Near-infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.

For nearly two decades, genomic prediction and selection have supported efforts to increase genetic gains in plant and animal improvement programs. However, novel phenomic strategies for predicting complex traits in maize have recently proven beneficial when integrated into across-environment sparse genomic prediction models. One phenomic data modality is whole grain near-infrared spectroscopy (NIRS), which records reflectance values of biological samples (e.g., maize kernels) based on chemical composition. Predictions of hybrid maize grain yield (GY) and 500-kernel weight (KW) across 2 years (2011-2012) and two management conditions (water-stressed and well-watered) were conducted using combinations of reflectance data obtained from high-throughput, F2 whole-kernel scans and genomic data obtained from genotyping-by-sequencing within four different cross-validation (CV) schemes (CV2, CV1, CV0, and CV00). When predicting the performance of untested genotypes in characterized (CV1) environments, genomic data were better than phenomic data for GY (0.689 ± 0.024-genomic vs. 0.612 ± 0.045-phenomic), but phenomic data were better than genomic data for KW (0.535 ± 0.034-genomic vs. 0.617 ± 0.145-phenomic). Multi-kernel models (combinations of phenomic and genomic relationship matrices) did not surpass single-kernel models for GY prediction in CV1 or CV00 (prediction of untested genotypes in uncharacterized environments); however, these models did outperform the single-kernel models for prediction of KW in these same CVs. Lasso regression applied to the NIRS data set selected a subset of 216 NIRS bands that achieved comparable prediction abilities to the full phenomic data set of 3112 bands predicting GY and KW under CV1 and CV00.

Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population.

Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials.

Aphid-Induced Volatiles and Subsequent Attraction of Natural Enemies Varies among Sorghum Cultivars.

The production of herbivore-induced plant volatiles (HIPVs) is a type of indirect defense used by plants to attract natural enemies and reduce herbivory by insect pests. In many crops little is known about genotypic variation in HIPV production or how this may affect natural enemy attraction. In this study, we identified and quantified HIPVs produced by 10 sorghum (Sorghum bicolor) cultivars infested with a prominent aphid pest, the sorghum aphid (Melanaphis sorghi Theobald). Volatiles were collected using dynamic headspace sampling techniques and identified and quantified using GC-MS. The total amounts of volatiles induced by the aphids did not differ among the 10 cultivars, but overall blends of volatiles differed significantly in composition. Most notably, aphid herbivory induced higher levels of methyl salicylate (MeSA) emission in two cultivars, whereas in four cultivars, the volatile emissions did not change in response to aphid infestation. Dual-choice olfactometer assays were used to determine preference of the aphid parasitoid, Aphelinus nigritus, and predator, Chrysoperla rufilabris, between plants of the same cultivar that were un-infested or infested with aphids. Two aphid-infested cultivars were preferred by natural enemies, while four other cultivars were more attractive to natural enemies when they were free of aphids. The remaining four cultivars elicited no response from parasitoids. Our work suggests that genetic variation in HIPV emissions greatly affects parasitoid and predator attraction to aphid-infested sorghum and that screening crop cultivars for specific predator and parasitoid attractants has the potential to improve the efficacy of biological control.

Use of genomic prediction to screen sorghum B-lines in hybrid testcrosses.

Use of trifluoromethanesulfonamide (TFMSA), a male gametocide, increases the opportunities to identify promising B-lines because large quantities of F1 seed can be generated prior to the laborious task of B-line sterilization. Combining TFMSA technology with genomic selection could efficiently evaluate sorghum B-lines in hybrid combination to maximize the rates of genetic gain of the crop. This study used two recombinant inbred B-line populations, consisting of 217 lines, which were testcrossed to two R-lines to produce 434 hybrids. Each population of testcross hybrids were evaluated across five environments. Population-based genomic prediction models were assessed across environments using three different cross-validation (CV) schemes, each with 70% training and 30% validation sets. The validation schemes were as follows: CV1-hybrids chosen randomly for validation; CV2-B-lines were randomly chosen, and each chosen B-line had one of the two corresponding testcross hybrids randomly chosen for the validation; and CV3-B-lines were randomly chosen, and each chosen B-line had both corresponding testcross hybrids chosen for the validation. CV1 and CV2 presented the highest prediction accuracies; nonetheless, the prediction accuracies of the CV schemes were not statistically different in many environments. We determined that combining the B-line populations could improve prediction accuracies, and the genomic prediction models were able to effectively rank the poorest 70% of hybrids even when genomic prediction accuracies themselves were low. Results indicate that combining genomic prediction models and TFMSA technology can effectively aid breeders in predicting B-line hybrid performance in early generations prior to the laborious task of generating A/B-line pairs.

