Traits In Sorghum Research Articles

Novel Allelic Mutations in Dw3 Gene That Affect the Height of Sorghum Plants

Breeding for dwarfing traits in sorghum is crucial. However, only three genes (Dw1–Dw3) that control plant height have been mapped. In this study, 634 sorghum cultivars were collected to investigate plant height and genotypes. Four were genotyped Dw1DW2Dw3 (wild type) but with different plant heights, and they were selected to construct two populations and map new dwarf genes. Bulked segregant analysis with whole-genome resequencing of the two populations identified the candidate gene in one same genomic region—on chromosome 7. Then, it was narrowed down to a region containing nine genes. Amino acid and DNA sequence analysis of the parent and offspring plants revealed that two novel allelic mutations in the Dw3 gene play a role in reducing the plant height—8R262 or 8R417, including 1 bp substitution and 2 bp deletions. Furthermore, we sequenced 19 cultivars that primarily exhibited a “one-dwarf” hybrid or wild-type and presumed another allelic mutation via the amino acid alignment of 8R019, 8R100, and 8R402, which was another one-base substitution. These results indicate that multiple types of allelic mutations in the Dw3 gene should be considered when identified or applied.

Progress and prospects in the molecular basic research on important traits in sorghum

Sorghum (Sorghum bicolor) is a significant crop serving food, energy, feed, and industrial raw materials, featuring extensive growth adaptability and diverse utility values. Despite the achievements in sorghum breeding in the last decades, conventional breeding methods still confront challenges such as lengthy breeding cycles, low efficiency, and complex genetic backgrounds. With the rapid advancement of molecular biology, genetics, and bioinformatics, molecular breeding has carved new pathways for enhancing sorghum yield and quality. This article reviews the molecular basic research progress in the key agronomic and adaptive traits of sorghum, including grain yield, grain quality, flowering time, plant height, tillering, stress resistance, and male sterility, and discusses future research priorities, offering novel insights and approaches for sorghum breeding.

Association mapping identifies stable loci containing novel genes for developmental and reproductive traits in sorghum.

Key message We mapped 11 sorghum traits, identified 33 candidate genes, and found a grain yield gene (GID1) that regulates seed development and a grass-specific tillering gene (DUF1618) transferred to Striga hermonthica.

Genetic diversity, population structure, and a genome-wide association study of sorghum lines assembled for breeding in Uganda.

Sorghum is an important source of food and feed worldwide. Developing sorghum core germplasm collections improves our understanding of the evolution and exploitation of genetic diversity in breeding programs. Despite its significance, the characterization of the genetic diversity of local germplasm pools and the identification of genomic loci underlying the variation of critical agronomic traits in sorghum remains limited in most African countries, including Uganda. In this study, we evaluated a collection of 543 sorghum accessions actively used in Ugandan breeding program across two cropping seasons at NaSARRI, Uganda, under natural field conditions. Phenotypic data analysis revealed significant (p<0.01) variation among accessions for days to 50% flowering, plant height, panicle exsertion, and grain yield, with broad-sense heritability (H²) estimates of 0.54, 0.9, 0.81, and 0.48, respectively, indicating a high genetic variability for these traits. We used a newly developed genomic resource of 7,156 single nucleotide polymorphism (SNP) markers to characterize the genetic diversity and population structure of this collection. On average, the SNP markers exhibited moderately high polymorphic information content (PIC = 0.3) and gene diversity (He = 0.3), while observed heterozygosity (Ho = 0.07) was low, typical for self-pollinating crops like sorghum. Admixture-based models, PCA, and cluster analysis all grouped the accessions into two subpopulations with relatively low genetic differentiation. Genome-wide association study (GWAS) identified candidate genes linked to key agronomic traits using a breeding diversity panel from Uganda. GWAS analysis using three different mixed models identified 12 genomic regions associated with days to flowering, plant height, panicle exsertion, grain yield, and glume coverage. Five core candidate genes were co-localized with these significant SNPs. The SNP markers and candidate genes discovered provide valuable insights into the genetic regulation of key agronomic traits and, upon validation, hold promise for genomics-driven breeding strategies in Uganda.

