Validation of sorghum quality control (QC) markers across African breeding lines.

Sorghum [Sorghum bicolor (L.) Moench] is a cereal crop of critical importance in the semi-arid tropics, particularly in Africa where it is second only to maize (Zea mays L.) by area of cultivation. The International Crops Research Institute for the Semi-Arid Tropics sorghum breeding program for Eastern and Southern Africa is the largest in the region and develops improved varieties for target agro-ecologies. Varietal purity and correct confirmation of new crosses are essential for the integrity and efficiency of a breeding program. We used 49 quality control (QC) kompetitive allele-specific PCR single nucleotide polymorphism (SNP) markers to genotype 716 breeding lines. Note that 46 SNPs were polymorphic with the top 10 most informative revealing polymorphism information content (PIC), minor allele frequency (MAF), and observed heterozygosity (Ho) of 0.37, 0.43, and 0.02, respectively, and explaining 45% of genetic variance within the first two principal components (PC). Thirty-nine markers were highly informative across 16 Burkina Faso breeding lines, out of which the top 10 revealed average PIC, MAF, and Ho of 0.36, 0.39, and 0.05, respectively. Discriminant analysis of principal components done using top 30 markers separated the breeding lines into five major clusters, three of which were distinct. Six of the top 10 most informative markers successfully confirmed hybridization of crosses between genotypes IESV240, KARIMTAMA1, F6YQ212, and FRAMIDA. A set of 10, 20, and 30 most informative markers are recommended for routine QC applications. Future effort should focus on the deployment of these markers in breeding programs for enhanced genetic gain.

Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources.

Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.

Genetic diversity analysis of East African sorghum (Sorghum bicolor [L.] Moench) germplasm collections for agronomic and nutritional quality traits.

Breeding for climate-resilient, high-yielding, and nutrient-rich sorghum cultivars is essential for sustainable food systems and enhanced livelihoods in sub-Saharan Africa. Therefore, this study aimed to determine the genetic diversity among East African sorghum germplasm collections through agronomic and nutritional quality traits to select promising lines for direct production or breeding. A collection of 348 sorghum germplasm was field evaluated at two locations in Uganda using an augmented design, and grain iron (Fe) and zinc (Zn) contents were profiled. Data were collected on 20 sorghum agro-morphological traits and Fe and Zn compositions. A significant (P ≤ 0.05) variation was detected amongst the test genotypes for all the assessed traits, suggesting the presence of sufficient genetic diversity for selection. High heritability (H2 > 0.60) and genetic advance as percent of the mean (GA >20%) were computed for grain yield, Zn content, and selected agronomic traits, ensuring genetic gains through selection. A significant positive correlation was recorded between Fe and Zn concentrations (r = 0.32, P < 0.001), allowing simultaneous selection for the two nutrient compositions. Cluster analysis based on phenotypic traits resolved the test sorghum genotypes into four distinct genetic groups. Six genotypes with superior agronomic traits and high Fe and Zn contents were identified for production or potential parents for quality breeding. Overall, the current study found considerable genetic variation among East African sorghum germplasm collections for strategic conservation and breeding in Uganda or similar agro-ecologies.

Genotypic Variation in Cultivated and Wild Sorghum Genotypes in Response to Striga hermonthica Infestation.

Striga hermonthica is the most important parasitic weed in sub-Saharan Africa and remains one of the most devastating biotic factors affecting sorghum production in the western regions of Kenya. Farmers have traditionally managed Striga using cultural methods, but the most effective and practical solution to poor smallholder farmers is to develop Striga-resistant varieties. This study was undertaken with the aim of identifying new sources of resistance to Striga in comparison with the conventional sources as standard checks. We evaluated 64 sorghum genotypes consisting of wild relatives, landraces, improved varieties, and fourth filial generation (F4) progenies in both a field trial and a pot trial. Data were collected for days to 50% flowering (DTF), dry panicle weight (DPW, g), plant height (PH, cm), yield (YLD, t ha-1), 100-grain weight (HGW, g), overall disease score (ODS), overall pest score (OPS), area under Striga number progress curve (ASNPC), maximum above-ground Striga (NSmax), and number of Striga-forming capsules (NSFC) at relevant stages. Genetic diversity and hybridity confirmation was determined using Diversity Arrays Technology sequencing (DArT-seq). Residual heterosis for HGW and NSmax was calculated as the percent increase or decrease in performance of F4 crossover midparent (MP). The top 10 best yielding genotypes were predominantly F4 crosses in both experiments, all of which yielded better than resistant checks, except FRAMIDA in the field trial and HAKIKA in the pot trial. Five F4 progenies (ICSVIII IN × E36-1, LANDIWHITE × B35, B35 × E36-1, F6YQ212 × B35, and ICSVIII IN × LODOKA) recorded some of the highest HGW in both trials revealing their stability in good performance. Three genotypes (F6YQ212, GBK045827, and F6YQ212xB35) and one check (SRN39) were among the most resistant to Striga in both trials. SNPs generated from DArT-seq grouped the genotypes into three major clusters, with all resistant checks grouping in the same cluster except N13. We identified more resistant and high-yielding genotypes than the conventional checks, especially among the F4 crosses, which should be promoted for adoption by farmers. Future studies will need to look for more diverse sources of Striga resistance and pyramid different mechanisms of resistance into farmer-preferred varieties to enhance the durability of Striga resistance in the fields of farmers.

Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain.

Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.

Compilation of an informative microsatellite set for genetic characterisation of East African finger millet (Eleusine coracana)

Background Genetic diversity of finger millet (Eleusine coracana), a nutritious neglected staple cereal in Africa and South Asia is largely uncharacterized. This study analysed 82 published SSR markers for finger millet across 10 diverse accessions to compile an informative set for genetic characterisation. Extensive optimization compared single samples with bulked leaf or bulked DNA samples for capturing within accession genetic diversity. The markers were evaluated to determine (1) how efficiently they amplified target loci during high-throughput genotyping with a generic PCR protocol, (2) ease of scoring PCR products and (3) polymorphism and ability to discern genetic diversity within the tested finger millet germplasm. Results Across 88 samples, the 52 markers that worked well amplified 274 alleles, ranging from 2 to 14 per locus with a mean of 4.89. Major allele frequency ranged from 0.18 to 0.93 with a mean of 0.57. Polymorphic Information Content (PIC) ranged from 0.13 to 0.88 with a mean of 0.5 and availability varied between 64 and 100% with a mean of 92.8%. Heterozygosity ranged from 0 to 1.0, with a mean of 0.26. Discussion Five individual samples from an accession captured the largest number of alleles per locus compared to the four different bulked sampling strategies but this difference was not significant. The identified set comprised 20 markers: UGEP24, UGEP53, UGEP84, UGEP27, UGEP98, UGEP95, UGEP64, UGEP33, UGEP67, UGEP106, UGEP110, UGEP57, UGEP96, UGEP66, UGEP46, UGEP79, UGEP20, UGEP12, UGEP73 and UGEP5 and was since used to assess East African finger millet genetic diversity in two separate studies.