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Understanding and exploiting genetic diversity is a key factor for the productive and stable production of rice. Utilizing 16 high-quality genomes that represent the subpopulation structure of Asian rice (O. sativa), plus the genomes of two close relatives (O. rufipogon and O. punctata), we built a pan-genome inversion index of 1,054 non-redundant inversions that span an average of ∼ 14% of the O. sativa cv. Nipponbare reference genome sequence. Using this index we estimated an inversion rate of 1,100 inversions per million years in Asian rice, which is 37 to 73 times higher than previously estimated for plants. Detailed analyses of these inversions showed evidence of their effects on gene regulation, recombination rate, linkage disequilibrium and agronomic trait performance. Our study uncovers the prevalence and scale of large inversions (≥ 100 kb) across the pan-genome of Asian rice, and hints at their largely unexplored role in functional biology and crop performance.

SciApps is an open-source, web-based platform for processing, storing, visualizing, and distributing genomic data and analysis results. Built upon the Tapis (formerly Agave) platform, SciApps brings users TB-scale of data storage via CyVerse Data Store and over one million CPUs via the Extreme Science and Engineering Discovery Environment (XSEDE) resources at Texas Advanced Computing Center (TACC). SciApps provides users ways to chain individual jobs into automated and reproducible workflows in a distributed cloud and provides a management system for data, associated metadata, individual analysis jobs, and multi-step workflows. This chapter provides examples of how to (1) submitting, managing, constructing workflows, (2) using public workflows for Bulked Segregant Analysis (BSA), (3) constructing a Data Analysis Center (DAC), and Data Coordination Center (DCC) for the plant ENCODE project.

Main conclusion SorghumBase provides a community portal that integrates genetic, genomic, and breeding resources for sorghum germplasm improvement. Abstract Public research and development in agriculture rely on proper data and resource sharing within stakeholder communities. For plant breeders, agronomists, molecular biologists, geneticists, and bioinformaticians, centralizing desirable data into a user-friendly hub for crop systems is essential for successful collaborations and breakthroughs in germplasm development. Here, we present the SorghumBase web portal (https://www.sorghumbase.org), a resource for the sorghum research community. SorghumBase hosts a wide range of sorghum genomic information in a modular framework, built with open-source software, to provide a sustainable platform. This initial release of SorghumBase includes: (1) five sorghum reference genome assemblies in a pan-genome browser; (2) genetic variant information for natural diversity panels and ethyl methanesulfonate (EMS)-induced mutant populations; (3) search interface and integrated views of various data types; (4) links supporting interconnectivity with other repositories including genebank, QTL, and gene expression databases; and (5) a content management system to support access to community news and training materials. SorghumBase offers sorghum investigators improved data collation and access that will facilitate the growth of a robust research community to support genomics-assisted breeding.

With the potential of Industry 4.0 technologies to enable sustainable manufacturing, asset life cycle management (ALCM) has been gaining increasing attention in recent years. This study explores the evolution of Industry 4.0 technology applications to sustainable ALCM from 2002 to 2021. This study is based on keywords collected from 3896 ALCM-related scientific articles published in the Web of Science, IEEE Xplore and Engineering Village between 2002 and 2021. We conducted a review analysis of these keywords using a network science-based methodology, which unlike the tedious traditional literature review methods, gives the capability to analyze a huge number of scientific articles efficiently. We built keyword co-occurrence networks (KCNs) from the keywords and explored the network characteristics to uncover meaningful knowledge patterns, knowledge components, knowledge structure, and research trends in the body of literature at the intersection of ALCM and Industry 4.0. The network modeling and data analysis results identify the emerging Industry 4.0-related keywords in ALCM literature and indicate the recent explosion of connectivity among keywords. We found IoT, predictive maintenance and big data to be the top three most popular Industry 4.0-related keywords in ALCM literature. Furthermore, this study maps relevant ALCM keywords in contemporary literature to the nine pillars of Industry 4.0 to help the responsible manufacturing community identify research trends and emerging technologies for sustainability.

