Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16–45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.

The stay-green drought adaptation mechanism has been widely promoted as a way of improving grain yield and lodging resistance in sorghum [Sorghum bicolor (L.) Moench] and as a result has been the subject of many physiological and genetic studies. The relevance of these studies to elite sorghum hybrids is not clear given that they sample a limited number of environments and were conducted using inbred lines or relatively small numbers of experimental F^ hybrids. In this study we Investigated the relationship between stay-green and yield using data from breeding trials that sampled 1668 unique hybrid combinations and 23 environments whose mean yields varied from 2.3 to 10.5 t ha"^ The strength and direction of the association between stay-green and grain yield varied with both environment and genetic background (male tester). The majority of associations were positive, particularly in environments with yields below 6 t ha"^ As trial mean yield increased above 6 t ha"^ there was a trend toward an increased number of negative associations; however, the number and magnitude of the positive associations were larger. Given that post-flowering drought is very commonly experienced by sorghum crops world wide and average yields are 1.2 and 2.5 t ha"^ for the world and Australia, respectively, our results indicate that selection for staygreen in elite sorghum hybrids may be broadly beneficial for increasing yield in a wide range of environments.

We describe the development and application of the Sorghum QTL Atlas, a high-resolution, open-access research platform to facilitate candidate gene identification across three cereal species, sorghum, maize and rice. Abstract The mechanisms governing the genetic control of many quantitative traits are only poorly understood and have yet to be fully exploited. Over the last two decades, over a thousand QTL and GWAS studies have been published in the major cereal crops including sorghum, maize and rice. A large body of information has been generated on the genetic basis of quantitative traits, their genomic location, allelic effects and epistatic interactions. However, such QTL information has not been widely applied by cereal improvement programs and genetic researchers worldwide. In part this is due to the heterogeneous nature of QTL studies which leads QTL reliability variation from study to study. Using approaches to adjust the QTL confidence interval, this platform provides access to the most updated sorghum QTL information than any database available, spanning 23 years of research since 1995. The QTL database provides information on the predicted gene models underlying the QTL CI, across all sorghum genome assembly gene sets and maize and rice genome assemblies and also provides information on the diversity of the underlying genes and information on signatures of selection in sorghum. The resulting high-resolution, open-access research platform facilitates candidate gene identification across 3 cereal species, sorghum, maize and rice. Using a number of trait examples, we demonstrate the power and resolution of the resource to facilitate comparative genomics approaches to provide a bridge between genomics and applied breeding.

Loss of genetic diversity in elite breeding populations is often identified as a potential impediment to future genetic gain. The use of diverse unadapted germplasm in breeding has been suggested as one way of combating this problem but often proves impractical, due to the poor performance of progeny produced by crosses between adapted and unadapted parent lines. This study evaluates the effectiveness of a breeding method aimed at utilizing unadapted sorghum [Sorghum bicolor (L.) Moench] germplasm. The method involves producing large BC.|F^ populations, using a single elite line as the recurrent parent, and then selecting the resulting progeny for key adaptive traits (e.g., height and flowering time). Populations of 30 to 90 BC^F^ lines derived from 56 unadapted parents were then evaluated in hybrid combination in 21 trials over a 4-yr period. The unadapted sources included lines with geographic or racial diversity, phenotypic diversity for key traits, elite lines from breeding programs in other countries, and cross-compatible wild species. Despite strong selection for acceptable height and maturity, considerable genetic variation for grain yield was retained in the populations, with molecular marker analysis indicating an average of 22% of the genome being retained in each line as compared with a theoretical 25% in the absence of selection. In all cases progeny were identified in each population that performed significantly better than the recurrent parent hybrid for grain yield, and in some cases specific adaptation of particular populations was observed. The method we used proved to be an effective way to introduce new alíeles from unadapted sorghum germplasm into elite breeding material. The potential of the populations as a resource for nested association mapping to elucidate the architecture of complex traits is discussed.

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

RESEARCHT he distribution of roots in the soil can infl uence the extent and timing of access to water and nutrients to support crop growth (Blum and Ritchie, 1984;Lynch and van Beem, 1993;Manschadi et al., 2006;Hammer et al., 2009). Despite its importance, little work has been done to include root-system architecture in crop improvement programs, because of the diffi culties involved in root recovery and in studying root-system architecture in situ. As a consequence, little information exists on the extent of genetic variation in traits associated with root-system architecture in sorghum [Sorghum bicolor (L.) Moench] and on the potential for manipulating this variation to best suit water availability in production environments. Hence, understanding of genetic variability in, and genetic control of, root-system architecture could assist sorghum crop improvement programs in developing desired root-system attributes for target environments.Root-system architecture, and hence water-extraction patterns, can depend on a range of traits. Root thickness and rooting

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