Evidence map›Paper›PMID 42886443›Full record

ReviewAdvanced biotechnology2026

Cross-domain signal grammars of transcription termination.

Shouqing Hou, Hongru Ma, Xuye Lang, Yuan Yao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advanced biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shouqing Hou *Department of Food Science and Engineering, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.
Hongru Ma *Zhejiang Key Laboratory of Intelligent Manufacturing for Functional Chemicals, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China.
Xuye LangZhejiang Key Laboratory of Intelligent Manufacturing for Functional Chemicals, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China. xuyelang@zju.edu.cn.
Yuan YaoDepartment of Food Science and Engineering, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China. yuanyao1@sjtu.edu.cn.ORCID http://orcid.org/0000-0001-5262-5115

Funding

'Pioneer' and 'Leading Goose' R&D Program of Zhejiang Province 2025C01102
6 · The paper itself

Abstract

Transcription termination establishes gene boundaries, recycles RNA polymerase, and prevents interference between neighboring transcription units. Termination depends on cis-acting elements, trans-acting factors, and the susceptibility of the elongation complex to pausing, cleavage, destabilization, or release. Predicted motifs, stable RNA ends, processing sites, readthrough regions, and polymerase-release regions are nevertheless often treated as measurements of the same event, which complicates mechanistic comparison and model development. This review compares termination signals as context-dependent rule systems in which sequence determinants, RNA structure and accessibility, and processing sites are interpreted through their order and spacing, molecular readers, conditional gates, and kinetic windows. It examines bacterial intrinsic and Rho-dependent termination, archaeal U-rich and cleavage-linked routes, PAS-centered RNAPII termination, and nuclear Pol I, Pol III, and specialized RNAPII pathways, showing how shared kinetic constraints are met by divergent molecular solutions shaped by cellular organization. Matching each signal feature to the measurement that supports it clarifies cross-domain comparisons and guides transcriptome-wide analysis, prediction, and terminator engineering in defined biological systems.

Indexed as

Machine learningRNA polymeraseRNA processingTerminator engineeringTranscription termination

Identifiers

PMID42886443

What OpenQuestion holds

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Registered trials

None linked

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.