We describe a time-resolved nascent single-cell RNA sequencing (RNA-seq) approach that measures gene-specific transcriptional noise and the fraction of active genes in S. cerevisiae. Most genes are expressed with near-constitutive behavior, while a subset of genes show high mRNA variance suggestive of transcription bursting. Transcriptional noise is highest in the cofactor/coactivator-redundant (CR) gene class (dependent on both SAGA and TFIID) and strongest in TATA-containing CR genes. Using this approach, we also find that histone gene transcription switches from a low-level, low-noise constitutive mode during M and M/G1 to an activated state in S phase that shows both an increase in the fraction of active promoters and a switch to a noisy and bursty transcription mode. Rapid depletion of cofactors SAGA and MED Tail indicates that both factors play an important role in stimulating the fraction of active promoters at CR genes, with a more modest role in transcriptional noise.
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http://dx.doi.org/10.1016/j.celrep.2024.114593 | DOI Listing |
rRNA-derived fragments (rRFs) are a class of emerging post-transcriptional regulators of gene expression likely binding to the transcripts of target genes. However, the lack of knowledge about such targets hinders our understanding of rRF functions or binding mechanisms. The paucity of resources supporting the identification of the targets of rRFs creates a bottleneck in the fast-developing field.
View Article and Find Full Text PDFNat Struct Mol Biol
January 2025
Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY, USA.
Following transcript release during intrinsic termination, Escherichia coli RNA polymerase (RNAP) often remains associated with DNA in a post-termination complex (PTC). RNAPs in PTCs are removed from the DNA by the SWI2/SNF2 adenosine triphosphatase (ATPase) RapA. Here we determined PTC structures on negatively supercoiled DNA and with RapA engaged to dislodge the PTC.
View Article and Find Full Text PDFAging results in a progressive decline in physiological function due to the deterioration of essential biological processes, such as transcription and RNA splicing, ultimately increasing mortality risk. Although proteomics is emerging as a powerful tool for elucidating the molecular mechanisms of aging, existing studies are constrained by limited proteome coverage and only observe a narrow range of lifespan. To overcome these limitations, we integrated the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of three brain tissues (cortex, hippocampus, striatum) and kidney in the C57BL/6JN mouse model, achieving quantification of 8,954 to 9,376 proteins per tissue (cumulatively 12,749 across all tissues).
View Article and Find Full Text PDFSci Rep
December 2024
Laboratory of Cell Vaccine, Microbial Research Center for Health and Medicine (MRCHM), National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), 7-6-8 Saito-Asagi, Ibaraki-Shi, Osaka, 567-0085, Japan.
Since designer cells are attracting much attention as a new modality in gene and cell therapy, it would be advantageous to develop synthetic receptors that recognize artificial ligands and activate solely signaling molecules of interest. In this study, we refined the construction of our previously developed minimal engineered receptors (MERs) to avoid off-target activation of STAT5 while maintaining on-target activation of signaling molecules corresponding to tyrosine motifs. Among the myristoylated, cytoplasmic, and transmembrane types of MERs, the cytoplasmic type had the highest signaling efficiency, although there was off-target activation of STAT5 upon ligand stimulation.
View Article and Find Full Text PDFPLoS One
December 2024
Servier, Research & Development, Gif-sur-Yvette, France.
Improving the selectivity and effectiveness of drugs represents a crucial issue for future therapeutic developments in immuno-oncology. Traditional bulk transcriptomics faces limitations in this context for the early phase of target discovery as resulting gene expression levels represent the average measure from multiple cell populations. Alternatively, single cell RNA sequencing can dive into unique cell populations transcriptome, facilitating the identification of specific targets.
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