Sorghum Dw2 Encodes a Protein Kinase Regulator of Stem Internode Length

Unveiling shared genetic regulators of plant architectural and biomass yield traits in the Sorghum Association Panel

Sorghum is emerging as an ideal genetic model for designing high-biomass bioenergy crops. Biomass yield, a complex trait influenced by various plant architectural characteristics, is typically regulated by numerous genes. This study aimed to dissect the genetic regulators underlying 14 plant architectural traits and 10 biomass yield traits in the Sorghum Association Panel across two growing seasons. We identified 321 associated loci through genome-wide association studies (GWAS), involving 234 264 single nucleotide polymorphisms (SNPs). These loci include genes with known associations to biomass traits, such as maturity, dwarfing (Dw), and leafbladeless1, as well as several uncharacterized loci not previously linked to these traits. We also identified 22 pleiotropic loci associated with variation in multiple phenotypes. Three of these loci, located on chromosomes 3 (S03_15463061), 6 (S06_42790178; Dw2), and 9 (S09_57005346; Dw1), exerted significant and consistent effects on multiple traits across both growing seasons. Additionally, we identified three genomic hotspots on chromosomes 6, 7, and 9, each containing multiple SNPs associated with variation in plant architecture and biomass yield traits. Chromosome-wise correlation analyses revealed multiple blocks of positively associated SNPs located near or within the same genomic regions. Finally, genome-wide correlation-based network analysis showed that loci associated with flowering, plant height, leaf traits, plant density, and tiller number per plant were highly interconnected with other genetic loci influencing plant architectural and biomass yield traits. The pyramiding of favorable alleles related to these traits holds promise for enhancing the future development of bioenergy sorghum crops.

The protein kinases KIPK and KIPK-LIKE1 suppress overbending during negative hypocotyl gravitropic growth in Arabidopsis

Plants use environmental cues to orient organ and plant growth, such as the direction of gravity or the direction, quantity, and quality of light. During the germination of Arabidopsis thaliana seeds in soil, negative gravitropism responses direct hypocotyl elongation such that the seedling can reach the light for photosynthesis and autotrophic growth. Similarly, hypocotyl elongation in the soil also requires mechanisms to efficiently grow around obstacles such as soil particles. Here, we identify KIPK (KINESIN-LIKE CALMODULIN-BINDING PROTEIN-INTERACTING PROTEIN KINASE) and the paralogous KIPKL1 (KIPK-LIKE1) as genetically redundant regulators of gravitropic hypocotyl bending. Moreover, we demonstrate that the homologous KIPKL2 (KIPK-LIKE2), which shows strong sequence similarity, must be functionally distinct. KIPK and KIPKL1 are polarly localized plasma membrane-associated proteins that can activate PIN-FORMED auxin transporters. KIPK and KIPKL1 are required to efficiently align hypocotyl growth with the gravity vector when seedling hypocotyls are grown on media plates or in soil, where contact with soil particles and obstacle avoidance impede direct negative gravitropic growth. Therefore, the polar KIPK and KIPKL1 kinases have different biological functions from the related AGC1 family kinases D6PK (D6 PROTEIN KINASE) or PAX (PROTEIN KINASE ASSOCIATED WITH BRX).

Genetic and Environmental Patterns Underlying Phenotypic Plasticity in Flowering Time and Plant Height in Sorghum

Phenotypic plasticity is the property of a genotype to produce different phenotypes under different environmental conditions. Understanding genetic and environmental factors behind phenotypic plasticity helps answer some longstanding biology questions and improve phenotype prediction. In this study, we investigated the phenotypic plasticity of flowering time and plant height with a set of diverse sorghum lines evaluated across 14 natural field environments. An environmental index was identified to quantitatively connect the environments. Reaction norms were then obtained with the identified indices for genetic dissection of phenotypic plasticity and performance prediction. Genome-wide association studies (GWAS) detected different sets of loci for reaction-norm parameters (intercept and slope), including 10 new genomic regions in addition to known maturity (Ma1) and dwarfing genes (Dw1, Dw2, Dw3, Dw4 and qHT7.1). Cross-validations under multiple scenarios showed promising results in predicting diverse germplasm in dynamic environments. Additional experiments conducted at four new environments, including one from a site outside of the geographical region of the initial environments, further validated the predictions. Our findings indicate that identifying the environmental index enriches our understanding of gene-environmental interplay underlying phenotypic plasticity, and that genomic prediction with the environmental dimension facilitates prediction-guided breeding for future environments.

A MYB transcription factor underlying plant height in sorghum qHT7.1 and maize Brachytic 1 loci

Manipulating plant height is an essential component of crop improvement. Plant height was generally reduced through breeding in wheat, rice, and sorghum to resist lodging and increase grain yield but kept high for bioenergy crops. Here, we positionally cloned a plant height quantitative trait locus (QTL) qHT7.1 as a MYB transcription factor controlling internode elongation, cell proliferation, and cell morphology in sorghum. A 740 bp transposable element insertion in the intronic region caused a partial mis-splicing event, generating a novel transcript that included an additional exon and a premature stop codon, leading to short plant height. The dominant allele had an overall higher expression than the recessive allele across development and internode position, while both alleles' expressions peaked at 46 days after planting and progressively decreased from the top to lower internodes. The orthologue of qHT7.1 was identified to underlie the brachytic1 (br1) locus in maize. A large insertion in exon 3 and a 160 bp insertion at the promoter region were identified in the br1 mutant, while an 18 bp promoter insertion was found to be associated with reduced plant height in a natural recessive allele. CRISPR/Cas9-induced gene knockout of br1 in two maize inbred lines showed significant plant height reduction. These findings revealed functional connections across natural, mutant, and edited alleles of this MYB transcription factor in sorghum and maize. This enriched our understanding of plant height regulation and enhanced our toolbox for fine-tuning plant height for crop improvement.

Decoding the genetic blueprint: regulation of key agricultural traits in sorghum

Sorghum, the fifth most important crop globally, thrives in challenging environments such as arid, saline-alkaline, and infertile regions. This remarkable crop, one of the earliest crops domesticated by humans, offers high biomass and stress-specific properties that render it suitable for a variety of uses including food, feed, bioenergy, and biomaterials. What's truly exciting is the extensive phenotypic variation in sorghum, particularly in traits related to growth, development, and stress resistance. This inherent adaptability makes sorghum a game-changer in agriculture. However, tapping into sorghum's full potential requires unraveling the complex genetic networks that govern its key agricultural traits. Understanding these genetic mechanisms is paramount for improving traits such as yield, quality, and tolerance to drought and saline-alkaline conditions. This review provides a comprehensive overview of functionally characterized genes and regulatory networks associated with plant and panicle architectures, as well as stress resistance in sorghum. Armed with this knowledge, we can develop more resilient and productive sorghum varieties through cutting-edge breeding techniques like genome-wide selection, gene editing, and synthetic biology. These approaches facilitate the identification and manipulation of specific genes responsible for desirable traits, ultimately enhancing agricultural performance and adaptability in sorghum.

