Genetic dissection of sorghum grain quality traits using diverse and segregating populations

Transcriptome and metabolome analyses reveal regulatory networks associated with nutrition synthesis in sorghum seeds

Cereal seeds are vital for food, feed, and agricultural sustainability because they store and provide essential nutrients to human and animal food and feed systems. Unraveling molecular processes in seed development is crucial for enhancing cereal grain yield and quality. We analyze spatiotemporal transcriptome and metabolome profiles during sorghum seed development in the inbred line 'BTx623'. Morphological and molecular analyses identify the key stages of seed maturation, specifying starch biosynthesis onset at 5 days post-anthesis (dpa) and protein at 10 dpa. Transcriptome profiling from 1 to 25 dpa reveal dynamic gene expression pathways, shifting from cellular growth and embryo development (1-5 dpa) to cell division, fatty acid biosynthesis (5-25 dpa), and seed storage compounds synthesis in the endosperm (5-25 dpa). Network analysis identifies 361 and 207 hub genes linked to starch and protein synthesis in the endosperm, respectively, which will help breeders enhance sorghum grain quality. The availability of this data in the sorghum reference genome line establishes a baseline for future studies as new pangenomes emerge, which will consider copy number and presence-absence variation in functional food traits.

Ameliorating the effects of multiple stresses on agronomic traits in crops: modern biotechnological and omics approaches

While global climate change poses a significant environmental threat to agriculture, the increasing population is another big challenge to food security. To address this, developing crop varieties with increased productivity and tolerance to biotic and abiotic stresses is crucial. Breeders must identify traits to ensure higher and consistent yields under inconsistent environmental challenges, possess resilience against emerging biotic and abiotic stresses and satisfy customer demands for safer and more nutritious meals. With the advent of omics-based technologies, molecular tools are now integrated with breeding to understand the molecular genetics of genotype-based traits and develop better climate-smart crops. The rapid development of omics technologies offers an opportunity to generate novel datasets for crop species. Identifying genes and pathways responsible for significant agronomic traits has been made possible by integrating omics data with genetic and phenotypic information. This paper discusses the importance and use of omics-based strategies, including genomics, transcriptomics, proteomics and phenomics, for agricultural and horticultural crop improvement, which aligns with developing better adaptability in these crop species to the changing climate conditions.

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.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

Genome-wide association study reveals genomic loci influencing agronomic traits in Ethiopian sorghum (Sorghum bicolor (L.) Moench) landraces

Uncovering the genetic basis of agronomic traits in sorghum landraces that have adapted to various agro-climatic conditions would contribute to sorghum improvement efforts around the world. To identify quantitative trait nucleotides (QTNs) associated with nine agronomic traits in a panel of 304 sorghum accessions collected from diverse environments across Ethiopia (considered to be the center of origin and diversity), multi-locus genome-wide association studies (ML-GWAS) were performed using 79,754 high quality single nucleotide polymorphism (SNP) markers. Association analyses using six ML-GWAS models identified a set of 338 significantly (LOD ≥ 3)-associated QTNs for nine agronomic traits of sorghum accessions evaluated in two environments (E1 and E2) and their combined dataset (Em). Of these, 121 reliable QTNs, including 13 for flowering time (DF), 13 for plant height (PH), 9 for tiller number (TN), 15 for panicle weight (PWT), 30 for grain yield per panicle (GYP), 12 for structural panicle mass (SPM), 13 for hundred seed weight (HSW), 6 for grain number per panicle (GNP), and 10 for panicle exertion (PE) were consistently detected by at least three ML-GWAS methods and/or in two different environments. Notably, Ethylene responsive transcription factor gene AP2/ERF, known for regulation of plant growth, and the sorghum Terminal flower1/TF1 gene, which functions in the control of floral architecture, were identified as strong candidate genes associated with PH and HSW, respectively. This study provides an entry point for further validation studies to elucidate complex mechanisms controlling important agronomic traits in sorghum.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01381-5.

