Genetic dissection of root architecture in Ethiopian sorghum landraces

KEY MESSAGE

This study quantified genetic variation in root system architecture (root number, angle, length and dry mass) within a diversity panel of 1771 Ethiopian sorghum landraces and identified 22 genomic regions associated with the root variations. The root system architecture (RSA) of crop plants influences adaptation to water-limited conditions and determines the capacity of a plant to access soil water and nutrients. Four key root traits (number, angle, length and dry mass) were evaluated in a diversity panel of 1771 Ethiopian sorghum landraces using purpose-built root chambers. Significant genetic variation was observed in all studied root traits, with nodal root angle ranging from 16.4° to 26.6°, with a high repeatability of 78.9%. Genome wide association studies identified a total of 22 genomic regions associated with root traits which were distributed on all chromosomes except chromosome SBI-10. Among the 22 root genomic regions, 15 co-located with RSA trait QTL previously identified in sorghum, with the remaining seven representing novel RSA QTL. The majority (85.7%) of identified root angle QTL also co-localized with QTL previously identified for stay-green in sorghum. This suggests that the stay-green phenotype might be associated with root architecture that enhances water extraction during water stress conditions. The results open avenues for manipulating root phenotypes to improve productivity in abiotic stress environments via marker-assisted selection.

Variation in mitogenome structural conformation in wild and cultivated lineages of sorghum corresponds with domestication history and plastome evolution

BACKGROUND

Mitochondria are organelles within eukaryotic cells that are central to the metabolic processes of cellular respiration and ATP production. However, the evolution of mitochondrial genomes (mitogenomes) in plants is virtually unknown compared to animal mitogenomes or plant plastids, due to complex structural variation and long stretches of repetitive DNA making accurate genome assembly more challenging. Comparing the structural and sequence differences of organellar genomes within and between sorghum species is an essential step in understanding evolutionary processes such as organellar sequence transfer to the nuclear genome as well as improving agronomic traits in sorghum related to cellular metabolism.

RESULTS

Here, we assembled seven sorghum mitochondrial and plastid genomes and resolved reticulated mitogenome structures with multilinked relationships that could be grouped into three structural conformations that differ in the content of repeats and genes by contig. The grouping of these mitogenome structural types reflects the two domestication events for sorghum in east and west Africa.

CONCLUSIONS

We report seven mitogenomes of sorghum from different cultivars and wild sources. The assembly method used here will be helpful in resolving complex genomic structures in other plant species. Our findings give new insights into the structure of sorghum mitogenomes that provides an important foundation for future research into the improvement of sorghum traits related to cellular respiration, cytonuclear incompatibly, and disease resistance.

Genetic modification of PIN genes induces causal mechanisms of stay-green drought adaptation phenotype

The stay-green trait is recognized as a key drought adaptation mechanism in cereals worldwide. Stay-green sorghum plants exhibit delayed senescence of leaves and stems, leading to prolonged growth, a reduced risk of lodging, and higher grain yield under end-of-season drought stress. More than 45 quantitative trait loci (QTL) associated with stay-green have been identified, including two major QTL (Stg1 and Stg2). However, the contributing genes that regulate functional stay-green are not known. Here we show that the PIN FORMED family of auxin efflux carrier genes induce some of the causal mechanisms driving the stay-green phenotype in sorghum, with SbPIN4 and SbPIN2 located in Stg1 and Stg2, respectively. We found that nine of 11 sorghum PIN genes aligned with known stay-green QTL. In transgenic studies, we demonstrated that PIN genes located within the Stg1 (SbPIN4), Stg2 (SbPIN2), and Stg3b (SbPIN1) QTL regions acted pleiotropically to modulate canopy development, root architecture, and panicle growth in sorghum, with SbPIN1, SbPIN2, and SbPIN4 differentially expressed in various organs relative to the non-stay-green control. The emergent consequence of such modifications in canopy and root architecture is a stay-green phenotype. Crop simulation modelling shows that the SbPIN2 phenotype can increase grain yield under drought.

Oculopharyngeal Muscular Dystrophy Ptosis, Mueller's Muscle Involvement, and a Review of Management Over 34 Years

PURPOSE

To review the management of the ptosis associated with oculopharyngeal muscular dystrophy (OPMD) from one author's experience over 34 years, demonstrate Mueller's muscle involvement in this disease, and how this impacts the preferred choice of surgery.

METHODS

Retrospective, nonrandomized comparative case series. Forty patients with OPMD who underwent primary bilateral ptosis surgery through an anterior eyelid incision and had their Mueller's muscle biopsied (one side) and sent for histopathologic analysis were selected for chart review. The main outcome measure was the presence or absence of dystrophic changes in the biopsied Mueller's muscle.

RESULTS

In 29/40 biopsies (72.5%), there were dystrophic changes and fatty infiltration of Mueller's muscle identified histopathologically.

CONCLUSIONS

Mueller's muscle is involved in the dystrophic process more often than expected contributing to ptosis in the OPMD syndrome. A combined Mueller's-aponeurotic advancement is more effective at elevating the eyelid than simply advancing the aponeurosis when Mueller's is fatty infiltrated at the time of external levator advancement surgery in our experience. Management strategies for ptosis surgery in OPMD are reviewed. The age of onset, levator muscle function, previous ptosis repair, how debilitated the patient is with their disease process systemically, as well as the presence of other eye problems (e.g., dry eye, prior glaucoma filtering procedures, history of corneal surgery, laser refractive procedure) are important clinical considerations in patients with OPMD.

Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery

In plant breeding, unmanned aerial vehicles (UAVs) carrying multispectral cameras have demonstrated increasing utility for high-throughput phenotyping (HTP) to aid the interpretation of genotype and environment effects on morphological, biochemical, and physiological traits. A key constraint remains the reduced resolution and quality extracted from "stitched" mosaics generated from UAV missions across large areas. This can be addressed by generating high-quality reflectance data from a single nadir image per plot. In this study, a pipeline was developed to derive reflectance data from raw multispectral UAV images that preserve the original high spatial and spectral resolutions and to use these for phenotyping applications. Sequential steps involved (i) imagery calibration, (ii) spectral band alignment, (iii) backward calculation, (iv) plot segmentation, and (v) application. Each step was designed and optimised to estimate the number of plants and count sorghum heads within each breeding plot. Using a derived nadir image of each plot, the coefficients of determination were 0.90 and 0.86 for estimates of the number of sorghum plants and heads, respectively. Furthermore, the reflectance information acquired from the different spectral bands showed appreciably high discriminative ability for sorghum head colours (i.e., red and white). Deployment of this pipeline allowed accurate segmentation of crop organs at the canopy level across many diverse field plots with minimal training needed from machine learning approaches.

Manipulating assimilate availability provides insight into the genes controlling grain size in sorghum

Variation in grain size, a major determinant of grain yield and quality in cereal crops, is determined by both the plant's genetic potential and the available assimilate to fill the grain in the absence of stress. This study investigated grain size variation in response to variation in assimilate supply in sorghum using a diversity panel (n = 837) and a backcross-nested association mapping population (n = 1421) across four experiments. To explore the effects of genetic potential and assimilate availability on grain size, the top half of selected panicles was removed at anthesis. Results showed substantial variation in five grain size parameters with high heritability. Artificial reduction in grain number resulted in a general increase in grain weight, with the extent of the increase varying across genotypes. Genome-wide association studies identified 44 grain size quantitative trait locus (QTL) that were likely to act on assimilate availability and 50 QTL that were likely to act on genetic potential. This finding was further supported by functional enrichment analysis and co-location analysis with known grain number QTL and candidate genes. RNA interference and overexpression experiments were conducted to validate the function of one of the identified gene, SbDEP1, showing that SbDEP1 positively regulates grain number and negatively regulates grain size by controlling primary branching in sorghum. Haplotype analysis of SbDEP1 suggested a possible role in racial differentiation. The enhanced understanding of grain size variation in relation to assimilate availability presented in this study will benefit sorghum improvement and have implications for other cereal crops.

Acute orbital inflammation with loss of vision: a paradoxical adverse event associated with infliximab therapy for Crohn's disease

Anti-TNF-α agents (e.g. infliximab, adalimumab, etanercept) are effective management options in various inflammatory and autoimmune diseases (e.g. inflammatory bowel disease). The occurrence during anti-TNF-α agent therapy of a new onset or exacerbation of an inflammatory condition that usually responds to this class of drug has been termed a paradoxical adverse event (PAE). A wide range of ophthalmic PAEs have been reported including uveitis, optic neuritis/neuropathy, scleritis, orbital myositis, retinal vasculitis, and others. The patient reported herein developed a dramatic orbital inflammatory PAE during his infliximab infusions, which manifested as an acute orbital apex syndrome with vision loss. Physicians using this medication should be aware of this serious vision-threatening PAE, and urgent therapy with high dose intravenous corticosteroids may be required.

Perspectives on Applications of Hierarchical Gene-To-Phenotype (G2P) Maps to Capture Non-stationary Effects of Alleles in Genomic Prediction

Genomic prediction of complex traits across environments, breeding cycles, and populations remains a challenge for plant breeding. A potential explanation for this is that underlying non-additive genetic (GxG) and genotype-by-environment (GxE) interactions generate allele substitution effects that are non-stationary across different contexts. Such non-stationary effects of alleles are either ignored or assumed to be implicitly captured by most gene-to-phenotype (G2P) maps used in genomic prediction. The implicit capture of non-stationary effects of alleles requires the G2P map to be re-estimated across different contexts. We discuss the development and application of hierarchical G2P maps that explicitly capture non-stationary effects of alleles and have successfully increased short-term prediction accuracy in plant breeding. These hierarchical G2P maps achieve increases in prediction accuracy by allowing intermediate processes such as other traits and environmental factors and their interactions to contribute to complex trait variation. However, long-term prediction remains a challenge. The plant breeding community should undertake complementary simulation and empirical experiments to interrogate various hierarchical G2P maps that connect GxG and GxE interactions simultaneously. The existing genetic correlation framework can be used to assess the magnitude of non-stationary effects of alleles and the predictive ability of these hierarchical G2P maps in long-term, multi-context genomic predictions of complex traits in plant breeding.

A rare case of intramuscular angioma involving the medial rectus muscle

Benign benign vascular tumors (e.g., hemangiomas) and malformations are commonly encountered lesions in all ages of life, especially in infancy and childhood. Hemangiomas are considered to be proliferative vascular lesions while malformations are defects of embryonal vascular morphogenesis. Less than 1% of hemangiomas within the body occur in skeletal muscle and of these approximately 15% have been reported to occur in the head and neck musculature (e.g. masseter, trapezius, sternocleidomastoid, mylohyoid, temporalis muscles) Intramuscular angioma (the preferred term for lesions formerly known as intramuscular hemangiomas by WHO Tumors of Soft Tissue and Bone Classification, 5th edition 2020) (IA) occurring in the extraocular muscles or palpebral muscles (orbicularis oculi) are extremely rare with only a few case reports in the English literature. To date, all the extraocular muscles have reportedly been involved. With the case reported herein, the medial rectus muscle appears to be the most common extraocular muscle involved.

