Complete telomere-to-telomere assemblies of two sorghum genomes to guide biological discovery.

The assembly of two sorghum T2T genomes corrected the assembly errors in the current reference, uncovered centromere variation, boosted functional genomics research, and accelerated sorghum improvement.

Genetic dissection of root architecture in Ethiopian sorghum landraces.

KEY MESSAGE: This study quantified genetic variation in root system architecture (root number, angle, length and dry mass) within a diversity panel of 1771 Ethiopian sorghum landraces and identified 22 genomic regions associated with the root variations. The root system architecture (RSA) of crop plants influences adaptation to water-limited conditions and determines the capacity of a plant to access soil water and nutrients. Four key root traits (number, angle, length and dry mass) were evaluated in a diversity panel of 1771 Ethiopian sorghum landraces using purpose-built root chambers. Significant genetic variation was observed in all studied root traits, with nodal root angle ranging from 16.4° to 26.6°, with a high repeatability of 78.9%. Genome wide association studies identified a total of 22 genomic regions associated with root traits which were distributed on all chromosomes except chromosome SBI-10. Among the 22 root genomic regions, 15 co-located with RSA trait QTL previously identified in sorghum, with the remaining seven representing novel RSA QTL. The majority (85.7%) of identified root angle QTL also co-localized with QTL previously identified for stay-green in sorghum. This suggests that the stay-green phenotype might be associated with root architecture that enhances water extraction during water stress conditions. The results open avenues for manipulating root phenotypes to improve productivity in abiotic stress environments via marker-assisted selection.

Variation in mitogenome structural conformation in wild and cultivated lineages of sorghum corresponds with domestication history and plastome evolution.

BACKGROUND: Mitochondria are organelles within eukaryotic cells that are central to the metabolic processes of cellular respiration and ATP production. However, the evolution of mitochondrial genomes (mitogenomes) in plants is virtually unknown compared to animal mitogenomes or plant plastids, due to complex structural variation and long stretches of repetitive DNA making accurate genome assembly more challenging. Comparing the structural and sequence differences of organellar genomes within and between sorghum species is an essential step in understanding evolutionary processes such as organellar sequence transfer to the nuclear genome as well as improving agronomic traits in sorghum related to cellular metabolism. RESULTS: Here, we assembled seven sorghum mitochondrial and plastid genomes and resolved reticulated mitogenome structures with multilinked relationships that could be grouped into three structural conformations that differ in the content of repeats and genes by contig. The grouping of these mitogenome structural types reflects the two domestication events for sorghum in east and west Africa. CONCLUSIONS: We report seven mitogenomes of sorghum from different cultivars and wild sources. The assembly method used here will be helpful in resolving complex genomic structures in other plant species. Our findings give new insights into the structure of sorghum mitogenomes that provides an important foundation for future research into the improvement of sorghum traits related to cellular respiration, cytonuclear incompatibly, and disease resistance.

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency.

KEY MESSAGE: Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program. Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow individual leaf width has been correlated with greater intrinsic water use efficiency in C4 species, the extent to which this translates to greater plant TE has not been investigated. The aims of this study were to evaluate the correlation of leaf width with TE at the whole-plant scale and investigate the genetic control of leaf width in sorghum. Two lysimetry experiments using 16 genotypes varying for stomatal conductance and three field trials using a large sorghum diversity panel (n = 701 lines) were conducted. Negative associations of leaf width with plant TE were found in the lysimetry experiments, suggesting narrow leaves may result in reduced plant transpiration without trade-offs in biomass accumulation. A wide range in width of the largest leaf was found in the sorghum diversity panel with consistent ranking among sorghum races, suggesting that environmental adaptation may have a role in modifying leaf width. Nineteen QTL were identified by genome-wide association studies on leaf width adjusted for flowering time. The QTL identified showed high levels of correspondence with those in maize and rice, suggesting similarities in the genetic control of leaf width across cereals. Three a priori candidate genes for leaf width, previously found to regulate dorsoventrality, were identified based on a 1-cM threshold. This study provides useful physiological and genetic insights for potential manipulation of leaf width to improve plant adaptation to diverse environments.

Genetic modification of PIN genes induces causal mechanisms of stay-green drought adaptation phenotype.

