Evidence map›Paper›PMID 40098977›Full record

ArticleFrontiers in genetics2025

Identification of QTL for branch traits in soybean (

Qichao Yang, Jing Wang, Yajun Xiong, Alu Mao, Zhiqing Zhang, Yijie Chen, Shirui Teng, Zhiyu Liu, Jun Wang, Jian Song and 1 more

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In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

11 authors.

Qichao Yang *MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Jing Wang *MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Yajun Xiong *MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Alu MaoMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Zhiqing ZhangMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Yijie ChenMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Shirui TengMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Zhiyu LiuMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Jun WangMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Jian SongMARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China.
Lijuan QiuThe Shennong Laboratory, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Branches are important for soybean yield, and previous studies examining branch traits have primarily focused on branch number (BN), while research assessing branch internode number (BIN), branch length (BL), and branch internode length (BIL) remains insufficient. Methods: A recombinant inbred line (RIL) population consisting of 364 lines was constructed by crossing ZD41 and ZYD02878. Based on the RIL population, we genetically analyzed four branch traits using four different GWAS methods including efficient mixed-model association expedited, restricted two-stage multi-locus genome-wide association analysis, trait analysis by association, evolution and linkage, and three-variance-component multi-locus random-SNP-effect mixed linear model analyses. Additionally, we screened candidate genes for the major QTL and constructed a genomic selection (GS) model to assess the prediction accuracy of the four branch traits. Results and Discussion: In this study, four branch traits (BN, BIN, BL, and BIL) were phenotypically analyzed using the F

Indexed as

branchcandidate genegenomic selectionQTLsoybean

Identifiers

PMID40098977
PMCPMC11911462

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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.