Evidence map›Paper›PMID 42649178›Full record

ArticleNature communications2026

A decoupled transcription platform enables tunable and predictable gene expression in yeast.

Yujie Chen, Hui Li, Lin Duan, Yang Liu, Jingrui Yan, Haoyang Chen, Jianguo Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Yujie Chen *State Key Laboratory of Gene Function and Modulation Research, School of Advanced Agricultural Sciences, Peking University, Beijing, China.ORCID 0000-0001-8791-593X
Hui Li *State Key Laboratory of Gene Function and Modulation Research, School of Advanced Agricultural Sciences, Peking University, Beijing, China.
Lin DuanState Key Laboratory of Gene Function and Modulation Research, School of Advanced Agricultural Sciences, Peking University, Beijing, China.
Yang LiuAcademy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Jingrui YanSchool of Food Science and Engineering, Hainan University, Haikou, China.
Haoyang ChenState Key Laboratory of Gene Function and Modulation Research, School of Advanced Agricultural Sciences, Peking University, Beijing, China.
Jianguo YangState Key Laboratory of Gene Function and Modulation Research, School of Advanced Agricultural Sciences, Peking University, Beijing, China. yangjg@pku.edu.cn.ORCID 0000-0002-6602-3462

Funding

National Science Foundation of China | Young Scientists Fund 32122006
6 · The paper itself

Abstract

Predictable control of gene expression is essential for building genetic circuits and improving metabolic pathways, but conventional promoter libraries often behave unpredictably when genes are combined. Here we develop CRISPR-Activated Promoter-based Orthogonal expression (CAPO), a quantitative platform for controlling multiple genes in yeast. CAPO uses synthetic CRISPR-activated promoters that remain silent until matching guide RNAs recruit dCas9-VPR. We tune each gene by varying guide RNA abundance with defined T7 promoters, while keeping regulatory channels orthogonal. CAPO reaches expression levels comparable to strong native yeast promoters, maintains low background activity, and preserves promoter-strength order across different genes. We apply CAPO to program broad fluorescence color outputs and to rapidly optimize lycopene and 3-hydroxypropionic acid biosynthesis. These results establish CAPO as a scalable platform for predictable engineering of eukaryotic gene networks.

Indexed as

Gene Expression Regulation, FungalSaccharomyces cerevisiaeTranscription, GeneticCRISPR-Cas SystemsGene Regulatory NetworksLactic AcidLycopenePromoter Regions, GeneticRNA, Guide, CRISPR-Cas Systemshydracrylic acidLactic AcidLycopeneRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID42649178
PMCPMC13518805

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.