{
    "abstract": "Sorghum is a vital cereal crop for over 750\u00a0million people, ranking 5th globally. It has multiple purposes, including food, feed, and biofuels, and is essential in Ethiopia, which has a rich genetic diversity of various agroecological zones.\nExplore marker-trait associations (MTAs) to identify quantitative trait nucleotides (QTNs) and new candidate genes associated with agronomic and yield contributing traits in Ethiopian sorghum landraces using multi-locus GWAS models to assist the genomic-assisted breeding strategies.\nThis study investigates the genetic basis of agronomic traits in Ethiopian sorghum landraces through multi-locus Genome-Wide Association Studies (ML-GWAS). 216 landraces, improved varieties, and check cultivars were obtained from the Ethiopian Biodiversity Institute and the National Sorghum Improvement Program for this study. The experiment was conducted over two cropping seasons, employing an \u03b1-lattice design for phenotyping key traits such as days to flowering, days to maturity, plant height, seed number per plant, grain yield, and thousand seed weight. A mixed linear model (MLM) was used to analyze the phenotypic data and estimate the genetic parameters including variances and the broad sense heritability. GBS with the ApeKI restriction enzyme provided 50,165 high-quality SNP markers. The six ML-GWAS models identified significant QTNs with a LOD score threshold value of \u2265\u20094.0. The analysis revealed major QTNs associated with traits across multiple chromosomes, supported by a stringent filtering criterion that ensured reliability. Co-localization with known QTLs was explored using the Sorghum QTL Atlas database and candidate genes within significant QTN regions, providing the genetic architecture influencing agronomic performance were identified via the Phytozome platform using the biomaRt package.\nPearson correlation analysis revealed significant associations among most traits, with p-values less than 0.0001, except for grain yield per plant which showed lower correlations with other traits. Genetic variability analysis indicated that days to flowering exhibited high heritability (0.7) and genetic advance (19.6%) as percent of mean, suggesting strong genetic control, while grain yield displayed extremely low h\nThis study enhances our understanding of the genetic diversity of Ethiopian sorghum landraces, crucial for breeding programs. It identifies key QTNs and candidate genes associated with important agronomic traits, offering insights for marker-assisted and genomic-assisted breeding. The ML-GWAS models highlight the genetic complexity of flowering time and grain yield traits, emphasizing the need for targeted breeding efforts to maximize sorghum productivity.",
    "authors": [
        {
            "affiliation": "College of Applied and Natural Sciences (CANS), Department of Biotechnology, Addis Ababa Science and Technology University (AASTU), Addis Ababa, Ethiopia.\nBiotechnology and Bioprocess Center of Excellence, AASTU, Addis Ababa, Ethiopia.\nCollege of Agriculture, Food and Climate Sciences, Department of Plant Sciences, Injibara University, Injibara, Ethiopia.",
            "firstname": "Addisu",
            "initials": "A",
            "lastname": "Getahun"
        },
        {
            "affiliation": "Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Almas All\u00e9 8, Lomma, Uppsala, 750 07, Sweden.",
            "firstname": "Admas",
            "initials": "A",
            "lastname": "Alemu"
        },
        {
            "affiliation": "Purdue University, 610 Purdue Mall, West Lafayette, IN, 47907, USA.",
            "firstname": "Habte",
            "initials": "H",
            "lastname": "Nida"
        },
        {
            "affiliation": "College of Applied and Natural Sciences (CANS), Department of Biotechnology, Addis Ababa Science and Technology University (AASTU), Addis Ababa, Ethiopia. adugna.abdi@aastu.edu.et.\nBiotechnology and Bioprocess Center of Excellence, AASTU, Addis Ababa, Ethiopia. adugna.abdi@aastu.edu.et.",
            "firstname": "Adugna Abdi",
            "initials": "AA",
            "lastname": "Woldesemayat"
        }
    ],
    "conclusions": "This study enhances our understanding of the genetic diversity of Ethiopian sorghum landraces, crucial for breeding programs. It identifies key QTNs and candidate genes associated with important agronomic traits, offering insights for marker-assisted and genomic-assisted breeding. The ML-GWAS models highlight the genetic complexity of flowering time and grain yield traits, emphasizing the need for targeted breeding efforts to maximize sorghum productivity.",
    "copyrights": "\u00a9 2025. The Author(s).",
    "doi": "10.1186/s12864-025-11458-4",
    "journal": "BMC genomics",
    "keywords": [
        "Agronomic traits",
        "Candidate genes",
        "Genetic diversity",
        "ML-GWAS",
        "Quantitative trait nucleotides",
        "Sorghum bicolor"
    ],
    "methods": "This study investigates the genetic basis of agronomic traits in Ethiopian sorghum landraces through multi-locus Genome-Wide Association Studies (ML-GWAS). 216 landraces, improved varieties, and check cultivars were obtained from the Ethiopian Biodiversity Institute and the National Sorghum Improvement Program for this study. The experiment was conducted over two cropping seasons, employing an \u03b1-lattice design for phenotyping key traits such as days to flowering, days to maturity, plant height, seed number per plant, grain yield, and thousand seed weight. A mixed linear model (MLM) was used to analyze the phenotypic data and estimate the genetic parameters including variances and the broad sense heritability. GBS with the ApeKI restriction enzyme provided 50,165 high-quality SNP markers. The six ML-GWAS models identified significant QTNs with a LOD score threshold value of \u2265\u20094.0. The analysis revealed major QTNs associated with traits across multiple chromosomes, supported by a stringent filtering criterion that ensured reliability. Co-localization with known QTLs was explored using the Sorghum QTL Atlas database and candidate genes within significant QTN regions, providing the genetic architecture influencing agronomic performance were identified via the Phytozome platform using the biomaRt package.",
    "publication_date": "2025-03-29",
    "pubmed_id": "40155810\n37312746\n30025025\n19609454\n33655424\n35360320\n28314933\n38475993\n23876160\n15821975\n16157678\n27898806\n23267105\n28028582\n33346083\n28141824\n28295030\n29234158\n29868068\n32972357\n30524459\n37730954\n23647851\n33276449\n0\n31191590\n35269548\n33871028\n36552318\n26316679\n18757942\n25237111\n23982223\n26056993\n17891371\n30969968\n24884377\n25122453\n23459955\n28769949\n38270755\n23708149\n33341904\n30804969\n27898829\n34376143\n29590108\n33217211\n24832503\n21573248\n33217211\n30100085\n26787347\n26719772\n22045659\n34492338\n22796960\n28158525\n30343386\n19144180\n22110026\n36344939\n17586829",
    "results": null,
    "title": "Multi-locus genome-wide association mapping for major agronomic and yield-related traits in sorghum (Sorghum bicolor (L.) moench) landraces.",
    "xml": "<Element 'PubmedArticle' at 0x78850346e840>"
}