Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.).

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

Legume seed system performance in sub-Saharan Africa: barriers, opportunities, and scaling options. A review.

As a fundamental pillar of food security in sub-Saharan Africa (SSA), ensuring seed security is critical to empowering farmers in cultivating food and livestock feed, thereby fostering income generation from agricultural outputs. Among the crops cultivated by smallholders, legumes have the potential to deliver multifaceted benefits. Legumes are nutrient-dense and enhance soil health through their nitrogen-fixing qualities. However, in many instances, the development, release, and supply of improved legume varieties are insufficient to meet the needs of smallholder farmers in SSA. Here, we systematically reviewed the literature to (i) identify and categorize existing legume seed systems, (ii) map legume varieties available to smallholders, (iii) identify barriers hindering the adoption of various legume varieties, and (iv) identify potential strategies and opportunities for strengthening legume seed systems in SSA. Our results demonstrate the coexistence of formal and informal seed systems within legume seed supply chains in SSA, each employing unique seed distribution channels. Smallholders, however, are shown to predominantly depend on the informal seed system to source most legume seeds except for commercially available varieties. We also identified a diverse range of legume varieties available to smallholders in the region, with farmers having varying trait preferences based on crop type and gender. Notably, high yield and abiotic stress tolerance were the most preferred traits. The adoption of these varieties, however, is influenced by various factors, including lack of timely access to seeds in adequate quantities from the formal seed system, high seed costs, and limited information on new varieties. The reviewed literature highlighted that utilizing improved legume varieties had a positive effect on smallholders, leading to improved welfare, food security, dietary diversity, and income. We conclude that the effective scaling of legume systems in SSA is contingent upon the presence of supportive policy frameworks and well-established technical support structures. Graphical Abstract: Packets of legume seeds within a legume germplasm and breeding program at the University of Zambia (Photo by Caitlin Breen, 2022). Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-024-00956-6.

Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) Under optimum and low nitrogen conditions.

Low soil nitrogen levels, compounded by the high costs associated with nitrogen supplementation through fertilizers, significantly contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). The discovery of genomic regions associated with low nitrogen tolerance in maize can enhance selection efficiency and facilitate the development of improved varieties. To elucidate the genetic architecture of grain yield (GY) and its associated traits (anthesis-silking interval (ASI), anthesis date (AD), plant height (PH), ear position (EPO), and ear height (EH)) under different soil nitrogen regimes, four F3 maize populations were evaluated in Kenya and Zimbabwe. GY and all the traits evaluated showed significant genotypic variance and moderate heritability under both optimum and low nitrogen stress conditions. A total of 91 quantitative trait loci (QTL) related to GY (11) and other secondary traits (AD (26), PH (19), EH (24), EPO (7) and ASI (4)) were detected. Under low soil nitrogen conditions, PH and ASI had the highest number of QTLs. Furthermore, some common QTLs were identified between secondary traits under both nitrogen regimes. These QTLs are of significant value for further validation and possible rapid introgression into maize populations using marker-assisted selection. Identification of many QTL with minor effects indicates genomic selection (GS) is more appropriate for their improvement. Genomic prediction within each population revealed low to moderately high accuracy under optimum and low soil N stress management. However, the accuracies were higher for GY, PH and EH under optimum compared to low soil N stress. Our findings indicate that genetic gain can be improved in maize breeding for low N stress tolerance by using GS.

Genome-wide association studies of grain yield and quality traits under optimum and low-nitrogen stress in tropical maize (Zea mays L.).

KEY MESSAGE: Genome-wide association study (GWAS) demonstrated that multiple genomic regions influence grain quality traits under nitrogen-starved soils. Using genomic prediction, genetic gains can be improved through selection for grain quality traits. Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.