ArticleGenome research2012
Noise-mean relationship in mutated promoters.
Article in Genome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
89 citing papers in PubMed, 178 citations in OpenAlex.
- Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data.Molecular systems biology · 2026Article
- Epistatic impacts of cis- and trans-regulatory mutations on the distribution of mutational effects for gene expression in Saccharomyces cerevisiae.Molecular biology and evolution · 2026Article
- Molecular evolution in light of regulatory-coding epistasis.EMBO reports · 2026Review
- Environmental impacts on gene expression noise and its relationship with fitness.bioRxiv : the preprint server for biology · 2026Article
- High-resolution binding data of TFIID and cofactors show promoter-specific differences in vivo.Research square · 2026Article
- High-resolution binding data of TFIID and cofactors show promoter-specific differencesbioRxiv : the preprint server for biology · 2025Article
- Article
- The impact of phenotypic heterogeneity on fungal pathogenicity and drug resistance.FEMS microbiology reviews · 2025Review
- Transcriptional noise, gene activation, and roles of SAGA and Mediator Tail measured using nucleotide recoding single-cell RNA-seq.Cell reports · 2024Article
- Analysis of developmental gene expression using smFISH andbioRxiv : the preprint server for biology · 2024Article
- Time will tell: comparing timescales to gain insight into transcriptional bursting.Trends in genetics : TIG · 2024Review
- Review
- The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian.Science advances · 2023Article
- Contributions of mutation and selection to regulatory variation: lessons from thePhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Broad compatibility between yeast UAS elements and core promoters and identification of promoter elements that determine cofactor specificity.Cell reports · 2023Article
- The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian.bioRxiv : the preprint server for biology · 2023Article
- Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics.Nucleic acids research · 2023Article
- Transcription factor binding process is the primary driver of noise in gene expression.PLoS genetics · 2022Article
- Gene regulation in Escherichia coli is commonly selected for both high plasticity and low noise.Nature ecology & evolution · 2022Article
- Mechanisms of protein evolution.Protein science : a publication of the Protein Society · 2022Review
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Gene expression depends on the frequency of transcription events (burst frequency) and on the number of mRNA molecules made per event (burst size). Both processes are encoded in promoter sequence, yet their dependence on mutations is poorly understood. Theory suggests that burst size and frequency can be distinguished by monitoring the stochastic variation (noise) in gene expression: Increasing burst size will increase mean expression without changing noise, while increasing burst frequency will increase mean expression and decrease noise. To reveal principles by which promoter sequence regulates burst size and frequency, we randomly mutated 22 yeast promoters chosen to span a range of expression and noise levels, generating libraries of hundreds of sequence variants. In each library, mean expression (m) and noise (coefficient of variation, η) varied together, defining a scaling curve: η(2) = b/m + η(ext)(2). This relation is expected if sequence mutations modulate burst frequency primarily. The estimated burst size (b) differed between promoters, being higher in promoter containing a TATA box and lacking a nucleosome-free region. The rare variants that significantly decreased b were explained by mutations in TATA, or by an insertion of an out-of-frame translation start site. The decrease in burst size due to mutations in TATA was promoter-dependent, but independent of other mutations. These TATA box mutations also modulated the responsiveness of gene expression to changing conditions. Our results suggest that burst size is a promoter-specific property that is relatively robust to sequence mutations but is strongly dependent on the interaction between the TATA box and promoter nucleosomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.