Ssl2/TFIIH function in transcription start site scanning by RNA Polymerase II in Saccharomyces cerevisiae

  1. Tingting Zhao
  2. Irina O Vvedenskaya
  3. William KM Lai
  4. Shrabani Basu
  5. B Franklin Pugh
  6. Bryce E Nickels
  7. Craig D Kaplan  Is a corresponding author
  1. University of Pittsburgh, United States
  2. Rutgers University, United States
  3. Cornell University, United States

Abstract

In Saccharomyces cerevisiae, RNA Polymerase II (Pol II) selects transcription start sites (TSS) by a unidirectional scanning process. During scanning, a preinitiation complex (PIC) assembled at an upstream core promoter initiates at select positions within a window ~40-120 basepairs downstream. Several lines of evidence indicate that Ssl2, the yeast homolog of XPB and an essential and conserved subunit of the general transcription factor (GTF) TFIIH, drives scanning through its DNA-dependent ATPase activity, therefore potentially controlling both scanning rate and scanning extent (processivity). To address questions of how Ssl2 functions in promoter scanning and interacts with other initiation activities, we leveraged distinct initiation-sensitive reporters to identify novel ssl2 alleles. These ssl2 alleles, many of which alter residues conserved from yeast to human, confer either upstream or downstream TSS shifts at the model promoter ADH1 and genome-wide. Specifically, tested ssl2 alleles alter TSS selection by increasing or narrowing the distribution of TSSs used at individual promoters. Genetic interactions of ssl2 alleles with other initiation factors are consistent with ssl2 allele classes functioning through increasing or decreasing scanning processivity but not necessarily scanning rate. These alleles underpin a residue interaction network that likely modulates Ssl2 activity and TFIIH function in promoter scanning. We propose that the outcome of promoter scanning is determined by two functional networks, the first being Pol II activity and factors that modulate it to determine initiation efficiency within a scanning window, and the second being Ssl2/TFIIH and factors that modulate scanning processivity to determine the width of the scanning widow.

Data availability

Genomics datasets generated in the current study are available in the NCBI BioProject and SRA, under the accession numbers of PRJNA681384 and SRP295731, respectively. The processed genomic data files are available in GEO, under the accession number of GSE182792. The streamlined commands to generate TSS-seq bedGraph files, count tables, tables of expression, spread and median TSS can be found at https://github.com/Kaplan-Lab-Pitt/Ssl2_scanning.

The following data sets were generated

Article and author information

Author details

  1. Tingting Zhao

    University of Pittsburgh, Pittsburgh, United States
    Competing interests
    No competing interests declared.
  2. Irina O Vvedenskaya

    Waksman Institute, Rutgers University, Piscataway, United States
    Competing interests
    No competing interests declared.
  3. William KM Lai

    Cornell University, Ithaca, United States
    Competing interests
    No competing interests declared.
  4. Shrabani Basu

    University of Pittsburgh, Pittsburgh, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5096-5490
  5. B Franklin Pugh

    Cornell University, Ithaca, United States
    Competing interests
    B Franklin Pugh, BFP has a financial interest in Peconic, LLC, which utilizes the ChIP-exo technology implemented in this study and could potentially benefit from the outcomes of this research..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8341-4476
  6. Bryce E Nickels

    Department of Genetics, Rutgers University, Piscataway, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7449-8831
  7. Craig D Kaplan

    University of Pittsburgh, Pittsburgh, United States
    For correspondence
    craig.kaplan@pitt.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7518-695X

Funding

National Institute of General Medical Sciences (R01GM120450)

  • Craig D Kaplan

National Institute of General Medical Sciences (R01GM059055)

  • B Franklin Pugh

National Institute of General Medical Sciences (R01GM059055)

  • Bryce E Nickels

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Eric J Wagner, University of Rochester Medical Center, United States

Version history

  1. Preprint posted: May 5, 2021 (view preprint)
  2. Received: June 4, 2021
  3. Accepted: October 14, 2021
  4. Accepted Manuscript published: October 15, 2021 (version 1)
  5. Version of Record published: November 12, 2021 (version 2)

Copyright

© 2021, Zhao et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,664
    views
  • 188
    downloads
  • 7
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Tingting Zhao
  2. Irina O Vvedenskaya
  3. William KM Lai
  4. Shrabani Basu
  5. B Franklin Pugh
  6. Bryce E Nickels
  7. Craig D Kaplan
(2021)
Ssl2/TFIIH function in transcription start site scanning by RNA Polymerase II in Saccharomyces cerevisiae
eLife 10:e71013.
https://doi.org/10.7554/eLife.71013

Share this article

https://doi.org/10.7554/eLife.71013

Further reading

    1. Genetics and Genomics
    2. Neuroscience
    Yifei Weng, Shiyi Zhou ... Coleen T Murphy
    Research Article

    Cognitive decline is a significant health concern in our aging society. Here, we used the model organism C. elegans to investigate the impact of the IIS/FOXO pathway on age-related cognitive decline. The daf-2 Insulin/IGF-1 receptor mutant exhibits a significant extension of learning and memory span with age compared to wild-type worms, an effect that is dependent on the DAF-16 transcription factor. To identify possible mechanisms by which aging daf-2 mutants maintain learning and memory with age while wild-type worms lose neuronal function, we carried out neuron-specific transcriptomic analysis in aged animals. We observed downregulation of neuronal genes and upregulation of transcriptional regulation genes in aging wild-type neurons. By contrast, IIS/FOXO pathway mutants exhibit distinct neuronal transcriptomic alterations in response to cognitive aging, including upregulation of stress response genes and downregulation of specific insulin signaling genes. We tested the roles of significantly transcriptionally-changed genes in regulating cognitive functions, identifying novel regulators of learning and memory. In addition to other mechanistic insights, a comparison of the aged vs young daf-2 neuronal transcriptome revealed that a new set of potentially neuroprotective genes is upregulated; instead of simply mimicking a young state, daf-2 may enhance neuronal resilience to accumulation of harm and take a more active approach to combat aging. These findings suggest a potential mechanism for regulating cognitive function with age and offer insights into novel therapeutic targets for age-related cognitive decline.

    1. Genetics and Genomics
    Samuel Pattillo Smith, Gregory Darnell ... Lorin Crawford
    Research Article

    LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.