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Gramene (http://www.gramene.org), a knowledgebase founded on comparative functional analyses of genomic and pathway data for model plants and major crops, supports agricultural researchers worldwide. The resource is committed to open access and reproducible science based on the FAIR data principles. Since the last NAR update, we made nine releases; doubled the genome portal's content; expanded curated genes, pathways and expression sets; and implemented the Domain Informational Vocabulary Extraction (DIVE) algorithm for extracting gene function information from publications. The current release, #63 (October 2020), hosts 93 reference genomes—over 3.9 million genes in 122 947 families with orthologous and paralogous classifications. Plant Reactome portrays pathway networks using a combination of manual biocuration in rice (320 reference pathways) and orthology-based projections to 106 species. The Reactome platform facilitates comparison between reference and projected pathways, gene expression analyses and overlays of gene–gene interactions. Gramene integrates ontology-based protein structure–function annotation; information on genetic, epigenetic, expression, and phenotypic diversity; and gene functional annotations extracted from plant-focused journals using DIVE. We train plant researchers in biocuration of genes and pathways; host curated maize gene structures as tracks in the maize genome browser; and integrate curated rice genes and pathways in the Plant Reactome.

The PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria × ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System., Measurement(s) DNA • genome • Metagenome Technology Type(s) DNA sequencing • PacBio Sequel System Factor Type(s) organism that had its genome sequenced Sample Characteristic - Organism Mus musculus • Rana muscosa • Fragaria x ananassa • Zea mays Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12855527

Improvements in long-read data and scaffolding technologies have enabled rapid generation of reference-quality assemblies for complex genomes. Still, an assessment of critical sequence depth and read length is important for allocating limited resources. To this end, we have generated eight assemblies for the complex genome of the maize inbred line NC358 using PacBio datasets ranging from 20 to 75 × genomic depth and with N50 subread lengths of 11–21 kb. Assemblies with ≤30 × depth and N50 subread length of 11 kb are highly fragmented, with even low-copy genic regions showing degradation at 20 × depth. Distinct sequence-quality thresholds are observed for complete assembly of genes, transposable elements, and highly repetitive genomic features such as telomeres, heterochromatic knobs, and centromeres. In addition, we show high-quality optical maps can dramatically improve contiguity in even our most fragmented base assembly. This study provides a useful resource allocation reference to the community as long-read technologies continue to mature., 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.

BackgroundSequencing 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.ResultsWe 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, andF1. Using the most robust programs, we create a comprehensive pipeline called Extensivede-novoTE 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.ConclusionsThe 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.

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of interfaces to genomic data across the tree of life, including reference genome sequence, gene models, transcriptional data, genetic variation and comparative analysis. Data may be accessed via our website, online tools platform and programmatic interfaces, with updates made four times per year (in synchrony with Ensembl). Here, we provide an overview of Ensembl Genomes, with a focus on recent developments. These include the continued growth, more robust and reproducible sets of orthologues and paralogues, and enriched views of gene expression and gene function in plants. Finally, we report on our continued deeper integration with the Ensembl project, which forms a key part of our future strategy for dealing with the increasing quantity of available genome-scale data across the tree of life.

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

The ability to expand crop plantations without irrigation is a major goal to increase agriculture sustainability. To achieve this end, we need to understand the mechanisms that govern plant growth responses under drought conditions. In this study, we combined physiological, transcriptomic, and genomic data to provide a comprehensive picture of drought and recovery responses in the leaves and roots of sugarcane. Transcriptomic profiling using oligoarrays and RNA-seq identified 2898 (out of 21,902) and 46,062 (out of 373,869) transcripts as differentially expressed, respectively. Co-expression analysis revealed modules enriched in photosynthesis, small molecule metabolism, alpha-amino acid metabolism, trehalose biosynthesis, serine family amino acid metabolism, and carbohydrate transport. Together, our findings reveal that carbohydrate metabolism is coordinated with the degradation of amino acids to provide carbon skeletons to the tricarboxylic acid cycle. This coordination may help to maintain energetic balance during drought stress adaptation, facilitating recovery after the stress is alleviated. Our results shed light on candidate regulatory elements and pave the way to biotechnology strategies towards the development of drought-tolerant sugarcane plants.

