Evidence map›Paper›PMID 39940920›Full record

ArticleInternational journal of molecular sciences2025

Integration of Genetic and Imaging Data to Detect QTL for Root Traits in Interspecific Soybean Populations.

Mohammad Shafiqul Islam, Jeong-Dong Lee, Qijian Song, Hyun Jo, Yoonha Kim

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Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mohammad Shafiqul IslamDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea.ORCID 0009-0000-9247-4489
Jeong-Dong LeeDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea.ORCID 0000-0003-3474-0384
Qijian SongSoybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville Agricultural Research Center, Beltsville, MD 20705, USA.
Hyun JoDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea.ORCID 0000-0002-2741-4049
Yoonha KimDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea.ORCID 0000-0003-0058-9161

Funding

Basic Science Research Program through the National Research Foundation of Korea 2021R1I1A3040280Korea Basic Science Institute (National Research Facilities and Equipment Centre) grant funded by the Ministry of Education 2021R1A6C101A416
6 · The paper itself

Abstract

Wild soybean, which has many desirable traits, such as adaptability to climate change-related stresses, is a valuable resource for expanding the narrow genetic diversity of cultivated soybeans. Plants require roots to adapt to different environments and optimize water and nutrient uptake to support growth and facilitate the storage of metabolites; however, it is challenging and costly to evaluate root traits under field conditions. Previous studies of quantitative trait loci (QTL) have been mainly based on cultivated soybean populations. In this study, an interspecific mapping population from a cross between wild soybean 'PI483463' and cultivar 'Hutcheson' was used to investigate QTLs associated with root traits using image data. Our results showed that 39 putative QTLs were distributed across 10 chromosomes (chr.). Seventeen of these were clustered in regions on chr. 8, 14, 15, 16, and 17, accounting for 19.92% of the phenotypic variation. We identified five significant QTL clusters influencing root-related traits, such as total root length, surface area, lateral total length, and number of tips, across five chr., with favorable alleles from both wild and cultivated soybeans. Furthermore, we identified eight candidate genes controlling these traits based on functional annotation. These genes were highly expressed in root tissues and directly or indirectly affected soybean root growth, development, and stress responses. Our results provide valuable insights for breeders aiming to optimize soybean root traits and leveraging genetic diversity from wild soybean species to develop varieties with improved root morphological traits, ultimately enhancing overall plant growth, productivity, and resilience.

Indexed as

Glycine maxPlant RootsQuantitative Trait LociChromosome MappingChromosomes, PlantPhenotypecandidate genesQTLRILsroot morphological traitsSNPsoybean

Identifiers

PMID39940920
PMCPMC11817972

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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.