Getahun Addisu, Alemu Admas, Nida Habte, Woldesemayat Adugna Abdi
College of Applied and Natural Sciences (CANS), Department of Biotechnology, Addis Ababa Science and Technology University (AASTU), Addis Ababa, Ethiopia.
Biotechnology and Bioprocess Center of Excellence, AASTU, Addis Ababa, Ethiopia.
BMC Genomics. 2025 Mar 28;26(1):304. doi: 10.1186/s12864-025-11458-4.
Sorghum is a vital cereal crop for over 750 million 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.
Explore 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.
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 α-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 ≥ 4.0. 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.
Pearson 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 (0.003). A total of 351,692 SNP markers were identified across 10 sorghum chromosomes from 216 Ethiopian sorghum landraces, and we have been refining this to 50,165 filtered SNPs. Manhattan plots indicated significant marker-trait associations (MTAs) across multiple chromosomes, particularly for days to flowering and plant height. Significant QTNs were associated with key traits including flowering time, plant height, and grain yield. ML-GWAS identified 176 QTNs with varying LOD scores and phenotypic effects. Multiple genes linked to these QTNs highlight the complexity of genetic interactions of studied traits with 36 unique and 12 major QTNs. Notable SNP markers were concentrated on chromosomes 1, 2, and 3, reinforcing the importance of these regions for breeding efforts. Candidate gene analysis revealed key genes regulating flowering time, stress response, and yield traits, which could serve as targets for genetic enhancement. In our study, key candidate genes have been successfully identified, these are regulating flowering time, maturity, and stress resilience. Genes such as Sobic.001G196700 and Sobic.002G183400 are identified as critical regulators of floral development. The stress-responsive gene Sobic.005G176100 (a mannose-6-phosphate isomerase), emphasizes the importance of resilience in sorghum cultivation under adverse conditions. Additionally, Sobic.003G324400 and Sobic.004G178300 are essential for regulating plant height and seed weight, making them valuable for yield enhancement breeding programs.
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.
高粱是超过7.5亿人的重要谷物作物，在全球排名第五。它有多种用途，包括食品、饲料和生物燃料，在埃塞俄比亚至关重要，该国不同农业生态区拥有丰富的遗传多样性。
利用多位点全基因组关联研究（GWAS）模型探索标记-性状关联（MTA），以识别埃塞俄比亚高粱地方品种中与农艺和产量贡献性状相关的数量性状核苷酸（QTN）和新的候选基因，辅助基因组辅助育种策略。
本研究通过多位点全基因组关联研究（ML-GWAS）调查埃塞俄比亚高粱地方品种农艺性状的遗传基础。从埃塞俄比亚生物多样性研究所和国家高粱改良计划获得了216个地方品种、改良品种和对照品种用于本研究。试验在两个种植季节进行，采用α-格子设计对开花天数、成熟天数、株高、单株种子数、籽粒产量和千粒重等关键性状进行表型分析。使用混合线性模型（MLM）分析表型数据并估计包括方差和广义遗传力在内的遗传参数。用ApeKI限制酶进行的简化基因组测序（GBS）提供了50165个高质量单核苷酸多态性（SNP）标记。六个ML-GWAS模型确定了LOD得分阈值≥4.0的显著QTN。分析揭示了多个染色体上与性状相关的主要QTN，严格的筛选标准确保了其可靠性。利用高粱QTL图谱数据库探索与已知QTL的共定位，并通过Phytozome平台使用biomaRt软件包鉴定显著QTN区域内的候选基因，确定影响农艺性能的遗传结构。
Pearson相关性分析显示，除单株籽粒产量与其他性状的相关性较低外，大多数性状之间存在显著关联，p值小于0.0001。遗传变异性分析表明，开花天数表现出高遗传力（0.7）和作为均值百分比的遗传进展（约19.6%），表明有较强的遗传控制，而籽粒产量的遗传力极低（0.003）。从216个埃塞俄比亚高粱地方品种中，在10条高粱染色体上共鉴定出351692个SNP标记，我们已将其精炼为50165个过滤后的SNP。曼哈顿图表明多个染色体上存在显著的标记-性状关联（MTA），特别是对于开花天数和株高。显著的QTN与包括开花时间、株高和籽粒产量在内的关键性状相关。ML-GWAS鉴定出176个具有不同LOD得分和表型效应的QTN。与这些QTN连锁的多个基因突出了所研究性状遗传相互作用复杂程度，有36个独特的和12个主要的QTN。显著的SNP标记集中在第1、2和3号染色体上，强化了这些区域在育种工作中的重要性。候选基因分析揭示了调控开花时间、胁迫响应和产量性状的关键基因，这些基因可作为遗传改良的靶点。在我们的研究中，已成功鉴定出关键候选基因，这些基因调控开花时间、成熟和胁迫恢复力。如Sobic.001G196700和Sobic.002G183400等基因被确定为花发育的关键调节因子。胁迫响应基因Sobic.005G176100（一种甘露糖-6-磷酸异构酶），强调了在不利条件下高粱种植中恢复力的重要性。此外，Sobic.003G324400和Sobic.004G|78300对调控株高和种子重量至关重要，使其对提高产量的育种计划具有重要价值。
本研究增进了我们对埃塞俄比亚高粱地方品种遗传多样性的理解，这对育种计划至关重要。它鉴定出与重要农艺性状相关的关键QTN和候选基因，为标记辅助和基因组辅助育种提供了见解。ML-GWAS模型突出了开花时间和籽粒产量性状的遗传复杂性，强调需要有针对性的育种努力以最大化高粱生产力。
