Pervasive transcription of the genome produces both stable and transient RNAs. We developed transient transcriptome sequencing (TT-seq), a protocol that uniformly maps the entire range of RNA-producing units and estimates rates of RNA synthesis and degradation. Application of TT-seq to human K562 cells recovers stable messenger RNAs and long intergenic noncoding RNAs and additionally maps transient enhancer, antisense, and promoter-associated RNAs. TT-seq analysis shows that enhancer RNAs are short-lived and lack U1 motifs and secondary structure. TT-seq also maps transient RNA downstream of polyadenylation sites and uncovers sites of transcription termination; we found, on average, four transcription termination sites, distributed in a window with a median width of ~3300 base pairs. Termination sites coincide with a DNA motif associated with pausing of RNA polymerase before its release from the genome.
Trypanosoma brucei developed a sophisticated life cycle to adapt to different host environments. Although developmental differentiation of T. brucei has been the topic of intensive research for decades, the mechanisms responsible for adaptation to different host environments are not well understood. We developed stable isotope labeling by amino acids in cell culture in trypanosomes to compare the proteomes of two different life cycle stages. Quantitative comparison of 4364 protein groups identified many proteins previously not known to be stage-specifically expressed. The identification of stage-specific proteins helps to understand how parasites adapt to different hosts and provides new insights into differences in metabolism, gene regulation, and cell architecture. A DEAD-box RNA helicase, which is highly up-regulated in the bloodstream form of this parasite and which is essential for viability and proper cell cycle progression in this stage is described as an example.
To monitor transcriptional regulation in human cells, rapid changes in enhancer and promoter activity must be captured with high sensitivity and temporal resolution. Here, we show that the recently established protocol TT‐seq (“transient transcriptome sequencing”) can monitor rapid changes in transcription from enhancers and promoters during the immediate response of T cells to ionomycin and phorbol 12‐myristate 13‐acetate (PMA). TT‐seq maps eRNAs and mRNAs every 5 min after T‐cell stimulation with high sensitivity and identifies many new primary response genes. TT‐seq reveals that the synthesis of 1,601 eRNAs and 650 mRNAs changes significantly within only 15 min after stimulation, when standard RNA‐seq does not detect differentially expressed genes. Transcription of enhancers that are primed for activation by nucleosome depletion can occur immediately and simultaneously with transcription of target gene promoters. Our results indicate that enhancer transcription is a good proxy for enhancer regulatory activity in target gene activation, and establish TT‐seq as a tool for monitoring the dynamics of enhancer landscapes and transcription programs during cellular responses and differentiation.
Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today's largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN consistently identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine.2 All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today’s largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN generally identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine.
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