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IntroductionThe agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped.MethodsTo bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources.ResultsHerein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments.DiscussionWe intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Abstract Background Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable. Results Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a “subpopulation aware” 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq). Conclusions This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

[This corrects the article DOI: 10.1371/journal.pone.0224086.].

Metal homeostasis has evolved to tightly modulate the availability of metals within the cell, avoiding cytotoxic interactions due to excess and protein inactivity due to deficiency. Even in the presence of homeostatic processes, however, low bioavailability of these essential metal nutrients in soils can negatively impact crop health and yield. While research has largely focused on how plants assimilate metals, acclimation to metal-limited environments requires a suite of strategies that are not necessarily involved in metal transport across membranes. The identification of these mechanisms provides a new opportunity to improve metal-use efficiency and develop plant foodstuffs with increased concentrations of bioavailable metal nutrients. Here, we investigate the function of two distinct subfamilies of the nucleotide-dependent metallochaperones (NMCs), named ZNG1 and ZNG2, that are found in plants, using Arabidopsis thaliana as a reference organism. AtZNG1 (AT1G26520) is an ortholog of human and fungal ZNG1, and like its previously characterized eukaryotic relatives, localizes to the cytosol and physically interacts with methionine aminopeptidase type I (AtMAP1A). Analysis of AtZNG1, AtMAP1A, AtMAP2A, and AtMAP2B transgenic mutants are consistent with the role of Arabidopsis ZNG1 as a Zn transferase for AtMAP1A, as previously described in yeast and zebrafish. Structural modeling reveals a flexible cysteine-rich loop that we hypothesize enables direct transfer of Zn from AtZNG1 to AtMAP1A during GTP hydrolysis. Based on proteomics and transcriptomics, loss of this ancient and conserved mechanism has pleiotropic consequences impacting the expression of hundreds of genes, including those involved in photosynthesis and vesicle transport. Members of the plant-specific family of NMCs, ZNG2A1 (AT1G80480) and ZNG2A2 (AT1G15730), are also required during Zn deficiency, but their target protein(s) remain to be discovered. RNA-seq analyses reveal wide-ranging impacts across the cell when the genes encoding these plastid-localized NMCs are disrupted.

Pan-genomes provide useful resources for evolutionary studies, functional genomics and breeding of cultivated plants. Here, the authors report a new rice pan-genome including 73 Asian rice and two wild relatives (Oryza rufipogon and O. punctata), and reveal the prevalence and scale of large inversions across the pan-genome.

Abstract Background Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.” Results We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation. Conclusion We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

AbstractThe genome sequence of the diploid and highly homozygous Vitis viniferaVitis.

IntroductionSorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations.MethodsExpanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs).ResultsWe show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes.DiscussionThese resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism.

Abstract Efficient acquisition and use of available phosphorus from the soil is crucial for plant growth, development, and yield. With an ever‐increasing acreage of croplands with suboptimal available soil phosphorus, genetic improvement of sorghum germplasm for enhanced phosphorus acquisition from soil is crucial to increasing agricultural output and reducing inputs, while confronted with a growing world population and uncertain climate. Sorghum bicolor is a globally important commodity for food, fodder, and forage. Known for robust tolerance to heat, drought, and other abiotic stresses, its capacity for optimal phosphorus use efficiency (PUE) is still being investigated for optimized root system architectures (RSA). Whilst a few RSA‐influencing genes have been identified in sorghum and other grasses, the epigenetic impact on expression and tissue‐specific activation of candidate PUE genes remains elusive. Here, we present transcriptomic, epigenetic, and regulatory network profiling of RSA modulation in the BTx623 sorghum background in response to limiting phosphorus (LP) conditions. We show that during LP, sorghum RSA is remodeled to increase root length and surface area, likely enhancing its ability to acquire P. Global DNA 5‐methylcytosine and H3K4 and H3K27 trimethylation levels decrease in response to LP, while H3K4me3 peaks and DNA hypomethylated regions contain recognition motifs of numerous developmental and nutrient responsive transcription factors that display disparate expression patterns between different root tissues (primary root apex, elongation zone, and lateral root apex).