Unravelling sorghum functional genomics and molecular breeding: past achievements and future prospects

Sorghum, renowned for its substantial biomass production and remarkable tolerance to various stresses, possesses extensive gene resources and phenotypic variations. A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands. In this context, we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade, accompanied by a summary of functional genomic platforms. We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits. Lastly, we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles, with the aim of accelerating the development of desired sorghum varieties.

Lskipk Lsatpase double mutants are necessary and sufficient for the compact plant architecture of butterhead lettuce

Lettuce, an important leafy vegetable crop worldwide, has rich variations in plant architecture. Butterhead lettuce, a popular horticultural type, has a unique plant architecture with loose leafy heads. The genetic and molecular mechanisms for such a compact plant architecture remain unclear. In this study we constructed a segregating population through crossing a butterhead cultivar and a stem lettuce cultivar. Genetic analysis identified the LsKIPK gene, which encodes a kinase, as the candidate gene controlling butterhead plant architecture. The Lskipk gene in the butterhead parent had a nonsense mutation, leading to a partial predicted protein. CRISPR/Cas9 and complementation tests verified its functions in plant architecture. We showed that the loss of function of LsKIPK is necessary but not sufficient for the butterhead plant architecture. To identify additional genes required for butterhead lettuce, we crossed a butterhead cultivar and a crisphead cultivar, both with the mutated Lskipk gene. Genetic mapping identified a new gene encoding an ATPase contributing to butterhead plant architecture. Knockout and complementation tests showed that loss of function of LsATPase is also required for the development of butterhead plant architecture. The Lskipk Lsatpase double mutation could reduce leaf size and leaf angle, leading to butterhead plant architecture. Expression and cytology analysis indicated that the loss of function of LsKIPK and LsATPase contributed to butterhead plant architecture by regulating cell wall development, a regulatory mechanism different from that for crisphead. This study provides new gene resources and theory for the breeding of the crop ideotype.

Research on Genotype Markers for Plant Height and Assisted Breeding of Key Sorghum Resources in China

Dwarfing and the selection of optimal plant types constitute the primary focus of sorghum breeding. However, the lack of clarity regarding the gene types associated with plant height genes Dw1-Dw4 in the primary breeding materials has led to increased plant heights in improved offspring of the same plant height type, resulting in unsatisfactory morphological traits. This study aimed to elucidate the gene types related to plant height in breeding materials, validate the regulatory mechanisms, and establish a material improvement system. The goal was to achieve molecular-marker-assisted dwarf breeding through the detection of plant height genes and the test cross verification of main Chinese sorghum materials. Using 38 main male sterile lines and 57 main restorer lines of grain sorghum as materials, three plant height genes were detected and classified. Ninety-five F1 generation hybrids of these materials, along with typical materials, were measured at the wax maturity stage. Test cross results demonstrated that the variation in dw1-dw3 genes in the breeding materials significantly influenced the plant height of hybrid offspring. The main male sterile lines in Chinese sorghum predominantly exhibited the "three-dwarf" type of Kafir and its improved lines, characterized by the genotype (Dw1-Dw2-dw3-dw4). On the other hand, restorer lines mainly showcased the improved "two-dwarf" (Dw1-Dw2-dw3-dw4) genotype of the Kaoliang/Caudatum subspecies, along with the "three-dwarf" type of some Kafir and its improved lines. The test materials predominantly contained dw3 genes, with relatively fewer dw1 genes in the restorer lines. The primary restorer materials lacked the dw2 gene, and dw2 significantly influenced plant type. The increased plant height in improved offspring of the same plant height type material was attributed to differences in gene types. Therefore, the enhancement of plant height in breeding materials should prioritize the use of different methods in conjunction with Dw1 and Dw2 classification.

Pilot-scale genome-wide association mapping in diverse sorghum germplasms identified novel genetic loci linked to major agronomic, root and stomatal traits

This genome-wide association studies (GWAS) used a subset of 96 diverse sorghum accessions, constructed from a large collection of 219 accessions for mining novel genetic loci linked to major agronomic, root morphological and physiological traits. The subset yielded 43,452 high quality single nucleotide polymorphic (SNP) markers exhibiting high allelic diversity. Population stratification showed distinct separation between caudatum and durra races. Linkage disequilibrium (LD) decay was rapidly declining with increasing physical distance across all chromosomes. The initial 50% LD decay was ~ 5 Kb and background level was within ~ 80 Kb. This study detected 42 significant quantitative trait nucleotide (QTNs) for different traits evaluated using FarmCPU, SUPER and 3VmrMLM which were in proximity with candidate genes related and were co-localized in already reported quantitative trait loci (QTL) and phenotypic variance (R2) of these QTNs ranged from 3 to 20%. Haplotype validation of the candidate genes from this study resulted nine genes showing significant phenotypic difference between different haplotypes. Three novel candidate genes associated with agronomic traits were validated including Sobic.001G499000, a potassium channel tetramerization domain protein for plant height, Sobic.010G186600, a nucleoporin-related gene for dry biomass, and Sobic.002G022600 encoding AP2-like ethylene-responsive transcription factor for plant yield. Several other candidate genes were validated and associated with different root and physiological traits including Sobic.005G104100, peroxidase 13-related gene with root length, Sobic.010G043300, homologous to Traes_5BL_8D494D60C, encoding inhibitor of apoptosis with iWUE, and Sobic.010G125500, encoding zinc finger, C3HC4 type domain with Abaxial stomatal density. In this study, 3VmrMLM was more powerful than FarmCPU and SUPER for detecting QTNs and having more breeding value indicating its reliable output for validation. This study justified that the constructed subset of diverse sorghums can be used as a panel for mapping other key traits to accelerate molecular breeding in sorghum.