Evaluation of genetic variability for major agro-morphological and stalk sugar traits in African sorghum genotypes

The study aimed to assess one hundred and twelve (112) accessions of sorghum sourced from Nigeria and other four African countries for their genetic variability, heritability (broad sense) and genetic advance components to identify promising accessions with high grain yield and sweet stalk which can serve as future parents for breeding dual-purpose lines. The accessions were evaluated at Ilora, Oyo State, Nigeria in a randomized complete block design (RCBD) layout with three replicates in two planting seasons (2020 and 2021). The results showed that the phenotypic coefficient of variation (PCV) was higher than the genotypic coefficient of variation (GCV). The highest PCV and GCV were grain yield (51.89%) and inflorescence length (42.26%), respectively, while a hundred seed grain weight had the lowest PCV (17.83%) and GCV (21.55%). The range of genetic advance over mean (GAM) was 28.33% for leaf width and 81.62% for inflorescence length. Inflorescence length had the highest values of heritability and GAM (0.88, 81.62%), while a low value was obtained for grain yield (0.27, 29.32%). Twenty-two accessions had higher grain yields than the yields of check varieties. The high-yielding accessions, SG57, SG31, SG06, and SG12 had grain yields of 3.07 t/ha, 2.89 t/ha, 2.76 t/ha and 2.73 t/ha, respectively. Fourteen accessions had wet stalks, of which 12 of the accessions had soluble stalk sugar (Brix) above 12%, which is comparable to the amount found in sweet sorghum. Three accessions with Brix above 12% (SG16, SG31, SG32) and high grain yields (2.32 t/ha, 2.89 t/ha and 2.02 t/ha) were identified as promising accessions. There is considerable genetic diversity among African sorghum accessions in Nigeria's southwest agroecosystem, which should improve food security and breeding potential.

Host Determinants of Fungal Species Composition and Symptom Manifestation in the Sorghum Grain Mold Disease Complex

Sorghum grain mold (SGM) is an important multifungal disease complex affecting sorghum (Sorghum bicolor) production systems worldwide. SGM-affected sorghum grain can be contaminated with potent fumonisin mycotoxins produced by Fusarium verticillioides, a prevalent SGM-associated taxon. Historically, efforts to improve resistance to SGM have achieved only limited success. Classical approaches to evaluating SGM resistance are based solely on disease severity, which offers little insight regarding the distinct symptom manifestations within the disease complex. In this study, three novel phenotypes were developed to facilitate assessment of SGM symptom manifestation. A sorghum diversity panel composed of 390 accessions was inoculated with endogenous strains of F. verticillioides and evaluated for these phenotypes, as well as for the conventional panicle grain mold severity rating phenotype, in South Carolina, U.S.A., in 2017 and 2019. Distributions of phenotype values were examined, broad-sense heritability was estimated, and relationships to botanical race were explored. A typology of SGM symptom manifestations was developed to classify accessions using principal component analysis and k-means clustering, constituting a novel option for basing breeding decisions on SGM outcomes more nuanced than disease severity. Genome-wide association studies were performed using SGM trait data, resulting in the identification of 19 significant single nucleotide polymorphisms in linkage disequilibrium with a total of 86 gene models. Our findings provide a basis of exploratory evidence regarding the genetic architecture of SGM symptom manifestation and indicate that traits other than disease severity could be tractable targets for SGM resistance breeding.

Genetic analysis of seed traits in Sorghum bicolor that affect the human gut microbiome

Prebiotic fibers, polyphenols and other molecular components of food crops significantly affect the composition and function of the human gut microbiome and human health. The abundance of these, frequently uncharacterized, microbiome-active components vary within individual crop species. Here, we employ high throughput in vitro fermentations of pre-digested grain using a human microbiome to identify segregating genetic loci in a food crop, sorghum, that alter the composition and function of human gut microbes. Evaluating grain produced by 294 sorghum recombinant inbreds identifies 10 loci in the sorghum genome associated with variation in the abundance of microbial taxa and/or microbial metabolites. Two loci co-localize with sorghum genes regulating the biosynthesis of condensed tannins. We validate that condensed tannins stimulate the growth of microbes associated with these two loci. Our work illustrates the potential for genetic analysis to systematically discover and characterize molecular components of food crops that influence the human gut microbiome.

