ArticleBMC plant biology2025
Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage.
Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Genome-wide association analysis reveals genetic variations and candidate genes associated with tannin and starch contents in sorghum.BMC genomics · 2026Article
- Biotechnological and genetic innovations to enhance sorghum adaptation under climate change.Frontiers in plant science · 2026Review
- Unearthing the hidden organ: vital role of the root in drought tolerance of plants.Plant molecular biology · 2025Review
- Classification of Heterotic Groups and Prediction of Heterosis in Sorghum Based on Whole-Genome Resequencing.International journal of molecular sciences · 2025Article
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8 authors.
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Abstract
Root system architecture (RSA) plays an important role in plant adaptation to drought stress. However, the genetic basis of RSA in sorghum has not been adequately elucidated. This study aimed to investigate the genetic bases of RSA traits through genome-wide association studies (GWAS) and determine genomic prediction (GP) accuracy in sorghum landraces at the seedling stage. Phenotypic data for nodal root angle (NRA), number of nodal roots (NNR), nodal root length (NRL), fresh shoot weight (FSW), dry shoot weight (DSW), and leaf area (LA) were collected from 160 sorghum accessions grown in soil-based rhizotrons. The sorghum panel was genotyped with 5,000 single nucleotide polymorphism (SNP) markers for use in the current GWAS and GP studies. A multi-locus model, Fixed and random model Circulating Probability Unification (FarmCPU), was applied for GWAS analysis. For GP, ridge-regression best linear unbiased prediction (RR-BLUP) and five different Bayesian models were applied. A total of 17 SNP loci significantly associated with the studied traits were identified, of which nine are novel loci. Among the traits, the highest number of significant marker-trait associations (MTAs) was identified for nodal root angle on chromosomes 1, 3, 6, and 7. The SNP loci that explain the highest proportion of phenotypic variance (PVE) include sbi32853830 (PVE = 18.2%), sbi29954292 (PVE = 18.1%), sbi24668980 (PVE = 10.8%), sbi3022983 (PVE = 7%), sbi29897704 (PVE = 6.4%) and sbi29897694 (PVE = 5.3%) for the traits NNR, LA, SDW, NRA, NRL and SFW, respectively. The genomic prediction accuracy estimated for the studied traits using five Bayesian models ranged from 0.30 to 0.63 while it ranged from 0.35 to 0.60 when the RR-BLUP model was used. The observed moderate to high prediction accuracy for each trait suggests that genomic selection could be a feasible approach to sorghum RSA-targeted selection and breeding. Overall, the present study provides insights into the genetic bases of RSA and offers an opportunity to speed up breeding for drought-tolerant sorghum varieties.
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