Evidence map›Paper›PMID 41712102›Full record

ReviewAdvanced biotechnology2026

Multiplex gene editing drives revolution in crop breeding: overlaid editing of multiple genes and customization of complex traits.

Jieni Lin, Hanipa Hazaisi, Yuefeng Guan, Mengyan Bai

Abstract readReview
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. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
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.

Jieni LinGuangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, College of Life Sciences, Guangzhou University, Guangzhou, 510006, China.
Hanipa HazaisiIli Agricultural Science Institute, Yining, 835100, China.
Yuefeng GuanGuangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, College of Life Sciences, Guangzhou University, Guangzhou, 510006, China. guan@gzhu.edu.cn.
Mengyan BaiGuangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, College of Life Sciences, Guangzhou University, Guangzhou, 510006, China. mengyanbai@gzhu.edu.cn.ORCID http://orcid.org/0009-0009-9766-8528

Funding

Chinese Academy of Agricultural Sciences from Institute of Crop Science 2023ZD040360104
6 · The paper itself

Abstract

Modern agriculture currently demands higher standards for the simultaneous improvement of crop yield, quality and stress resistance. However, traditional crop breeding methods can no longer meet the needs of modern agricultural development. Improving a single trait is no longer sufficient to meet the multifaceted demands of modern agricultural production and consumer expectations. Multiple traits breeding has increasingly become a key objective in current crop breeding. Over the past decade, CRISPR/Cas9-based multiplex genome editing (MGE) has enabled efficient pyramiding and precise regulation of multiple traits via targeted editing of multiple gene loci, revolutionizing crop breeding. In this review, we briefly describe the core CRISPR/Cas-based MGE strategies and technical workflows, and thoroughly discuss the practical outcomes of MGE applications in various fields, such as enhancing crop stress resistance, increasing yield and improving quality. This review aims to provide a summary and theoretical reference for crop breeding, as well as open up new ideas for achieving different breeding goals.

Indexed as

CRISPR/Cas9Crop breedingGene editing strategiesMultiplex genome editing

Identifiers

PMID41712102
PMCPMC12920966

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.