ArticleBMC genomics2024
Characterization of genetic diversity and identification of genetic loci associated with carbon allocation in N
Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Impact ofPlants (Basel, Switzerland) · 2026Article
- YOLO-based high-throughput phenotyping pipeline for soybean nodulation traits in genomic research.Frontiers in plant science · 2026Article
- Molecular characterization and fertilizer optimization in soybean to maximize productivity and minimize environmental impact.Scientific reports · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundEfficient capture and use of resources is critical for optimal plant growth and productivity. Both shoot and root growth are essential for resource acquisition, namely light and CO
resultsA diversity panel of 402 soybean genotypes was phenotyped outdoors in a deep-tube system without addition of mineral N to measure allocation of biomass to the shoot, root, and nodules, as well as to determine nodule number, mean nodule biomass, and total shoot N accumulation. Wide ranges in phenotypes were observed for each of these traits, demonstrating extensive natural diversity in C partitioning and SNF in soybean. Using a set of 35,647 single nucleotide polymorphism (SNP) markers, we identified 121 SNPs tagging 103 QTLs that include both 84 novel and 19 previously identified QTLs for the eight examined traits. A candidate gene search identified 79 promising gene models in the vicinity of these QTLs. Favorable alleles of QTLs identified here may be used in breeding programs to develop elite cultivars with altered C partitioning.
conclusionsThis study provides novel insights into the diversity of biomass allocation in soybean and illustrates that the traits measured here are heritable and quantitative. QTLs identified in this study can be used in genomic prediction models as well as for further investigation of candidate genes and their roles in determining partitioning of fixed C. Enhancing our understanding of C partitioning in plants may lead to elite cultivars with optimized resource use efficiencies.
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