Transcription factors are managers of the cellular factory, and key components to many diseases. Many non-coding single nucleotide polymorphisms affect transcription factors, either by directly altering the protein or its functional activity at individual binding sites. Here we first briefly summarize high-throughput approaches to studying transcription factor activity. We then demonstrate, using published chromatin accessibility data (specifically ATAC-seq), that the genome-wide profile of TF recognition motifs relative to regions of open chromatin can determine the key transcription factor altered by a perturbation. Our method of determining which TFs are altered by a perturbation is simple, is quick to implement, and can be used when biological samples are limited. In the future, we envision that this method could be applied to determine which TFs show altered activity in response to a wide variety of drugs and diseases.

Background: The increase in DNA copy number in Down syndrome (DS; caused by trisomy 21) has led to the DNA dosage hypothesis, which posits that the level of gene expression is proportional to the gene’s DNA copy number. Yet many reports have suggested that a proportion of chromosome 21 genes are dosage compensated back towards typical expression levels (1.0×). In contrast, other reports suggest that dosage compensation is not a common mechanism of gene regulation in trisomy 21, providing support to the DNA dosage hypothesis. Results: In our work, we use both simulated and real data to dissect the elements of differential expression analysis that can lead to the appearance of dosage compensation, even when compensation is demonstrably absent. Using lymphoblastoid cell lines derived from a family with an individual with Down syndrome, we demonstrate that dosage compensation is nearly absent at both nascent transcription (GRO-seq) and steady-state RNA (RNA-seq) levels. Furthermore, we link the limited apparent dosage compensation to expected allelic variation in transcription levels. Conclusions: Transcription dosage compensation does not occur in Down syndrome. Simulated data containing no dosage compensation can appear to have dosage compensation when analyzed via standard methods. Moreover, some chromosome 21 genes that appear to be dosage compensated are consistent with allele specific expression.

We present a fast and simple algorithm to detect nascent RNA transcription in global nuclear run-on sequencing (GROseq). GRO-seq is a relatively new protocol that captures nascent transcripts from actively engaged polymerase, providing a direct readout on bona fide transcription. Most traditional assays, such as RNA-seq, measure steady state RNA levels which are affected by transcription, post-transcriptional processing, and RNA stability. GRO-seq data, however, presents unique analysis challenges that are only beginning to be addressed. Here, we describe a new algorithm, Fast Read Stitcher (FStitch), that takes advantage of two popular machine-learning techniques, hidden Markov models and logistic regression, to classify which regions of the genome are transcribed. Given a small user-defined training set, our algorithm is accurate, robust to varying read depth, annotation agnostic, and fast. Analysis of GRO-seq data without a priori need for annotation uncovers surprising new insights into several aspects of the transcription process.

We observed that heat shock of Caenorhabditis elegans leads to the formation of nuclear double-stranded RNA (dsRNA) foci, detectable with a dsRNA-specific monoclonal antibody. These foci significantly overlap with nuclear HSF-1 granules. To investigate the molecular mechanism(s) underlying dsRNA foci formation, we used RNA-seq to globally characterize total RNA and immunoprecipitated dsRNA from control and heat shocked worms. We find a subset of both sense and antisense transcripts enriched in the dsRNA pool by heat shock overlap with dsRNA transcripts enriched by deletion of tdp-1, which encodes the C. elegans ortholog of TDP-43. Interestingly, transcripts involved in translation are over-represented in the dsRNAs induced by either heat shock or deletion of tdp-1. Also enriched in the dsRNA transcripts are sequences downstream of annotated genes (DoGs), which we globally quantified with a new algorithm. To validate these observations, we used fluorescence in situ hybridization (FISH) to confirm both antisense and downstream of gene transcription for eif-3.B, one of the affected loci we identified.