Diet affects the human gut microbiome, but studies linking crop genetics to seed traits that influence the human gut microbiome are lacking. Here, the authors develop an in vitro microbiome screening method and reveal the association between sorghum genes regulating condensed tannin biosynthesis and human gut microbiome.

Sorghum Association Panel whole-genome sequencing establishes cornerstone resource for dissecting genomic diversity

Association mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole-genome sequencing (WGS) of 400 sorghum (Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25-72×), enabling the development of a high-density genomic marker set of 43 983 694 variants including single-nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower-density marker sets. WGS identified and scored variants in 5-kb bins where available genotyping-by-sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six F_st peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources.

Near Infrared Spectroscopic Evaluation of Starch Properties of Diverse Sorghum Populations

Starch, mainly composed of amylose and amylopectin, is the major nutrient in grain sorghum. Amylose and amylopectin composition affects the starch properties of sorghum flour which in turn determine the suitability of sorghum grains for various end uses. Partial least squares regression models on near infrared (NIR) spectra were developed to estimate starch and amylose contents in intact grain sorghum samples. Sorghum starch calibration model with a coefficient of determination (R2) = 0.87, root mean square error of cross validation (RMSECV) = 1.57% and slope = 0.89 predicted the starch content of validation set with R2 = 0.76, root mean square error of prediction (RMSEP) = 2.13%, slope = 0.93 and bias = 0.20%. Amylose calibration model with R2 = 0.84, RMSECV = 2.96% and slope = 0.86 predicted the amylose content in validation samples with R2 = 0.76, RMSEP = 2.60%, slope = 0.98 and bias = −0.44%. Final starch and amylose cross validated calibration models were constructed combining respective calibration and validation sets and used to predict starch and amylose contents in 1337 grain samples from two diverse sorghum populations. Protein and moisture contents of the samples were determined using previously tested NIR spectroscopy models. The distribution of starch and protein contents in the samples of low amylose (<5%) and normal amylose (>15%) and the overall relationship between starch and protein contents of the sorghum populations were investigated. Percent starch and protein were negatively correlated, low amylose lines tended to have lower starch and higher protein contents than lines with high amylose. The results showed that NIR spectroscopy of whole grain can be used as a high throughput pre-screening method to identify sorghum germplasm with specific starch quality traits to develop hybrids for various end uses.

Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects

Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

Biochemical composition of selected lines from sorghum (Sorghum bicolor L.) landraces

Present findings revealed a great variation in protein, oil, starch, tannin and phytic acid-like biochemical attributes of sorghum genotypes. GT bi-plot analysis was used for assessment of biochemical analysis results. Sorghum is quite resistant to negative environmental conditions. Thus, it has become the basic source of nutrient in majority of developing countries. It is also used as a supporting product against several diseases. In this study, biochemical composition of new 154 sorghum lines, selected from Turkish sorghum landraces through morphological, biochemical and molecular studies, was determined. Present findings revealed based on average of two years that crude protein content of 80 lines (> 9.65%), digestible protein content of 94 lines (> 56.25%), crude oil content of 75 lines (> 3.87%), resistant starch ratio of 32 lines (> 3.93%), starch content of two lines (> 77.07%) and amylose content of 10 lines (> %25.26) were greater than standard cultivar with the greatest values and amylopectin contents of 74 lines (< 47.75%) were lower than the standard cultivar with the lowest values. As the average of years, phytic acid contents and condense tannins contents of the lines, respectively, varied between 0.02 (IS 12850/1)-6.49% (PI 177161 03/2) and 0.09 (IS 12819/1)-5.38% (PI 255738 02/3). With this study, several sorghum lines superior than the standard cultivars were identified. Those lines can be used for direct cultivar registration in short run and can be used as parent materials in further breeding studies to be conducted for various purposes in long run.