Sorghum: A Multipurpose Crop

Sorghum (Sorghum bicolor L.) is one of the top five cereal crops in the world in terms of production and planting area and is widely grown in areas with severe abiotic stresses such as drought and saline-alkali land due to its excellent stress resistance. Moreover, sorghum is a rare multipurpose crop that can be classified into grain sorghum, energy sorghum, and silage sorghum according to its domestication direction and utilization traits, endowing it with broad breeding and economic value. In this review, we mainly discuss the latest research progress and regulatory genes of agronomic traits of sorghum as a grain, energy, and silage crop, as well as the future improvement direction of multipurpose sorghum. We also emphasize the feasibility of cultivating multipurpose sorghum through genetic engineering methods by exploring potential targets using wild sorghum germplasm and genetic resources, as well as genomic resources.

Deleterious mutations predicted in the sorghum (Sorghum bicolor) Maturity (Ma) and Dwarf (Dw) genes from whole-genome resequencing

In sorghum [Sorghum bicolor (L.) Moench] the Maturity (Ma1, Ma2, Ma3, Ma4, Ma5, Ma6) and Dwarf (Dw1, Dw2, Dw3, Dw4) loci, encode genes controlling flowering time and plant height, respectively, which are critical for designing sorghum ideotypes for a maturity timeframe and a harvest method. Publicly available whole-genome resequencing data from 860 sorghum accessions was analyzed in silico to identify genomic variants at 8 of these loci (Ma1, Ma2, Ma3, Ma5, Ma6, Dw1, Dw2, Dw3) to identify novel loss of function alleles and previously characterized ones in sorghum germplasm. From ~ 33 million SNPs and ~ 4.4 million InDels, 1445 gene variants were identified within these 8 genes then evaluated for predicted effect on the corresponding encoded proteins, which included newly identified mutations (4 nonsense, 15 frameshift, 28 missense). Likewise, most accessions analyzed contained predicted loss of function alleles (425 ma1, 22 ma2, 40 ma3, 74 ma5, 414 ma6, 289 dw1, 268 dw2 and 45 dw3) at multiple loci, but 146 and 463 accessions had no predicted ma or dw mutant alleles, respectively. The ma and dw alleles within these sorghum accessions represent a valuable source for manipulating flowering time and plant height to develop the full range of sorghum types: grain, sweet and forage/biomass.

Harnessing the Genetic Basis of Sorghum Biomass-Related Traits to Facilitate Bioenergy Applications

The extensive use of fossil fuels and global climate change have raised ever-increasing attention to sustainable development, global food security and the replacement of fossil fuels by renewable energy. Several C4 monocot grasses have excellent photosynthetic ability, stress tolerance and may rapidly produce biomass in marginal lands with low agronomic inputs, thus representing an important source of bioenergy. Among these grasses, Sorghum bicolor has been recognized as not only a promising bioenergy crop but also a research model due to its diploidy, simple genome, genetic diversity and clear orthologous relationship with other grass genomes, allowing sorghum research to be easily translated to other grasses. Although sorghum molecular genetic studies have lagged far behind those of major crops (e.g., rice and maize), recent advances have been made in a number of biomass-related traits to dissect the genetic loci and candidate genes, and to discover the functions of key genes. However, molecular and/or targeted breeding toward biomass-related traits in sorghum have not fully benefited from these pieces of genetic knowledge. Thus, to facilitate the breeding and bioenergy applications of sorghum, this perspective summarizes the bioenergy applications of different types of sorghum and outlines the genetic control of the biomass-related traits, ranging from flowering/maturity, plant height, internode morphological traits and metabolic compositions. In particular, we describe the dynamic changes of carbohydrate metabolism in sorghum internodes and highlight the molecular regulators involved in the different stages of internode carbohydrate metabolism, which affects the bioenergy utilization of sorghum biomass. We argue the way forward is to further enhance our understanding of the genetic mechanisms of these biomass-related traits with new technologies, which will lead to future directions toward tailored designing sorghum biomass traits suitable for different bioenergy applications.

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.

Sugar accumulation enhancement in sorghum stem is associated with reduced reproductive sink strength and increased phloem unloading activity

Sweet sorghum has emerged as a promising source of bioenergy mainly due to its high biomass and high soluble sugar yield in stems. Studies have shown that loss-of-function Dry locus alleles have been selected during sweet sorghum domestication, and decapitation can further boost sugar accumulation in sweet sorghum, indicating that the potential for improving sugar yields is yet to be fully realized. To maximize sugar accumulation, it is essential to gain a better understanding of the mechanism underlying the massive accumulation of soluble sugars in sweet sorghum stems in addition to the Dry locus. We performed a transcriptomic analysis upon decapitation of near-isogenic lines for mutant (d, juicy stems, and green leaf midrib) and functional (D, dry stems and white leaf midrib) alleles at the Dry locus. Our analysis revealed that decapitation suppressed photosynthesis in leaves, but accelerated starch metabolic processes in stems. SbbHLH093 negatively correlates with sugar levels supported by genotypes (DD vs. dd), treatments (control vs. decapitation), and developmental stages post anthesis (3d vs.10d). D locus gene SbNAC074A and other programmed cell death-related genes were downregulated by decapitation, while sugar transporter-encoding gene SbSWEET1A was induced. Both SbSWEET1A and Invertase 5 were detected in phloem companion cells by RNA in situ assay. Loss of the SbbHLH093 homolog, AtbHLH093, in Arabidopsis led to a sugar accumulation increase. This study provides new insights into sugar accumulation enhancement in bioenergy crops, which can be potentially achieved by reducing reproductive sink strength and enhancing phloem unloading.

Development of InDels markers for the identification of cytoplasmic male sterility in Sorghum by complete chloroplast genome sequences analysis

Cytoplasmic male sterility (CMS) is predominantly used for F1 hybrid breeding and seed production in Sorghum. DNA markers to distinguish between normal fertile (CMS-N) and sterile (CMS-S) male cytoplasm can facilitate F1 hybrid cultivar development in Sorghum breeding programs. In this study, the complete chloroplast (cp) genome sequences of CMS-S and Korean Sorghum cultivars were obtained using next-generation sequencing. The de novo assembled genome size of ATx623, the CMS-S line of the chloroplast, was 140,644bp. When compared to the CMS-S and CMS-N cp genomes, 19 single nucleotide polymorphisms (SNPs) and 142 insertions and deletions (InDels) were identified, which can be used for marker development for breeding, population genetics, and evolution studies. Two InDel markers with sizes greater than 20 bp were developed to distinguish cytotypes based on the copy number variation of lengths as 28 and 22 bp tandem repeats, respectively. Using the newly developed InDel markers with five pairs of CMS-S and their near isogenic maintainer line, we were able to easily identify their respective cytotypes. The InDel markers were further examined and applied to 1,104 plants from six Korean Sorghum cultivars to identify variant cytotypes. Additionally, the phylogenetic analysis of seven Sorghum species with complete cp genome sequences, including wild species, indicated that CMS-S and CMS-N contained Milo and Kafir cytotypes that might be hybridized from S. propinquum and S. sudanese, respectively. This study can facilitate F1 hybrid cultivar development by providing breeders with reliable tools for marker-assisted selection to breed desirable Sorghum varieties.