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.

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.

Transferable DNA markers are essential for breeding and genetics. Grapevine (Vitis) breeders utilize disease resistance alleles from congeneric species ~20 million years divergent, but existing Vitis marker platforms have cross-species transfer rates as low as 2%. Here, we apply a marker strategy targeting the inferred Vitis core genome. Incorporating seven linked-read de novo assemblies and three existing assemblies, the Vitis collinear core genome is estimated to converge at 39.8 Mb (8.67% of the genome). Adding shotgun genome sequences from 40 accessions enables identification of conserved core PCR primer binding sites flanking polymorphic haplotypes with high information content. From these target regions, we develop 2,000 rhAmpSeq markers as a PCR multiplex and validate the panel in four biparental populations spanning the diversity of the Vitis genus, showing transferability increases to 91.9%. This marker development strategy should be widely applicable for genetic studies in many taxa, particularly those ~20 million years divergent., 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.

Maize and sorghum are both important crops with similar overall plant architectures, but they have key differences, especially in regard to their inflorescences. To better understand these two organisms at the molecular level, we compared expression profiles of both protein-coding and noncoding transcripts in 11 matched tissues using single-molecule, long-read, deep RNA sequencing. This comparative analysis revealed large numbers of novel isoforms in both species. Evolutionarily young genes were likely to be generated in reproductive tissues and usually had fewer isoforms than old genes. We also observed similarities and differences in alternative splicing patterns and activities, both among tissues and between species. The maize subgenomes exhibited no bias in isoform generation; however, genes in the B genome were more highly expressed in pollen tissue, whereas genes in the A genome were more highly expressed in endosperm. We also identified a number of splicing events conserved between maize and sorghum. In addition, we generated comprehensive and high-resolution maps of poly(A) sites, revealing similarities and differences in mRNA cleavage between the two species. Overall, our results reveal considerable splicing and expression diversity between sorghum and maize, well beyond what was reported in previous studies, likely reflecting the differences in architecture between these two species.

Grain number per panicle is an important component of grain yield in sorghum (Sorghum bicolor (L.)) and other cereal crops. Previously, we reported that mutations in multi-seeded 1 (MSD1) and MSD2 genes result in a two-fold increase in grain number per panicle due to the restoration of the fertility of the pedicellate spikelets, which invariably abort in natural sorghum accessions. Here, we report the identification of another gene, MSD3, which is also involved in the regulation of grain numbers in sorghum. Four bulked F2 populations from crosses between BTx623 and each of the independent msd mutants p6, p14, p21, and p24 were sequenced to 20&times, coverage of the whole genome on a HiSeq 2000 system. Bioinformatic analyses of the sequence data showed that one gene, Sorbi_3001G407600, harbored homozygous mutations in all four populations. This gene encodes a plastidial &omega, 3 fatty acid desaturase that catalyzes the conversion of linoleic acid (18:2) to linolenic acid (18:3), a substrate for jasmonic acid (JA) biosynthesis. The msd3 mutants had reduced levels of linolenic acid in both leaves and developing panicles that in turn decreased the levels of JA. Furthermore, the msd3 panicle phenotype was reversed by treatment with methyl-JA (MeJA). Our characterization of MSD1, MSD2, and now MSD3 demonstrates that JA-regulated processes are critical to the msd phenotype. The identification of the MSD3 gene reveals a new target that could be manipulated to increase grain number per panicle in sorghum, and potentially other cereal crops, through the genomic editing of MSD3 functional orthologs.

