Biology subjects

van der Velde, A. G.

Publications and source records attributed to van der Velde, A. G..

3 recordsLinked to original sources

bioRxiv2021

Factorbook: an Updated Catalog of Transcription Factor Motifs and Candidate Regulatory Motif Sites

The human genome contains roughly 1,600 transcription factors (TFs) (1), DNA-binding proteins recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX (2), and in vivo, using techniques including ChIP-seq (3, 4). We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. We will continue to expand the resource as ENCODE Phase IV data are released.

bioinformatics↗

bioRxiv2020

Annotation of Chromatin States in 66 Complete Mouse Epigenomes During Development

The morphologically and functionally distinct cell types of a multicellular organism are maintained by epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 10.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions throughout the developmental time course. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by Polycomb Repressive Complex proteins and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.

bioinformatics↗

bioRxiv2016

LR-DNase: Predicting TF binding from DNase-seq data

Transcription factors play a key role in the regulation of gene expression. Hypersensitivity to DNase I cleavage has long been used to gauge the accessibility of genomic DNA for transcription factor binding and as an indicator of regulatory genomic locations. An increasing amount of ChIP-seq data on a large number of TFs is being generated, mostly in a small number of cell types. DNase-seq data are being produced for hundreds of cell types. We aimed to develop a computational method that could combine ChIP-seq and DNase-seq data to predict TF binding sites in a wide variety of cell types. We trained and tested a logistic regression model, called LR-DNase, to predict binding sites for a specific TF using seven features derived from DNase-seq and genomic sequence. We calculated the area under the precision-recall curve at a false discovery rate cutoff of 0.5 for the LR-DNase model, a number of logistic regression models with fewer features, and several existing state-of-the-art TF binding prediction methods. The LR-DNase model outperformed existing unsupervised and supervised methods. Additionally, for many TFs, a model that uses only two features, DNase-seq reads and motif score, was sufficient to match the performance of the best existing methods.

bioinformatics↗