Construction of a high-density genetic linkage map and QTL mapping for bioenergy-related traits in sweet sorghum [Sorghum bicolor (L.) Moench]

Sorghum is an important but arguably undervalued cereal crop, grown in large areas in Asia and Africa due to its natural resilience to drought and heat. There is growing demand for sweet sorghum as a source of bioethanol as well as food and feed. The improvement of bioenergy-related traits directly affects bioethanol production from sweet sorghum; therefore, understanding the genetic basis of these traits would enable new cultivars to be developed for bioenergy production. In order to reveal the genetic architecture behind bioenergy-related traits, we generated an F₂ population from a cross between sweet sorghum cv. 'Erdurmus' and grain sorghum cv. 'Ogretmenoglu'. This was used to construct a genetic map from SNPs discovered by double-digest restriction-site associated DNA sequencing (ddRAD-seq). F₃ lines derived from each F₂ individual were phenotyped for bioenergy-related traits in two different locations and their genotypes were analyzed with the SNPs to identify QTL regions. On chromosomes 1, 7, and 9, three major plant height (PH) QTLs (qPH1.1, qPH7.1, and qPH9.1) were identified, with phenotypic variation explained (PVE) ranging from 10.8 to 34.8%. One major QTL (qPJ6.1) on chromosome 6 was associated with the plant juice trait (PJ) and explained 35.2% of its phenotypic variation. For fresh biomass weight (FBW), four major QTLs (qFBW1.1, qFBW6.1, qFBW7.1, and qFBW9.1) were determined on chromosomes 1, 6, 7, and 9, which explained 12.3, 14.5, 10.6, and 11.9% of the phenotypic variation, respectively. Moreover, two minor QTLs (qBX3.1 and qBX7.1) of Brix (BX) were mapped on chromosomes 3 and 7, explaining 8.6 and 9.7% of the phenotypic variation, respectively. The QTLs in two clusters (qPH7.1/qBX7.1 and qPH7.1/qFBW7.1) overlapped for PH, FBW and BX. The QTL, qFBW6.1, has not been previously reported. In addition, eight SNPs were converted into cleaved amplified polymorphic sequences (CAPS) markers, which can be easily detected by agarose gel electrophoresis. These QTLs and molecular markers can be used for pyramiding and marker-assisted selection studies in sorghum, to develop advanced lines that include desirable bioenergy-related traits.

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.

Genetic architecture and molecular regulation of sorghum domestication

Over time, wild crops have been domesticated by humans, and the knowledge gained from parallel selection and convergent domestication-related studies in cereals has contributed to current techniques used in molecular plant breeding. Sorghum (Sorghum bicolor (L.) Moench) is the world's fifth-most popular cereal crop and was one of the first crops cultivated by ancient farmers. In recent years, genetic and genomic studies have provided a better understanding of sorghum domestication and improvements. Here, we discuss the origin, diversification, and domestication processes of sorghum based on archeological discoveries and genomic analyses. This review also comprehensively summarized the genetic basis of key genes related to sorghum domestication and outlined their molecular mechanisms. It highlights that the absence of a domestication bottleneck in sorghum is the result of both evolution and human selection. Additionally, understanding beneficial alleles and their molecular interactions will allow us to quickly design new varieties by further de novo domestication.

Genetic control of morphological traits useful for improving sorghum

Global climate change and global warming, coupled with the growing population, have raised concerns about sustainable food supply and bioenergy demand. Sorghum [Sorghum bicolor (L.) Moench] ranks fifth among cereals produced worldwide; it is a C₄ crop with a higher stress tolerance than other major cereals and has a wide range of uses, such as grains, forage, and biomass. Therefore, sorghum has attracted attention as a promising crop for achieving sustainable development goals (SDGs). In addition, sorghum is a suitable genetic model for C₄ grasses because of its high morphological diversity and relatively small genome size compared to other C₄ grasses. Although sorghum breeding and genetic studies have lagged compared to other crops such as rice and maize, recent advances in research have identified several genes and many quantitative trait loci (QTLs) that control important agronomic traits in sorghum. This review outlines traits and genetic information with a focus on morphogenetic aspects that may be useful in sorghum breeding for grain and biomass utilization.

OMICS in Fodder Crops: Applications, Challenges, and Prospects

Biomass yield and quality are the primary targets in forage crop improvement programs worldwide. Low-quality fodder reduces the quality of dairy products and affects cattle's health. In multipurpose crops, such as maize, sorghum, cowpea, alfalfa, and oat, a plethora of morphological and biochemical/nutritional quality studies have been conducted. However, the overall growth in fodder quality improvement is not on par with cereals or major food crops. The use of advanced technologies, such as multi-omics, has increased crop improvement programs manyfold. Traits such as stay-green, the number of tillers per plant, total biomass, and tolerance to biotic and/or abiotic stresses can be targeted in fodder crop improvement programs. Omic technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, provide an efficient way to develop better cultivars. There is an abundance of scope for fodder quality improvement by improving the forage nutrition quality, edible quality, and digestibility. The present review includes a brief description of the established omics technologies for five major fodder crops, i.e., sorghum, cowpea, maize, oats, and alfalfa. Additionally, current improvements and future perspectives have been highlighted.

Genome-wide analyses using multi-locus models revealed marker-trait associations for major agronomic traits in Sorghum bicolor

Globally, sorghum is the fifth most important cereal crop, and it is a major crop in Ethiopia, where it has a high genetic diversity. The country's sorghum gene pool contributes significantly to sorghum improvement worldwide. This study aimed to identify genomic regions and candidate genes associated with major agronomic traits in sorghum by using its genetic resources in Ethiopia for a genome-wide association study (GWAS). Phenotypic data of days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT), and grain yield (GY) were collected from a GWAS panel comprising 324 sorghum accessions grown in three environments. SeqSNP, a targeted genotyping method, was used to genotype the panel using 5,000 gene-based single nucleotide polymorphism (SNP) markers. For marker-trait association (MTA) analyses, fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) models were used. In all traits, high phenotypic variation was observed, with broad-sense heritability ranging from 0.32 (for GY) to 0.90 (for PALH). A population structure, principal component analysis, and kinship analysis revealed that the accessions could be divided into two groups. In total, 54 MTAs were identified, 11 of which were detected by both BLINK and farmCPU. MTAs identified for each trait ranged from five (PAWT and GY) to fourteen (PH) representing both novel and previously identified quantitative trait loci (QTLs). Three SNPs were associated with more than one trait, including a SNP within the Sobic.004G189200 gene that was associated with PH and PAWT. Major effect SNP loci, Sbi2393610 (PVE = 23.3%), Sbi10438246 (PVE = 35.2%), Sbi17789352 (PVE = 11.9%) and Sbi30169733 (PVE = 18.9%) on chromosomes 1, 3, 5 and 9 that showed strong association signals for PAWD, DTF, GY and PALH, respectively, were major findings of this study. The SNP markers and candidate genes identified in this study provide insights into the genetic control of grain yield and related agronomic traits, and once validated, the markers could be used in genomics-led breeding.