To build a large-scale genomic resource for functional validation of sorghum genes through EMS-mutagenized BTx623 seeds, we deep sequenced (30-60X) an additional 445 phenotyped EMS mutant lines. 4.2 million EMS mutations are called with nearly 36,800 mutations that could have a disruptive effect on functions of over 15,500 genes. Combining variants carried by both the natural population and previous EMS efforts, over 69% of sorghum coding genes (23644) are now presented with one or more mutations that are, or are predicted to be, disruptive to their functions. Our results show that the EMS population carries more significant mutations but less in each sample than the natural population, which makes it more powerful in elucidating sorghum gene functions on a large scale and requiring less work in validation of candidate causal genes. We have made the data available through two ways, one is the integration with the BSAseq workflow that supports retrieving independent EMS samples carrying the same genes with significant mutation for complementary testing, and the other is a web application for directly querying genes with significant mutations on SciApps.org.

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression.One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

An a-maize-ing set of genomes Maize is an important crop cultivated worldwide. As maize spread across the world, selection for local environments resulted in variation, but the impact on differences between the genome has not been quantified. By producing high-quality genomic sequences of the 26 lines used in the maize nested association mapping panel, Hufford et al . map important traits and demonstrate the diversity of maize. Examining RNA and methylation of genes across accessions, the authors identified a core set of maize genes. Beyond this core set, comparative analysis across lines identified high levels of variation in the total set of genes, the maize pan-genome. The value of this resource was further exemplified by mapping quantitative traits of interest, including those related to pathogen resistance. —LMZ

Summary With the advance of next-generation sequencing technologies and reductions in the costs of these techniques, bulked segregant analysis (BSA) has become not only a powerful tool for mapping quantitative trait loci but also a useful way to identify causal gene mutations underlying phenotypes of interest. However, due to the presence of background mutations and errors in sequencing, genotyping, and reference assembly, it is often difficult to distinguish true causal mutations from background mutations. In this study, we developed the BSAseq workflow, which includes an automated bioinformatics analysis pipeline with a probabilistic model for estimating the linked region (the region linked to the causal mutation) and an interactive Shiny web application for visualizing the results. We deeply sequenced a sorghum male-sterile parental line (ms8) to capture the majority of background mutations in our bulked F2 data. We applied the workflow to 11 bulked sorghum F2 populations and 1 rice F2 population and identified the true causal mutation in each population. The workflow is intuitive and straightforward, facilitating its adoption by users without bioinformatics analysis skills. We anticipate that the BSAseq workflow will be broadly applicable to the identification of causal mutations for many phenotypes of interest. Availability and implementation BSAseq is freely available on https://www.sciapps.org/page/bsa. Supplementary information Supplementary data are available at Bioinformatics online.

MaizeCODE is a project aimed at identifying and analyzing functional elements in the maize genome. In its initial phase, MaizeCODE assayed up to five tissues from four maize strains (B73, NC350, W22, TIL11) by RNA-Seq, Chip-Seq, RAMPAGE, and small RNA sequencing. To facilitate reproducible science and provide both human and machine access to the MaizeCODE data, we enhanced SciApps, a cloud-based portal, for analysis and distribution of both raw data and analysis results. Based on the SciApps workflow platform, we generated new components to support the complete cycle of MaizeCODE data management. These include publicly accessible scientific workflows for the reproducible and shareable analysis of various functional data, a RESTful API for batch processing and distribution of data and metadata, a searchable data page that lists each MaizeCODE experiment as a reproducible workflow, and integrated JBrowse genome browser tracks linked with workflows and metadata. The SciApps portal is a flexible platform that allows the integration of new analysis tools, workflows, and genomic data from multiple projects. Through metadata and a ready-to-compute cloud-based platform, the portal experience improves access to the MaizeCODE data and facilitates its analysis.

Motivation The rapid accumulation of both sequence and phenotype data generated by high-throughput methods has increased the need to store and analyze data on distributed storage and computing systems. Efficient data management across these heterogeneous systems requires a workflow management system to simplify the task of analysis through automation and make large-scale bioinformatics analyses accessible and reproducible. Results We developed SciApps, a web-based platform for reproducible bioinformatics workflows. The platform is designed to automate the execution of modular Agave apps and support execution of workflows on local clusters or in a cloud. Two workflows, one for association and one for annotation, are provided as exemplar scientific use cases. Availability and implementation https://www.sciapps.org Supplementary information Supplementary data are available at Bioinformatics online.