Genetic variability, correlation and path analysis studies for yield and yield contributing traits in sorghum (Sorghum bicolor (L.) Moench)

Genetic variability, correlation and path analysis studies for yield and yield contributing traits in sorghum (Sorghum bicolor (L.) Moench)

Correlation and principal component analysis of morphophysiological and biochemical traits in sorghum under drought stress

Correlation and principal component analysis of morphophysiological and biochemical traits in sorghum under drought stress

Genomic co-localization of variation affecting agronomic and human gut microbiome traits in a meta-analysis of diverse sorghum.

Substantial functional metabolic diversity exists within species of cultivated grain crops that directly or indirectly provide more than half of all calories consumed by humans around the globe. While such diversity is the molecular currency used for improving agronomic traits, diversity is poorly characterized for its effects on human nutrition and utilization by gut microbes. Moreover, we know little about agronomic traits' potential tradeoffs and pleiotropic effects on human nutritional traits. Here, we applied a quantitative genetics approach using a meta-analysis and parallel genome-wide association studies of Sorghum bicolor traits describing changes in the composition and function of human gut microbe communities, and any of 200 sorghum seed and agronomic traits across a diverse sorghum population to identify associated genetic variants. A total of 15 multiple-effect loci (MEL) were initially found where different alleles in the sorghum genome produced changes in seed that affected the abundance of multiple bacterial taxa across 2 human microbiomes in automated in vitro fermentations. Next, parallel genome-wide studies conducted for seed, biochemical, and agronomic traits in the same population identified significant associations within the boundaries of 13/15 MEL for microbiome traits. In several instances, the colocalization of variation affecting gut microbiome and agronomic traits provided hypotheses for causal mechanisms through which variation could affect both agronomic traits and human gut microbes. This work demonstrates that genetic factors affecting agronomic traits in sorghum seed can also drive significant effects on human gut microbes, particularly bacterial taxa considered beneficial. Understanding these pleiotropic relationships will inform future strategies for crop improvement toward yield, sustainability, and human health.

Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa.

Crop rotation has been considered a potential solution to mitigate the negative effects of the continuous cropping of sorghum, including soil quality issues, inadequate plant development, and diminished yield and quality. A two-year field experiment was conducted to compare the effects of sorghum-sorghum continuous cropping and quinoa-sorghum rotation on soil properties and sorghum yield. The treatments were arranged in a randomized complete block design with three replicates. Sorghum seeds (Jinza 22) and quinoa seeds ('Jiaqi 1' variety) were used. Soil samples were collected before and during the experiment for the analysis of physicochemical properties. The yield traits of sorghum were measured at maturity. The results showed that soil nutrients and organic matter were higher in the top 0-20 cm soil depth compared to 20-40 cm depth, with significant differences observed between cropping systems. Sorghum-quinoa cropping increased soil total N and organic matter, particularly at the jointing and maturity stages of sorghum. However, the available phosphorus was higher under continuous cropping at all growth stages. Crop rotation significantly improved sorghum yield traits, including spike fresh weight, spike dry weight, grain weight per spike, and grain yield per hectare. A correlation analysis revealed positive relationships between soil total N, organic matter, and sorghum yield. Overall, sorghum-quinoa rotation demonstrated potential for improving soil fertility and enhancing crop productivity compared to continuous cropping, although further studies are needed to explore the long-term effects and optimize management practices.

Identification and analysis of novel recessive alleles for Tan1 and Tan2 in sorghum.

The identification and analysis of allelic variation are important bases for crop diversity research, trait domestication and molecular marker development. Grain tannin content is a very important quality trait in sorghum. Higher tannin levels in sorghum grains are usually required when breeding varieties resistant to bird damage or those used for brewing liquor. Non-tannin-producing or low-tannin-producing sorghum accessions are commonly used for food and forage. Tan1 and Tan2, two important cloned genes, regulate tannin biosynthesis in sorghum, and mutations in one or two genes will result in low or no tannin content in sorghum grains. Even if sorghum accessions contain dominant Tan1 and Tan2, the tannin contents are distributed from low to high, and there must be other new alleles of the known regulatory genes or new unknown genes contributing to tannin production. The two parents 8R306 and 8R191 did not have any known recessive alleles for Tan1 and Tan2, and it was speculated that they probably both had dominant Tan1 and Tan2 genotypes. However, the phenotypes of two parents were different; 8R306 had tannins and 8R191 had non-tannins in the grains, so these two parents were constructed as a RIL population. Bulked segregant analysis (BSA) was used to determine other new alleles of Tan1 and Tan2 or new Tannin locus. Tan1 and Tan2 full-length sequences and tannin contents were detected in wild sorghum resources, landraces and cultivars. We identified two novel recessive tan1-d and tan1-e alleles and four recessive Tan2 alleles, named as tan2-d, tan2-e, tan2-f, and tan2-g. These recessive alleles led to loss of function of Tan1 and Tan2, and low or no tannin content in sorghum grains. The loss-of-function alleles of tan1-e and tan2-e were only found in Chinese landraces, and other alleles were found in landraces and cultivars grown all around the world. tan1-a and tan1-b were detected in foreign landraces, Chinese cultivars and foreign cultivars, but not in Chinese landraces. These results implied that Tan1 and Tan2 recessive alleles had different geographically distribution in the worldwide, but not all recessive alleles had been used in breeding. The discovery of these new alleles provided new germplasm resources for breeding sorghum cultivars for food and feed, and for developing molecular markers for low-tannin or non-tannin cultivar-assisted breeding in sorghum.