As in other cereal crops, the panicles of sorghum (Sorghum bicolor (L.) Moench) comprise two types of floral spikelets (grass flowers). Only sessile spikelets (SSs) are capable of producing viable grains, whereas pedicellate spikelets (PSs) cease development after initiation and eventually abort. Consequently, grain number per panicle (GNP) is lower than the total number of flowers produced per panicle. The mechanism underlying this differential fertility is not well understood. To investigate this issue, we isolated a series of EMS-induced multiseeded (msd) mutants that result in full spikelet fertility, effectively doubling GNP. Previously, we showed that MSD1 is a TCP (Teosinte branched/Cycloidea/PCF) transcription factor that regulates jasmonic acid (JA) biosynthesis, and ultimately floral sex organ development. Here, we show that MSD2 encodes a lipoxygenase (LOX) that catalyzes the first committed step of JA biosynthesis. Further, we demonstrate that MSD1 binds to the promoters of MSD2 and other JA pathway genes. Together, these results show that a JA-induced module regulates sorghum panicle development and spikelet fertility. The findings advance our understanding of inflorescence development and could lead to new strategies for increasing GNP and grain yield in sorghum and other cereal crops.SignificanceThrough a single base pair mutation, grain number can be increased by ~200% in the globally important crop Sorghum bicolor. This mutation affects the expression of an enzyme, MSD2, that catalyzes the jasmonic acid pathway in developing floral meristems. The global gene expression profile in this enzymatic mutant is similar to that of a transcription factor mutant, msd1, indicating that disturbing any component of this regulatory module disrupts a positive feedback loop that occurs normally due to regular developmental perception of jasmonic acid. Additionally, the MSD1 transcription factor is able to regulate MSD2 in addition to other jasmonic acid pathway genes, suggesting that it is a primary transcriptional regulator of this hormone signaling pathway in floral meristems.

Sequencing technology and assembly algorithms have matured to the point that high-qualityde novoassembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and allow for annotation of TEs. There are numerous methods for each class of elements with unknown relative performance metrics. We benchmarked existing programs based on a curated library of rice TEs. Using the most robust programs, we created a comprehensive pipeline called Extensivede-novoTE Annotator (EDTA) that produces a condensed TE library for annotations of structurally intact and fragmented elements. EDTA is open-source and freely available:https://github.com/oushujun/EDTA.

Haplotype phasing of genetic variants in maize is important for interpretation of the genome, population genetic analysis and functional genomic analysis of allelic activity. Accordingly, accurate methods for phasing the full-length isoforms are essential for functional genomics studies. We performed an isoform-level phasing study in maize, using two inbred lines and their reciprocal crosses, based on the single-molecule full-length cDNA sequencing. To phase and analyze the full-length transcripts between hybrids and parents, we developed a tool called IsoPhase. Using this tool, we validated the majority of SNPs called against matching short-read data and identified cases of allele-specific, gene-level and isoform-level expression. Our results revealed that maize parental lines and hybrid lines exhibit different splicing activities. After phasing 6,907 genes in two reciprocal hybrids using embryo, endosperm and root tissues, we annotated the SNPs and identified large-effect genes. In addition, based on single-molecule sequencing, we identified parent-of-origin isoforms in maize hybrids, distinct novel isoforms in maize parent and hybrid lines, and imprinted genes from different tissues. Finally, we characterized variation in cis- and trans-regulatory effects. Our study provides measures of haplotypic expression that could increase accuracy in studies of allelic expression.

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.

