Evidence map›Paper›PMID 41013176›Full record

ArticleBMC genomic data2025

Genome-wide identification of QTNs and candidate genes in Ethiopian sorghum (Sorghum bicolor (L.) moench) landraces using SNP-based approaches.

Addisu Getahun, Habte Nida, Adugna Abdi Woldesemayat

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Article in BMC genomic data, 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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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Addisu GetahunCollege of Natural and Applied Sciences (CNAS), Department of Biotechnology, Addis Ababa Science and Technology University (AASTU), 16417, Addis Ababa, Ethiopia.
Habte NidaPurdue University, 610 Purdue Mall, West Lafayette, IN, 47907, USA.
Adugna Abdi WoldesemayatCollege of Natural and Applied Sciences (CNAS), Department of Biotechnology, Addis Ababa Science and Technology University (AASTU), 16417, Addis Ababa, Ethiopia. adugnaabdi@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSorghum, a diploid C4 cereal (2n = 2x = 20) with a 750 Mbp genome, is widely adaptable to tropical and temperate climates. As its center of origin and diversity, Ethiopia holds valuable genetic variation for improving yield and nutritional traits. This study aimed to identify and functionally characterize quantitative trait nucleotides (QTNs) linked to key agronomic and yield-related traits and their associated candidate genes.

methodsTwo hundred sixteen sorghum genotypes were evaluated over two seasons in northwestern Ethiopia using an alpha lattice design. Agronomic traits assessed included days to flowering, days to maturity, plant height, seed number per plant, seed yield, and thousand-seed weight. Genotyping-by-sequencing (GBS) generated 351,692 SNPs, with 50,165 high-quality markers retained. Candidate gene identification and functional characterization were carried out using a combination of bioinformatics tools and publicly available databases. Data normalization and analysis were conducted using META-R and SAS JMP. Linkage disequilibrium was assessed via TASSEL 5.0, and multi-locus genome-wide association study (ML-GWAS) identified significant QTNs (LOD ≥ 4.0) associated with phenotypic traits.

resultThis study investigates the genetic basis of key agronomic and yield related traits in sorghum by identifying QTNs associated with phenotypic variation. Descriptive statistics revealed notable variability in traits such as days to flowering (101 days), days to maturity (145.77 days), plant height (357.47 cm), seed number per plant (1808.92 count), seed yield (45.07 g), and thousand-seed weight (23.44 g). Correlation analysis showed strong relationships, particularly between days to flowering and maturity (r = 0.7058). ML-GWAS detected 176 QTNs across all 10 chromosomes, with 34 considered reliable Due to their consistent identification across multiple models. 117 candidate genes were mapped to these QTNs, associated with six major traits: 20 for flowering time, 16 for maturity, 16 for plant height, 17 for seed number per plant, 38 for seed yield, and 10 for seed weight. Key genes included Sobic.001G196700 (flowering time) and Sobic.005G176100 (stress responses). Two important regulatory genes, SbMADS1 and SbFT, were highlighted for their roles in flowering regulation. SbMADS1 influences days to flowering, while SbFT acts as a mobile signal integrating photoperiod cues. These genes are involved in starch and sucrose metabolism pathways, essential for energy storage and mobilization, thereby supporting improved growth and yield in sorghum.

conclusionThis study highlights the complexity of trait inheritance shaped by diverse genetic factors and underscores the significance of major, stable, and unique QTNs for marker-assisted selection. Functional genome annotation revealed that candidate genes are involved in key biological processes and metabolic pathways, including starch and sucrose metabolism, secondary metabolism, and hormonal signaling.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociSorghumEthiopiaGenes, PlantGenome, PlantGenome-Wide Association StudyGenotypeLinkage DisequilibriumPhenotypeCandidate genesGenome-wide association studyMetabolic pathwaysQuantitative trait nucleotidesSorghum bicolor

Identifiers

PMID41013176
PMCPMC12465425

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LicenceCC BY-NC-ND
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