Genomic prediction can be used to screen sorghum B-lines for hybrid grain yield and days to mid-anthesis. Using genomic prediction and the chemical gametocide TFMSA can increase the rate of genetic gain in sorghum B-lines. Using testers to screen sorghum B-line populations is an effective method for screening with genomic prediction. Genomic prediction can effectively predict hybrid performance within and across populations of sorghum B-lines. The ability to accurately rank hybrid performance remained relatively consistent regardless of prediction accuracy.

Biophysical, Nutraceutical, and Technofunctional Features of Specialty Cereals: Pigmented Popcorn and Sorghum.

Different pigmented corn and sorghum types were evaluated to characterize their biophysical, nutraceutical, and technofunctional properties for the first time. Commercially pigmented (blue, purple, red, black, and yellow) popcorn (Zea mays var. everta) and sorghum (Sorghum bicolor L.) of yellow and red colors were analyzed. Biophysical and proximal analyses were performed using official methods. The nutraceutical profile included the total phenolic and anthocyanin content. In addition, rheological, structural, and morphological studies were conducted. The results demonstrated significant differences between the popcorn samples and grain types, especially in terms of their biophysical and proximate features. The nutraceutical profile revealed that these specialty grains contained higher concentrations of antioxidant compounds (up to 3-fold when compared with the other grains). The rheological analysis demonstrated that sorghum grains developed higher peak viscosities than popcorn. According to the structural assessments, the type A pattern displayed peaks at the interplanar spaces corresponding to the crystalline and amorphous regions in all the samples. The data obtained in this study provides a base to further investigate the products obtained using these biomaterials.

Evaluating Introgression Sorghum Germplasm Selected at the Population Level While Exploring Genomic Resources as a Screening Method.

To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation of exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of BC-NAM populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC1F3 line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence (GBS) as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.

Non-Destructive Direct Pericarp Thickness Measurement of Sorghum Kernels Using Extended-Focus Optical Coherence Microscopy.

Non-destructive measurements of internal morphological structures in plant materials such as seeds are of high interest in agricultural research. The estimation of pericarp thickness is important to understand the grain quality and storage stability of seeds and can play a crucial role in improving crop yield. In this study, we demonstrate the applicability of fiber-based Bessel beam Fourier domain (FD) optical coherence microscopy (OCM) with a nearly constant high lateral resolution maintained at over ~400 µm for direct non-invasive measurement of the pericarp thickness of two different sorghum genotypes. Whereas measurements based on axial profiles need additional knowledge of the pericarp refractive index, en-face views allow for direct distance measurements. We directly determine pericarp thickness from lateral sections with a 3 µm resolution by taking the width of the signal corresponding to the pericarp at the 1/e threshold. These measurements enable differentiation of the two genotypes with 100% accuracy. We find that trading image resolution for acquisition speed and view size reduces the classification accuracy. Average pericarp thicknesses of 74 µm (thick phenotype) and 43 µm (thin phenotype) are obtained from high-resolution lateral sections, and are in good agreement with previously reported measurements of the same genotypes. Extracting the morphological features of plant seeds using Bessel beam FD-OCM is expected to provide valuable information to the food processing industry and plant breeding programs.

Genetic Diversity and Classification of Colletotrichum sublineola Pathotypes Using a Standard Set of Sorghum Differentials.

Anthracnose, incited by Colletotrichum sublineola, is the most destructive foliar disease of sorghum and, under severe conditions, yield losses can exceed 80% on susceptible cultivars. The hyper-variable nature of the pathogen makes its management challenging despite the occurrence of several resistant sources. In this study, the genetic variability and pathogenicity of 140 isolates of C. sublineola, which were sequenced using restriction site-associated sequencing (RAD-Seq), resulted in 1244 quality SNPs. The genetic relationship based on the SNP data showed low to high genetic diversity based on isolates' origin. Isolates from Georgia and North Carolina were grouped into multiple clusters with some level of genetic relationships to each other. Even though some isolates from Texas formed a cluster, others clustered with isolates from Puerto Rico. The isolates from Puerto Rico showed scattered distribution, indicating the diverse nature of these isolates. A population structure and cluster analysis revealed that the genetic variation was stratified into eight populations and one admixture group. The virulence pattern of 30 sequenced isolates on 18 sorghum differential lines revealed 27 new pathotypes. SC748-5, SC112-14, and Brandes were resistant to all the tested isolates, while BTx623 was susceptible to all. Line TAM428 was susceptible to all the pathotypes, except for pathotype 26. Future use of the 18 differentials employed in this study, which contains cultivars/lines which have been used in the Americas, Asia, and Africa, could allow for better characterization of C. sublineola pathotypes at a global level, thus accelerating the development of sorghum lines with stable resistance to the anthracnose pathogen.