Farmers’ production constraints, preferred varietal traits and perceptions on sorghum grain mold in Senegal

Improving sorghum adoption rates by developing adapted varieties that meet end-user preferences is a major challenge in West Africa. In this study, a participatory rural appraisal was undertaken to identify the main sorghum production constraints, farmers’ preferred variety traits and their perceptions on sorghum grain mold. The study was conducted in four representative rural communities located in the main sorghum producing area of Senegal. A total of 260 farmers were interviewed and data were collected through focus group discussions and individual questionnaires. Our results indicated that Striga, insects, poor soil fertility and drought are the major sorghum producing constraints in Senegal. Grain mold was identified as the second most important sorghum disease after the damping-off. Discoloration on grain surface was the most important criteria farmers used to recognize the disease. The most important sorghum traits farmers desired in improved varieties are medium to short plant maturity cycle, medium plant height, large open or semi-compact panicle, big and white grain, and adaptation to local growing conditions. The results showed that the sorghum cropping system is dominated by male farmers who mainly grow local landraces. These results will provide updated recommendations for the breeding products profile to meet end-user preferences in Senegal.

EFFECTS OF RAINWATER HARVESTING PRACTICES ON BIOMASS YIELD AND MORPHOMETRIC TRAITS OF SORGHUM (Sorghum bicolor L. Moench) IN SEMI-ARID KITUI COUNTY, KENYA

&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;: Sorghum is an important source of fodder in the semi-arid areas of Kenya. However, its biomass yield has remained low due to the low soil moisture content which is associated with low rainfall. &lt;strong&gt; Objective:&lt;/strong&gt; To evaluate the synergistic effects of combining rainwater harvesting practices on biomass yield and the morphometric traits of sorghum in semi-arid Kitui County. &lt;strong&gt;Methodology&lt;/strong&gt;: The study was conducted in a randomized complete block design under rainfed conditions between March and August 2021 at the Research Farm of South Eastern Kenya University. It had twelve treatments, including three farming systems (conventional flat planting, ridge and furrow, and zai pits) with three soil mulching types (transparent plastic film mulch, black plastic film mulch, and grass mulch). The farming systems without mulching were used as control treatments. Data were subjected to analysis of variance and means were separated using Fisher’s protected Least Significant Difference test at 0.05 %. &lt;strong&gt;Results:&lt;/strong&gt; The zai pits with black plastic film mulch and flat planting with grass mulch had the highest and lowest moisture content of 68.65% and 52.5% respectively compared to flat planting. The highest biomass yield was observed in ridge-furrow with black plastic film mulch (3283.33kg ha-&lt;sup&gt;1&lt;/sup&gt;) and ridge–furrow with transparent plastic film mulch (3266.03) and was not significantly different. The lowest biomass yield was recorded in conventional flat planting and zai pits and was not significantly different. In all treatments, there was a significant increase (p ≤ 0.05) in morphometric traits. &lt;strong&gt;Implications: &lt;/strong&gt;The farming system and the type of soil mulching determined the increase of soil moisture content, biomass yield, and morphometric traits. &lt;strong&gt;Conclusion&lt;/strong&gt;: Combining ridge-furrow and black plastic mulch is recommended to improve the biomass yield of sorghum in semi-arid Kitui County, and other areas with similar agroecological conditions.&lt;/p&gt;

Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum.