The stay-green trait is recognized as a key drought adaptation mechanism in cereals worldwide. Stay-green sorghum plants exhibit delayed senescence of leaves and stems, leading to prolonged growth, a reduced risk of lodging, and higher grain yield under end-of-season drought stress. More than 45 quantitative trait loci (QTL) associated with stay-green have been identified, including two major QTL (Stg1 and Stg2). However, the contributing genes that regulate functional stay-green are not known. Here we show that the PIN FORMED family of auxin efflux carrier genes induce some of the causal mechanisms driving the stay-green phenotype in sorghum, with SbPIN4 and SbPIN2 located in Stg1 and Stg2, respectively. We found that nine of 11 sorghum PIN genes aligned with known stay-green QTL. In transgenic studies, we demonstrated that PIN genes located within the Stg1 (SbPIN4), Stg2 (SbPIN2), and Stg3b (SbPIN1) QTL regions acted pleiotropically to modulate canopy development, root architecture, and panicle growth in sorghum, with SbPIN1, SbPIN2, and SbPIN4 differentially expressed in various organs relative to the non-stay-green control. The emergent consequence of such modifications in canopy and root architecture is a stay-green phenotype. Crop simulation modelling shows that the SbPIN2 phenotype can increase grain yield under drought.

Genetic and genomic diversity in the sorghum gene bank collection of Uganda.

BACKGROUND: The Plant Genetic Resources Centre at the Uganda National Gene Bank houses has over 3000 genetically diverse landraces and wild relatives of Sorghum bicolor accessions. This genetic diversity resource is untapped, under-utilized, and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole-genome SNP markers (DArTseq). Discriminant analysis of principal components (DAPC) was implemented to study the racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize the sub-groups present in the Ugandan (UG) germplasm. RESULTS: Population structure and phylogenetic analysis revealed the presence of five subgroups among the Ugandan accessions. The samples from the highlands of the southwestern region were genetically distinct as compared to the rest of the population. This subset was predominated by the caudatum race and unique in comparison to the other sub-populations. In this study, we detected QTL for juvenile cold tolerance by genome-wide association studies (GWAS) resulting in the identification of 4 markers associated (-log10p > 3) to survival under cold stress under both field and climate chamber conditions, located on 3 chromosomes (02, 06, 09). To our best knowledge, the QTL on Sb09 with the strongest association was discovered for the first time. CONCLUSION: This study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining. In face of adverse climate change, identification of genomic regions potentially involved in the adaptation of Ugandan sorghum accessions to cooler climatic conditions would be of interest for the expansion of sorghum production into temperate latitudes.

Maximizing value of genetic sequence data requires an enabling environment and urgency.

Severe price spikes of the major grain commodities and rapid expansion of cultivated area in the past two decades are symptoms of a severely stressed global food supply. Scientific discovery and improved agricultural productivity are needed and are enabled by unencumbered access to, and use of, genetic sequence data. In the same way the world witnessed rapid development of vaccines for COVID-19, genetic sequence data afford enormous opportunities to improve crop production. In addition to an enabling regulatory environment that allowed for the sharing of genetic sequence data, robust funding fostered the rapid development of coronavirus diagnostics and COVID-19 vaccines. A similar level of commitment, collaboration, and cooperation is needed for agriculture.

Decoding the sorghum methylome: understanding epigenetic contributions to agronomic traits.

DNA methylation is a chromatin modification that plays an essential role in regulating gene expression and genome stability and it is typically associated with gene silencing and heterochromatin. Owing to its heritability, alterations in the patterns of DNA methylation have the potential to provide for epigenetic inheritance of traits. Contemporary epigenomic technologies provide information beyond sequence variation and could supply alternative sources of trait variation for improvement in crops such as sorghum. Yet, compared with other species such as maize and rice, the sorghum DNA methylome is far less well understood. The distribution of CG, CHG, and CHH methylation in the genome is different compared with other species. CG and CHG methylation levels peak around centromeric segments in the sorghum genome and are far more depleted in the gene dense chromosome arms. The genes regulating DNA methylation in sorghum are also yet to be functionally characterised; better understanding of their identity and functional analysis of DNA methylation machinery mutants in diverse genotypes will be important to better characterise the sorghum methylome. Here, we catalogue homologous genes encoding methylation regulatory enzymes in sorghum based on genes in Arabidopsis, maize, and rice. Discovering variation in the methylome may uncover epialleles that provide extra information to explain trait variation and has the potential to be applied in epigenome-wide association studies or genomic prediction. DNA methylation can also improve genome annotations and discover regulatory elements underlying traits. Thus, improving our knowledge of the sorghum methylome can enhance our understanding of the molecular basis of traits and may be useful to improve sorghum performance.

