With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.

Grain yield and its primary determinants, grain number and weight, are important traits in cereal crops that have been well studied; however, the genetic basis of and interactions between these traits remain poorly understood. Characterization of grain yield per primary panicle (YPP), grain number per primary panicle (GNP), and 1000‐grain weight (TGW) in sorghum [ Sorghum bicolor (L.) Moench], a hardy C ₄ cereal with a genome size of ∼730 Mb, was implemented in a diversity panel containing 390 accessions. These accessions were genotyped to obtain 268,830 single‐nucleotide polymorphisms (SNPs). Genome‐wide association studies (GWAS) were performed to identify loci associated with each grain yield component and understand the genetic interactions between these traits. Genome‐wide association studies identified associations across the genome with YPP, GNP, and TGW that were located within previously mapped sorghum QTL for panicle weight, grain yield, and seed size, respectively. There were no significant associations between GNP and TGW that were within 100 kb, much greater than the average linkage disequilibrium (LD) in sorghum. The identification of nonoverlapping loci for grain number and weight suggests these traits may be manipulated independently to increase the grain yield of sorghum. Following GWAS, genomic regions surrounding each associated SNP were mined for candidate genes. Previously published expression data indicated several TGW candidate genes, including an ethylene receptor homolog, were primarily expressed within developing seed tissues to support GWAS. Furthermore, maize ( Zea mays L.) homologs of identified TGW candidates were differentially expressed within the seed between small‐ and large‐kernel lines from a segregating maize population.

Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are still unresolved. The goals of this study were to quantify natural variation of sorghum grain composition and to identify single-nucleotide polymorphisms (SNPs) associated with variation in grain composition concentrations. In this study, we quantified protein, fat, and starch in a global sorghum diversity panel using near-infrared spectroscopy (NIRS). Protein content ranged from 8.1 to 18.8%, fat content ranged from 1.0 to 4.3%, and starch content ranged from 61.7 to 71.1%. Durra and bicolor-durra sorghum from Ethiopia and India had the highest protein and fat and the lowest starch content, while kafir sorghum from USA, India, and South Africa had the lowest protein and the highest starch content. Genome-wide association studies (GWAS) identified quantitative trait loci (QTL) for sorghum protein, fat, and starch. Previously published RNAseq data was used to identify candidate genes within a GWAS QTL region. A putative alpha-amylase 3 gene, which has previously been shown to be associated with grain composition traits, was identified as a strong candidate for protein and fat variation. We identified promising sources of genetic material for manipulation of grain composition traits, and several loci and candidate genes that may control sorghum grain composition. This survey of grain composition in sorghum germplasm and identification of protein, fat, and starch QTL contributes to our understanding of the genetic basis of natural variation in sorghum grain nutritional traits.

Seedling establishment and seed nutritional quality require the sequestration of sufficient element nutrients. The identification of genes and alleles that modify element content in the grains of cereals, including sorghum (Sorghum bicolor), is fundamental to developing breeding and selection methods aimed at increasing bioavailable element content and improving crop growth. We have developed a high-throughput work flow for the simultaneous measurement of multiple elements in sorghum seeds. We measured seed element levels in the genotyped Sorghum Association Panel, representing all major cultivated sorghum races from diverse geographic and climatic regions, and mapped alleles contributing to seed element variation across three environments by genome-wide association. We observed significant phenotypic and genetic correlation between several elements across multiple years and diverse environments. The power of combining high-precision measurements with genome-wide association was demonstrated by implementing rank transformation and a multilocus mixed model to map alleles controlling 20 element traits, identifying 255 loci affecting the sorghum seed ionome. Sequence similarity to genes characterized in previous studies identified likely causative genes for the accumulation of zinc, manganese, nickel, calcium, and cadmium in sorghum seeds. In addition to strong candidates for these five elements, we provide a list of candidate loci for several other elements. Our approach enabled the identification of single-nucleotide polymorphisms in strong linkage disequilibrium with causative polymorphisms that can be evaluated in targeted selection strategies for plant breeding and improvement.

Key message Coordinated association and linkage mapping identified 25 grain quality QTLs in multiple environments, and fine mapping of the Wx locus supports the use of high-density genetic markers in linkage mapping. Abstract There is a wide range of end-use products made from cereal grains, and these products often demand different grain characteristics. Fortunately, cereal crop species including sorghum [Sorghum bicolor (L.) Moench] contain high phenotypic variation for traits influencing grain quality. Identifying genetic variants underlying this phenotypic variation allows plant breeders to develop genotypes with grain attributes optimized for their intended usage. Multiple sorghum mapping populations were rigorously phenotyped across two environments (SC Coastal Plain and Central TX) in 2 years for five major grain quality traits: amylose, starch, crude protein, crude fat, and gross energy. Coordinated association and linkage mapping revealed several robust QTLs that make prime targets to improve grain quality for food, feed, and fuel products. Although the amylose QTL interval spanned many megabases, the marker with greatest significance was located just 12 kb from waxy (Wx), the primary gene regulating amylose production in cereal grains. This suggests higher resolution mapping in recombinant inbred line (RIL) populations can be obtained when genotyped at a high marker density. The major QTL for crude fat content, identified in both a RIL population and grain sorghum diversity panel, encompassed the DGAT1 locus, a critical gene involved in maize lipid biosynthesis. Another QTL on chromosome 1 was consistently mapped in both RIL populations for multiple grain quality traits including starch, crude protein, and gross energy. Collectively, these genetic regions offer excellent opportunities to manipulate grain composition and set up future studies for gene validation.

The animal industry is a major sector of agriculture in the southeastern United States, but a large deficit exists in regional feed grains needed to support the industry. An increase in production of sorghum [Sorghum bicolor (L.) Moench], a water‐ and nutrient‐use‐efficient cereal, on marginal lands could lead to an alternative crop option for growers and reduce the current grain deficit. Quantitative trait locus (QTL) mapping of grain yield components in two sorghum biparental recombinant inbred line (RIL) populations was performed to better understand the genetic basis of grain yield and characterize these traits in a marginal environment. A more robust knowledge of the genetics underlying these complex traits could provide insights into molecular breeding strategies that aim to increase genetic gain. Specific yield traits investigated were grain number per primary panicle (GNP), 1000‐grain weight (TGW), and grain yield per primary panicle (YPP). Two‐year phenotyping in the South Carolina coastal plain revealed greater than threefold variation for both GNP and YPP, whereas TGW variation was just above twofold in both RIL families. There were 16 total yield trait QTL identified across both populations. Of the 16, eight QTL colocated with previously published QTL for yield‐related traits, including a QTL on chromosome 1 that was significant for all three grain yield components. A novel QTL for TGW was identified on chromosome 5 that explained >21% of the phenotypic variance observed in one RIL population. This QTL and the seven additional novel QTL identified in this study provide new targets for grain yield improvement in sorghum.