Genetic differentiation analysis for the identification of complementary parental pools for sorghum hybrid breeding in Ethiopia

Prediction of biomass sorghum hybrids using environmental feature-enriched genomic combining ability models in tropical environments

KEY MESSAGE

Incorporating environmental features improved the predictive ability of genomic prediction models under multi-environment trials in tropical conditions. Gathering environmental and genomic information can benefit the breeding of sorghum hybrids by overcoming complications imposed by the genotype-by-environment interaction (GEI). In this study, we explored the value of combining environmental features (EFs) and genomic data to enhance predictions for biomass sorghum hybrid breeding, addressing GEI complexities. We also investigated if considering specific time windows for EFs improves the prediction. We used a historical dataset from a tropical biomass sorghum breeding program featuring 253 genotypes across 64 trials. Initially, a first-stage analysis was performed to obtain the adjusted means (EBLUEs) and scrutinize the impact of 29 EFs (geographic, climatic, and soil-related EFs) on GEI. Subsequently, in the second-stage analysis, we used data from 221 hybrids that had both parents genotyped to evaluate the predictive ability and assertiveness of 12 models with different effects. The most relevant EFs included soil organic carbon, insolation on a horizontal surface, longitude, temperature at dew point, and nitrogen content. Across three cross-validation scenarios (CV1, CV0, and CV00), the most effective model encompassed main combining ability effects, GEI, and G ω I (genotype-by-specific environmental effects interaction), utilizing an environmental kinship matrix ( Ω ) derived from mean EF values. Only in CV2, a model with a similar structure but utilizing Ω from specific time windows outperformed others. Our findings highlight the potential of integrating environmental and genomic data to refine predictive models for optimizing biomass sorghum hybrid breeding strategies.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

Optimizing hybrid vigor: a comprehensive analysis of genetic distance and heterosis in eggplant landraces

INTRODUCTION

This study explored the molecular characterization of 14 eggplant (brinjal) genotypes to evaluate their genetic diversity and the impact of heterosis. As eggplant is a vital horticultural crop with substantial economic and nutritional value, a comprehensive understanding of its genetic makeup and heterosis effects is essential for effective breeding strategies. Our aim was not only to dissect the genetic diversity among these genotypes but also to determine how genetic distance impacts heterotic patterns, which could ultimately help improve hybrid breeding programs.

METHODS

Genetic diversity was assessed using 20 SSR markers, and the parental lines were grouped into five clusters based on the Unweighted Pair Group Method of Arithmetic Means (UPGMA). Heterosis was examined through yield and yield-related traits among parents and hybrids.

RESULTS

Polymorphisms were detected in eight out of the twenty SSR markers across the parental lines. Notably, a high genetic distance was observed between some parents. The analysis of yield and yield-related traits demonstrated significant heterosis over mid, superior, and standard parents, particularly in fruit yield per plant. Two crosses (RKML-26 X PPC and RKML1 X PPC) displayed substantial heterosis over mid and better parents, respectively. However, the positive correlation between genetic distance and heterosis was only up to a certain threshold; moderate genetic distance often resulted in higher heterosis compared to very high genetic distance.

DISCUSSION

These findings emphasize the critical role of parental selection in hybrid breeding programs. The results contribute to the understanding of the relationship between genetic distance and heterosis, and it is suggested that future research should delve into the genetic mechanisms that drive heterosis and the effect of genetic distance variance on heterosis. The insights drawn from this study can be harnessed to enhance crop yield and economic value in breeding programs.

Development of a new AgriSeq 4K mid-density SNP genotyping panel and its utility in pearl millet breeding

Pearl millet is a crucial nutrient-rich staple food in Asia and Africa and adapted to the climate of semi-arid topics. Since the genomic resources in pearl millet are very limited, we have developed a brand-new mid-density 4K SNP panel and demonstrated its utility in genetic studies. A set of 4K SNPs were mined from 925 whole-genome sequences through a comprehensive in-silico pipeline. Three hundred and seventy-three genetically diverse pearl millet inbreds were genotyped using the newly-developed 4K SNPs through the AgriSeq Targeted Genotyping by Sequencing technology. The 4K SNPs were uniformly distributed across the pearl millet genome and showed considerable polymorphism information content (0.23), genetic diversity (0.29), expected heterozygosity (0.29), and observed heterozygosity (0.03). The SNP panel successfully differentiated the accessions into two major groups, namely B and R lines, through genetic diversity, PCA, and structure models as per their pedigree. The linkage disequilibrium (LD) analysis showed Chr3 had higher LD regions while Chr1 and Chr2 had more low LD regions. The genetic divergence between the B- and R-line populations was 13%, and within the sub-population variability was 87%. In this experiment, we have mined 4K SNPs and optimized the genotyping protocol through AgriSeq technology for routine use, which is cost-effective, fast, and highly reproducible. The newly developed 4K mid-density SNP panel will be useful in genomics and molecular breeding experiments such as assessing the genetic diversity, trait mapping, backcross breeding, and genomic selection in pearl millet.

Sorghum genetic, genomic, and breeding resources

Sorghum research has entered an exciting and fruitful era due to the genetic, genomic, and breeding resources that are now available to researchers and plant breeders. As the world faces the challenges of a rising population and a changing global climate, new agricultural solutions will need to be developed to address the food and fiber needs of the future. To that end, sorghum will be an invaluable crop species as it is a stress-resistant C₄ plant that is well adapted for semi-arid and arid regions. Sorghum has already remained as a staple food crop in many parts of Africa and Asia and is critically important for animal feed and niche culinary applications in other regions, such as the United States. In addition, sorghum has begun to be developed into a promising feedstock for forage and bioenergy production. Due to this increasing demand for sorghum and its potential to address these needs, the continuous development of powerful community resources is required. These resources include vast collections of sorghum germplasm, high-quality reference genome sequences, sorghum association panels for genome-wide association studies of traits involved in food and bioenergy production, mutant populations for rapid discovery of causative genes for phenotypes relevant to sorghum improvement, gene expression atlas, and online databases that integrate all resources and provide the sorghum community with tools that can be used in breeding and genomic studies. Used in tandem, these valuable resources will ensure that the rate, quality, and collaborative potential of ongoing sorghum improvement efforts is able to rival that of other major crops.