Tall 3-dwarfs: oxymoron or opportunity to increase grain yield in sorghum?

Plant height was positively correlated with grain yield across a large set of 3-dwarf sorghum hybrids and production environments in north-eastern Australia. In industrialised countries, plant breeders tend to select for short plant stature in cereals like wheat, barley and rice, but also grain sorghum. This is mainly to prevent stalk lodging and to allow for machine harvesting. However, this counteracts an intrinsic positive relationship between plant height and yield potential often observed in cereals. We used data from multi-environment breeding trials comprising large sets of female sorghum lines from a range of pedigrees in hybrid combination with five different male testers. The hybrids were grown in 22 different rainfed environments in north-eastern Australia, which allowed us to thoroughly examine the relationship between plant height and yield across a range of productivity levels. Covariate analysis showed that in 38 out of the 90 tested relationships, grain yield was significantly (p < 0.05) positively and in only one case significantly negatively associated with plant height. This strong positive association between the traits was supported by the observation that 87% of the effects were either positive or zero. The effects of height on yield ranged from a decrease of 0.015 t ha^-1 to an increase of 0.057 t ha^-1 cm^-1. The majority of the negative effects were observed in low-yielding trials and the positive effect of height tended to increase with increasing mean trial yield. Opportunities to increase yield potential by selecting for slightly taller sorghum hybrids therefore need to be explored in context with the target environments and in combination with other means to control the risks of lodging.

Genetic diversity of Ethiopian sorghum reveals signatures of climatic adaptation

A large collection of Ethiopian sorghum landraces, characterized by agro-ecology and racial-group, was found to contain high levels of diversity and admixture, with significant SNP associations identified for environmental adaptation. Sorghum [Sorghum bicolor L. (Moench)] is a major staple food crop in Ethiopia, exhibiting extensive genetic diversity with adaptations to diverse agroecologies. The environmental and climatic drivers, as well as the genomic basis of adaptation, are poorly understood in Ethiopian sorghum and are critical elements for the development of climate-resilient crops. Exploration of the genome-environment association (GEA) is important for identifying adaptive loci and predicting phenotypic variation. The current study aimed to better understand the GEA of a large collection of Ethiopian sorghum landraces (n = 940), characterized with genome-wide SNP markers, to investigate key traits related to adaptation to temperature, precipitation and altitude. The Ethiopian sorghum landrace collection was found to consist of 12 subpopulations with high levels of admixture (47%), representing all the major racial groups of cultivated sorghum with the exception of kafir. Redundancy analysis indicated that agroecology explained up to 10% of the total SNP variation, and geographical location up to 6%. GEA identified 18 significant SNP markers for environmental variables. These SNPs were found to be significantly enriched (P < 0.05) for a priori QTL for drought and cold adaptation. The findings from this study improve our understanding of the genetic control of adaptive traits in Ethiopian sorghum. Further, the Ethiopian sorghum germplasm collection provides sources of adaptation to harsh environments (cold and/or drought) that could be deployed in breeding programs globally for abiotic stress adaptation.

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals

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.

Multi-environment analysis of sorghum breeding trials using additive and dominance genomic relationships

Multi-environment models using marker-based kinship information for both additive and dominance effects can accurately predict hybrid performance in different environments. Sorghum is an important hybrid crop that is grown extensively in many subtropical and tropical regions including Northern NSW and Queensland in Australia. The highly varying weather patterns in the Australian summer months mean that sorghum hybrids exhibit a great deal of variation in yield between locations. To ultimately enable prediction of the outcome of crossing parental lines, both additive effects on yield performance and dominance interaction effects need to be characterised. This paper demonstrates that fitting a linear mixed model that includes both types of effects calculated using genetic markers in relationship matrices improves predictions. Genotype by environment interactions was investigated by comparing FA1 (single-factor analytic) and FA2 (two-factor analytic) structures. The G×E causes a change in hybrid rankings between trials with a difference of up to 25% of the hybrids in the top 10% of each trial. The prediction accuracies increased with the addition of the dominance term (over and above that achieved with an additive effect alone) by an average of 15% and a maximum of 60%. The percentage of dominance of the total genetic variance varied between trials with the trials with higher broad-sense heritability having the greater percentage of dominance. The inclusion of dominance in the factor analytic models improves the accuracy of the additive effects. Breeders selecting high yielding parents for crossing need to be aware of effects due to environment and dominance.

