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.

SummaryThe positive effects of stay-green quantitative trait loci on grain yield of sorghum under post-anthesis drought are emergent consequences of their effects on water-use patterns, resulting from changes in pre-anthesis canopy size.

Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1-Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.

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.

SummaryStay-green is an integrated drought adaptation trait characterized by a distinct green leaf phenotype during grain filling under terminal drought. We used sorghum (Sorghum bicolor), a repository of drought adaptation mechanisms, to elucidate the physiological and genetic mechanisms underpinning stay-green.Near-isogenic sorghum lines (cv RTx7000) were characterized in a series of field and managed-environment trials (seven experiments and 14 environments) to determine the influence of four individual stay-green (Stg1-4) quantitative trait loci (QTLs) on canopy development, water use and grain yield under post-anthesis drought.The Stg QTL decreased tillering and the size of upper leaves, which reduced canopy size at anthesis. This reduction in transpirational leaf area conserved soil water before anthesis for use during grain filling. Increased water uptake during grain filling of Stg near-isogenic lines (NILs) relative to RTx7000 resulted in higher post-anthesis biomass production, grain number and yield. Importantly, there was no consistent yield penalty associated with the Stg QTL in the irrigated control.These results establish a link between the role of the Stg QTL in modifying canopy development and the subsequent impact on crop water use patterns and grain yield under terminal drought.

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers.

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.

Root architecture traits in wheat are important in deep soil moisture acquisition and may be used to improve adaptation to water-limited environments. The genetic architecture of two root traits, seminal root angle and seminal root number, were investigated using a doubled haploid population derived from SeriM82 and Hartog. Multiple novel quantitative trait loci (QTL) were identified, each one having a modest effect. For seminal root angle, four QTL (-log10(P) >3) were identified on 2A, 3D, 6A and 6B, and two suggestive QTL (-log10(P) >2) on 5D and 6B. For root number, two QTL were identified on 4A and 6A with four suggestive QTL on 1B, 3A, 3B and 4A. QTL for root angle and root number did not co-locate. Transgressive segregation was found for both traits. Known major height and phenology loci appear to have little effect on root angle and number. Presence or absence of the T1BL.1RS translocation did not significantly influence root angle. Broad sense heritability (h (2)) was estimated as 50 % for root angle and 31 % for root number. Root angle QTL were found to be segregating between wheat cultivars adapted to the target production region indicating potential to select for root angle in breeding programs.