Expression data from vegetative tissues of grain, sweet and bioenergy sorghums
ABSTRACT: We developed a commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) and generated this dataset to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (corn and sugarcane) were also included in our array design. 78 samples were analyzed from four different tissue types (shoot, seedling, leaves and stem), two dissected stem tissues (pith and rind) and six diverse genotypes (PI455230, Atlas, PI152611, AR2400, R159, and Fremont)
Project description:BACKGROUND: Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. RESULTS: This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. CONCLUSIONS: Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.
Project description:We developed a commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) and generated this dataset to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (corn and sugarcane) were also included in our array design. 78 samples were analyzed from four different tissue types (shoot, seedling, leaves and stem), two dissected stem tissues (pith and rind) and six diverse genotypes (PI455230, Atlas, PI152611, AR2400, R159, and Fremont)
Project description:Sorghum vegetative tissues are becoming increasingly important for biofuel production. The composition of sorghum stem tissues is influenced by genotype, environment and photoperiod sensitivity, and varies widely between varieties and also between different stem tissues (outer rind vs inner pith). Here, the amount of cellulose, (1,3;1,4)-?-glucan, arabinose and xylose in the stems of twelve diverse sorghum varieties, including four photoperiod-sensitive varieties, was measured. At maturity, most photoperiod-insensitive lines had 1% w/w (1,3;1,4)-?-glucan in stem pith tissue whilst photoperiod-sensitive varieties remained in a vegetative stage and accumulated up to 6% w/w (1,3;1,4)-?-glucan in the same tissue. Three sorghum lines were chosen for further study: a cultivated grain variety (Sorghum bicolor BTx623), a sweet variety (S. bicolor Rio) and a photoperiod-sensitive wild line (S. bicolor ssp. verticilliflorum Arun). The Arun line accumulated 5.5% w/w (1,3;1,4)-?-glucan and had higher SbCslF6 and SbCslH3 transcript levels in pith tissues than did photoperiod-insensitive varieties Rio and BTx623 (<1% w/w pith (1,3;1,4)-?-glucan). To assess the digestibility of the three varieties, stem tissue was treated with either hydrolytic enzymes or dilute acid and the release of fermentable glucose was determined. Despite having the highest lignin content, Arun yielded significantly more glucose than the other varieties, and theoretical calculation of ethanol yields was 10 344 L ha-1 from this sorghum stem tissue. These data indicate that sorghum stem (1,3;1,4)-?-glucan content may have a significant effect on digestibility and bioethanol yields. This information opens new avenues of research to generate sorghum lines optimised for biofuel production.
Project description:<h4>Background</h4>The sorghum stem can be divided into the pith and rind parts with obvious differences in cell type and chemical composition, thus arising the different recalcitrance to enzyme hydrolysis and demand for different pretreatment conditions. The introduction of organic solvents in the pretreatment can reduce over-degradation of cellulose and hemicellulose, but significance of organic solvent addition in pretreatment of different parts of sorghum stem is still unclear. Valorization of each component is critical for economy of sorghum biorefinery. Therefore, in this study, NaOH-ethanol pretreatment condition for different parts of the sorghum stem was optimized to maximize <i>p</i>-coumaric acid release and total reducing sugar recovery.<h4>Result</h4>Ethanol addition improved <i>p</i>-coumaric acid release and delignification efficiency, but significantly reduced hemicellulose deconstruction in NaOH-ethanol pretreatment. Optimization using the response surface methodology revealed that the pith, rind and whole stem require different NaOH-ethanol pretreatment conditions for maximal <i>p</i>-coumaric acid release and xylan preservation. By respective optimal NaOH-ethanol pretreatment, the <i>p</i>-coumaric acid release yields reached 94.07%, 97.24% and 95.05% from pith, rind and whole stem, which increased by 8.16%, 8.38% and 8.39% compared to those of NaOH-pretreated samples. The xylan recoveries of pith, rind and whole stem reached 76.80%, 88.46% and 85.01%, respectively, which increased by 47.75%, 15.11% and 35.97% compared to NaOH pretreatment. Adding xylanase significantly enhanced the enzymatic saccharification of pretreated residues. The total reducing sugar yields after respective optimal NaOH-ethanol pretreatment and enzymatic hydrolysis reached 84.06%, 82.29% and 84.09% for pith, rind and whole stem, respectively, which increased by 29.56%, 23.67% and 25.56% compared to those of NaOH-pretreated samples. Considering the separation cost of the different stem parts, whole sorghum stem can be directly used as feedstock in industrial biorefinery.<h4>Conclusion</h4>These results indicated that NaOH-ethanol is effective for the efficient fractionation and pretreatment of sorghum biomass. This work will help to understand the differences of different parts of sorghum stem under NaOH-ethanol pretreatment, thereby improving the full-component utilization of sorghum stem.