Primary ductal adenocarcinoma of the lacrimal gland: A review and report of five cases

Primary ductal adenocarcinoma (PDA) is a rare epithelial tumor of the lacrimal gland. Herein we report 5 cases and review 29 published cases of PDA of the lacrimal gland. Among these 5 cases, the most common clinical presentation was painless swelling and/or proptosis of their eye. The size of the lesions ranged from 1.6 to 2.5 cm. Histopathologic examination revealed proliferations of ductal or gland-like cells with vesiculated pleomorphic nuclei and prominent nucleoli. Tumor cells stained positive for epithelial and apocrine differentiation markers. Immunohistochemistry for human epidermal growth factor 2 was positive in 2 of the 4 cases. Four of the five patients were alive at the last follow-up visit. One died with bone metastases, which were diagnosed 25 months after exenteration and then survived an additional 51 months. On reviewing of twenty-nine previously published cases of PDA, the mean age of diagnosis was 58 years, with a male predominance (75%). Fifteen patients (54%) had distant metastases, 1 (4%) had local recurrence, and 10 (37%) suffered from a PDA-related death. PDA is a high-grade aggressive epithelial tumor of the lacrimal gland. Although rare, awareness and recognition of this malignancy are important to help determine prognosis and treatment options.

Crop Genomics Goes Beyond a Single Reference Genome

The inadequacy of a single reference genome to capture the full landscape of genetic diversity within a species constrains exploration of genetic variation for crop improvement. A recent study by Yang et al. has demonstrated the value of multiple reference-quality genomes in capturing structural variants and guiding biological discovery.

Combining pedigree and genomic information to improve prediction quality: an example in sorghum

The use of a kinship matrix integrating pedigree- and marker-based relationships optimized the performance of genomic prediction in sorghum, especially for traits of lower heritability. Selection based on genome-wide markers has become an active breeding strategy in crops. Genomic prediction models can make use of pedigree information to account for the residual polygenic effects not captured by markers. Our aim was to evaluate the impact of using pedigree and genomic information on prediction quality of breeding values for different traits in sorghum. We explored BLUP models that use weighted combinations of pedigree and genomic relationship matrices. The optimal weighting factor was empirically determined in order to maximize predictive ability after evaluating a range of candidate weights. The phenotypic data consisted of testcross evaluations of sorghum parental lines across multiple environments. All lines were genotyped, and full pedigree information was available. The performance of the best predictive combined matrix was compared to that of models fitting the component matrices independently. Model performance was assessed using cross-validation technique. Fitting a combined pedigree-genomic matrix with the optimal weight always yielded the largest increases in predictive ability and the largest reductions in prediction bias relative to the simple G-BLUP. However, the weight that optimized prediction varied across traits. The benefits of including pedigree information in the genomic model were more relevant for traits with lower heritability, such as grain yield and stay-green. Our results suggest that the combination of pedigree and genomic relatedness can be used to optimize predictions of complex traits in crops when the additive variation is not fully explained by markers.

A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting

The yield of cereal crops such as sorghum (Sorghum bicolor L. Moench) depends on the distribution of crop-heads in varying branching arrangements. Therefore, counting the head number per unit area is critical for plant breeders to correlate with the genotypic variation in a specific breeding field. However, measuring such phenotypic traits manually is an extremely labor-intensive process and suffers from low efficiency and human errors. Moreover, the process is almost infeasible for large-scale breeding plantations or experiments. Machine learning-based approaches like deep convolutional neural network (CNN) based object detectors are promising tools for efficient object detection and counting. However, a significant limitation of such deep learning-based approaches is that they typically require a massive amount of hand-labeled images for training, which is still a tedious process. Here, we propose an active learning inspired weakly supervised deep learning framework for sorghum head detection and counting from UAV-based images. We demonstrate that it is possible to significantly reduce human labeling effort without compromising final model performance (R ² between human count and machine count is 0.88) by using a semitrained CNN model (i.e., trained with limited labeled data) to perform synthetic annotation. In addition, we also visualize key features that the network learns. This improves trustworthiness by enabling users to better understand and trust the decisions that the trained deep learning model makes.

Genomic Prediction of Grain Yield and Drought-Adaptation Capacity in Sorghum Is Enhanced by Multi-Trait Analysis

Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorghum breeding for broad adaptation to a range of environments. Genomic prediction for these traits may be enhanced by joint multi-trait analysis. The objectives of this study were to assess the capacity of multi-trait models to improve genomic prediction of parental breeding values for grain yield and stay-green in sorghum by using information from correlated auxiliary traits, and to determine the combinations of traits that optimize predictive results in specific scenarios. The dataset included phenotypic performance of 2645 testcross hybrids across 26 environments as well as genomic and pedigree information on their female parental lines. The traits considered were grain yield (GY), stay-green (SG), plant height (PH), and flowering time (FT). We evaluated the improvement in predictive performance of multi-trait G-BLUP models relative to single-trait G-BLUP. The use of a blended kinship matrix exploiting pedigree and genomic information was also explored to optimize multi-trait predictions. Predictive ability for GY increased up to 16% when PH information on the training population was exploited through multi-trait genomic analysis. For SG prediction, full advantage from multi-trait G-BLUP was obtained only when GY information was also available on the predicted lines per se, with predictive ability improvements of up to 19%. Predictive ability, unbiasedness and accuracy of predictions from conventional multi-trait G-BLUP were further optimized by using a combined pedigree-genomic relationship matrix. Results of this study suggest that multi-trait genomic evaluation combining routinely measured traits may be used to improve prediction of crop productivity and drought adaptability in grain sorghum.

