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.

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. AbstractThere 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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-016-2844-6) contains supplementary material, which is available to authorized users.

Population structure is an important factor that affects the accuracy of estimated breeding values in genomic prediction. Natural sorghum [Sorghum bicolor (L.) Moench] populations exhibit population structure resulting from genetic and morphological differentiation due to evolutionary divergence. To study the impact of sorghum racial structure and diversity in genomic prediction, we conducted two cross‐validation (CV) experiments: CV1, proportional sampling from races; and CV2, sampling from across race (AR) or within race (WR). A diversity panel with 389 individuals with 224,007 single nucleotide polymorphisms was used for genomic prediction. Genomic heritabilities for traits were positively correlated (0.63) with their mean prediction accuracy (r) from CV1, and within‐subpopulation variance accounted for ∼80% of total genetic variance. The CV1 prediction accuracy ranged from 0.52–0.69, but r declined by 39 and 54% on average for WR and AR methods, respectively. As a predictor, race explained 30–50% of covariance for grain and panicle traits, but race was a bad predictor of plant height, as expected. Grain weight was consistently the best predicted trait across CV1 and CV2 methods except in AR. Difference in average r for WR and AR was greater in durra and caudatum, small in kafir, and nonexistent in guinea and mixed subgroups. We observed higher prevalence of minor alleles among guinea and mixed subgroups, highlighting contribution of allelic diversity towards prediction accuracy. Genomic prediction in sorghum will benefit from utilization of interracial diversity, and we emphasize the need for further investigations into the role of racial structure in genomic prediction.

Sorghum bicolor, a photosynthetically efficient C4 grass, represents an important source of grain, forage, fermentable sugars, and cellulosic fibers that can be utilized in myriad applications ranging from bioenergy to bioindustrial feedstocks. Sorghum’s efficient fixation of carbon per unit time per unit area per unit input has led to its classification as a preferred biomass crop highlighted by its designation as an advanced biofuel by the U.S. Department of Energy. Due to its extensive genetic diversity and worldwide colonization, sorghum has considerable diversity for a range of phenotypes influencing productivity, composition, and sink/source dynamics. To dissect the genetic basis of these key traits, we present a sorghum carbon-partitioning nested association mapping population generated by crossing 11 diverse founder lines with Grassl as the single recurrent female. By exploiting existing variation among cellulosic, forage, sweet and grain sorghum carbon partitioning regimes, the sorghum carbon-partitioning nested association mapping population will allow the identification of important biomass-associated traits, elucidate the genetic architecture underlying carbon partitioning and improve our understanding of the genetic determinants affecting unique phenotypes within Poaceae. We contrast this nested association mapping population with an existing grain population generated using Tx430 as the recurrent female. Genotypic data are assessed for quality by examining variant density, nucleotide diversity, linkage decay, and is validated using pericarp and testa phenotypes to map known genes affecting these phenotypes. We release the 11-family nested association mapping population along with corresponding genomic data for use in genetic, genomic, and agronomic studies with a focus on carbon-partitioning regimes.

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.