The genetic basis of general plant vigor is of major interest to food producers, yet the trait is recalcitrant to genetic mapping because of the number of loci involved, their small effects, and linkage. Observations of heterosis in many crops suggests that recessive, malfunctioning versions of genes are a major cause of poor performance, yet we have little information on the mutational spectrum underlying these disruptions. To address this question, we generated a long-read assembly of a tropical japonica rice (Oryza sativa) variety, Carolina Gold, which allowed us to identify structural mutations (>50 bp) and orient them with respect to their ancestral state using the outgroup, Oryza glaberrima. Supporting prior work, we find substantial genome expansion in the sativa branch. While transposable elements (TEs) account for the largest share of size variation, the majority of events are not directly TE-mediated. Tandem duplications are the most common source of insertions and are highly enriched among 50-200bp mutations. To explore the relative impact of various mutational classes on crop fitness, we then track these structural events over the last century of US rice improvement using 101 resequenced varieties. Within this material, a pattern of temporary hybridization between medium and long-grain varieties was followed by recent divergence. During this long-term selection, structural mutations that impact gene exons have been removed at a greater rate than intronic indels and single-nucleotide mutations. These results support the use of ab initio estimates of mutational burden, based on structural data, as an orthogonal predictor in genomic selection., Author summary Some crop varieties have superior performance across years and environments. In hybrids, harmful mutations in one parent are masked by the ancestral alleles in the other parent, resulting in increased vigor. Unfortunately, these mutations are very difficult to identify precisely because, individually, they only have a small effect. In this study, we use long-read sequencing to characterize the entire mutational spectrum between two rice varieties. We then track these mutations through the last century of rice breeding. We show that large structural mutations in exons are selected against at a greater rate than any other mutational class. These findings illuminate the nature of deleterious alleles and will guide attempts to predict variety vigor based solely on genomic information.

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.

Author(s): Bukowski, Robert; Guo, Xiaosen; Lu, Yanli; Zou, Cheng; He, Bing; Rong, Zhengqin; Wang, Bo; Xu, Dawen; Yang, Bicheng; Xie, Chuanxiao; Fan, Longjiang; Gao, Shibin; Xu, Xun; Zhang, Gengyun; Li, Yingrui; Jiao, Yinping; Doebley, John F; Ross-Ibarra, Jeffrey; Lorant, Anne; Buffalo, Vince; Romay, M Cinta; Buckler, Edward S; Ware, Doreen; Lai, Jinsheng; Sun, Qi; Xu, Yunbi | Abstract: BackgroundCharacterization of genetic variations in maize has been challenging, mainly due to deterioration of collinearity between individual genomes in the species. An international consortium of maize research groups combined resources to develop the maize haplotype version 3 (HapMap 3), built from whole-genome sequencing data from 1218 maize lines, covering predomestication and domesticated Zea mays varieties across the world.ResultsA new computational pipeline was set up to process more than 12 trillion bp of sequencing data, and a set of population genetics filters was applied to identify more than 83 million variant sites.ConclusionsWe identified polymorphisms in regions where collinearity is largely preserved in the maize species. However, the fact that the B73 genome used as the reference only represents a fraction of all haplotypes is still an important limiting factor.

Plant plastids and mitochondria have dynamic proteomes. Protein homeostasis in these organelles is maintained by a proteostasis network containing protein chaperones, peptidases, and their substrate recognition factors. However, many peptidases, as well as their functional connections and substrates, are poorly characterized. This review provides a systematic insight into the organellar peptidase network in Arabidopsis thaliana. We present a compendium of known and putative Arabidopsis peptidases and inhibitors, and compare the distribution of plastid and mitochondrial peptidases to the total peptidase complement. This comparison shows striking biases, such as the (near) absence of cysteine and aspartic peptidases and peptidase inhibitors, whereas other peptidase families were exclusively organellar; reasons for such biases are discussed. A genome-wide mRNA-based coexpression data set was generated based on quality controlled and normalized public data, and used to infer additional plastid peptidases and to generate a coexpression network for 97 organellar peptidase baits (1742 genes, making 2544 edges). The graphical network includes 10 modules with specialized/enriched functions, such as mitochondrial protein maturation, thermotolerance, senescence, or enriched subcellular locations such as the thylakoid lumen or chloroplast envelope. The peptidase compendium, including the autophagy and proteosomal systems, and the annotation based on the MEROPS nomenclature of peptidase clans and families, is incorporated into the Plant Proteome Database.