The gene expression landscape across different tissues and developmental stages reflects their biological functions and evolutionary patterns. Integrative and comprehensive analyses of all transcriptomic data in an organism are instrumental to obtaining a comprehensive picture of gene expression landscape. Such studies are still very limited in sorghum, which limits the discovery of the genetic basis underlying complex agricultural traits in sorghum. We characterized the genome-wide expression landscape for sorghum using 873 RNA-sequencing (RNA-seq) datasets representing 19 tissues. Our integrative analysis of these RNA-seq data provides the most comprehensive transcriptomic atlas for sorghum, which will be valuable for the sorghum research community for functional characterizations of sorghum genes. Based on the transcriptome atlas, we identified 595 housekeeping genes (HKGs) and 2080 tissue-specific expression genes (TEGs) for the 19 tissues. We identified different gene features between HKGs and TEGs, and we found that HKGs have experienced stronger selective constraints than TEGs. Furthermore, we built a transcriptome-wide co-expression network (TW-CEN) comprising 35 modules with each module enriched in specific Gene Ontology terms. High-connectivity genes in TW-CEN tend to express at high levels while undergoing intensive selective pressure. We also built global and seed-preferential co-expression networks of starch synthesis pathways, which indicated that photosynthesis and microtubule-based movement play important roles in starch synthesis. The global transcriptome atlas of sorghum generated by this study provides an important functional genomics resource for trait discovery and insight into starch synthesis regulation in sorghum.

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers.

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink's yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height (Dw1 and Dw2) and the YELLOW SEED1 locus (Y1) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

Genetic diversity, correlation and genotype × yield × trait (GYT) analysis of grain yield and nutritional quality traits in sorghum (Sorghum bicolor [L.] Moench) genotypes in Tigray, northern Ethiopia

Selecting sorghum genotypes with higher grain yield and nutritional quality is essential to tackle food insecurity and malnutrition in arid and semi-arid areas. Therefore, this study aimed to determine the genetic diversity, trait association and genotype by yield by trait (GYT) analysis and to select superior sorghum genotypes. One hundred and ten sorghum genotypes were evaluated at three locations in Tigray during the 2018 and 2019 growing seasons using alpha lattice design. Traits such as grain yield, protein content, ash content, starch content, zinc content, iron content, calcium content and magnesium content were profiled. Results showed that wide range and highly significant (p < 0.001) genotype mean performance in each environment as well as combined environments. Several highly performing genotypes were distinguished for each trait studied that could be exploited as breeding parents or direct use. This study further detected highly significant variation (p < 0.001) among the test genotypes for all the traits studied in individual environments and across environments suggesting the presence of sufficient genetic diversity for selection. The high broad-sense heritability (H2 > 0.9) in all individual environments and moderate to high (H2 > 0.0.41 < 0.82) in pooled environments recorded in the present study assured the possibility of effective selection among the genotypes. Besides, strong positive and negative associations were detected between some of the traits in individual and across environments. The significant positive association between traits indicates that both the traits can be improved concurrently through direct selection. Using the GYT analysis, we suggest ten promising sorghum genotypes for direct use or breeding programs in arid and semi-arid areas in general and in Tigray in particular.

Major impacts of widespread structural variation on sorghum.

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype-phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

Mapping and Screening of Candidate Gene Regulating the Biomass Yield of Sorghum (Sorghum bicolor L.).

Biomass yield is one of the important traits of sorghum, which is greatly affected by leaf morphology. In this study, a lobed-leaf mutant (sblob) was screened and identified, and its F2 inbred segregating line was constructed. Subsequently, MutMap and whole-genome sequencing were employed to identify the candidate gene (sblob1), the locus of which is Sobic.003G010300. Pfam and homologous analysis indicated that sblob1 encodes a Cytochrome P450 protein and plays a crucial role in the plant serotonin/melatonin biosynthesis pathway. Structural and functional changes in the sblob1 protein were elucidated. Hormone measurements revealed that sblob1 regulates both leaf morphology and sorghum biomass through regulation of the melatonin metabolic pathway. These findings provide valuable insights for further research and the enhancement of breeding programs, emphasizing the potential to optimize biomass yield in sorghum cultivation.

