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At least 181 records · Page 10

RhizoGrid Indexed Sorghum Rhizosphere Multi-Omics

PerCon SFA project data dentification of spatially resolved biomarkers of drought in Sorghum bicolor rhizosphere molecular-microbe interactions using a novel root cartography "RhizoGrid" system for sampling plants under drought and control conditions across 10 equally sized root zone environments (4 quadrants each). Each quadrant was sampled and processed for 16S amplicon, metabolomics, and X-ray computed tomography (XCT). Data download includes experimental metadata and results files for 16S rRNA sequence analysis of microbial community assembly (processed data files), liquid chromatography mass spectrometry (LC-MS) metabolomics analysis of microbial community root exudates (processed data files), X-ray computed tomography (XCT) spatial gradient analysis (raw and processed data files) of microbial community composition, and related computational modeling outputs.

59 BASIC BIOLOGICAL SCIENCES↗

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F 6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative feedstock analysis in Setaria viridis L. as a model for C 4 bioenergy grasses and panicoid crop species

Second generation feedstocks for bioethanol will likely include a sizable proportion of perennial C4 grasses, principally in the Panicoideae clade. The Panicoideae contain agronomically important annual grasses including Zea mays L. (maize), Sorghum bicolor (L.) Moench (sorghum), and Saccharum officinarum L. (sugar cane) as well as promising second generation perennial feedstocks including Miscanthus × giganteus and Panicum virgatum L. (switchgrass). The underlying complexity of these polyploid grass genomes is a major limitation for their direct manipulation and thus driving a need for rapidly cycling comparative model. Setaria viridis (green millet) is a rapid cycling C4 panicoid grass with a relatively small and sequenced diploid genome and abundant seed production. Stable, transient, and protoplast transformation technologies have also been developed for Setaria viridis making it a potentially excellent model for other C4 bioenergy grasses. Here, the lignocellulosic feedstock composition, cellulose biosynthesis inhibitor response and saccharification dynamics of Setaria viridis are compared with the annual sorghum and maize and the perennial switchgrass bioenergy crops as a baseline study into the applicability for translational research. A genome-wide systematic investigation of the cellulose synthase-A genes was performed identifying eight candidate sequences. Two developmental stages; (a) metabolically active young tissue and (b) metabolically plateaued (mature) material are examined to compare biomass performance metrics.

09 BIOMASS FUELS↗

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [ Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height ( Dw1 and Dw2 ) and the YELLOW SEED1 locus ( Y1 ) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

bioenergy association panel↗

Comprehensive Economic Impacts ofWild Pigs on Producers of Six Crops in the South-Eastern US and California

Wild pigs (Sus scrofa) cause damage to agricultural crops in their native range as well as in the portions of the globe where they have been introduced. In the US, states with the highest introduced wild pig populations are Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, and Texas. The present study summarizes the first survey-based effort to value the full extent of wild pig damage to producers of six crops in these eleven US states. The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2022 to a sample of 11,495 producers of corn (Zea mays), soybeans (Glycine max), wheat (Triticum spp.), rice (Oryza sativa), peanuts (Arachis hypogaea), and sorghum (Sorghum bicolor) in these 11 states. Our findings suggest that the economic burden of wild pigs on producers of these crops is substantial and not limited to the direct and most identifiable categories of crop damage (i.e., production value lost due to depredation, trampling and rooting). We estimate that the annual cost to producers of these six crops in the surveyed states in 2021 was almost USD 700 million.

99 GENERAL AND MISCELLANEOUS↗

Small signaling peptides, phylogenetic analysis

ML Phylogenetic analysis of small signaling peptides in Arabidopsis, Sorghum bicolor, Rice, Wheat, Maize, and Brachypodium. Sorghum only phylogenetic trees were used to name genes. All trees but RALF tree are rooted at midpoint.

Kurtz, Evan [Department of Biochemistry and Biophy↗

Reflectance of vegetation, soil, and water

The author has identified the following significant results. A study was conducted in a 340-acre (139 hectares) field of grain sorghum (Sorghum bicolor (L.) Moench) to determine if multispectral data from ERTS-1 could be used to detect differences in chlorophyll concentration between iron-deficient (chlorotic) and apparently normal (green) grain sorghum. Chlorotic sorghum areas 2.8 acres (1.1 hectares) or larger in size were identified on a computer printout of band 5 data which contains the chlorophyll absorption band at the 0.65 micron wavelength. ERTS resolution is sufficient for practical applications in detecting iron-deficient sorghum in otherwise uniform fields. The first classification map of the study county has been produced. Vegetation (crops), rangeland, bare soil, water, and an undefined (all other) category occupied 15.2, 45.0, 19.1, 0.02, and 20.6% of the land area, respectively.

Wiegand, C. L.↗

Comparisons among a new soil index and other two- and four-dimensional vegetation indices

The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in LANDSAT MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS 5 and MSS 6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation.