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate elucidation of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here, we report the assembly and annotation of maize, a genetic and agricultural model species, using Single Molecule Real-Time (SMRT) sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and significant improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed over 130,000 intact transposable elements (TEs), allowing us to identify TE lineage expansions unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by SMRT sequencing. In addition, comparative optical mapping of two other inbreds revealed a prevalence of deletions in the low gene density region and maize lineage-specific genes.

Now in its 10th year, the Gramene database (http://www.gramene.org) has grown from its primary focus on rice, the first fully-sequenced grass genome, to become a resource for major model and crop plants including Arabidopsis, Brachypodium, maize, sorghum, poplar and grape in addition to several species of rice. Gramene began with the addition of an Ensembl genome browser and has expanded in the last decade to become a robust resource for plant genomics hosting a wide array of data sets including quantitative trait loci (QTL), metabolic pathways, genetic diversity, genes, proteins, germplasm, literature, ontologies and a fully-structured markers and sequences database integrated with genome browsers and maps from various published studies (genetic, physical, bin, etc.). In addition, Gramene now hosts a variety of web services including a Distributed Annotation Server (DAS), BLAST and a public MySQL database. Twice a year, Gramene releases a major build of the database and makes interim releases to correct errors or to make important updates to software and/or data.

Repetitive sequences, primarily transposable elements form an indispensable part of eukaryotic genomes. However, little is known about how these sequences originate, evolve and function in context of a genome. In an attempt to address this question, we performed a comparative analysis of repetitive DNA sequences in the genus Oryza, representing ~15 million years of evolution. Both Class I and Class II transposable elements, through their expansion, loss and movement in the genome, were found to influence genome size variation in this genus. We identified 38 LTRretrotransposon families that are present in 1,500 or more copies throughout Oryza, and many are preferentially amplified in specific lineages. The data presented here, besides furthering our understanding of genome organization in the genus Oryza, will aid in the assembly, annotation and analysis of genomic data, as part of the future genome sequencing projects of O. sativa wild relatives.

The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement.

Gramene (www.gramene.org) is a curated resource for genetic, genomic and comparative genomics data for the major crop species, including rice, maize, wheat and many other plant (mainly grass) species. Gramene is an open-source project. All data and software are freely downloadable through the ftp site (ftp.gramene.org/pub/gramene) and available for use without restriction. Gramene's core data types include genome assembly and annotations, other DNA/mRNA sequences, genetic and physical maps/markers, genes, quantitative trait loci (QTLs), proteins, ontologies, literature and comparative mappings. Since our last NAR publication 2 years ago, we have updated these data types to include new datasets and new connections among them. Completely new features include rice pathways for functional annotation of rice genes; genetic diversity data from rice, maize and wheat to show genetic variations among different germplasms; large-scale genome comparisons among Oryza sativa and its wild relatives for evolutionary studies; and the creation of orthologous gene sets and phylogenetic trees among rice, Arabidopsis thaliana, maize, poplar and several animal species (for reference purpose). We have significantly improved the web interface in order to provide a more user-friendly browsing experience, including a dropdown navigation menu system, unified web page for markers, genes, QTLs and proteins, and enhanced quick search functions.

The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here we present a protein-DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.

The Plant Ontology Consortium (POC) (www.plantontology.org) is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. A primary goal of the POC is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures and developmental stages. These provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across datasets within a database or between multiple databases. The current version of the ontology integrates diverse vocabularies used to describeArabidopsis, maize and rice (Oryzasp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) forArabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved.