Genetic analysis for morphological, quality and biofuel related traits in sweet sorghum [Sorghum bicolor (L.) Moench

The present investigation was aimed to study the relationship between different methods of diallel data analysis of ethanol yield traits in sweet sorghum to select the relevant superior genotypes. Half-diallel hybrid analysis revealed that both general and specific combining abilities were significant for all the traits studied but the specific combining ability (SCA) was higher than the general combining ability (GCA), suggesting that the non-additive gene action is more important than additive one in controlling the studied traits. Graphically, traits of juice extraction percent, juice yield, and stripped stalk yield were most correlated with ethanol yield. Griffing and GT-biplot analyses produced equivalent results for GCA and SCA and were useful in estimating gene action by identifying the superior crosses across all the correlated traits and comparing the genotypes based on multiple traits. For the ethanol yield trait, genotype, Rio showed good GCA and was considered the best combiner parent, while crosses, Sugar Drib× Ramada and Sugar Drib × Honey may be used for the selection of the relevant traits in sorghum breeding programs to improve ethanol yield trait.

GrainPointNet: A deep-learning framework for non-invasive sorghum panicle grain count phenotyping

Grain count is an important trait in sorghum because it is highly correlated to the potential yield. By accurately phenotyping the number of grains per panicle, farmers and agronomists can better monitor crop development. Additionally, mapping the spatial variability of grain count can help identify areas of the field with higher or lower potential yields, allowing for targeted management strategies. This study introduces a method for predicting grain count for sorghum panicles by employing a deep learning-based regression framework for point clouds and Red Green Blue (RGB) images. The framework integrates global features derived from a point cloud model of the panicle and grain counts detected from a sequence of RGB images. The models were evaluated on a paired dataset of point cloud models and RGB images collected for 147 sorghum panicles, which included a variety of panicle structures and grain counts. The point cloud models were constructed via a proximal structure-from-motion-based photogrammetry workflow. The model uses PointNet as the backbone network for processing the point clouds and YoloV5 for detecting grains from RGB images. Following the grain detection step, a scaled dot product attention module is integrated into the network to process the grain counts obtained from the RGB image sequence. Finally, the global features for the point cloud model and the grain counts are combined to predict the total grain count for the panicle. Furthermore, the models are also evaluated on downscaled low-resolution point clouds to assess their potential to be adapted in the future for point cloud models for panicles acquired in the field. The models were able to predict grain counts for the high-resolution point cloud dataset with a mean absolute percent error of 6.5% and 6.8% for the low-resolution point cloud dataset. The results serve as a proof of concept to demonstrate the viability of using a multimodal approach based on point clouds and RGB images to estimate grain count per panicle. Additional enhancements to the model like the inclusion of a module to register the point cloud and the RGB images, and evaluating more point cloud backbone networks can help further strengthen the method.

Impact of root architecture and transpiration rate on drought tolerance in stay‐green sorghum

AbstractSorghum [Sorghum bicolor (L.) Moench] yield loss due to terminal drought stress is common in semiarid regions. Stay‐green is a drought adaptation trait, and a deeper understanding of stay‐green‐associated traits is necessary for sorghum breeding. We hypothesize that the stay‐green trait in sorghum may be associated with the root architecture and transpiration rate under drought stress. The objectives were to (i) identify the relationship among stay‐green‐associated traits, (ii) compare the root system architecture and transpiration rate of stay‐green (B35 and 296B) and senescent (BTx623 and R16) genotypes under drought stress, and (iii) quantify the impacts of reproductive stage drought stress on gas exchange and grain yield of stay‐green and senescent genotypes. A series of drought experiments were conducted with these genotypes. Under drought stress, the stay‐green genotypes had an increased total root length in the top 30–60 cm (18%) and 60–90 cm of soil (45%) than the senescent genotypes. In contrast, under progressive soil drying, stay‐green genotypes had a decreased transpiration rate (9%) than senescent genotypes by an early (∼1 h) partial closure of stomata under high vapor pressure deficit conditions. The increased seed yield (43%) in stay‐green genotypes is due to an increased photosynthetic rate (30%) and individual seed size (35%) than senescent genotypes. Overall, it is concluded that stay‐green phenotypes had two distinct drought adaptive mechanisms: (i) increased root length for increased soil exploration for water and (ii) an early decrease in the transpiration rate to conserve soil moisture. Identifying genomic markers for these traits would accelerate drought‐tolerant sorghum breeding.

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.