Sorghum breeding in the genomic era: opportunities and challenges

The importance and potential of the multi-purpose crop sorghum in global food security have not yet been fully exploited, and the integration of the state-of-art genomics and high-throughput technologies into breeding practice is required. Sorghum, a historically vital staple food source and currently the fifth most important major cereal, is emerging as a crop with diverse end-uses as food, feed, fuel and forage and a model for functional genetics and genomics of tropical grasses. Rapid development in high-throughput experimental and data processing technologies has significantly speeded up sorghum genomic researches in the past few years. The genomes of three sorghum lines are available, thousands of genetic stocks accessible and various genetic populations, including NAM, MAGIC, and mutagenised populations released. Functional and comparative genomics have elucidated key genetic loci and genes controlling agronomical and adaptive traits. However, the knowledge gained has far away from being translated into real breeding practices. We argue that the way forward is to take a genome-based approach for tailored designing of sorghum as a multi-functional crop combining excellent agricultural traits for various end uses. In this review, we update the new concepts and innovation systems in crop breeding and summarise recent advances in sorghum genomic researches, especially the genome-wide dissection of variations in genes and alleles for agronomically important traits. Future directions and opportunities for sorghum breeding are highlighted to stimulate discussion amongst sorghum academic and industrial communities.

Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-offs in Sorghum

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome wide association studies conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

Genetic diversity for starch quality and alkali spreading value in sorghum

Sorghum is an important food crop in many parts of Africa and Asia. Landraces of sorghum are known to exhibit variation in food quality traits including starch and protein content and composition. In this study, a panel of diverse sorghum breeding lines and 788 sorghum conversion (SC) lines representing the global germplasm diversity of the crop were evaluated for variation in starch quality based on alkali spreading value (ASV). A small number of genotypes with stable expression of the ASV+ phenotype across seasons were identified; mostly representing Nandyal types from India. Genetic studies showed the ASV+ phenotype was inherited as a recessive trait. Whole genome resequencing of ASV+ donor lines revealed SNPs in genes involved in starch biosynthesis. A genome wide association study (GWAS) identified a significant SNP associated with ASV near Sobic.010G273800, a starch branching enzyme I precursor, and Sobic.010G274800 and Sobic.010G275001, both annotated as glucosyltransferases. Physiochemical analyses of accessions with contrasting ASV phenotypes demonstrated an environment dependent lower starch gelatinization temperature (GT), amylose content of approximately 22%, and good gel consistency. The starch quality attributes of these lines could be valuable in food products that require good gel consistency and viscosity.

Identification of Novel Genomic Associations and Gene Candidates for Grain Starch Content in Sorghum

Starch accumulated in the endosperm of cereal grains as reserve energy for germination serves as a staple in human and animal nutrition. Unraveling genetic control for starch metabolism is important for breeding grains with high starch content. In this study, we used a sorghum association panel with 389 individuals and 141,557 single nucleotide polymorphisms (SNPs) to fit linear mixed models (LMM) for identifying genomic regions and potential candidate genes associated with starch content. Three associated genomic regions, one in chromosome (chr) 1 and two novel associations in chr-8, were identified using combination of LMM and Bayesian sparse LMM. All significant SNPs were located within protein coding genes, with SNPs ∼ 52 Mb of chr-8 encoding a Casperian strip membrane protein (CASP)-like protein (Sobic.008G111500) and a heat shock protein (HSP) 90 (Sobic.008G111600) that were highly expressed in reproductive tissues including within the embryo and endosperm. The HSP90 is a potential hub gene with gene network of 75 high-confidence first interactors that is enriched for five biochemical pathways including protein processing. The first interactors of HSP90 also showed high transcript abundance in reproductive tissues. The candidates of this study are likely involved in intricate metabolic pathways and represent candidate gene targets for source-sink activities and drought and heat stress tolerance during grain filling.

QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in Plants

Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. While it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as the training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. The average precision was 0.027 for Arabidopsis and 0.029 for rice. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. In addition, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.

Genome-wide variations analysis of sorghum cultivar Hongyingzi for brewing Moutai liquor

Background

Hongyingzi is a sorghum (Sorghum bicolor L. Moench) cultivar for brewing Moutai liquor. For an overall understanding of the whole genome of Hongyingzi, we performed whole-genome resequencing technology to reveal its comprehensive variations.

Results

Compared with the BTx623 reference genome, we uncovered 1,885,774 single nucleotide polymorphisms (SNPs), 309,381 small fragments insertions and deletions (Indels), 31,966 structural variations (SVs), and 217,273 copy number variations (CNVs). These alterations conferred 29,614 gene variations. It was also predicted that 35 gene variations were related to the multidrug and toxic efflux (MATE) transporter, chalcone synthase (CHS), ATPase isoform 10 (AHA10) transporter, dihydroflavonol-4-reductase (DFR), the laccase 15 (LAC15), flavonol 3′-hydroxylase (F3′H), flavanone 3-hydroxylase (F3H), O-methyltransferase (OMT), flavonoid 3′5′ hydroxylase (F3′5′H), UDP-glucose:sterol-glucosyltransferase (SGT), flavonol synthase (FLS), and chalcone isomerase (CHI) involved in the tannin synthesis.

Conclusions

These results would provide theoretical supports for the molecular markers developments and gene function studies related to the tannin synthesis, and the genetic improvement of liquor-making sorghum based on the genome editing technology.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Genome-wide association study reveals that different pathways contribute to grain quality variation in sorghum (Sorghum bicolor)

BACKGROUND

In sorghum (Sorghum bicolor), one paramount breeding objective is to increase grain quality. The nutritional quality and end use value of sorghum grains are primarily influenced by the proportions of tannins, starch and proteins, but the genetic basis of these grain quality traits remains largely unknown. This study aimed to dissect the natural variation of sorghum grain quality traits and identify the underpinning genetic loci by genome-wide association study.

RESULTS

Levels of starch, tannins and 17 amino acids were quantified in 196 diverse sorghum inbred lines, and 44 traits based on known metabolic pathways and biochemical interactions amongst the 17 amino acids calculated. A Genome-wide association study (GWAS) with 3,512,517 SNPs from re-sequencing data identified 14, 15 and 711 significant SNPs which represented 14, 14, 492 genetic loci associated with levels of tannins, starch and amino acids in sorghum grains, respectively. Amongst these significant SNPs, two SNPs were associated with tannin content on chromosome 4 and colocalized with three previously identified loci for Tannin1, and orthologs of Zm1 and TT16 genes. One SNP associated with starch content colocalized with sucrose phosphate synthase gene. Furthermore, homologues of opaque1 and opaque2 genes associated with amino acid content were identified. Using the KEGG pathway database, six and three candidate genes of tannins and starch were mapped into 12 and 3 metabolism pathways, respectively. Thirty-four candidate genes were mapped into 16 biosynthetic and catabolic pathways of amino acids. We finally reconstructed the biosynthetic pathways for aspartate and branched-chain amino acids based on 15 candidate genes identified in this study.

CONCLUSION

Promising candidate genes associated with grain quality traits have been identified in the present study. Some of them colocalized with previously identified genetic regions, but novel candidate genes involved in various metabolic pathways which influence grain quality traits have been dissected. Our study acts as an entry point for further validation studies to elucidate the complex mechanisms controlling grain quality traits such as tannins, starch and amino acids in sorghum.