Transcriptional regulation of the raffinose family oligosaccharides pathway in Sorghum bicolor reveals potential roles in leaf sucrose transport and stem sucrose accumulation.

Bioenergy sorghum hybrids are being developed with enhanced drought tolerance and high levels of stem sugars. Raffinose family oligosaccharides (RFOs) contribute to plant environmental stress tolerance, sugar storage, transport, and signaling. To better understand the role of RFOs in sorghum, genes involved in myo-inositol and RFO metabolism were identified and relative transcript abundance analyzed during development. Genes involved in RFO biosynthesis (SbMIPS1, SbInsPase, SbGolS1, SbRS) were more highly expressed in leaves compared to stems and roots, with peak expression early in the morning in leaves. SbGolS, SbRS, SbAGA1 and SbAGA2 were also expressed at high levels in the leaf collar and leaf sheath. In leaf blades, genes involved in myo-inositol biosynthesis (SbMIPS1, SbInsPase) were expressed in bundle sheath cells, whereas genes involved in galactinol and raffinose synthesis (SbGolS1, SbRS) were expressed in mesophyll cells. Furthermore, SbAGA1 and SbAGA2, genes that encode neutral-alkaline alpha-galactosidases that hydrolyze raffinose, were differentially expressed in minor vein bundle sheath cells and major vein and mid-rib vascular and xylem parenchyma. This suggests that raffinose synthesized from sucrose and galactinol in mesophyll cells diffuses into vascular bundles where hydrolysis releases sucrose for long distance phloem transport. Increased expression (>20-fold) of SbAGA1 and SbAGA2 in stem storage pith parenchyma of sweet sorghum between floral initiation and grain maturity, and higher expression in sweet sorghum compared to grain sorghum, indicates these genes may play a key role in non-structural carbohydrate accumulation in stems.

Genetic variation in hydrogen cyanide potential of perennial sorghum evaluated by colorimetry.

Both annual and perennial sorghum biomass serve as important forage for ruminant animals around the world. Unfortunately, sorghum can produce hydrogen cyanide (HCN), which, if occurring in high enough concentrations, can be toxic or lethal to animals that consume it. The objectives of this study were to develop a fast and inexpensive colorimetric assay to measure the hydrogen cyanide potential (HCN-P) as well as to compare this with existing visual assays while assessing the range of variation for HCN-P among perennial and annual sorghum biomass. The HCN-P of 100 sorghum lines derived from an interspecific hybridization program was determined over 2 years (establishment and regrowth) using both visual and colorimetric assays. Visual assessment underestimated the HCN-P and was less accurate than colorimetry. Repeatability for HCN-P across all sampling dates was functionally zero in the visual assessment and low for the colorimetric assay. This was mostly explained by the significant pedigree × year interaction effects and growth stage. Growth stage substantially influenced HCN-P, which should be considered when feeding animals on fresh forage.

Genetic control of source-sink relationships in grain sorghum.

MAIN CONCLUSION: QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Application of X-ray computed tomography to analyze the structure of sorghum grain.

BACKGROUND: The structural characteristics of whole sorghum kernels are known to affect end-use quality, but traditional evaluation of this structure is two-dimensional (i.e., cross section of a kernel). Current technology offers the potential to consider three-dimensional structural characteristics of grain. X-ray computed tomography (CT) presents one such opportunity to nondestructively extract quantitative data from grain caryopses which can then be related to end-use quality. RESULTS: Phenotypic measurements were extracted from CT scans of grain sorghum caryopses. Extensive phenotypic variation was found for embryo volume, endosperm hardness, endosperm texture, endosperm volume, pericarp volume, and kernel volume. CT derived estimates were strongly correlated with ground truth measurements enabling the identification of genotypes with superior structural characteristics. CONCLUSIONS: Presented herein is a phenotyping pipeline developed to quantify three-dimensional structural characteristics from grain sorghum caryopses which increases the throughput efficiency of previously difficult to measure traits. Adaptation of this workflow to other small-seeded crops is possible providing new and unique opportunities for scientists to study grain in a nondestructive manner which will ultimately lead to improvements end-use quality.

