Evidence map›Paper›PMID 42897357›Full record

ReviewRice (New York, N.Y.)2026

Precision Editing of Cis-Regulatory Elements Drives Crops Quantitative Traits Genetic Improvement: From Functional Dissection to Intelligent Design.

Yulin Li, Xiangyu Zhang, Yongtao Cui, Guiqi Shang, Yue Wu, Yiyuan Ma, Tian Tian, Mengru Liu, Shifei Sang

Abstract readReview
In one paragraph

Review in Rice (New York, N.Y.), 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

9 authors.

Yulin Li *Engineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Xiangyu Zhang *Engineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Yongtao Cui *Institute of Crops and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China.
Guiqi ShangEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Yue WuEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Yiyuan MaEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Tian TianEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Mengru LiuEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China.
Shifei SangEngineering Research Center of Crop Genetic Improvement and Germplasm Innovation in Henan Province, College of Life Sciences, Henan Normal University, Xinxiang, 453007, Henan, China. sangshifei@htu.edu.cn.ORCID https://orcid.org/0000-0002-0874-5256

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since most agronomic traits are quantitative, ensuring food security under the pressures of global climate change and population growth increasingly relies on the precise and efficient genetic improvement of crop quantitative traits, making it a central focus of breeding research. Traditional breeding and transgenic approaches are often insufficient for modulating complex quantitative traits. In contrast, the advent of gene-editing technologies has opened new avenues for crop genetic improvement. Notably, the editing of cis-regulatory elements allows fine-tuning of gene expression levels and spatiotemporal patterns without altering coding sequences, enabling targeted optimization of quantitative traits such as yield, quality, and stress resistance. This review systematically summarizes the evolution of cis-regulatory element editing technologies, from early random mutagenesis and screening to targeted dissection guided by functional genomics and, more recently, to intelligent design integrating multi-omics and artificial intelligence, highlighting key technologies, representative applications, and inherent limitations at each stage while discussing future research directions in data integration, algorithm development, and tool deployment. We hope this review will provide both theoretical guidance and practical strategies for intelligent crop breeding.

Indexed as

Artificial intelligenceCis-regulatory elementsFunctional dissectionGene editingIntelligent designQuantitative traits

Identifiers

PMID42897357
PMCPMC13680586

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.