Evidence map›Paper›PMID 40402953›Full record

ArticlePloS one2025

Genome-wide association analysis and genomic selection for leaf-related traits of maize.

Yukang Zeng, Xiaoming Xu, Jiale Jiang, Shaohang Lin, Zehui Fan, Yao Meng, Atikaimu Maimaiti, Penghao Wu, Jiaojiao Ren

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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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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

7 citing papers in PubMed.

  1. Article
  2. Mining ofHorticulture research · 2026
    Article
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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.

Yukang ZengCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Xiaoming XuCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Jiale JiangCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Shaohang LinCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Zehui FanCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Yao MengCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Atikaimu MaimaitiCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.
Penghao WuCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0001-5567-158X
Jiaojiao RenCollege of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang, China.ORCID https://orcid.org/0009-0001-3542-2954

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maize is an important food crop worldwide. The length, width, and area of leaves are crucial traits of plant architecture and further influencing plant density, photosynthesis, and crop yield. To dissect the genetic architecture of leaf length, leaf width, and leaf area, a multi-parents doubled haploid (DH) population was used for genome-wide association study (GWAS) and genomic selection (GS). The length, width, and area of the first leaf above the uppermost ear, the uppermost ear leaf, and the first leaf below the uppermost ear were evaluated in multi-environment trials. Using BLINK and FarmCPU for GWAS, 19 significant single nucleotide polymorphisms (SNPs) on chromosomes 1, 2, 5, 6, 8, 9, and 10 were associated with leaf length, 49 SNPs distributed over all 10 chromosomes were associated with leaf width, and 37 SNPs distributed on all 10 chromosomes except for chromosome 3 were associated with leaf area. The phenotypic variation explained (PVE) by each QTL ranged from 0.05% to 27.46%. Fourteen pleiotropic SNPs were detected by at least two leaf-related traits. A total of 57 candidate genes were identified for leaf-related traits, of which 44 were annotated with known functions. Candidate genes Zm00001d032866, Zm00001D022209, and Zm00001d001980 are involved in leaf senescence. Zm00001d026130, Zm00001d002429, Zm00001d023225, and Zm00001d046767 play important roles in leaf development. GS analysis showed that when 60% of the total genotypes was used as the training population and 3000 SNPs were used for prediction, moderate prediction accuracy was obtained for leaf length, leaf width, and leaf area. The prediction accuracy would be improved by using top significantly associated SNPs for GS. The current study provides a better understanding of the genetic basis of leaf length, leaf width, and leaf area, and valuable information for improving plant architecture by implementing GS.

Indexed as

Genome-Wide Association StudyPlant LeavesSelection, GeneticZea maysChromosomes, PlantGenome, PlantPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID40402953
PMCPMC12097558

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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.