Genetic control of leaf angle in sorghum and its effect on light interception.

Developing sorghum genotypes adapted to different light environments requires understanding of a plant's ability to capture light, determined through leaf angle specifically. This study dissected the genetic basis of leaf angle in 3 year field trials at two sites, using a sorghum diversity panel (729 accessions). A wide range of variation in leaf angle with medium heritability was observed. Leaf angle explained 36% variation in canopy light extinction coefficient, highlighting the extent to which variation in leaf angle influences light interception at the whole-canopy level. This study also found that the sorghum races of Guinea and Durra consistently having the largest and smallest leaf angle, respectively, highlighting the potential role of leaf angle in adaptation to distinct environments. The genome-wide association study detected 33 quantitative trait loci (QTLs) associated with leaf angle. Strong synteny was observed with previously detected leaf angle QTLs in maize (70%) and rice (40%) within 10 cM, among which the overlap was significantly enriched according to χ2 tests, suggesting a highly consistent genetic control in grasses. A priori leaf angle candidate genes identified in maize and rice were found to be enriched within a 1-cM window around the sorghum leaf angle QTLs. Additionally, protein domain analysis identified the WD40 protein domain as being enriched within a 1-cM window around the QTLs. These outcomes show that there is sufficient heritability and natural variation in the angle of upper leaves in sorghum which may be exploited to change light interception and optimize crop canopies for different contexts.

Manipulating assimilate availability provides insight into the genes controlling grain size in sorghum.

Variation in grain size, a major determinant of grain yield and quality in cereal crops, is determined by both the plant's genetic potential and the available assimilate to fill the grain in the absence of stress. This study investigated grain size variation in response to variation in assimilate supply in sorghum using a diversity panel (n = 837) and a backcross-nested association mapping population (n = 1421) across four experiments. To explore the effects of genetic potential and assimilate availability on grain size, the top half of selected panicles was removed at anthesis. Results showed substantial variation in five grain size parameters with high heritability. Artificial reduction in grain number resulted in a general increase in grain weight, with the extent of the increase varying across genotypes. Genome-wide association studies identified 44 grain size quantitative trait locus (QTL) that were likely to act on assimilate availability and 50 QTL that were likely to act on genetic potential. This finding was further supported by functional enrichment analysis and co-location analysis with known grain number QTL and candidate genes. RNA interference and overexpression experiments were conducted to validate the function of one of the identified gene, SbDEP1, showing that SbDEP1 positively regulates grain number and negatively regulates grain size by controlling primary branching in sorghum. Haplotype analysis of SbDEP1 suggested a possible role in racial differentiation. The enhanced understanding of grain size variation in relation to assimilate availability presented in this study will benefit sorghum improvement and have implications for other cereal crops.

Extensive variation within the pan-genome of cultivated and wild sorghum.

Sorghum is a drought-tolerant staple crop for half a billion people in Africa and Asia, an important source of animal feed throughout the world and a biofuel feedstock of growing importance. Cultivated sorghum and its inter-fertile wild relatives constitute the primary gene pool for sorghum. Understanding and characterizing the diversity within this valuable resource is fundamental for its effective utilization in crop improvement. Here, we report analysis of a sorghum pan-genome to explore genetic diversity within the sorghum primary gene pool. We assembled 13 genomes representing cultivated sorghum and its wild relatives, and integrated them with 3 other published genomes to generate a pan-genome of 44,079 gene families with 222.6 Mb of new sequence identified. The pan-genome displays substantial gene-content variation, with 64% of gene families showing presence/absence variation among genomes. Comparisons between core genes and dispensable genes suggest that dispensable genes are important for sorghum adaptation. Extensive genetic variation was uncovered within the pan-genome, and the distribution of these variations was influenced by variation of recombination rate and transposable element content across the genome. We identified presence/absence variants that were under selection during sorghum domestication and improvement, and demonstrated that such variation had important phenotypic outcomes that could contribute to crop improvement. The constructed sorghum pan-genome represents an important resource for sorghum improvement and gene discovery.

Genomic resources in plant breeding for sustainable agriculture.

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Large-scale genome-wide association study reveals that drought-induced lodging in grain sorghum is associated with plant height and traits linked to carbon remobilisation.

