Evidence map›Paper›PMID 25260329›Full record

ArticleThe European physical journal. E, Soft matter2014

Relationship between promoter sequence and its strength in gene expression.

Jingwei Li, Yunxin Zhang

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Article in The European physical journal. E, Soft matter, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. EngineeredJournal of fungi (Basel, Switzerland) · 2026
    Article
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  3. Article
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  6. From genetics to biotechnology: Synthetic biology as a flexible course-embedded research experience.Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
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  12. Rapid generation of hypomorphic mutations.Nature communications · 2017
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jingwei LiShanghai Key Laboratory for Contemporary Applied Mathematics, Centre for Computational Systems Biology, School of Mathematical Sciences, Fudan University, 200433, Shanghai, China.
Yunxin Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Promoter strength, or activity, is important in genetic engineering and synthetic biology. A constitutive promoter with a certain strength for one given RNA can often be reused for other RNAs. Therefore, the strength of one promoter is mainly determined by its nucleotide sequence. One of the main difficulties in genetic engineering and synthetic biology is how to control the expression of a certain protein at a given level. One usually used way to achieve this goal is to choose one promoter with a suitable strength which can be employed to regulate the rate of transcription, which then leads to the required level of protein expression. For this purpose, so far, many promoter libraries have been established experimentally. However, theoretical methods to predict the strength of one promoter from its nucleotide sequence are desirable. Such methods are not only valuable in the design of promoter with specified strength, but also meaningful to understand the mechanism of promoter in gene transcription. In this study, through various tests, a theoretical model is presented to describe the relationship between promoter strength and nucleotide sequence. Our analysis shows that promoter strength is greatly influenced by nucleotide groups with three adjacent nucleotides in their sequences. Meanwhile, nucleotides in different regions of promoter sequence have different effects on promoter strength. Based on experimental data for E. coli promoters, our calculations indicate that nucleotides in the -10 region, the -35 region, and the discriminator region of a promoter sequence are more important for determining promoter strength than those in the spacing region. With model parameter values obtained by fitting to experimental data, four promoter libraries are theoretically built for the corresponding experimental environments under which data for promoter strength in gene expression has been measured previously.

Indexed as

Gene ExpressionPromoter Regions, GeneticAlgorithmsDNA, BacterialDNA-Directed RNA PolymerasesEscherichia coliGenetic EngineeringModels, BiologicalSynthetic BiologyThermodynamicsDNA, BacterialDNA-Directed RNA Polymerases

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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.