Project description:Pith parenchyma cells store water in various plant organs. These cells are especially important for producing sugar and ethanol from the sugar juice of grass stems. In many plants, the death of pith parenchyma cells reduces their stem water content. Previous studies proposed that a hypothetical D gene might be responsible for the death of stem pith parenchyma cells in Sorghum bicolor, a promising energy grass, although its identity and molecular function are unknown. Here, we identify the D gene and note that it is located on chromosome 6 in agreement with previous predictions. Sorghum varieties with a functional D allele had stems enriched with dry, dead pith parenchyma cells, whereas those with each of six independent nonfunctional D alleles had stems enriched with juicy, living pith parenchyma cells. D expression was spatiotemporally coupled with the appearance of dead, air-filled pith parenchyma cells in sorghum stems. Among D homologs that are present in flowering plants, Arabidopsis ANAC074 also is required for the death of stem pith parenchyma cells. D and ANAC074 encode previously uncharacterized NAC transcription factors and are sufficient to ectopically induce programmed death of Arabidopsis culture cells via the activation of autolytic enzymes. Taken together, these results indicate that D and its Arabidopsis ortholog, ANAC074, are master transcriptional switches that induce programmed death of stem pith parenchyma cells. Thus, targeting the D gene will provide an approach to breeding crops for sugar and ethanol production.
Project description:Late embryogenesis abundant (LEA) proteins, the space fillers or molecular shields, are the hydrophilic protective proteins which play an important role during plant development and abiotic stress. The systematic survey and characterization revealed a total of 68 LEA genes, belonging to 8 families in Sorghum bicolor. The LEA-2, a typical hydrophobic family is the most abundant family. All of them are evenly distributed on all 10 chromosomes and chromosomes 1, 2, and 3 appear to be the hot spots. Majority of the S. bicolor LEA (SbLEA) genes are intron less or have fewer introns. A total of 22 paralogous events were observed and majority of them appear to be segmental duplications. Segmental duplication played an important role in SbLEA-2 family expansion. A total of 12 orthologs were observed with Arabidopsis and 13 with Oryza sativa. Majority of them are basic in nature, and targeted by chloroplast subcellular localization. Fifteen miRNAs targeted to 25 SbLEAs appear to participate in development, as well as in abiotic stress tolerance. Promoter analysis revealed the presence of abiotic stress-responsive DRE, MYB, MYC, and GT1, biotic stress-responsive W-Box, hormone-responsive ABA, ERE, and TGA, and development-responsive SKn cis-elements. This reveals that LEA proteins play a vital role during stress tolerance and developmental processes. Using microarray data, 65 SbLEA genes were analyzed in different tissues (roots, pith, rind, internode, shoot, and leaf) which show clear tissue specific expression. qRT-PCR analysis of 23 SbLEA genes revealed their abundant expression in various tissues like roots, stems and leaves. Higher expression was noticed in stems compared to roots and leaves. Majority of the SbLEA family members were up-regulated at least in one tissue under different stress conditions. The SbLEA3-2 is the regulator, which showed abundant expression under diverse stress conditions. Present study provides new insights into the formation of LEAs in S. bicolor and to understand their role in developmental processes under stress conditions, which may be a valuable source for future research.
Project description:With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.
Project description:Sweet sorghum [Sorghum bicolor (L.) Moench] is a type of cultivated sorghum characterized by the accumulation of high levels of sugar in the stems and high biomass accumulation, making this crop an important feedstock for bioenergy production. Sweet sorghum breeding programs that focus on bioenergy have two main goals: to improve quantity and quality of sugars in the juicy stem and to increase fresh biomass productivity. Genetic diversity studies are very important for the success of a breeding program, especially in the early stages, where understanding the genetic relationship between accessions is essential to identify superior parents for the development of improved breeding lines. The objectives of this study were: to perform phenotypic and molecular characterization of 100 sweet sorghum accessions from the germplasm bank of the Embrapa Maize and Sorghum breeding program; to examine the relationship between the phenotypic and the molecular diversity matrices; and to infer about the population structure in the sweet sorghum accessions. Morphological and agro-industrial traits related to sugar and biomass production were used for phenotypic characterization, and single nucleotide polymorphisms (SNPs) were used for molecular diversity analysis. Both phenotypic and molecular characterizations revealed the existence of considerable genetic diversity among the 100 sweet sorghum accessions. The correlation between the phenotypic and the molecular diversity matrices was low (0.35), which is in agreement with the inconsistencies observed between the clusters formed by the phenotypic and the molecular diversity analyses. Furthermore, the clusters obtained by the molecular diversity analysis were more consistent with the genealogy and the historic background of the sweet sorghum accessions than the clusters obtained through the phenotypic diversity analysis. The low correlation observed between the molecular and the phenotypic diversity matrices highlights the complementarity between the molecular and the phenotypic characterization to assist a breeding program.
Project description:This study used with RNA-Seq to examine the tissue specific expression data within sorghum plants for improving the Sorghum bicolor gene annotation. We examined the RNA from tissues (spikelet, seed and stem) in Sorghum bicolor (BTx623).Total RNAs form each tissues were extracted using SDS/phenol method followed by LiCl purification
Project description:The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesC?, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.