Targeting Spt5-Pol II by Small-Molecule Inhibitors Uncouples Distinct Activities and Reveals Additional Regulatory Roles

Bahat, Anat; Lahav, Or; Plotnikov, A.N.; Leshkowitz, Dena; Dikstein, Rivka

doi:10.1016/j.molcel.2019.08.024

Cited by 21 publications

(32 citation statements)

References 65 publications

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“…These overall trends were also observed within PI distributions when we extended this analysis to publicly available data ( Supplemental Fig. 12 ).While the PI is known to depend on the method used to define the paused region [ 15 , 24 ], we found that the trends across protocols remained consistent even with different pause windows and read counting software ( Supplemental Fig. 16 ).…”

Section: Resultssupporting

confidence: 57%

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries

et al. 2022

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Background A variety of protocols exist for producing whole genome run-on transcription datasets. However, little is known about how differences between these protocols affect the signal within the resulting libraries. Results Using run-on transcription datasets generated from the same biological system, we show that a variety of GRO- and PRO-seq preparation methods leave identifiable signatures within each library. Specifically we show that the library preparation method results in differences in quality control metrics, as well as differences in the signal distribution at the 5 ′ end of transcribed regions. These shifts lead to disparities in eRNA identification, but do not impact analyses aimed at inferring the key regulators involved in changes to transcription. Conclusions Run-on sequencing protocol variations result in technical signatures that can be used to identify both the enrichment and library preparation method of a particular data set. These technical signatures are batch effects that limit detailed comparisons of pausing ratios and eRNAs identified across protocols. However, these batch effects have only limited impact on our ability to infer which regulators underlie the observed transcriptional changes.

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Section: Resultssupporting

confidence: 57%

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries

et al. 2022

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“…This enabled to identify withaferin A, a previously characterised molecule with anti-inflammatory and anticancer activities, as allosteric inhibitor of NF-κB dimerisation. In another study, ∼100 000 pure natural plant molecules were screened to identify inhibitors of Spt5, a disease-associated transcription elongation factor that directly interacts with Rpb1, the large subunit of RNA polymerase II [ 81 ]. The authors identified several compounds that interfere with Spt5/Rpb1 PCA signal and Spt5 functions in cells.…”

Section: Pcas Applied To Large-scale Analysis Of Ppismentioning

confidence: 99%

Protein-fragment complementation assays for large-scale analysis of protein–protein interactions

Blaszczak

Sudevan

Wysocki

et al. 2021

Biochemical Society Transactions

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Protein–protein interactions (PPIs) orchestrate nearly all biological processes. They are also considered attractive drug targets for treating many human diseases, including cancers and neurodegenerative disorders. Protein-fragment complementation assays (PCAs) provide a direct and straightforward way to study PPIs in living cells or multicellular organisms. Importantly, PCAs can be used to detect the interaction of proteins expressed at endogenous levels in their native cellular environment. In this review, we present the principle of PCAs and discuss some of their advantages and limitations. We describe their application in large-scale experiments to investigate PPI networks and to screen or profile PPI targeting compounds.

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“…As Supt4h and Supt5h are needed for normal functioning of mammalian cells, extensive knockdown can result in broad effects on cellular RNA synthesis ( 53 ), whereas partial knockdown is associated with limited changes in RNAPII-S2 template occupancy and RNA synthesis (Figures 1 and 5 ; see also ( 16 , 18 , 39 )). As introns were included in our calculations of G + C content, and total gene length and G + C content are determined largely by sequences present in introns ( 54 ), intronic sequences, which are less conserved among species than exonic sequences ( 55 ) substantially affect the template occupancy we have reported.…”

Section: Discussionmentioning

confidence: 99%

DSIF modulates RNA polymerase II occupancy according to template G + C content

Deng

Zhang

et al. 2022

NAR Genomics and Bioinformatics

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The DSIF complex comprising the Supt4h and Supt5h transcription elongation proteins clamps RNA polymerase II (RNAPII) onto DNA templates, facilitating polymerase processivity. Lowering DSIF components can differentially decrease expression of alleles containing nucleotide repeat expansions, suggesting that RNAPII transit through repeat expansions is dependent on DSIF functions. To globally identify sequence features that affect dependence of the polymerase on DSIF in human cells, we used ultra-deep ChIP-seq analysis and RNA-seq to investigate and quantify the genome-wide effects of Supt4h loss on template occupancy and transcript production. Our results indicate that RNAPII dependence on Supt4h varies according to G + C content. Effects of DSIF knockdown were prominent during transcription of sequences high in G + C but minimal for sequences low in G + C and were particularly evident for G + C-rich segments of long genes. Reanalysis of previously published ChIP-seq data obtained from mouse cells showed similar effects of template G + C composition on Supt5h actions. Our evidence that DSIF dependency varies globally in different template regions according to template sequence composition suggests that G + C content may have a role in the selectivity of Supt4h knockdown and Supt5h knockdown during transcription of gene alleles containing expansions of G + C-rich repeats.

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Targeting Spt5-Pol II by Small-Molecule Inhibitors Uncouples Distinct Activities and Reveals Additional Regulatory Roles

Cited by 21 publications

References 65 publications

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries

Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries

Protein-fragment complementation assays for large-scale analysis of protein–protein interactions

DSIF modulates RNA polymerase II occupancy according to template G + C content

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