Biology subjects

Taing, L.

Publications and source records attributed to Taing, L..

3 recordsLinked to original sources

bioRxiv2021

CHIPS: A Snakemake pipeline for quality control and reproducible processing of chromatin profiling data

MotivationThe chromatin profile measured by ATAC-seq, ChIP-seq, or DNase-seq experiments can identify genomic regions critical in regulating gene expression and provide insights on biological processes such as diseases and development. However, quality control and processing chromatin profiling data involve many steps, and different bioinformatics tools are used at each step. It can be challenging to manage the analysis. ResultsWe developed a Snakemake pipeline called CHIPS (CHromatin enrichment Processor) to streamline the processing of ChIP-seq, ATAC-seq, and DNase-seq data. The pipeline supports single- and paired-end data and is flexible to start with FASTQ or BAM files. It includes basic steps such as read trimming, mapping, and peak calling. In addition, it calculates quality control metrics such as contamination profiles, PCR bottleneck coefficient, the fraction of reads in peaks, percentage of peaks overlapping with the union of public DNaseI hypersensitivity sites, and conservation profile of the peaks. For downstream analysis, it carries out peak annotations, motif finding, and regulatory potential calculation for all genes. The pipeline ensures that the processing is robust and reproducible. AvailabilityCHIPS is available at https://github.com/liulab-dfci/CHIPS

bioinformatics↗

bioRxiv2020

CoBRA: Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis - from differential peak calling to pathway analysis

ChIP-seq and ATAC-seq have become essential technologies used as effective methods of measuring protein-DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates correct normalization between samples, adjustment of copy number variations, and integration of new downstream analysis tools. Here we present CoBRA, a modularized computational workflow which quantifies ChIP and ATAC-seq peak regions and performs unsupervised and supervised analysis. CoBRA provides a comprehensive state-of-the-art ChIP and ATAC-seq analysis pipeline that is usable by scientists with limited computational experience. This enables researchers to gain rapid insight into protein-DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference DB and pathway analysis. Code availability: https://bitbucket.org/cfce/cobra

bioinformatics↗

bioRxiv2020

Translational profiling of mouse dopaminoceptive neurons reveals a role of PGE2 in dorsal striatum

Forebrain dopaminoceptive neurons play a key role in movement, action selection, motivation, and working memory. Their activity is dysregulated in addiction, Parkinsons disease and other conditions. To characterize the diverse dopamine target neuronal populations, we compare translating mRNAs in neurons of dorsal striatum and nucleus accumbens expressing D1 or D2 dopamine receptor and prefrontal cortex expressing D1 receptor. We identify D1/D2 and striatal dorso-ventral differences in the translational and splicing landscapes, which establish the characteristics of dopaminoceptive neurons. Expression differences and network analyses identify novel transcription factors with presumptive roles in these differences. Prostaglandin E2 appears as a candidate upstream regulator in the dorsal striatum, a hypothesis supported by converging functional evidence indicating its role in enhancing D2 dopamine receptor action. Our study provides powerful resources for characterizing dopamine target neurons, new information about striatal gene expression patterns, and reveals the unforeseen role of prostaglandin E2 in the dorsal striatum.

neuroscience↗