CRISPR for accelerating genetic gains in under-utilized crops of the drylands: Progress and prospects

Technologies and innovations are critical for addressing the future food system needs where genetic resources are an essential component of the change process. Advanced breeding tools like "genome editing" are vital for modernizing crop breeding to provide game-changing solutions to some of the "must needed" traits in agriculture. CRISPR/Cas-based tools have been rapidly repurposed for editing applications based on their improved efficiency, specificity and reduced off-target effects. Additionally, precise gene-editing tools such as base editing, prime editing, and multiplexing provide precision in stacking of multiple traits in an elite variety, and facilitating specific and targeted crop improvement. This has helped in advancing research and delivery of products in a short time span, thereby enhancing the rate of genetic gains. A special focus has been on food security in the drylands through crops including millets, teff, fonio, quinoa, Bambara groundnut, pigeonpea and cassava. While these crops contribute significantly to the agricultural economy and resilience of the dryland, improvement of several traits including increased stress tolerance, nutritional value, and yields are urgently required. Although CRISPR has potential to deliver disruptive innovations, prioritization of traits should consider breeding product profiles and market segments for designing and accelerating delivery of locally adapted and preferred crop varieties for the drylands. In this context, the scope of regulatory environment has been stated, implying the dire impacts of unreasonable scrutiny of genome-edited plants on the evolution and progress of much-needed technological advances.

Bioenergy sorghum stem growth regulation: intercalary meristem localization, development, and gene regulatory network analysis

Bioenergy sorghum is a highly productive drought tolerant C₄ grass that accumulates 80% of its harvestable biomass in approximately 4 m length stems. Stem internode growth is regulated by development, shading, and hormones that modulate cell proliferation in intercalary meristems (IMs). In this study, sorghum stem IMs were localized above the pulvinus at the base of elongating internodes using magnetic resonance imaging, microscopy, and transcriptome analysis. A change in cell morphology/organization occurred at the junction between the pulvinus and internode where LATERAL ORGAN BOUNDARIES (SbLOB), a boundary layer gene, was expressed. Inactivation of an AGCVIII kinase in DDYM (dw2) resulted in decreased SbLOB expression, disrupted IM localization, and reduced internode cell proliferation. Transcriptome analysis identified approximately 1000 genes involved in cell proliferation, hormone signaling, and other functions selectively upregulated in the IM compared with a non-meristematic stem tissue. This cohort of genes is expressed in apical dome stem tissues before localization of the IM at the base of elongating internodes. Gene regulatory network analysis identified connections between genes involved in hormone signaling and cell proliferation. The results indicate that gibberellic acid induces accumulation of growth regulatory factors (GRFs) known to interact with ANGUSTIFOLIA (SbAN3), a master regulator of cell proliferation. GRF:AN3 was predicted to induce SbARF3/ETT expression and regulate SbAN3 expression in an auxin-dependent manner. GRFs and ARFs regulate genes involved in cytokinin and brassinosteroid signaling and cell proliferation. The results provide a molecular framework for understanding how hormone signaling regulates the expression of genes involved in cell proliferation in the stem IM.

CRISPR/Cas9-mediated tetra-allelic mutation of the 'Green Revolution' SEMIDWARF-1 (SD-1) gene confers lodging resistance in tef (Eragrostis tef)

Tef is a staple food and a valuable cash crop for millions of people in Ethiopia. Lodging is a major limitation to tef production, and for decades, the development of lodging resistant varieties proved difficult with conventional breeding approaches. We used CRISPR/Cas9 to introduce knockout mutations in the tef orthologue of the rice SEMIDWARF-1 (SD-1) gene to confer semidwarfism and ultimately lodging resistance. High frequency recovery of transgenic and SD-1 edited tef lines was achieved in two tef cultivars by Agrobacterium-mediated delivery into young leaf explants of gene editing reagents along with transformation and regeneration enhancing morphogenic genes, BABY BOOM (BBM) and WUSCHEL2 (WUS2). All of the 23 lines analyzed by next-generation sequencing had at least two or more alleles of SD-1 mutated. Of these, 83% had tetra-allelic frameshift mutations in the SD-1 gene in primary tef regenerants, which were inherited in subsequent generations. Phenotypic data generated on T₁ and T₂ generations revealed that the sd-1 lines have reduced culm and internode lengths with no reduction in either panicle or peduncle lengths. These characteristics are comparable with rice sd-1 plants. Measurements of lodging, in greenhouse-grown plants, showed that sd-1 lines have significantly higher resistance to lodging at the heading stage compared with the controls. This is the first demonstration of the feasibility of high frequency genetic transformation and CRISPR/Cas9-mediated genome editing in this highly valuable but neglected crop. The findings reported here highlight the potential of genome editing for the improvement of lodging resistance and other important traits in tef.

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

We explore the use of deep convolutional neural networks (CNNs) trained on overhead imagery of biomass sorghum to ascertain the relationship between single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the phenotypes they control. We consider both CNNs trained explicitly on the classification task of predicting whether an image shows a plant with a reference or alternate version of various SNPs as well as CNNs trained to create data-driven features based on learning features so that images from the same plot are more similar than images from different plots, and then using the features this network learns for genetic marker classification. We characterize how efficient both approaches are at predicting the presence or absence of a genetic markers, and visualize what parts of the images are most important for those predictions. We find that the data-driven approaches give somewhat higher prediction performance, but have visualizations that are harder to interpret; and we give suggestions of potential future machine learning research and discuss the possibilities of using this approach to uncover unknown genotype × phenotype relationships.