Genetic Architecture of Chilling Tolerance in Sorghum Dissected with a Nested Association Mapping Population

Dissecting the genetic architecture of stress tolerance in crops is critical to understand and improve adaptation. In temperate climates, early planting of chilling-tolerant varieties could provide longer growing seasons and drought escape, but chilling tolerance (<15°) is generally lacking in tropical-origin crops. Here we developed a nested association mapping (NAM) population to dissect the genetic architecture of early-season chilling tolerance in the tropical-origin cereal sorghum (Sorghum bicolor [L.] Moench). The NAM resource, developed from reference line BTx623 and three chilling-tolerant Chinese lines, is comprised of 771 recombinant inbred lines genotyped by sequencing at 43,320 single nucleotide polymorphisms. We phenotyped the NAM population for emergence, seedling vigor, and agronomic traits (>75,000 data points from ∼16,000 plots) in multi-environment field trials in Kansas under natural chilling stress (sown 30-45 days early) and normal growing conditions. Joint linkage mapping with early-planted field phenotypes revealed an oligogenic architecture, with 5-10 chilling tolerance loci explaining 20-41% of variation. Surprisingly, several of the major chilling tolerance loci co-localize precisely with the classical grain tannin (Tan1 and Tan2) and dwarfing genes (Dw1 and Dw3) that were under strong directional selection in the US during the 20^th century. These findings suggest that chilling sensitivity was inadvertently selected due to coinheritance with desired nontannin and dwarfing alleles. The characterization of genetic architecture with NAM reveals why past chilling tolerance breeding was stymied and provides a path for genomics-enabled breeding of chilling tolerance.

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high-throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype-phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.

QTL mapping and validation of fertility restoration in West African sorghum A1 cytoplasm and identification of a potential causative mutation for Rf2

Key message Major A ₁ cytoplasm fertility restoration loci, Rf ₂ and Rf ₅ , were found in the West African sorghum. A potential causative mutation for Rf ₂ was identified. KASP markers were validated on independent material. To accelerate the identification and development of hybrid parental lines in West African (WA) sorghum, this study aimed to understand the genetics underlying the fertility restoration (Rf) in WA A₁ cytoplasmic male sterility system and to develop markers for a routine use in WA breeding programs. We genotyped by sequencing three F₂ populations to map the Rf quantitative trait loci (QTL), validated the molecular KASP markers developed from those QTL in two F_2:3 populations, and assessed the most promising markers on a set of 95 R- and B-lines from WA breeding programs. Seven QTL were found across the three F₂ populations. On chromosome SBI-05, we found a major fertility restorer locus (Rf₅) for two populations with the same male parent, explaining 19 and 14% of the phenotypic variation in either population. Minor QTL were detected in these two populations on chromosomes SBI-02, SBI-03, SBI-04 and SBI-10. In the third population, we identified one major fertility restorer locus on chromosome SBI-02, Rf₂, explaining 31% of the phenotypic variation. Pentatricopeptide repeat genes in the Rf₂ QTL region were sequenced, and we detected in Sobic.002G057050 a missense mutation in the first exon, explaining 81% of the phenotypic variation in a F_2:3 population and clearly separating B- from R-lines. The KASP marker developed from this mutation stands as a promising tool for routine use in WA breeding programs.

Genome-Wide Association Studies for Five Forage Quality-Related Traits in Sorghum (Sorghum bicolor L.)

Understanding the genetic function of the forage quality-related traits, including crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose (HC), and cellulose (CL) contents, is essential for the identification of forage quality genes and selection of effective molecular markers in sorghum. In this study, we genotyped 245 sorghum accessions by 85,585 single-nucleotide polymorphisms (SNPs) and obtained the phenotypic data from four environments. The SNPs and phenotypic data were applied to multi-locus genome-wide association studies (GWAS) with the mrMLM software. A total of 42 SNPs were identified to be associated with the five forage quality-related traits. Moreover, three and two quantitative trait nucleotides (QTNs) were simultaneously detected among them by three and two multi-locus methods, respectively. One QTN on chromosome 5 was found to be associated simultaneously with CP, NDF, and ADF. Furthermore, 3, 2, 2, 5, and 2 candidate genes were identified to be responsible for CP, NDF, ADF, HC, and CL contents, respectively. These results provided insightful information of the forage quality-related traits and would facilitate the genetic improvement of sorghum forage quality in the future.