Evidence map›Paper›PMID 42620842›Full record

ArticleFrontiers in plant science2026

Decoding the genetic architecture of seed quality traits in mungbean through quantitative trait loci mapping.

Chunxiu Ren, Lipan Qiao, Jiaqi Qiao, Huimei Sun, Hongjie Li, Bin Li, Xiaopeng Hao, Fan Yang, Dongao Huo

Abstract read
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Article in Frontiers in plant science, 2026. 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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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chunxiu RenCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Lipan QiaoCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Jiaqi QiaoCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Huimei SunCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Hongjie LiCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Bin LiKey Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Xiaopeng HaoCenter for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, China.
Fan YangCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.
Dongao HuoCollege of Biological Sciences and Technology, Taiyuan Normal University, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Mungbean [ Methods: In this study, a recombinant inbred line (RIL) population derived from a cross between Zhonglv1 and HB211 was developed, and phenotypic data were collected across three distinct environments. Three complementary QTL mapping methods-composite interval mapping (CIM), inclusive composite interval mapping (ICIM), and multiple QTL mapping (MQM)-were utilized to detect genomic regions associated with protein, starch, oil, and moisture content. Results and discussion: In total, 162 QTLs were identified, including 44, 30, 43, and 45 QTLs were identified for protein, starch, oil, and moisture content, respectively. Among these, stable QTLs were consistently detected across multiple environments and methods, highlighting their potential utility in breeding applications. The putative candidate genes underlying these robust QTLs were further annotated, providing preliminary insights into the genetic control of seed quality traits. This study establishes a comprehensive genetic framework for future functional studies and the development of improved mungbean varieties with enhanced seed quality.

Indexed as

candidate genemungbeanQTLRILseed quality

Identifiers

PMID42620842
PMCPMC13485905

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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.