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

A high-density linkage map of finger millet provides QTL for blast resistance and other agronomic traits

Finger millet [Eleusine coracana (L.) Gaertn.] is a critical subsistence crop in eastern Africa and southern Asia but has few genomic resources and modern breeding programs. To aid in the understanding of finger millet genomic organization and genes underlying disease resistance and agronomically important traits, we generated a F_2:3 population from a cross between E. coracana (L.) Gaertn. subsp. coracana accession ACC 100007 and E. coracana (L.) Gaertn. subsp. africana , accession GBK 030647. Phenotypic data on morphology, yield, and blast (Magnaporthe oryzae) resistance traits were taken on a subset of the F_2:3 population in a Kenyan field trial. The F_2:3 population was genotyped via genotyping-by-sequencing (GBS) and the UGbS-Flex pipeline was used for sequence alignment, nucleotide polymorphism calling, and genetic map construction. An 18-linkage-group genetic map consisting of 5,422 markers was generated that enabled comparative genomic analyses with rice (Oryza sativa L.), foxtail millet [Setaria italica (L.) P. Beauv.], and sorghum [Sorghum bicolor (L.) Moench]. Notably, we identified conserved acrocentric homoeologous chromosomes (4A and 4B in finger millet) across all species. Significant quantitative trait loci (QTL) were discovered for flowering date, plant height, panicle number, and blast incidence and severity. Sixteen putative candidate genes that may underlie trait variation were identified. Seven LEUCINE-RICH REPEAT-CONTAINING PROTEIN genes, with homology to nucleotide-binding site leucine-rich repeat (NBS-LRR) disease resistance proteins, were found on three chromosomes under blast resistance QTL. This high-marker-density genetic map provides an important tool for plant breeding programs and identifies genomic regions and genes of critical interest for agronomic traits and blast resistance.

Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range

Phenotypic plasticity is observed widely in plants and often studied with reaction norms for adult plant or end-of-season traits. Uncovering genetic, environmental and developmental patterns behind the observed phenotypic variation under natural field conditions is needed. Using a sorghum (Sorghum bicolor) genetic population evaluated for plant height in seven natural field conditions, we investigated the major pattern that differentiated these environments. We then examined the physiological relevance of the identified environmental index by investigating the developmental trajectory of the population with multistage height measurements in four additional environments and conducting crop growth modelling. We found that diurnal temperature range (DTR) during the rapid growth period of sorghum development was an effective environmental index. Three genetic loci (Dw1, Dw3 and qHT7.1) were consistently detected for individual environments, reaction-norm parameters across environments and growth-curve parameters through the season. Their genetic effects changed dynamically along the environmental gradient and the developmental stage. A conceptual model with three-dimensional reaction norms was proposed to showcase the interconnecting components: genotype, environment and development. Beyond genomic and environmental analyses, further integration of development and physiology at the whole-plant and molecular levels into complex trait dissection would enhance our understanding of mechanisms underlying phenotypic variation.

Genetic control of source-sink relationships in grain sorghum

QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

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.

Assessing combining abilities, genomic data, and genotype × environment interactions to predict hybrid grain sorghum performance

Genomic selection in maize (Zea mays L.) has been one factor that has increased the rate of genetic gain when compared with other cereals. However, the technological foundations in maize also exist in other cereal crops that would allow prediction of hybrid performance based on general (GCA) and specific (SCA) combining abilities applied through genomic-enabled prediction models. Further, the incorporation of genotype × environment (G × E) interaction effects present an opportunity to deploy hybrids to targeted environments. To test these concepts, a factorial mating design of elite yet divergent grain sorghum lines generated hybrids for evaluation. Inbred parents were genotyped, and markers were used to assess population structure and develop the genomic relationship matrix (GRM). Grain yield, height, and days to anthesis were collected for hybrids in replicated trials, and best linear unbiased estimates were used to train classical GCA-SCA-based and genomic (GB) models under a hierarchical Bayesian framework. To incorporate population structure, GB was fitted using the GRM of both parents and hybrids. For GB models, G × E interaction effects were included by the Hadamard product between GRM and environments. A leave-one-out cross-validation scheme was used to study the prediction capacity of models. Classical and genomic models effectively predicted hybrid performance and prediction accuracy increased by including genomic data. Genomic models effectively partitioned the variation due to GCA, SCA, and their interaction with the environment. A strategy to implement genomic selection for hybrid sorghum [Sorghum bicolor (L.) Moench] breeding is presented herein.

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 dissection of QTLs associated with spikelet-related traits and grain size in sorghum

Although spikelet-related traits such as size of anther, spikelet, style, and stigma are associated with sexual reproduction in grasses, no QTLs have been reported in sorghum. Additionally, there are only a few reports on sorghum QTLs related to grain size, such as grain length, width, and thickness. In this study, we performed QTL analyses of nine spikelet-related traits (length of sessile spikelet, pedicellate spikelet, pedicel, anther, style, and stigma; width of sessile spikelet and stigma; and stigma pigmentation) and six grain-related traits (length, width, thickness, length/width ratio, length/thickness ratio, and width/thickness ratio) using sorghum recombinant inbred lines. We identified 36 and 7 QTLs for spikelet-related traits and grain-related traits, respectively, and found that most sorghum spikelet organ length- and width-related traits were partially controlled by the dwarf genes Dw1 and Dw3. Conversely, we found that these Dw genes were not strongly involved in the regulation of grain size. The QTLs identified in this study aid in understanding the genetic basis of spikelet- and grain-related traits in sorghum.

Quantitative trait mapping of plant architecture in two BC1F2 populations of Sorghum Bicolor × S. halepense and comparisons to two other sorghum populations

Comparing populations derived, respectively, from polyploid Sorghum halepense and its progenitors improved knowledge of plant architecture and showed that S. halepense harbors genetic novelty of potential value for sorghum improvement Vegetative growth and the timing of the vegetative-to-reproductive transition are critical to a plant's fitness, directly and indirectly determining when and how a plant lives, grows and reproduces. We describe quantitative trait analysis of plant height and flowering time in the naturally occurring tetraploid Sorghum halepense, using two novel BC₁F₂ populations totaling 246 genotypes derived from backcrossing two tetraploid Sorghum bicolor x S. halepense F₁ plants to a tetraploidized S. bicolor. Phenotyping for two years each in Bogart, GA and Salina, KS allowed us to dissect variance into narrow-sense genetic (QTLs) and environmental components. In crosses with a common S. bicolor BTx623 parent, comparison of QTLs in S. halepense, its rhizomatous progenitor S. propinquum and S. bicolor race guinea which is highly divergent from BTx623 permit inferences of loci at which new alleles have been associated with improvement of elite sorghums. The relative abundance of QTLs unique to the S. halepense populations may reflect its polyploidy and subsequent 'diploidization' processes often associated with the formation of genetic novelty, a possibility further supported by a high level of QTL polymorphism within sibling lines derived from a common S. halepense parent. An intriguing hypothesis for further investigation is that polyploidy of S. halepense following 96 million years of abstinence, coupled with natural selection during its spread to diverse environments across six continents, may provide a rich collection of novel alleles that offer potential opportunities for sorghum improvement.