Wiegand, C. L.↗

Comparisons among a new soil index and other two- and four-dimensional vegetation indices

The 2-D difference vegetation index (DVI) and perpendicular vegetation index (PVI), and the 4-D green vegetation index (GVI) are compared in Landsat MSS data from grain sorghum (Sorghum bicolor, L. Moench) fields for the years 1973 to 1977. PVI and DVI were more closely related to LAI than was GVI. A new 2-D soil line index (SLI), the vector distance from the soil line origin to the point of intersection of PVI with the soil line, is defined and compared with the 4-D soil brightness index, SBI. SLI (based on MSS and MSS7) and SL16 (based on MSS5 and MSS6) were smaller in magnitude than SBI but contained similar information about the soil background. These findings indicate that vegetation and soil indices calculated from the single visible and reflective infrared band sensor systems, such as the AVHRR of the TIROS-N polar orbiting series of satellites, will be meaningful for synoptic monitoring of renewable vegetation. Previously announced in STAR as N83-14567

Wiegand, C. L.↗

Photomorphogenesis and photoassimilation in soybean and sorghum grown under broad spectrum or blue-deficient light sources

The role of blue light in plant growth and development was investigated in soybean (Glycine max [L.] Merr. cv Williams) and sorghum (Sorghum bicolor [L.] Moench. cv Rio) grown under equal photosynthetic photon fluxes (approximately 500 micromoles per square meter per second) from broad spectrum daylight fluorescent or blue-deficient, narrow-band (589 nanometers) low pressure sodium (LPS) lamps. Between 14 and 18 days after sowing, it was possible to relate adaptations in photosynthesis and leaf growth to dry matter accumulation. Soybean development under LPS light was similar in several respects to that of shaded plants, consistent with an important role for blue light photoreceptors in regulation of growth response to irradiance. Thus, soybeans from LPS conditions partitioned relatively more growth to leaves and maintained higher average leaf area ratios (mean LAR) that compensated lower net assimilation rates (mean NAR). Relative growth rates were therefore comparable to plants from daylight fluorescent lamps. Reductions in mean NAR were matched by lower rates of net photosynthesis (A) on an area basis in the major photosynthetic source (first trifoliolate) leaf. Lower A in soybean resulted from reduced leaf dry matter per unit leaf area, but lower A under LPS conditions in sorghum correlated with leaf chlorosis and reduced total nitrogen (not observed in soybean). In spite of a lower A, mean NAR was larger in sorghum from LPS conditions, resulting in significantly greater relative growth rates (mean LAR was approximately equal for both light conditions). Leaf starch accumulation rate was higher for both species and starch content at the end of the dark period was elevated two- and three-fold for sorghum and soybean, respectively, under LPS conditions. Possible relations between starch accumulation, leaf export, and plant growth in response to spectral quality were considered.

NASA Discipline Life Support Systems↗

Chemical restrictions of roots in Ultisol subsoils lessened by long-term management

Exchangeable Al in subsoils of Ultisols in the southeastern USA can restrict rooting depth. Downward movement of basic cations (Ca, Mg, and K), applied as lime and fertilizer, may diminish that restriction over time. Materials from the argillic horizon were collected from three paired sites, having managed (long-term cropping) and nonmanaged topsoils (Typic Paleudults and Hapludults). One managed site was cropped continuously for 15 yr while the others were cultivated for more than 30 yr. Concentrations of extractable cations and other nutrients from the paired sites were compared to determine the magnitude of change due to management. The ability of the subsoils to support plant growth was evaluated in a missing-nutrient greenhouse experiment with sorghum [Sorghum bicolor (L.) Moench]. Subsoils of managed sites had greater effective cation-exchange capacity (CEC) and base saturation than those of non-managed sites. While availabilities of Ca, Mg, and K in subsoils of nonmanaged sites were inadequate to support maximal plant growth, they were adequate in subsoils of managed sites. Compared with nonmanaged sites, KCl-exchangeable Al in subsoils of managed sites was 23% lower at the 15-yr location and 65 and 100% lower at the two other locations. In the absence of lime, sorghum growth was almost totally inhibited on nonmanaged subsoils amended with optimum nutrients. On the managed subsoils, where 100, 65, and 23% of the nonmanaged exchangeable Al had been neutralized by topsoil fertilization and liming, growth reductions under the same conditions were 0, 50, and 100%, respectively. Thus, relatively long-term management had improved these Ultisol subsoils for root growth and development.

NASA Discipline Life Support Systems↗

Complex of mutualistic microbes designed to increase plant productivity

The present disclosure provides agricultural compositions and methods of using these compositions to increase plant growth, pathogen resistance and drought tolerance. The agricultural compositions disclosed herein comprise mixtures of mutualistic beneficial fungi such as Laccaria bicolor and Piriformispora indica, and bacterial strains of Pseudomonas.

59 BASIC BIOLOGICAL SCIENCES↗

Hypernetwork Science: From Multidimensional Networks to Computational Topology

As data structures and mathematical objects used for complex systems modeling, hypergraphs sit nicely poised between on the one hand the world of network models, and on the other that of higher-order mathematical abstractions from algebra, lattice theory, and topology. They are able to represent complex systems interactions more faithfully than graphs and networks, while also being some of the simplest classes of systems representing topological structures as collections of multidimensional objects connected in a particular pattern. In this paper we discuss the role of (undirected) hypergraphs in the science of complex networks, and provide a mathematical overview of the core concepts needed for hypernetwork modeling, including duality and the relationship to bicolored graphs, quantitative adjacency and incidence, the nature of walks in hypergraphs, and available topological relationships and properties. We close with a brief discussion of two example applications: biomedical databases for disease analysis, and domain-name system (DNS) analysis of cyber data.

Joslyn, Cliff A.↗

Complex of mutualistic microbes designed to increase plant productivity

The present disclosure provides agricultural compositions and methods of using these compositions to increase plant growth, pathogen resistance and drought tolerance. The agricultural compositions disclosed herein comprise mixtures of mutualistic beneficial fungi such as Laccaria bicolor and Piriformispora indica, and bacterial strains of Pseudomonas.

Labbe, Jessy L.↗