Sequence depth and read length determine the quality of genome assembly. Here, the authors leverage a set of PacBio reads to develop guidelines for sequencing and assembly of complex plant genomes in order to allocate finite resources using maize as an example.

Abstract Creating gapless telomere-to-telomere assemblies of complex genomes is one of the ultimate challenges in genomics. We use two independent assemblies and an optical map-based merging pipeline to produce a maize genome (B73-Ab10) composed of 63 contigs and a contig N50 of 162 Mb. This genome includes gapless assemblies of chromosome 3 (236 Mb) and chromosome 9 (162 Mb), and 53 Mb of the Ab10 meiotic drive haplotype. The data also reveal the internal structure of seven centromeres and five heterochromatic knobs, showing that the major tandem repeat arrays (CentC, knob180, and TR-1) are discontinuous and frequently interspersed with retroelements.

Trait introgression requires universal markers, but cross-species transferability of current SNP markers can be as low as 2%. Here, the authors use an AmpSeq haplotype strategy targeting the collinear core genome for marker development and show transferability increases to 91.4% in the Vitis genus.

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.

Abstract Background Sequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and provide an opportunity for comprehensive annotation of TEs. Numerous methods exist for annotation of each class of TEs, but their relative performances have not been systematically compared. Moreover, a comprehensive pipeline is needed to produce a non-redundant library of TEs for species lacking this resource to generate whole-genome TE annotations. Results We benchmark existing programs based on a carefully curated library of rice TEs. We evaluate the performance of methods annotating long terminal repeat (LTR) retrotransposons, terminal inverted repeat (TIR) transposons, short TIR transposons known as miniature inverted transposable elements (MITEs), and Helitrons. Performance metrics include sensitivity, specificity, accuracy, precision, FDR, and F 1. Using the most robust programs, we create a comprehensive pipeline called Extensive de-novo TE Annotator (EDTA) that produces a filtered non-redundant TE library for annotation of structurally intact and fragmented elements. EDTA also deconvolutes nested TE insertions frequently found in highly repetitive genomic regions. Using other model species with curated TE libraries (maize and Drosophila), EDTA is shown to be robust across both plant and animal species. Conclusions The benchmarking results and pipeline developed here will greatly facilitate TE annotation in eukaryotic genomes. These annotations will promote a much more in-depth understanding of the diversity and evolution of TEs at both intra- and inter-species levels. EDTA is open-source and freely available: https://github.com/oushujun/EDTA.

Inflorescence architecture affects crop grain yield. Here, the authors deploy whole-genome sequencing-based bulk segregant analysis to identify the causal gene of a sorghum multi-seeded (msd) mutant and suggest MSD1 regulating the fertility of the pedicellate spikelets through jasmonic acid pathway.

Core Ideas The male‐sterile 9 (ms9) is a novel nuclear male‐sterile mutant in sorghum. The Ms9 gene encodes a PHD‐finger transcription factor critical for pollen development. The identification of the Ms9 gene provides a strategy to control male sterility in sorghum. Nuclear male sterility (NMS) is important for understanding microspore development and could facilitate the development of new strategies to control male sterility. Several NMS lines and mutants have been reported in sorghum [Sorghum bicolor (L.) Moench] previously. However, no male‐sterile gene has been identified, hampering the utility of NMS in sorghum breeding. In this study, we characterized a new NMS mutant, male sterile 9 (ms9), which is distinct from all other reported NMS loci. The ms9 mutant is stable under a variety of environmental conditions. Homozygous ms9 plants produced normal ovaries but small pale‐colored anthers that contained no pollen grains. Microscopic analyses revealed abnormal microspore development of ms9 at the midmicrospore stage, causing degeneration of microspore inside the anther lobes and male sterility of ms9 plants. Using MutMap, we identified the Ms9 gene as a plant homeotic domain (PHD)‐finger transcription factor similar to Ms1 in Arabidopsis thaliana (L.) Heynh. and Ptc1 in rice (Oryza sativa L.). Ms9 is the first NMS gene identified in sorghum. Thus, the Ms9 gene and ms9 mutant provide new genetic tools for studying pollen development and controlling male sterility in sorghum.