From Traditional Breeding to Genome Editing for Boosting Productivity of the Ancient Grain Tef [Eragrostis tef (Zucc.) Trotter]

Tef (Eragrostis tef (Zucc.) Trotter) is a staple food crop for 70% of the Ethiopian population and is currently cultivated in several countries for grain and forage production. It is one of the most nutritious grains, and is also more resilient to marginal soil and climate conditions than major cereals such as maize, wheat and rice. However, tef is an extremely low-yielding crop, mainly due to lodging, which is when stalks fall on the ground irreversibly, and prolonged drought during the growing season. Climate change is triggering several biotic and abiotic stresses which are expected to cause severe food shortages in the foreseeable future. This has necessitated an alternative and robust approach in order to improve resilience to diverse types of stresses and increase crop yields. Traditional breeding has been extensively implemented to develop crop varieties with traits of interest, although the technique has several limitations. Currently, genome editing technologies are receiving increased interest among plant biologists as a means of improving key agronomic traits. In this review, the potential application of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (CRISPR-Cas) technology in improving stress resilience in tef is discussed. Several putative abiotic stress-resilient genes of the related monocot plant species have been discussed and proposed as target genes for editing in tef through the CRISPR-Cas system. This is expected to improve stress resilience and boost productivity, thereby ensuring food and nutrition security in the region where it is needed the most.

The dominance model for heterosis explains culm length genetics in a hybrid sorghum variety

Heterosis helps increase the biomass of many crops; however, while models for its mechanisms have been proposed, it is not yet fully understood. Here, we use a QTL analysis of the progeny of a high-biomass sorghum F₁ hybrid to examine heterosis. Five QTLs were identified for culm length and were explained using the dominance model. Five resultant homozygous dominant alleles were used to develop pyramided lines, which produced biomasses like the original F₁ line. Cloning of one of the uncharacterised genes (Dw7a) revealed that it encoded a MYB transcription factor, that was not yet proactively used in modern breeding, suggesting that combining classic dw1or dw3, and new (dw7a) genes is an important breeding strategy. In conclusion, heterosis is explained in this situation by the dominance model and a combination of genes that balance the shortness and early flowering of the parents, to produce F₁ seed yields.

Integration of high-density genetic mapping with transcriptome analysis uncovers numerous agronomic QTL and reveals candidate genes for the control of tillering in sorghum

Phenotypes such as branching, photoperiod sensitivity, and height were modified during plant domestication and crop improvement. Here, we perform quantitative trait locus (QTL) mapping of these and other agronomic traits in a recombinant inbred line (RIL) population derived from an interspecific cross between Sorghum propinquum and Sorghum bicolor inbred Tx7000. Using low-coverage Illumina sequencing and a bin-mapping approach, we generated ∼1920 bin markers spanning ∼875 cM. Phenotyping data were collected and analyzed from two field locations and one greenhouse experiment for six agronomic traits, thereby identifying a total of 30 QTL. Many of these QTL were penetrant across environments and co-mapped with major QTL identified in other studies. Other QTL uncovered new genomic regions associated with these traits, and some of these were environment-specific in their action. To further dissect the genetic underpinnings of tillering, we complemented QTL analysis with transcriptomics, identifying 6189 genes that were differentially expressed during tiller bud elongation. We identified genes such as Dormancy Associated Protein 1 (DRM1) in addition to various transcription factors that are differentially expressed in comparisons of dormant to elongating tiller buds and lie within tillering QTL, suggesting that these genes are key regulators of tiller elongation in sorghum. Our study demonstrates the usefulness of this RIL population in detecting domestication and improvement-associated genes in sorghum, thus providing a valuable resource for genetic investigation and improvement to the sorghum community.

The AGCVIII kinase Dw2 modulates cell proliferation, endomembrane trafficking, and MLG/xylan cell wall localization in elongating stem internodes of Sorghum bicolor

Stems of bioenergy sorghum (Sorghum bicolor L. Moench.), a drought-tolerant C4 grass, contain up to 50 nodes and internodes of varying length that span 4-5 m and account for approximately 84% of harvested biomass. Stem internode growth impacts plant height and biomass accumulation and is regulated by brassinosteroid signaling, auxin transport, and gibberellin biosynthesis. In addition, an AGCVIII kinase (Dw2) regulates sorghum stem internode growth, but the underlying mechanism and signaling network are unknown. Here we provide evidence that mutation of Dw2 reduces cell proliferation in internode intercalary meristems, inhibits endocytosis, and alters the distribution of heteroxylan and mixed linkage glucan in cell walls. Phosphoproteomic analysis showed that Dw2 signaling influences the phosphorylation of proteins involved in lipid signaling (PLDδ), endomembrane trafficking, hormone, light, and receptor signaling, and photosynthesis. Together, our results show that Dw2 modulates endomembrane function and cell division during sorghum internode growth, providing insight into the regulation of monocot stem development.

High planting density induces the expression of GA3-oxidase in leaves and GA mediated stem elongation in bioenergy sorghum

The stems of bioenergy sorghum hybrids at harvest are > 4 m long, contain > 40 internodes and account for ~ 80% of harvested biomass. In this study, bioenergy sorghum hybrids were grown at four planting densities (~ 20,000 to 132,000 plants/ha) under field conditions for 60 days to investigate the impact shading has on stem growth and biomass accumulation. Increased planting density induced a > 2-fold increase in sorghum internode length and a ~ 22% decrease in stem diameter, a typical shade avoidance response. Shade-induced internode elongation was due to an increase in cell length and number of cells spanning the length of internodes. SbGA3ox2 (Sobic.003G045900), a gene encoding the last step in GA biosynthesis, was expressed ~ 20-fold higher in leaf collar tissue of developing phytomers in plants grown at high vs. low density. Application of GA3 to bioenergy sorghum increased plant height, stem internode length, cell length and the number of cells spanning internodes. Prior research showed that sorghum plants lacking phytochrome B, a key photoreceptor involved in shade signaling, accumulated more GA1 and displayed shade avoidance phenotypes. These results are consistent with the hypothesis that increasing planting density induces expression of GA3-oxidase in leaf collar tissue, increasing synthesis of GA that stimulates internode elongation.

