3. DIDO3 influences the expression of genes encoding chromatin remodeling components, as well as those involved in transcriptional dynamics and three-dimensional chromatin organization. These findings suggest that DIDO3 is associated with both transcriptional regulation and chromatin organization, with potential implications in terms of cell differentiation and tumorigenesis.

bioinformatics↗

Predicting biological pathways of chemical compounds with a profile-inspired aproach

Assignment of chemical compounds to biological pathways is a crucial step to understand the relationship between the chemical repertory of an organism and its biology. Protein sequence profiles are very successful in capturing the main structural and functional features of a protein family, and can be used to assign new members to it based on matching of their sequences against these profiles. In this work, we extend this idea to chemical compounds, constructing a profile-inspired model for a set of related metabolites (those in the same biological pathway), based on a fragment-based vectorial representation of their chemical structures. We use this representation to predict the biological pathway of a chemical compound with good overall accuracy (AUC 0.74-0.90 depending on the database tested), and analyzed some factors that affect performance. The approach, which is compared with equivalent methods, can in addition detect those molecular fragments characteristic of a pathway. The method is available as a graphical interactive web server http://csbg.cnb.csic.es/iFragMent

systems biology↗