Aerial Imagery Analysis - Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy

Sorghum (Sorghum bicolor L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure. We propose a two-step machine-based image processing method to detect and count the number of heads from high-resolution images captured by unmanned aerial vehicles (UAVs) in a breeding trial. To demonstrate the performance of the proposed method, 52 images were manually labeled; the precision and recall of head detection were 0.87 and 0.98, respectively, and the coefficient of determination (R 2) between the manual and new methods of counting was 0.84. To verify the utility of the method in breeding programs, a geolocation-based plot segmentation method was applied to pre-processed ortho-mosaic images to extract >1000 plots from original RGB images. Forty of these plots were randomly selected and labeled manually; the precision and recall of detection were 0.82 and 0.98, respectively, and the coefficient of determination between manual and algorithm counting was 0.56, with the major source of error being related to the morphology of plants resulting in heads being displayed both within and outside the plot in which the plants were sown, i.e., being allocated to a neighboring plot. Finally, the potential applications in yield estimation from UAV-based imagery from agronomy experiments and scouting of production fields are also discussed.

Integrating modelling and phenotyping approaches to identify and screen complex traits: transpiration efficiency in cereals

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plant and with the environment, and to identify traits of most relevance to the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to characterize traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their value in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding programme. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programmes for improving yield gains in target populations of environments.

Unsuspected and misdiagnosed posterior uveal melanoma following enucleation and evisceration in Ottawa-Gatineau

OBJECTIVE

There is a gap in the recent literature on the topic of clinically misdiagnosed and unsuspected posterior uveal melanomas (PUM) with a calculation of the frequency of these events for a specific geographical area. As the only ophthalmic pathology laboratory in our region, we determined the rate of these outcomes over a 16-year period.

METHODS

We retrospectively reviewed 2558 consecutive ophthalmic pathologic specimens in the Ottawa-Gatineau region, of which 334 were eviscerations and 227 were enucleations. We calculated the frequency of clinically misdiagnosed PUM and of clinically unsuspected PUM. We also determined the rate of uveal melanoma undergoing enucleation.

RESULTS

From 100 diagnoses of PUM, 2 (2.0%) cases were clinically unsuspected and 2 (2.0%) cases were clinically misdiagnosed. The rate of uveal melanoma undergoing enucleation was 5.6 cases per 1 000 000 of population per annum. From 2009 to 2012, the incidence of this event was 3.8 cases per 1 000 000 per annum, which was lower than the previous three 4-year increments.

CONCLUSIONS

We present the first and only single-centred, population-based data on the rates of unsuspected PUM and of clinical misdiagnosis of PUM in the era of modern diagnostic imaging. Our rate of clinical misdiagnosis is within the range of recent reports of this event. Unsuspected PUM occurred at a rate substantially lower than previously published. The incidence of uveal melanoma undergoing enucleation has decreased despite an increase in population, which reflects a shift in management from enucleation to radiation therapy.

Characterization of Linkage Disequilibrium and Population Structure in a Mungbean Diversity Panel

Mungbean [Vigna radiata (L.) R. Wilczek var. radiata] is an important grain legume globally, providing a high-quality plant protein source largely produced and consumed in South and East Asia. This study aimed to characterize a mungbean diversity panel consisting of 466 cultivated accessions and demonstrate its utility by conducting a pilot genome-wide association study of seed coat color. In addition 16 wild accessions were genotyped for comparison and in total over 22,000 polymorphic genome-wide SNPs were identified and used to analyze the genetic diversity, population structure, linkage disequilibrium (LD) of mungbean. Polymorphism was lower in the cultivated accessions in comparison to the wild accessions, with average polymorphism information content values 0.174, versus 0.305 in wild mungbean. LD decayed in ∼100 kb in cultivated lines, a distance higher than the linkage decay of ∼60 kb estimated in wild mungbean. Four distinct subgroups were identified within the cultivated lines, which broadly corresponded to geographic origin and seed characteristics. In a pilot genome-wide association mapping study of seed coat color, five genomic regions associated were identified, two of which were close to seed coat color genes in other species. This mungbean diversity panel constitutes a valuable resource for genetic dissection of important agronomical traits to accelerate mungbean breeding.

Investigating successive Australian barley breeding populations for stable resistance to leaf rust

Genome-wide association studies of barley breeding populations identified candidate minor genes for pairing with the adult plant resistance gene Rph20 to provide stable leaf rust resistance across environments. Stable resistance to barley leaf rust (BLR, caused by Puccinia hordei) was evaluated across environments in barley breeding populations (BPs). To identify genomic regions that can be combined with Rph20 to improve adult plant resistance (APR), two BPs genotyped with the Diversity Arrays Technology genotyping-by-sequencing platform (DArT-seq) were examined for reaction to BLR at both seedling and adult growth stages in Australian environments. An integrated consensus map comprising both first- and second-generation DArT platforms was used to integrate QTL information across two additional BPs, providing a total of four interrelated BPs and 15 phenotypic data sets. This enabled identification of key loci underpinning BLR resistance. The APR gene Rph20 was the only active resistance region consistently detected across BPs. Of the QTL identified, RphQ27 on chromosome 6HL was considered the best candidate for pairing with Rph20. RphQ27 did not align or share proximity with known genes and was detected in three of the four BPs. The combination of RphQ27 and Rph20 was of low frequency in the breeding material; however, strong resistance responses were observed for the lines carrying this pairing. This suggests that the candidate minor gene RphQ27 can interact additively with Rph20 to provide stable resistance to BLR across diverse environments.

Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step modelling process where global and local trends are fitted after trying several candidate spatial models. This paper reports the application of a novel spatial method that accounts for all types of continuous field variation in a single modelling step by fitting a smooth surface. The method uses two-dimensional P-splines with anisotropic smoothing formulated in the mixed model framework, referred to as SpATS model. We applied this methodology to a series of large and partially replicated sorghum breeding trials. The new model was assessed in comparison with the more elaborate standard spatial models that use autoregressive correlation of residuals. The improvements in precision and the predictions of genotypic values produced by the SpATS model were equivalent to those obtained using the best fitting standard spatial models for each trial. One advantage of the approach with SpATS is that all patterns of spatial trend and genetic effects were modelled simultaneously by fitting a single model. Furthermore, we used a flexible model to adequately adjust for field trends. This strategy reduces potential parameter identification problems and simplifies the model selection process. Therefore, the new method should be considered as an efficient and easy-to-use alternative for routine analyses of plant breeding trials.

Whole-Genome Analysis of Candidate genes Associated with Seed Size and Weight in Sorghum bicolor Reveals Signatures of Artificial Selection and Insights into Parallel Domestication in Cereal Crops

Seed size and seed weight are major quality attributes and important determinants of yield that have been strongly selected for during crop domestication. Limited information is available about the genetic control and genes associated with seed size and weight in sorghum. This study identified sorghum orthologs of genes with proven effects on seed size and weight in other plant species and searched for evidence of selection during domestication by utilizing resequencing data from a diversity panel. In total, 114 seed size candidate genes were identified in sorghum, 63 of which exhibited signals of purifying selection during domestication. A significant number of these genes also had domestication signatures in maize and rice, consistent with the parallel domestication of seed size in cereals. Seed size candidate genes that exhibited differentially high expression levels in seed were also found more likely to be under selection during domestication, supporting the hypothesis that modification to seed size during domestication preferentially targeted genes for intrinsic seed size rather than genes associated with physiological factors involved in the carbohydrate supply and transport. Our results provide improved understanding of the complex genetic control of seed size and weight and the impact of domestication on these genes.

Whole-Genome Analysis of Candidate genes Associated with Seed Size and Weight in Sorghum bicolor Reveals Signatures of Artificial Selection and Insights into Parallel Domestication in Cereal Crops

Seed size and seed weight are major quality attributes and important determinants of yield that have been strongly selected for during crop domestication. Limited information is available about the genetic control and genes associated with seed size and weight in sorghum. This study identified sorghum orthologs of genes with proven effects on seed size and weight in other plant species and searched for evidence of selection during domestication by utilizing resequencing data from a diversity panel. In total, 114 seed size candidate genes were identified in sorghum, 63 of which exhibited signals of purifying selection during domestication. A significant number of these genes also had domestication signatures in maize and rice, consistent with the parallel domestication of seed size in cereals. Seed size candidate genes that exhibited differentially high expression levels in seed were also found more likely to be under selection during domestication, supporting the hypothesis that modification to seed size during domestication preferentially targeted genes for intrinsic seed size rather than genes associated with physiological factors involved in the carbohydrate supply and transport. Our results provide improved understanding of the complex genetic control of seed size and weight and the impact of domestication on these genes.

Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines

Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain. In addition, these methods are typically restricted to point estimates of particular traits, such as leaf senescence or flowering and do not capture the dynamic nature of crop growth. In water-limited environments in particular, information on leaf area development over time would provide valuable insight into water use and adaptation to water scarcity during specific phenological stages of crop development. Current methods to estimate plant leaf area index (LAI) involve destructive sampling and are not practical in breeding. Unmanned aerial vehicles (UAV) and proximal-sensing technologies open new opportunities to assess these traits multiple times in large small-plot trials. We analyzed vegetation-specific crop indices obtained from a narrowband multi-spectral camera on board a UAV platform flown over a small pilot trial with 30 plots (10 genotypes randomized within 3 blocks). Due to variable emergence we were able to assess the utility of these vegetation indices to estimate canopy cover and LAI over a large range of plant densities. We found good correlations between the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) with plant number per plot, canopy cover and LAI both during the vegetative growth phase (pre-anthesis) and at maximum canopy cover shortly after anthesis. We also analyzed the utility of time-sequence data to assess the senescence pattern of sorghum genotypes known as fast (senescent) or slow senescing (stay-green) types. The Normalized Difference Red Edge (NDRE) index which estimates leaf chlorophyll content was most useful in characterizing the leaf area dynamics/senescence patterns of contrasting genotypes. These methods to monitor dynamics of green and senesced leaf area are suitable for out-scaling to enhance phenotyping of additional crop canopy characteristics and likely crop yield responses among genotypes across large fields and multiple dates.

Domestication and the storage starch biosynthesis pathway: signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either 'Landraces' or 'Wild and Weedy' genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.

Whole Genome Sequencing Reveals Potential New Targets for Improving Nitrogen Uptake and Utilization in Sorghum bicolor

Nitrogen (N) fertilizers are a major agricultural input where more than 100 million tons are supplied annually. Cereals are particularly inefficient at soil N uptake, where the unrecovered nitrogen causes serious environmental damage. Sorghum bicolor (sorghum) is an important cereal crop, particularly in resource-poor semi-arid regions, and is known to have a high NUE in comparison to other major cereals under limited N conditions. This study provides the first assessment of genetic diversity and signatures of selection across 230 fully sequenced genes putatively involved in the uptake and utilization of N from a diverse panel of sorghum lines. This comprehensive analysis reveals an overall reduction in diversity as a result of domestication and a total of 128 genes displaying signatures of purifying selection, thereby revealing possible gene targets to improve NUE in sorghum and cereals alike. A number of key genes appear to have been involved in selective sweeps, reducing their sequence diversity. The ammonium transporter (AMT) genes generally had low allelic diversity, whereas a substantial number of nitrate/peptide transporter 1 (NRT1/PTR) genes had higher nucleotide diversity in domesticated germplasm. Interestingly, members of the distinct race Guinea margaritiferum contained a number of unique alleles, and along with the wild sorghum species, represent a rich resource of new variation for plant improvement of NUE in sorghum.

