Biology subjects

Chou, S.-P.

Publications and source records attributed to Chou, S.-P..

6 recordsLinked to original sources

bioRxiv2022

The Long Noncoding RNA Playrr Regulates Pitx2 Dosage and Protects Against Cardiac Arrhythmias

RationaleThe most significantly associated atrial fibrillation (AF) risk loci in humans map to a noncoding gene desert upstream of the evolutionarily conserved left-right (LR) transcription factor Pitx2, a master regulator of LR asymmetric organ development. Pitx2 dosage is fundamentally linked to the development of sinus node dysfunction (SND) and AF, the most common cardiac arrhythmia affecting adults, but the mechanistic basis for this remains obscure. We identified a conserved long noncoding RNA (lncRNA), Playrr, which is exclusively transcribed on the embryos right side, opposite to Pitx2 on the left, that participates in mutually antagonistic transcriptional regulation with Pitx2. ObjectiveThe objective of this study was to investigate a role of Playrr in regulating Pitx2 transcription and protecting against the development of cardiac rhythm disturbances. Methods and ResultsPlayrr expression in the developing heart was analyzed with RNA in situ hybridization. Playrr was expressed asymmetrically (on the right) to Pitx2 (on the left) in developing mouse embryos, including in mouse embryonic sinoatrial node cells. We utilized CRISPR/Cas9 genome editing in mice to target Playrr, generating mice lacking Playrr RNA transcript (PlayrrEx1sj allele). Using qRT-PCR we detected upregulation of the cardiac isoform, Pitx2c, during visceral organ morphogenesis in PlayrrEx1sj mutant embryos. Surface ECG (AliveCor(R)) and 24-hour telemetry ECG detected bradycardia and irregular interbeat (R-R) intervals suggestive of SND in PlayrrEx1sj mutant adults. Programmed stimulation of PlayrrEx1sj mutant adults resulted in pacing-induced AF. Within the right atrium of PlayrrEx1sj mutant hearts, Massons trichrome stain revealed increased collagen deposition indicative of fibrosis, and immunofluorescence demonstrated mis-localization of Connexin 43 in atrial cardiomyocytes. These findings suggested an altered atrial substrate in PlayrrEx1sj adult mice. Finally, transcriptomic analysis by chromatin run-on and sequencing (ChRO-seq) in atria of PlayrrEx1sj mutant mice compared to wild type controls revealed differential expression of genes involved in cell-cell adhesion and motility, fibrosis, and dysregulation of the key cardiac genes Tbx5 and Hcn1. ConclusionsAdult mice lacking functional Playrr lncRNA transcript have baseline bradyarrhythmia and increased susceptibility to AF. These cardiac phenotypes are similar to those observed in Pitx2 heterozygous mice. Interactions between Pitx2 and Playrr may provide a genetic mechanism for modulating Pitx2 dosage and susceptibility to SND and AF.

developmental biology↗

bioRxiv2021

Genetic Dissection of the RNA Polymerase II Transcription Cycle

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate the strength of base pairing between A-T or G-C dinucleotides as key determinants to the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

genomics↗

bioRxiv2020

Uncovering Transcriptional Dark Matter via Gene Annotation Independent Single-Cell RNA Sequencing Analysis

Single-cell RNA sequencing (scRNA-seq) enables the study of cell biology with high resolution. scRNA-seq expression analyses rely on the availability of a high quality annotation of genes in the genome. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, gene annotations often fail to cover the full transcriptome of every cell type at every stage of development, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant information beyond the scope of the best available gene annotation. This is achieved by performing single-cell expression analysis on any region in the genome for which transcriptional products are detected. Our routine identifies transcriptionally active regions (TARs) using a hidden Markov model, generates a matrix of expression levels for all TARs across all cells in a dataset, performs single-cell TAR expression analysis to identify TARs that are biologically significant, and then annotates biologically significant TARs using gene homology analysis. This procedure leverages single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts in complex tissues and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

bioinformatics↗

bioRxiv2020

Accurate imputation of histone modifications using transcription

The role of histone modifications in transcription remains incompletely understood. Here we used experimental perturbations combined with sensitive machine learning tools that infer the distribution of histone marks using maps of nascent transcription. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3 consistent with a role for RNA in recruiting PRC2. A subset of DNase-I hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than a regulatory, role in transcription.

genomics↗

bioRxiv2019

The virome in adult monozygotic twins with concordant or discordant gut microbiomes

The virome is one of the most variable components of the human gut microbiome. Within twin-pairs, viromes have been shown to be similar for infants but not for adults, indicating that as twins age and their environments and microbiomes diverge, so do their viromes. The degree to which the microbiome drives the viromes vast diversity is unclear. Here, we examined the relationship between microbiome diversity and virome diversity in 21 adult monozygotic twin pairs selected for high or low microbiome concordance. Viromes derived from virus-like particles were unique to each subject, dominated by Caudovirales and Microviridae, and exhibited a small core that included crAssphage. Microbiome-discordant twins had more dissimilar viromes compared to microbiome-concordant twins, and the richer the microbiomes, the richer the viromes. These patterns were driven by the bacteriophages, not eukaryotic viruses. These observations support a strong role of the microbiome in patterning the virome.

microbiology↗

bioRxiv2018

AlleleHMM: a data-driven method to identify allele-specific differences in distributed functional genomic marks

How DNA sequence variation influences gene expression remains poorly understood. Diploid organisms have two homologous copies of their DNA sequence in the same nucleus, providing a rich source of information about how genetic variation affects a wealth of biochemical processes. However, few computational methods have been developed to discover allele-specific differences in functional genomic data. Existing methods either treat each SNP independently, limiting statistical power, or combine SNPs across gene annotations, preventing the discovery of allele specific differences in unexpected genomic regions. Here we introduce AlleleHMM, a new computational method to identify blocks of neighboring SNPs that share similar allele-specific differences in mark abundance. AlleleHMM uses a hidden Markov model to divide the genome among three hidden states based on allele frequencies in genomic data: a symmetric state (state S) which shows no difference between alleles, and regions with a higher signal on the maternal (state M) or paternal (state P) allele. AlleleHMM substantially outperformed naive methods using both simulated and real genomic data, particularly when input data had realistic levels of overdispersion. Using PRO-seq data, AlleleHMM identified thousands of allele specific blocks of transcription in both coding and non-coding genomic regions. AlleleHMM is a powerful tool for discovering allele-specific regions in functional genomic datasets.

bioinformatics↗