Evidence map›Paper›PMID 40888956›Full record

ArticlePlant cell reports2025

Identification of key candidate genes regulating hundred-grain weight in the maize inbred line Ye107 from Southern China.

Xiaoli Hong, Ranjan K Shaw, Fuyan Jiang, Jiachen Sun, Yaqi Bi, Xiao Wu, Tao Dai, Fengli Ye, Jiaguo Zhu, Tingting Guan and 2 more

Abstract read
In one paragraph

Article in Plant cell reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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

12 authors.

Xiaoli HongInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Ranjan K ShawInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Fuyan JiangInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Jiachen SunInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Yaqi BiInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Xiao WuInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Tao DaiInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Fengli YeInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Jiaguo ZhuInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Tingting GuanInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Chunxia XuInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
Xingming FanInstitute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China. xingmingfan@163.com.ORCID http://orcid.org/0009-0009-4742-9246

Funding

Yunnan Province High-Level Talent and Innovation Team Program 202405AS350030
6 · The paper itself

Abstract

key messageA potential candidate gene regulating maize hundred-grain weight was identified in the Ye107 inbred line through a genome-wide association study and QTL mapping, providing insights for high-yield maize breeding. Hundred-grain weight (HGW) is a key agronomic trait that significantly affects maize yield. Identifying HGW-related candidate genes is crucial for genetic improvement of maize. To overcome the limitations of traditional association panels in dissecting complex traits and to improve detection power and accuracy, this study constructed a multi-parent population (MPP). The MPP, consisting of 482 F

Indexed as

Edible GrainGenes, PlantZea maysChinaChromosome MappingGenome-Wide Association StudyInbreedingPhenotypePlant BreedingPolymorphism, Single NucleotideQuantitative Trait LociCandidate genesGEBVGWASHundred-grain weightMaizeQTL mapping

Identifiers

PMID40888956
PMCPMC12402048

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.