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the ?pan-genome? of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Summary:CMap is a web-based tool for displaying and comparing maps of any type and from any species. A user can compare an unlimited number of maps, view pair-wise comparisons of known correspondences, and search for maps or for features by name, species, type and accession. CMap is freely available, can run on a variety of database engines and uses only free and open software components. Availability: http://www.gmod.org/cmap Contact: kclark@cshl.edu

Panzea (http://www.panzea.org), the public web site of the project 'Molecular and Functional Diversity in the Maize Genome', has expanded over the past two years in data content, display tools and informational sections. The most significant data content expansions occurred for the single nucleotide polymorphism (SNP), sequencing, isozyme and phenotypic data types. We have enhanced our existing web display tools and have launched a number of new tools for data display and analysis. For example, we have implemented one that allows users to find polymorphisms between two accessions, a geographic map tool to visualize the geographic distribution of SNPs, simple sequence repeats (SSRs) and isozyme alleles and a graphical view of the placement of Panzea markers and genes/loci on genetic and physical maps. One goal of the informatics component of our project has been to generate code that can be used by other groups. We have enhanced our existing code base and have made our new tools available. Finally, we have also made available new informational sections as part of our educational and outreach efforts.

Background Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. Results RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. Conclusions Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway/.

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant’s platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses., This Community Page highlights the iPlant Collaborative, which provides scalable and extensible data management and computational resources for life science research, including learning materials and support to readily integrate these resources with existing workflows.

Background Higher plants exhibit remarkable phenotypic plasticity allowing them to adapt to an extensive range of environmental conditions. Sorghum is a cereal crop that exhibits exceptional tolerance to adverse conditions, in particular, water-limiting environments. This study utilized next generation sequencing (NGS) technology to examine the transcriptome of sorghum plants challenged with osmotic stress and exogenous abscisic acid (ABA) in order to elucidate genes and gene networks that contribute to sorghum's tolerance to water-limiting environments with a long-term aim of developing strategies to improve plant productivity under drought. Results RNA-Seq results revealed transcriptional activity of 28,335 unique genes from sorghum root and shoot tissues subjected to polyethylene glycol (PEG)-induced osmotic stress or exogenous ABA. Differential gene expression analyses in response to osmotic stress and ABA revealed a strong interplay among various metabolic pathways including abscisic acid and 13-lipoxygenase, salicylic acid, jasmonic acid, and plant defense pathways. Transcription factor analysis indicated that groups of genes may be co-regulated by similar regulatory sequences to which the expressed transcription factors bind. We successfully exploited the data presented here in conjunction with published transcriptome analyses for rice, maize, and Arabidopsis to discover more than 50 differentially expressed, drought-responsive gene orthologs for which no function had been previously ascribed. Conclusions The present study provides an initial assemblage of sorghum genes and gene networks regulated by osmotic stress and hormonal treatment. We are providing an RNA-Seq data set and an initial collection of transcription factors, which offer a preliminary look into the cascade of global gene expression patterns that arise in a drought tolerant crop subjected to abiotic stress. These resources will allow scientists to query gene expression and functional annotation in response to drought.

International audience; Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the plant Arabidopsis thaliana containing about 6200 highly reliable interactions between about 2700 proteins. A global organization of plant biological processes emerges from community analyses of the resulting network, together with large numbers of novel hypothetical functional links between proteins and pathways. We observe a dynamic rewiring of interactions following gene duplication events, providing evidence for a model of evolution acting upon interactome networks. This and future plant interactome maps should facilitate systems approaches to better understand plant biology and improve crops.

