ArticleBMC genomics2020
QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 27 citations in OpenAlex.
- Photosynthesis-informed breeding to enhance Soybean (Glycine max) yield potential: a framework integrating high-throughput phenomics, genomic prediction and G×E×M.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Iron Chlorin e6 Improves Soybean Yield by Maintaining Chlorophyll Stability and Promoting Carbohydrate Accumulation Under Saline-Alkali Stress.Plants (Basel, Switzerland) · 2026Article
- Identification of photosynthetic pigment content-related genes in peanut (Arachis hypogaea L.) by GWAS and RNA-seq.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Loss-of-function allele of the soybean flowering/maturation gene TOF11 increases free amino acid content at the edamame stage and improves eating quality.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- High resolution QTL mapping and candidate gene mining for seed oil content and fatty acid composition in soybean.BMC plant biology · 2025Article
- QTL mapping for yield contributing traits in mungbean (Vigna radiata L.) using a RIL population.Scientific reports · 2025Article
- High-density genetic map construction and QTL analysis of the first flower node in kenaf using RAD-seq.BMC plant biology · 2024Article
- Combo chloro-photosynthetic device and applications for greenhouse gas reduction campaign and smart agriculture.Heliyon · 2024Article
- Article
- Genome-Wide Association Study Identified Novel SNPs Associated with Chlorophyll Content in Maize.Genes · 2023Article
- Identifying Soybean Pod Borer (International journal of molecular sciences · 2022Article
- Construction of a high-density genetic map and localization of grazing-tolerant QTLs inFrontiers in plant science · 2022Article
- Article
- Genome-Wide Identification and Characterization of TALE Superfamily Genes in Soybean (International journal of molecular sciences · 2021Article
- Genetic Mapping by Sequencing More Precisely Detects Loci Responsible for Anaerobic Germination Tolerance in Rice.Plants (Basel, Switzerland) · 2021Article
- Utilization of a Sugarcane100K Single Nucleotide Polymorphisms Microarray-Derived High-Density Genetic Map in Quantitative Trait Loci Mapping and Function Role Prediction of Genes Related to Chlorophyll Content in Sugarcane.Frontiers in plant science · 2021Article
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5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundDifferent soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach.
resultsCorrelation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots.
conclusionsThe detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits.
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