KEY MESSAGE: We detected 213 lodging QTLs and demonstrated that drought-induced stem lodging in grain sorghum is substantially associated with stay-green and plant height suggesting a critical role of carbon remobilisation. Sorghum is generally grown in water limited conditions and often lodges under post-anthesis drought, which reduces yield and quality. Due to its complexity, our understanding on the genetic control of lodging is very limited. We dissected the genetic architecture of lodging in grain sorghum through genome-wide association study (GWAS) on 2308 unique hybrids grown in 17 Australian sorghum trials over 3 years. The GWAS detected 213 QTLs, the majority of which showed a significant association with leaf senescence and plant height (72% and 71%, respectively). Only 16 lodging QTLs were not associated with either leaf senescence or plant height. The high incidence of multi-trait association for the lodging QTLs indicates that lodging in grain sorghum is mainly associated with plant height and traits linked to carbohydrate remobilisation. This result supported the selection for stay-green (delayed leaf senescence) to reduce lodging susceptibility, rather than selection for short stature and lodging resistance per se, which likely reduces yield. Additionally, our data suggested a protective effect of stay-green on weakening the association between lodging susceptibility and plant height. Our study also showed that lodging resistance might be improved by selection for stem composition but was unlikely to be improved by selection for classical resistance to stalk rots.

Genetic Diversity of C4 Photosynthesis Pathway Genes in Sorghum bicolor (L.).

C4 photosynthesis has evolved in over 60 different plant taxa and is an excellent example of convergent evolution. Plants using the C4 photosynthetic pathway have an efficiency advantage, particularly in hot and dry environments. They account for 23% of global primary production and include some of our most productive cereals. While previous genetic studies comparing phylogenetically related C3 and C4 species have elucidated the genetic diversity underpinning the C4 photosynthetic pathway, no previous studies have described the genetic diversity of the genes involved in this pathway within a C4 crop species. Enhanced understanding of the allelic diversity and selection signatures of genes in this pathway may present opportunities to improve photosynthetic efficiency, and ultimately yield, by exploiting natural variation. Here, we present the first genetic diversity survey of 8 known C4 gene families in an important C4 crop, Sorghum bicolor (L.) Moench, using sequence data of 48 genotypes covering wild and domesticated sorghum accessions. Average nucleotide diversity of C4 gene families varied more than 20-fold from the NADP-malate dehydrogenase (MDH) gene family (θπ = 0.2 × 10-3) to the pyruvate orthophosphate dikinase (PPDK) gene family (θπ = 5.21 × 10-3). Genetic diversity of C4 genes was reduced by 22.43% in cultivated sorghum compared to wild and weedy sorghum, indicating that the group of wild and weedy sorghum may constitute an untapped reservoir for alleles related to the C4 photosynthetic pathway. A SNP-level analysis identified purifying selection signals on C4 PPDK and carbonic anhydrase (CA) genes, and balancing selection signals on C4 PPDK-regulatory protein (RP) and phosphoenolpyruvate carboxylase (PEPC) genes. Allelic distribution of these C4 genes was consistent with selection signals detected. A better understanding of the genetic diversity of C4 pathway in sorghum paves the way for mining the natural allelic variation for the improvement of photosynthesis.

Multi-environment analysis of sorghum breeding trials using additive and dominance genomic relationships.

KEY MESSAGE: Multi-environment models using marker-based kinship information for both additive and dominance effects can accurately predict hybrid performance in different environments. Sorghum is an important hybrid crop that is grown extensively in many subtropical and tropical regions including Northern NSW and Queensland in Australia. The highly varying weather patterns in the Australian summer months mean that sorghum hybrids exhibit a great deal of variation in yield between locations. To ultimately enable prediction of the outcome of crossing parental lines, both additive effects on yield performance and dominance interaction effects need to be characterised. This paper demonstrates that fitting a linear mixed model that includes both types of effects calculated using genetic markers in relationship matrices improves predictions. Genotype by environment interactions was investigated by comparing FA1 (single-factor analytic) and FA2 (two-factor analytic) structures. The G×E causes a change in hybrid rankings between trials with a difference of up to 25% of the hybrids in the top 10% of each trial. The prediction accuracies increased with the addition of the dominance term (over and above that achieved with an additive effect alone) by an average of 15% and a maximum of 60%. The percentage of dominance of the total genetic variance varied between trials with the trials with higher broad-sense heritability having the greater percentage of dominance. The inclusion of dominance in the factor analytic models improves the accuracy of the additive effects. Breeders selecting high yielding parents for crossing need to be aware of effects due to environment and dominance.