Erratum to: SorGSD: a sorghum genome SNP database

[This corrects the article DOI: 10.1186/s13068-015-0415-8.].

SorGSD: a sorghum genome SNP database

BACKGROUND

Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required.

RESULTS

Based on the assembled and annotated genome sequences of Sorghum bicolor (v2.1) and the recently published sorghum re-sequencing data, ~62.9 M SNPs were identified among 48 sorghum accessions and included in a newly developed sorghum genome SNP database SorGSD (http://sorgsd.big.ac.cn). The diverse panel of 48 sorghum lines can be classified into four groups, improved varieties, landraces, wild and weedy sorghums, and a wild relative Sorghum propinquum. SorGSD has a web-based query interface to search or browse SNPs from individual accessions, or to compare SNPs among several lines. The query results can be visualized as text format in tables, or rendered as graphics in a genome browser. Users may find useful annotation from query results including type of SNPs such as synonymous or non-synonymous SNPs, start, stop of splice variants, chromosome locations, and links to the annotation on Phytozome (www.phytozome.net) sorghum genome database. In addition, general information related to sorghum research such as online sorghum resources and literature references can also be found on the website. All the SNP data and annotations can be freely download from the website.

CONCLUSIONS

SorGSD is a comprehensive web-portal providing a database of large-scale genome variation across all racial types of cultivated sorghum and wild relatives. It can serve as a bioinformatics platform for a range of genomics and molecular breeding activities for sorghum and for other C4 grasses.

Fine mapping of qGW1, a major QTL for grain weight in sorghum

We detected seven QTLs for 100-grain weight in sorghum using an F 2 population, and delimited qGW1 to a 101-kb region on the short arm of chromosome 1, which contained 13 putative genes. Sorghum is one of the most important cereal crops. Breeding high-yielding sorghum varieties will have a profound impact on global food security. Grain weight is an important component of grain yield. It is a quantitative trait controlled by multiple quantitative trait loci (QTLs); however, the genetic basis of grain weight in sorghum is not well understood. In the present study, using an F2 population derived from a cross between the grain sorghum variety SA2313 (Sorghum bicolor) and the Sudan-grass variety Hiro-1 (S. bicolor), we detected seven QTLs for 100-grain weight. One of them, qGW1, was detected consistently over 2 years and contributed between 20 and 40 % of the phenotypic variation across multiple genetic backgrounds. Using extreme recombinants from a fine-mapping F3 population, we delimited qGW1 to a 101-kb region on the short arm of chromosome 1, containing 13 predicted gene models, one of which was found to be under purifying selection during domestication. However, none of the grain size candidate genes shared sequence similarity with previously cloned grain weight-related genes from rice. This study will facilitate isolation of the gene underlying qGW1 and advance our understanding of the regulatory mechanisms of grain weight. SSR markers linked to the qGW1 locus can be used for improving sorghum grain yield through marker-assisted selection.

Genetic differentiation analysis for the identification of complementary parental pools for sorghum hybrid breeding in Ethiopia

The potential for exploiting heterosis for sorghum hybrid production in Ethiopia with improved local adaptation and farmers preferences has been investigated and populations suitable for initial hybrid development have been identified. Hybrids in sorghum have demonstrated increased productivity and stability of performance in the developed world. In Ethiopia, the uptake of hybrid sorghum has been limited to date, primarily due to poor adaptation and absence of farmer's preferred traits in existing hybrids. This study aimed to identify complementary parental pools to develop locally adapted hybrids, through an analysis of whole genome variability of 184 locally adapted genotypes and introduced hybrid parents (R and B). Genetic variability was assessed using genetic distance, model-based STRUCTURE analysis and pair-wise comparison of groups. We observed a high degree of genetic similarity between the Ethiopian improved inbred genotypes and a subset of landraces adapted to lowland agro-ecology with the introduced R lines. This coupled with the genetic differentiation from existing B lines, indicated that these locally adapted genotype groups are expected to have similar patterns of heterotic expression as observed between introduced R and B line pools. Additionally, the hybrids derived from these locally adapted genotypes will have the benefit of containing farmers preferred traits. The groups most divergent from introduced B lines were the Ethiopian landraces adapted to highland and intermediate agro-ecologies and a subset of lowland-adapted genotypes, indicating the potential for increased heterotic response of their hybrids. However, these groups were also differentiated from the R lines, and hence are different from the existing complementary heterotic pools. This suggests that although these groups could provide highly divergent parental pools, further research is required to investigate the extent of heterosis and their hybrid performance.