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 uploading private or public data into the KBase Narrative Interface, analyzing it using a rich, extensible array of computational and data-analytics tools, and securely sharing 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 differentially expressed during drought-stress in Sorghum bicolor, an important sustainable production crop plant. We then show how we can 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.

Zea mays is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing ∼70% of the genes annotated in maize RefGen_v3 genome. A large proportion of transcripts (57%) represent novel, sometimes tissue-specific, isoforms of known genes and 3% correspond to novel gene loci. In other cases, the identified transcripts have improved existing gene models. Averaging across all six tissues, 90% of the splice junctions are supported by short reads from matched tissues. In addition, we identified a large number of novel long non-coding RNAs and fusion transcripts and found that DNA methylation plays an important role in generating various isoforms. Our results show that characterization of the maize B73 transcriptome is far from complete, and that maize gene expression is more complex than previously thought., Zea mays is an important crop species and genetic model but uncertainties remain regarding the structure of the transcriptome. Here Wang et al. use single-molecule sequencing and size-fractionated libraries to identify novel transcripts and isoforms illustrating the complexity of maize mRNA.

The formation of band structures in different peritectic alloys directionally solidified under transverse static magnetic fields was observed. Unidirectional thermoelectric–magnetic convection (TEMC), which modified solute transport in the liquid phase, was principally responsible for band-structure formation. A simple TEMC-regime-based model for predicting the compositional ranges in which band structures could form in alloys directionally solidified under transverse static magnetic fields was developed. The theoretical predictions agreed well with the experimental results.

SciApps, a lightweight bioinformatics workflow system powered by the CyVerse infrastructure, uses the Agave Science API to manage the entire cycle of analysis jobs between XSEDE HPC and the CyVerse Data Store. SciApps provides a graphical user interface for job submission, workflow creation, and management of both jobs and workflows. Each reproducible workflow, along with all inputs and results, is retrievable with a unique ID.

Peritectic alloy Cu-10.5 at.% Sn was directionally solidified at various growth speeds under a transverse static magnetic field. The experimental results indicated that the magnetic field caused the deformation of macroscopic interface morphology, the crystal orientation of primary phase along solidification direction, and the occurrence of peritectic reaction. The numerical simulations showed that the application of the magnetic field induced the formation of a unidirectional thermoelectric magnetic convection (TEMC), which modified solute transport in the liquid phase thereby enriching the solute concentration both at the sample and tri-junction scales. The modification of solidification structures under the magnetic field should be attributed to TEMC driven heat transfer and solute transport.

International audience; The influence of a weak transverse magnetic field on the microstructure in directionally solidified Cu-20 wt.% Sn peritectic alloys at low speeds (0.8-1.2 mu m/s) was investigated. Experimental results indicated that the magnetic field caused the evolution of the two-phase microstructure from coupled growth to band. Moreover, it was also found that the magnetic field induced the crystal orientation of the primary phase. The above results may be attributed to the effect of the magnetic field on the mass and heat transfer during directional solidification.

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Effect of a high magnetic field on the morphology of the primary dendrite in directionally solidified Pb-25 at% Bi peritectic alloy was investigated experimentally. Results indicated that the high magnetic field caused the irregularity and break of the primary dendrite. As the applied magnetic field increased, the primary dendritic spacing increased. Further, the Seebeck voltage near the liquid–solid interface was measured at various growth speeds. It was found that the Seebeck voltage decreased as the growth speed increased. The above results may be attributed to the thermoelectric magnetic force (TEMF) imposed on the solid. The primary dendrite fragments, surrounded by the peritectic phase, which is associated with the increase of the dendritic spacing.

International audience; The effects of an axial high magnetic field on the growth of the alpha-Al dendrites and the alignment of the iron-intermetallics (beta-AlSiFe phases) in directionally solidified Al-7 wt% Si and Al-7 wt% Si-1 wt% Fe alloys were investigated experimentally. The results showed that the application of a high magnetic field changed the alpha-Al dendrite morphology significantly. Indeed, a high magnetic field caused the deformation of the alpha-Al dendrites and induced the occurrence of the columnar-to-equiaxed transition (CET). It was also found that a high magnetic field was capable of aligning the beta-AlSiFe phases with the < 001 >-crystal direction along the solidification direction. Further, the Seebeck thermoelectric signal at the liquid/solid interface in the Al-7 wt% Si alloys was measured in situ and the results indicated that the value of the Seebeck signal was of the order of 10 mu V. The modification of the alpha-Al dendrite morphology under the magnetic field should be attributed to the thermoelectric magnetic force acting on the alpha-Al dendrites. The magnetization force may be responsible for the alignment of the beta-AlSiFe phases under the magnetic field

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Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.