Assessing combining abilities, genomic data, and genotype × environment interactions to predict hybrid grain sorghum performance.

Genomic selection in maize (Zea mays L.) has been one factor that has increased the rate of genetic gain when compared with other cereals. However, the technological foundations in maize also exist in other cereal crops that would allow prediction of hybrid performance based on general (GCA) and specific (SCA) combining abilities applied through genomic-enabled prediction models. Further, the incorporation of genotype × environment (G × E) interaction effects present an opportunity to deploy hybrids to targeted environments. To test these concepts, a factorial mating design of elite yet divergent grain sorghum lines generated hybrids for evaluation. Inbred parents were genotyped, and markers were used to assess population structure and develop the genomic relationship matrix (GRM). Grain yield, height, and days to anthesis were collected for hybrids in replicated trials, and best linear unbiased estimates were used to train classical GCA-SCA-based and genomic (GB) models under a hierarchical Bayesian framework. To incorporate population structure, GB was fitted using the GRM of both parents and hybrids. For GB models, G × E interaction effects were included by the Hadamard product between GRM and environments. A leave-one-out cross-validation scheme was used to study the prediction capacity of models. Classical and genomic models effectively predicted hybrid performance and prediction accuracy increased by including genomic data. Genomic models effectively partitioned the variation due to GCA, SCA, and their interaction with the environment. A strategy to implement genomic selection for hybrid sorghum [Sorghum bicolor (L.) Moench] breeding is presented herein.

High planting density induces the expression of GA3-oxidase in leaves and GA mediated stem elongation in bioenergy sorghum.

The stems of bioenergy sorghum hybrids at harvest are > 4 m long, contain > 40 internodes and account for ~ 80% of harvested biomass. In this study, bioenergy sorghum hybrids were grown at four planting densities (~ 20,000 to 132,000 plants/ha) under field conditions for 60 days to investigate the impact shading has on stem growth and biomass accumulation. Increased planting density induced a > 2-fold increase in sorghum internode length and a ~ 22% decrease in stem diameter, a typical shade avoidance response. Shade-induced internode elongation was due to an increase in cell length and number of cells spanning the length of internodes. SbGA3ox2 (Sobic.003G045900), a gene encoding the last step in GA biosynthesis, was expressed ~ 20-fold higher in leaf collar tissue of developing phytomers in plants grown at high vs. low density. Application of GA3 to bioenergy sorghum increased plant height, stem internode length, cell length and the number of cells spanning internodes. Prior research showed that sorghum plants lacking phytochrome B, a key photoreceptor involved in shade signaling, accumulated more GA1 and displayed shade avoidance phenotypes. These results are consistent with the hypothesis that increasing planting density induces expression of GA3-oxidase in leaf collar tissue, increasing synthesis of GA that stimulates internode elongation.

Phenotypic, Phytochemical, and Transcriptomic Analysis of Black Sorghum (Sorghum bicolor L.) Pericarp in Response to Light Quality.

Black sorghum [Sorghum bicolor (L.) Moench] is characterized by the black appearance of the pericarp and production of 3-deoxyanthocyanidins (3-DOA), which are valued for their cytotoxicity to cancer cells and as natural food colorants and antioxidant additives. The black pericarp phenotype is not fully penetrant in all environments, which implicates the light spectrum and/or photoperiod as the critical factor for trait expression. In this study, black- or red-pericarp genotypes were grown under regimes of visible light, visible light supplemented with UVA or supplemented with UVA plus UVB (or dark control). Pericarp 3-DOAs and pericarp pigmentation were maximized in the black genotype exposed to a light regime supplemented with UVB. Changes in gene expression during black pericarp development revealed that ultraviolet light activates genes related to plant defense, reactive oxygen species, and secondary metabolism, suggesting that 3-DOA accumulation is associated with activation of flavonoid biosynthesis and several overlapping defense and stress signaling pathways.

Discovering Biomass Structural Determinants Defining the Properties of Plant-Derived Renewable Carbon Fiber.