Spot form of net blotch resistance in barley is under complex genetic control

Evaluation of resistance to Pyrenophora teres f. maculata in barley breeding populations via association mapping revealed a complex genetic architecture comprising a mixture of major and minor effect genes. In the search for stable resistance to spot form of net blotch (Pyrenophora teres f. maculata, SFNB), association mapping was conducted on four independent barley (Hordeum vulgare L.) breeding populations comprising a total of 898 unique elite breeding lines from the Northern Region Barley Breeding Program in Australia for discovery of quantitative trait loci (QTL) influencing resistance at seedling and adult plant growth stages. A total of 29 significant QTL were validated across multiple breeding populations, with 22 conferring resistance at both seedling and adult plant growth stages. The remaining 7 QTL conferred resistance at either seedling (2 QTL) or adult plant (5 QTL) growth stages only. These 29 QTL represented 24 unique genomic regions, of which five were found to co-locate with previously identified QTL for SFNB. The results indicated that SFNB resistance is controlled by a large number of QTL varying in effect size with large effects QTL on chromosome 7H. A large proportion of the QTL acted in the same direction for both seedling and adult responses, suggesting that phenotypic selection for SFNB resistance performed at either growth stage could achieve adequate levels of resistance. However, the accumulation of specific resistance alleles on several chromosomes must be considered in molecular breeding selection strategies.

Drought adaptation of stay-green sorghum is associated with canopy development, leaf anatomy, root growth, and water uptake

Stay-green sorghum plants exhibit greener leaves and stems during the grain-filling period under water-limited conditions compared with their senescent counterparts, resulting in increased grain yield, grain mass, and lodging resistance. Stay-green has been mapped to a number of key chromosomal regions, including Stg1, Stg2, Stg3, and Stg4, but the functions of these individual quantitative trait loci (QTLs) remain unclear. The objective of this study was to show how positive effects of Stg QTLs on grain yield under drought can be explained as emergent consequences of their effects on temporal and spatial water-use patterns that result from changes in leaf-area dynamics. A set of four Stg near-isogenic lines (NILs) and their recurrent parent were grown in a range of field and semicontrolled experiments in southeast Queensland, Australia. These studies showed that the four Stg QTLs regulate canopy size by: (1) reducing tillering via increased size of lower leaves, (2) constraining the size of the upper leaves; and (3) in some cases, decreasing the number of leaves per culm. In addition, they variously affect leaf anatomy and root growth. The multiple pathways by which Stg QTLs modulate canopy development can result in considerable developmental plasticity. The reduction in canopy size associated with Stg QTLs reduced pre-flowering water demand, thereby increasing water availability during grain filling and, ultimately, grain yield. The generic physiological mechanisms underlying the stay-green trait suggest that similar Stg QTLs could enhance post-anthesis drought adaptation in other major cereals such as maize, wheat, and rice.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

A QTL model for the genetic control of tillering in sorghum is proposed, presenting new opportunities for sorghum breeders to select germplasm with tillering characteristics appropriate for their target environments. Tillering in sorghum can be associated with either the carbon supply-demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

Stay-green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns

Stay-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.

A physiological framework to explain genetic and environmental regulation of tillering in sorghum

Tillering determines the plant size of sorghum (Sorghum bicolor) and an understanding of its regulation is important to match genotypes to prevalent growing conditions in target production environments. The aim of this study was to determine the physiological and environmental regulation of variability in tillering among sorghum genotypes, and to develop a framework for this regulation. Diverse sorghum genotypes were grown in three experiments with contrasting temperature, radiation and plant density to create variation in tillering. Data on phenology, tillering, and leaf and plant size were collected. A carbohydrate supply/demand (S/D) index that incorporated environmental and genotypic parameters was developed to represent the effects of assimilate availability on tillering. Genotypic differences in tillering not explained by this index were defined as propensity to tiller (PTT) and probably represented hormonal effects. Genotypic variation in tillering was associated with differences in leaf width, stem diameter and PTT. The S/D index captured most of the environmental effects on tillering and PTT most of the genotypic effects. A framework that captures genetic and environmental regulation of tillering through assimilate availability and PTT was developed, and provides a basis for the development of a model that connects genetic control of tillering to its phenotypic consequences.

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

"To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants." Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.

Whole-genome sequencing reveals untapped genetic potential in Africa's indigenous cereal crop sorghum

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.

Sorghum is a drought-resistant food and feed cereal crop used by over half a billion of the world’s poorest people. Here the authors present high-coverage resequencing genome data of 44 sorghum lines of varying geographic and taxonomic origin, which include a number of sorghum wild relatives.

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

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.

Genetic variability in high temperature effects on seed-set in sorghum

Sorghum (Sorghum bicolor (L.) Moench) is grown as a dryland crop in semiarid subtropical and tropical environments where it is often exposed to high temperatures around flowering. Projected climate change is likely to increase the incidence of exposure to high temperature, with potential adverse effects on growth, development and grain yield. The objectives of this study were to explore genetic variability for the effects of high temperature on crop growth and development, in vitro pollen germination and seed-set. Eighteen diverse sorghum genotypes were grown at day : night temperatures of 32 : 21°C (optimum temperature, OT) and 38 : 21°C (high temperature, HT during the middle of the day) in controlled environment chambers. HT significantly accelerated development, and reduced plant height and individual leaf size. However, there was no consistent effect on leaf area per plant. HT significantly reduced pollen germination and seed-set percentage of all genotypes; under HT, genotypes differed significantly in pollen viability percentage (17-63%) and seed-set percentage (7-65%). The two traits were strongly and positively associated (R2=0.93, n=36, P<0.001), suggesting a causal association. The observed genetic variation in pollen and seed-set traits should be able to be exploited through breeding to develop heat-tolerant varieties for future climates.