The maize genome, with its large complement of transposons and repeats, is a paradigm for the study of epigenetic mechanisms such as paramutation and imprinting. Here, we present the genome-wide map of cytosine methylation for two maize inbred lines, B73 and Mo17. CG (65%) and CHG (50%) methylation (where H = A, C, or T) is highest in transposons, while CHH (5%) methylation is likely guided by 24-nt, but not 21-nt, small interfering RNAs (siRNAs). Correlations with methylation patterns suggest that CG methylation in exons (8%) may deter insertion of Mutator transposon insertion, while CHG methylation at splice acceptor sites may inhibit RNA splicing. Using the methylation map as a guide, we used low-coverage sequencing to show that parental methylation differences are inherited by recombinant inbred lines. However, frequent methylation switches, guided by siRNA, persist for up to eight generations, suggesting that epigenetic inheritance resembling paramutation is much more common than previously supposed. The methylation map will provide an invaluable resource for epigenetic studies in maize.

Effect of a weak transverse magnetic field on the microstructures in directionally solidified Fe-Ni and Pb-Bi peritectic alloys has been investigated experimentally. The results indicate that the magnetic field can induce the formation of banded and island-like structures and refine the primary phase in peritectic alloys. The above results are enhanced with increasing magnetic field. Furthermore, electron probe micro analyzer (EPMA) analysis reveals that the magnetic field increases the Ni solute content on one side and enhances the solid solubility in the primary phase in the Fe-Ni alloy. The thermoelectric (TE) power difference at the liquid/solid interface of the Pb-Bi peritectic alloy is measured in situ, and the results show that a TE power difference exists at the liquid/solid interface. 3 D numerical simulations for the TE magnetic convection in the liquid are performed, and the results show that a unidirectional TE magnetic convection forms in the liquid near the liquid/solid interface during directional solidification under a transverse magnetic field and that the amplitude of the TE magnetic convection at different scales is different. The TE magnetic convections on the macroscopic interface and the cell/dendrite scales are responsible for the modification of microstructures during directional solidification under a magnetic field.

A Taiwanese manufacturer of off-road utility vehicles (OUVs) was so concerned by the increased number in U.S. accidents and federal probes, involving OUVs from other manufacturers in the industry that it recently funded a thorough, analytical crashworthiness evaluation of its production vehicle body structure. The approach is to employ a transient dynamic, large-strain, material nonlinear finite-element modelling and analysis using LS-DYNA, with adequate model validation. The current paper, Part I of two, presents two sets of model validation via experimental modal analysis (EMA) and drop impact tests. The transfer of impact kinetic energy to vehicle structure's internal energy results in extreme deformation, and material nonlinearity/plasticity. Model validation is thus a must for accurate simulation. EMA was first conducted to obtain the natural frequencies and the associate mode shapes to validate the distributed stiffness and mass, both of which can significantly influence the sequence of plastic defo...

This paper, Part II of two, presents the simulations of various impact crashes for an off-road utility vehicle (OUV) to assess the structural crashworthiness and the potential occupant injuries. The approach is to employ a transient dynamic, large-strain, material non-linear finite-element analysis (FEA) using LS-DYNA, with model validations, which were addressed in Part I of this two-part paper. The full vehicle finite-element model (FEM) is established by integrating the validated body structure, front bumper, chassis components, powertrain components, fuel tank, seats and container. Structural deformations and internal energies are extracted from simulation results for evaluating crashworthiness of the full vehicle structure. Head Injury Criterion (HIC) and Thoracic Trauma Index (TTI) obtained from the dummy are used to assess the potential injuries of occupant during the impact crashes. The simulation results help identify weaker parts of body structure for future vehicle design improvement.