Traditional lignocellulosic feedstock research has focused on biomass characteristics essential for improving saccharification efficiency, yet the key biomass features underlying high-quality renewable lignin materials remain unknown. Nevertheless, modern biorefinery cannot achieve sustainability and cost-effectiveness unless the lignin stream can be valorized. We hereby addressed these scientific gaps by investigating biomass characteristics defining lignin-based carbon materials properties. Lignin from eight sorghum samples with diverse characteristics was fabricated into carbon fibers (CFs). Remarkably, only lignin uniformity was found to define CF mechanical performance, highlighting the new structure-property relationship. Contrarily, lignin content and composition did not impact on carbon material properties. Mechanistic study by XRD and Raman spectroscopy revealed that higher lignin uniformity enhanced CF microstructures, in particular, turbostratic carbon content. The study for the first time highlighted lignin uniformity as an important biomass structure determinant for renewable products, which opened up new avenues for feedstock design toward diverse products enabling sustainable and cost-effective bioeconomy.

Low-field magnetic resonance imaging of roots in intact clayey and silty soils.

The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T2 (4 ms) and the typical root water relaxation time T2 (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-D MRI projection images were produced of roots with a diameter range of 1.5-2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. Additionally, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.

Identification of QTL for Target Leaf Spot resistance in Sorghum bicolor and investigation of relationships between disease resistance and variation in the MAMP response.

Target leaf spot (TLS) of sorghum, a foliar disease caused by the necrotrophic fungus Bipolaris cookei (also known as Bipolaris sorghicola), can affect grain yield in sorghum by causing premature drying of leaves and defoliation. Two sorghum recombinant inbred line (RIL) populations, BTx623/BTx642 and BTx623/SC155-14E, were assessed for TLS resistance in replicated trials. Using least square mean trait data, four TLS resistance QTL were identified, two in each population. Of these, three were previously unidentified while a major QTL on chromosome 5 in the BTx623/BTx642 RIL population corresponded to the previously identified TLS resistance gene ds1. A set of sorghum lines were assessed for production of reactive oxygen species induced by treatment with the microbe-associated molecular pattern (MAMP) flg22 (a derivative of flagellin). Flg22-induced ROS production varied between lines in a consistent fashion. One QTL associated with variation in the flg22 response was detected in the RIL populations. No evidence was found to link variation in the MAMP response to variation in TLS resistance.

Sorghum bicolor x S. halepense interspecific hybridization is influenced by the frequency of 2n gametes in S. bicolor.

Tetraploid johnsongrass [Sorghum halepense (L.) Pers.] is a sexually-compatible weedy relative of diploid sorghum [Sorghum bicolor (L.) Moench]. To determine the extent of interspecific hybridization between male sterile grain sorghum and johnsongrass and the ploidy of their progeny, cytoplasmic (CMS), genetic (GMS) and chemically induced male sterile lines of Tx623 and Tx631 were pollinated with johnsongrass pollen. At maturity 1% and 0.07% of the developing seeds of Tx623 and Tx631 respectively were recovered. Ninety-one percent of recovered hybrids were tetraploid and two percent were triploid, the tetraploids resulting from 2n gametes present in the sorghum female parent. Their formation appears to be genotype dependent as more tetraploids were recovered from Tx623 than Tx631. Because a tetraploid sorghum x johnsongrass hybrid has a balanced genome, they are male and female fertile providing opportunities for gene flow between the two species. Given the differences in 2n gamete formation among Tx623 and Tx631, seed parent selection may be one way of reducing the likelihood of gene flow. These studies were conducted in controlled and optimum conditions; the actual outcrossing rate in natural conditions is expected to be much lower. More studies are needed to assess the rates of hybridization, fitness, and fertility of the progeny under field conditions.

Genome-Wide Association Mapping of Grain Mold Resistance in the US Sorghum Association Panel.

Sorghum [ (L.) Moench] production in warm and humid regions is limited by grain mold disease, which can be caused by a complex of >40 pathogenic and opportunistic fungi. The identification of resistant plants within temperate-adapted germplasm is imperative for the development of better-adapted varieties. The performance of 331 accessions from the previously genotyped sorghum association panel (SAP) was evaluated in four tropical environments. Only 18 accessions showed low seed deterioration and high emergence rates. The resistant accessions showed high variation in seed tannin contents and panicle shape, indicating that grain mold resistance is not associated with a single phenotypic trait. Seed mycoflora analysis recovered pathogenic fungi , , and in both resistant and susceptible accessions. By genome-wide association scans using 268,289 single nucleotide polymorphisms (SNPs), we identified two loci associated with low seed deterioration and another associated with emergence rate. Candidate genes within these loci included one gene () and two genes ( and ) with domains associated with systemic acquired resistance, suggesting that resistance involved pathogen recognition and downstream signaling cascades. This study provides insight into the genetic control of grain mold resistance as well as valuable accessions for breeding programs in temperate environments.