Advances in transcriptomics have provided an exceptional opportunity to study functional implications of the genetic variability. Technologies such as RNA-Seq have emerged as state-of-the-art techniques for transcriptome analysis that take advantage of high-throughput next-generation sequencing. However, similar to their predecessors, these approaches continue to impose major challenges on full-length transcript structure identification, primarily due to inherent limitations of read length. With the development of single-molecule sequencing (SMS) from PacBio, a growing number of studies on the transcriptome of different organisms have been reported. SMS has emerged as advantageous for comprehensive genome annotation including identification of novel genes/isoforms, long non-coding RNAs and fusion transcripts. This approach can be used across a broad spectrum of species to better interpret the coding information of the genome, and facilitate the biological function study. We provide an overview of SMS platform and its diverse applications in various biological studies, and our perspective on the challenges associated with the transcriptome studies.

The sophistication of gene prediction algorithms and the abundance of RNA-based evidence for the maize genome may suggest that manual curation of gene models is no longer necessary. However, quality metrics generated by the MAKER-P gene annotation pipeline identified 17,225 of 130,330 (13%) protein-coding transcripts in the B73 Reference Genome V4 gene set with models of low concordance to available biological evidence. Working with eight graduate students, we used the Apollo annotation editor to curate 86 transcript models flagged by quality metrics and a complimentary method using the Gramene gene tree visualizer. All of the triaged models had significant errors-including missing or extra exons, non-canonical splice sites, and incorrect UTRs. A correct transcript model existed for about 60% of genes (or transcripts) flagged by quality metrics; we attribute this to the convention of elevating the transcript with the longest coding sequence (CDS) to the canonical, or first, position. The remaining 40% of flagged genes resulted in novel annotations and represent a manual curation space of about 10% of the maize genome (~4,000 protein-coding genes). MAKER-P metrics have a specificity of 100%, and a sensitivity of 85%; the gene tree visualizer has a specificity of 100%. Together with the Apollo graphical editor, our double triage provides an infrastructure to support the community curation of eukaryotic genomes by scientists, students, and potentially even citizen scientists.

Gramene (http://www.gramene.org) is an online, open source, curated resource for plant comparative genomics and pathway analysis designed to support researchers working in plant genomics, breeding, evolutionary biology, system biology, and metabolic engineering. It exploits phylogenetic relationships to enrich the annotation of genomic data and provides tools to perform powerful comparative analyses across a wide spectrum of plant species. It consists of an integrated portal for querying, visualizing and analyzing data for 44 plant reference genomes, genetic variation data sets for 12 species, expression data for 16 species, curated rice pathways and orthology-based pathway projections for 66 plant species including various crops. Here we briefly describe the functions and uses of the Gramene database.

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.

Sorghum (Sorghum bicolor Moench, L.) plant accumulates copious layers of epi-cuticular wax (EW) on its aerial surfaces, to a greater extent than most other crops. EW provides a vapor barrier that reduces water loss, and is therefore considered to be a major determinant of sorghum's drought tolerance. However, little is known about the genes responsible for wax accumulation in sorghum. We isolated two allelic mutants, bloomless40-1 (bm40-1) and bm40-2, from a mutant library constructed from ethyl methane sulfonate (EMS) treated seeds of an inbred, BTx623. Both mutants were nearly devoid of the EW layer. Each bm mutant was crossed to the un-mutated BTx623 to generated F2 populations that segregated for the bm phenotype. Genomic DNA from 20 bm F2 plants from each population was bulked for whole genome sequencing. A single gene, Sobic.001G228100, encoding a GDSL-like lipase/acylhydrolase, had unique homozygous mutations in each bulked F2 population. Mutant bm40-1 harbored a missense mutation in the gene, whereas bm40-2 had a splice donor site mutation. Our findings thus provide strong evidence that mutation in this GDSL-like lipase gene causes the bm phenotype, and further demonstrate that this approach of sequencing two independent allelic mutant populations is an efficient method for identifying causal mutations. Combined with allelic mutants, MutMap provides powerful method to identify all causal genes for the large collection of bm mutants in sorghum, which will provide insight into how sorghum plants accumulate such abundant EW on their aerial surface. This knowledge may facilitate the development of tools for engineering drought-tolerant crops with reduced water loss.