The Road to Sorghum Domestication: Evidence From Nucleotide Diversity and Gene Expression Patterns

Native African cereals (sorghum, millets) ensure food security to millions of low-income people from low fertility and drought-prone regions of Africa and Asia. In spite of their agronomic importance, the genetic bases of their phenotype and adaptations are still not well-understood. Here we focus on Sorghum bicolor, which is the fifth cereal worldwide for grain production and constitutes the staple food for around 500 million people. We leverage transcriptomic resources to address the adaptive consequences of the domestication process. Gene expression and nucleotide variability were analyzed in 11 domesticated and nine wild accessions. We documented a downregulation of expression and a reduction of diversity both in nucleotide polymorphism (30%) and gene expression levels (18%) in domesticated sorghum. These findings at the genome-wide level support the occurrence of a global reduction of diversity during the domestication process, although several genes also showed patterns consistent with the action of selection. Nine hundred and forty-nine genes were significantly differentially expressed between wild and domesticated gene pools. Their functional annotation points to metabolic pathways most likely contributing to the sorghum domestication syndrome, such as photosynthesis and auxin metabolism. Coexpression network analyzes revealed 21 clusters of genes sharing similar expression patterns. Four clusters (totaling 2,449 genes) were significantly enriched in differentially expressed genes between the wild and domesticated pools and two were also enriched in domestication and improvement genes previously identified in sorghum. These findings reinforce the evidence that the combined and intricated effects of the domestication and improvement processes do not only affect the behaviors of a few genes but led to a large rewiring of the transcriptome. Overall, these analyzes pave the way toward the identification of key domestication genes valuable for genetic resources characterization and breeding purposes.

Dissecting the Genetic Architecture of Biofuel-Related Traits in a Sorghum Breeding Population

In sorghum [Sorghum bicolor (L.) Moench], hybrid cultivars for the biofuel industry are desired. Along with selection based on testcross performance, evaluation of the breeding population per se is also important for the success of hybrid breeding. In addition to additive genetic effects, non-additive (i.e., dominance and epistatic) effects are expected to contribute to the performance of early generations. Unfortunately, studies on early generations in sorghum breeding programs are limited. In this study, we analyzed a breeding population for bioenergy sorghum, which was previously developed based on testcross performance, to compare genomic selection models both trained on and evaluated for the per se performance of the 3^rd generation S₀ individuals. Of over 200 ancestral inbred accessions in the base population, only 13 founders contributed to the 3^rd generation as progenitors. Compared to the founders, the performances of the population per se were improved for target traits. The total genetic variance within the S₀ generation progenies themselves for all traits was mainly additive, although non-additive variances contributed to each trait to some extent. For genomic selection, linear regression models explicitly considering all genetic components showed a higher predictive ability than other linear and non-linear models. Although the number and effect distribution of underlying loci was different among the traits, the influence of priors for marker effects was relatively small. These results indicate the importance of considering non-additive effects for dissecting the genetic architecture of early breeding generations and predicting the performance per se.

Voxel carving-based 3D reconstruction of sorghum identifies genetic determinants of light interception efficiency

Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions' accuracy.

Increased Power and Accuracy of Causal Locus Identification in Time Series Genome-wide Association in Sorghum

The phenotypes of plants develop over time and change in response to the environment. New engineering and computer vision technologies track these phenotypic changes. Identifying the genetic loci regulating differences in the pattern of phenotypic change remains challenging. This study used functional principal component analysis (FPCA) to achieve this aim. Time series phenotype data were collected from a sorghum (Sorghum bicolor) diversity panel using a number of technologies including conventional color photography and hyperspectral imaging. This imaging lasted for 37 d and centered on reproductive transition. A new higher density marker set was generated for the same population. Several genes known to control trait variation in sorghum have been previously cloned and characterized. These genes were not confidently identified in genome-wide association analyses at single time points. However, FPCA successfully identified the same known and characterized genes. FPCA analyses partitioned the role these genes play in controlling phenotypes. Partitioning was consistent with the known molecular function of the individual cloned genes. These data demonstrate that FPCA-based genome-wide association studies can enable robust time series mapping analyses in a wide range of contexts. Moreover, time series analysis can increase the accuracy and power of quantitative genetic analyses.

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.

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.

Semantic Segmentation of Sorghum Using Hyperspectral Data Identifies Genetic Associations

This study describes the evaluation of a range of approaches to semantic segmentation of hyperspectral images of sorghum plants, classifying each pixel as either nonplant or belonging to one of the three organ types (leaf, stalk, panicle). While many current methods for segmentation focus on separating plant pixels from background, organ-specific segmentation makes it feasible to measure a wider range of plant properties. Manually scored training data for a set of hyperspectral images collected from a sorghum association population was used to train and evaluate a set of supervised classification models. Many algorithms show acceptable accuracy for this classification task. Algorithms trained on sorghum data are able to accurately classify maize leaves and stalks, but fail to accurately classify maize reproductive organs which are not directly equivalent to sorghum panicles. Trait measurements extracted from semantic segmentation of sorghum organs can be used to identify both genes known to be controlling variation in a previously measured phenotypes (e.g., panicle size and plant height) as well as identify signals for genes controlling traits not previously quantified in this population (e.g., stalk/leaf ratio). Organ level semantic segmentation provides opportunities to identify genes controlling variation in a wide range of morphological phenotypes in sorghum, maize, and other related grain crops.

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

Background

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response.

Results

We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions.

Conclusions

The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

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.

Simultaneous Parameter Learning and Bi-clustering for Multi-Response Models

We consider multi-response and multi-task regression models, where the parameter matrix to be estimated is expected to have an unknown grouping structure. The groupings can be along tasks, or features, or both, the last one indicating a bi-cluster or “checkerboard” structure. Discovering this grouping structure along with parameter inference makes sense in several applications, such as multi-response Genome-Wide Association Studies (GWAS). By inferring this additional structure we can obtain valuable information on the underlying data mechanisms (e.g., relationships among genotypes and phenotypes in GWAS). In this paper, we propose two formulations to simultaneously learn the parameter matrix and its group structures, based on convex regularization penalties. We present optimization approaches to solve the resulting problems and provide numerical convergence guarantees. Extensive experiments demonstrate much better clustering quality compared to other methods, and our approaches are also validated on real datasets concerning phenotypes and genotypes of plant varieties.