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals.

Grain size is a key yield component of cereal crops and a major quality attribute. It is determined by a genotype's genetic potential and its capacity to fill the grains. This study aims to dissect the genetic architecture of grain size in sorghum. An integrated genome-wide association study (GWAS) was conducted using a diversity panel (n = 837) and a BC-NAM population (n = 1421). To isolate genetic effects associated with genetic potential of grain size, rather than the genotype's capacity to fill the grains, a treatment of removing half of the panicle was imposed during flowering. Extensive and highly heritable variation in grain size was observed in both populations in 5 field trials, and 81 grain size QTL were identified in subsequent GWAS. These QTL were enriched for orthologues of known grain size genes in rice and maize, and had significant overlap with SNPs associated with grain size in rice and maize, supporting common genetic control of this trait among cereals. Grain size genes with opposite effect on grain number were less likely to overlap with the grain size QTL from this study, indicating the treatment facilitated identification of genetic regions related to the genetic potential of grain size. These results enhance understanding of the genetic architecture of grain size in cereal, and pave the way for exploration of underlying molecular mechanisms and manipulation of this trait in breeding practices.

Crop Genomics Goes Beyond a Single Reference Genome.

The inadequacy of a single reference genome to capture the full landscape of genetic diversity within a species constrains exploration of genetic variation for crop improvement. A recent study by Yang et al. has demonstrated the value of multiple reference-quality genomes in capturing structural variants and guiding biological discovery.

Genomic Prediction of Grain Yield and Drought-Adaptation Capacity in Sorghum Is Enhanced by Multi-Trait Analysis.

Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorghum breeding for broad adaptation to a range of environments. Genomic prediction for these traits may be enhanced by joint multi-trait analysis. The objectives of this study were to assess the capacity of multi-trait models to improve genomic prediction of parental breeding values for grain yield and stay-green in sorghum by using information from correlated auxiliary traits, and to determine the combinations of traits that optimize predictive results in specific scenarios. The dataset included phenotypic performance of 2645 testcross hybrids across 26 environments as well as genomic and pedigree information on their female parental lines. The traits considered were grain yield (GY), stay-green (SG), plant height (PH), and flowering time (FT). We evaluated the improvement in predictive performance of multi-trait G-BLUP models relative to single-trait G-BLUP. The use of a blended kinship matrix exploiting pedigree and genomic information was also explored to optimize multi-trait predictions. Predictive ability for GY increased up to 16% when PH information on the training population was exploited through multi-trait genomic analysis. For SG prediction, full advantage from multi-trait G-BLUP was obtained only when GY information was also available on the predicted lines per se, with predictive ability improvements of up to 19%. Predictive ability, unbiasedness and accuracy of predictions from conventional multi-trait G-BLUP were further optimized by using a combined pedigree-genomic relationship matrix. Results of this study suggest that multi-trait genomic evaluation combining routinely measured traits may be used to improve prediction of crop productivity and drought adaptability in grain sorghum.

Combining pedigree and genomic information to improve prediction quality: an example in sorghum.

KEY MESSAGE: The use of a kinship matrix integrating pedigree- and marker-based relationships optimized the performance of genomic prediction in sorghum, especially for traits of lower heritability. Selection based on genome-wide markers has become an active breeding strategy in crops. Genomic prediction models can make use of pedigree information to account for the residual polygenic effects not captured by markers. Our aim was to evaluate the impact of using pedigree and genomic information on prediction quality of breeding values for different traits in sorghum. We explored BLUP models that use weighted combinations of pedigree and genomic relationship matrices. The optimal weighting factor was empirically determined in order to maximize predictive ability after evaluating a range of candidate weights. The phenotypic data consisted of testcross evaluations of sorghum parental lines across multiple environments. All lines were genotyped, and full pedigree information was available. The performance of the best predictive combined matrix was compared to that of models fitting the component matrices independently. Model performance was assessed using cross-validation technique. Fitting a combined pedigree-genomic matrix with the optimal weight always yielded the largest increases in predictive ability and the largest reductions in prediction bias relative to the simple G-BLUP. However, the weight that optimized prediction varied across traits. The benefits of including pedigree information in the genomic model were more relevant for traits with lower heritability, such as grain yield and stay-green. Our results suggest that the combination of pedigree and genomic relatedness can be used to optimize predictions of complex traits in crops when the additive variation is not fully explained by markers.