Biology subjects

Pratt, H. E.

Publications and source records attributed to Pratt, H. E..

3 recordsLinked to original sources

bioRxiv2024

An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional Regulation

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, The ENCODE consortium mapped biochemical signals across many cell types and tissues and integrated these data to develop a Registry of 0.9 million human and 300 thousand mouse candidate cis-Regulatory Elements (cCREs) annotated with potential functions1. We have expanded the Registry to include 2.35 million human and 927 thousand mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded Registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays like STARR-seq, MPRA, CRISPR perturbation, and transgenic mouse assays now cover over 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer/silencer roles in different cellular contexts. Integrating the Registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by discovering KLF1 as a novel causal gene for red blood cell traits. This expanded Registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

genomics↗

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

GS-Preprocess: Containerized GUIDE-seq Data Analysis Tools with Diverse Sequencer Compatibility

RNA-guided nucleases (e.g. CRISPR-Cas) are used in a breadth of clinical and basic scientific subfields for the investigation or modification of biological processes. While these modern platforms for site-specific DNA cleavage are highly accurate, some applications (e.g. gene editing therapeutics) cannot tolerate DNA breaks at off-target sites, even at low levels. Thus, it is critically important to determine the genome-wide targeting profile of candidate RNA-guided nucleases prior to use. GUIDE-seq is a high-quality, easy-to-execute molecular method that detects and quantifies off-target cleavage. However, this method may remain costly or inaccessible to some researchers due to its library sequencing and analysis protocols, which require a MiSeq platform that must be preprogramed for non-standard output. Here, we present GS-Preprocess, an open-source containerized software that can use standard raw data output (BCL file format) from any Illumina sequencer to create input for the Bioconductor GUIDEseq off-target profiling package. Single-command GS-Preprocess performs FASTQ demultiplexing, adapter trimming, alignment, and UMI reference construction, improving the ease and accessibility of the GUIDE-seq method for a wide range of researchers.

bioinformatics↗