Background Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of data between information resources difficult and labor intensive. A recently described semantic web protocol, the Simple Semantic Web Architecture and Protocol (SSWAP; pronounced "swap") offers the ability to describe data and services in a semantically meaningful way. We report how three major information resources (Gramene, SoyBase and the Legume Information System [LIS]) used SSWAP to semantically describe selected data and web services. Methods We selected high-priority Quantitative Trait Locus (QTL), genomic mapping, trait, phenotypic, and sequence data and associated services such as BLAST for publication, data retrieval, and service invocation via semantic web services. Data and services were mapped to concepts and categories as implemented in legacy and de novo community ontologies. We used SSWAP to express these offerings in OWL Web Ontology Language (OWL), Resource Description Framework (RDF) and eXtensible Markup Language (XML) documents, which are appropriate for their semantic discovery and retrieval. We implemented SSWAP services to respond to web queries and return data. These services are registered with the SSWAP Discovery Server and are available for semantic discovery at http://sswap.info. Results A total of ten services delivering QTL information from Gramene were created. From SoyBase, we created six services delivering information about soybean QTLs, and seven services delivering genetic locus information. For LIS we constructed three services, two of which allow the retrieval of DNA and RNA FASTA sequences with the third service providing nucleic acid sequence comparison capability (BLAST). Conclusions The need for semantic integration technologies has preceded available solutions. We report the feasibility of mapping high priority data from local, independent, idiosyncratic data schemas to common shared concepts as implemented in web-accessible ontologies. These mappings are then amenable for use in semantic web services. Our implementation of approximately two dozen services means that biological data at three large information resources (Gramene, SoyBase, and LIS) is available for programmatic access, semantic searching, and enhanced interaction between the separate missions of these resources.

A-Maize-ing Maize is one of our oldest and most important crops, having been domesticated approximately 9000 years ago in central Mexico. Schnable et al. (p. 1112 ; see the cover) present the results of sequencing the B73 inbred maize line. The findings elucidate how maize became diploid after an ancestral doubling of its chromosomes and reveals transposable element movement and activity and recombination. Vielle-Calzada et al. (p. 1078 ) have sequenced the Palomero Toluqueño ( Palomero ) landrace, a highland popcorn from Mexico, which, when compared to the B73 line, reveals multiple loci impacted by domestication. Swanson-Wagner et al. (p. 1118 ) exploit possession of the genome to analyze expression differences occurring between lines. The identification of single nucleotide polymorphisms and copy number variations among lines was used by Gore et al. (p. 1115 ) to generate a Haplotype map of maize. While chromosomal diversity in maize is high, it is likely that recombination is the major force affecting the levels of heterozygosity in maize. The availability of the maize genome will help to guide future agricultural and biofuel applications (see the Perspective by Feuillet and Eversole ).

MicroRNAs (miRNAs) are small, non-coding RNAs that play essential roles in plant growth, development, and stress response. We conducted a genome-wide survey of maize miRNA genes, characterizing their structure, expression, and evolution. Computational approaches based on homology and secondary structure modeling identified 150 high-confidence genes within 26 miRNA families. For 25 families, expression was verified by deep-sequencing of small RNA libraries that were prepared from an assortment of maize tissues. PCR–RACE amplification of 68 miRNA transcript precursors, representing 18 families conserved across several plant species, showed that splice variation and the use of alternative transcriptional start and stop sites is common within this class of genes. Comparison of sequence variation data from diverse maize inbred lines versus teosinte accessions suggest that the mature miRNAs are under strong purifying selection while the flanking sequences evolve equivalently to other genes. Since maize is derived from an ancient tetraploid, the effect of whole-genome duplication on miRNA evolution was examined. We found that, like protein-coding genes, duplicated miRNA genes underwent extensive gene-loss, with ∼35% of ancestral sites retained as duplicate homoeologous miRNA genes. This number is higher than that observed with protein-coding genes. A search for putative miRNA targets indicated bias towards genes in regulatory and metabolic pathways. As maize is one of the principal models for plant growth and development, this study will serve as a foundation for future research into the functional roles of miRNA genes., Author Summary MicroRNAs are non-coding RNAs that regulate gene expression post-transcriptionally and play roles in diverse pathways including those acting on development and responses to stress. Here, we describe a genome-wide computational prediction of maize miRNA genes and their characterization with respect to expression, putative targets, evolution following whole genome duplication, and allelic diversity. The structures of unprocessed primary miRNA transcripts were determined by 5′ RACE and 3′ RACE. Expression profiles were surveyed in five tissue types by deep-sequencing of small RNA libraries. We predicted miRNA targets computationally based on the most recent maize protein annotations. Analysis of the predicted functions of target genes, on the basis of gene ontology, supported their roles in regulatory processes. We identified putative orthologs in Sorghum based on an analysis of synteny and found that maize-homoeologous miRNA genes were retained more frequently than expected. We also explored miRNA nucleotide diversity among many maize inbred lines and partially inbred teosinte lines. The results indicated that mature miRNA genes were highly conserved during their evolution. This preliminary characterization based on our findings provides a framework for future analysis of miRNA genes and their roles in key traits of maize as feed, fodder, and biofuel.

Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on ∼1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses., Author Summary Maize is a major cereal crop and key experimental system for eukaryotic biology. Previous investigations of the maize genome at the sequence level have primarily focused on analyses of genome survey sequences and BAC contigs. Here we used a comprehensive set of resources to construct an ordered and oriented 22-Mb sequence from chromosome 4 that represents 1% of the maize genome. Genome annotation revealed the presence of 544 genes that are interspersed with transposable elements (TEs), which occupy 83.8% of the sequence. Fifty-one genes were involved in 14 tandem gene clusters and most appear to have arisen after lineage divergence. TEs, especially helitrons, were found to contain gene fragments and were widely distributed in gene-rich regions. Large inversions and unequal gene deletion between the two homoeologous maize regions were the main contributors to synteny disruption among maize, sorghum, and rice. We also show that small RNAs are primarily associated with TEs across the region. Comparison of this ordered and oriented sequence with the corresponding uncurated region in the whole genome sequence of maize resulted in improvements in TE annotation that will ultimately enhance detection sensitivity and characterization of TEs. Doing so is likely to improve the specificity of gene annotations.

About 85% of the maize genome consists of highly repetitive sequences that are interspersed by low-copy, gene-coding sequences. The maize community has dealt with this genomic complexity by the construction of an integrated genetic and physical map (iMap), but this resource alone was not sufficient for ensuring the quality of the current sequence build. For this purpose, we constructed a genome-wide, high-resolution optical map of the maize inbred line B73 genome containing >91,000 restriction sites (averaging 1 site/∼23 kb) accrued from mapping genomic DNA molecules. Our optical map comprises 66 contigs, averaging 31.88 Mb in size and spanning 91.5% (2,103.93 Mb/∼2,300 Mb) of the maize genome. A new algorithm was created that considered both optical map and unfinished BAC sequence data for placing 60/66 (2,032.42 Mb) optical map contigs onto the maize iMap. The alignment of optical maps against numerous data sources yielded comprehensive results that proved revealing and productive. For example, gaps were uncovered and characterized within the iMap, the FPC (fingerprinted contigs) map, and the chromosome-wide pseudomolecules. Such alignments also suggested amended placements of FPC contigs on the maize genetic map and proactively guided the assembly of chromosome-wide pseudomolecules, especially within complex genomic regions. Lastly, we think that the full integration of B73 optical maps with the maize iMap would greatly facilitate maize sequence finishing efforts that would make it a valuable reference for comparative studies among cereals, or other maize inbred lines and cultivars., Author Summary The maize genome contains abundant repeats interspersed by low-copy, gene-coding sequences that make it a challenge to sequence; consequently, current BAC sequence assemblies average 11 contigs per clone. The iMap deals with such complexity by the judicious integration of IBM genetic and B73 physical maps, but the B73 genome structure could differ from the IBM population because of genetic recombination and subsequent rearrangements. Accordingly, we report a genome-wide, high-resolution optical map of maize B73 genome that was constructed from the direct analysis of genomic DNA molecules without using genetic markers. The integration of optical and iMap resources with comparisons to FPC maps enabled a uniquely comprehensive and scalable assessment of a given BAC's sequence assembly, its placement within a FPC contig, and the location of this FPC contig within a chromosome-wide pseudomolecule. As such, the overall utility of the maize optical map for the validation of sequence assemblies has been significant and demonstrates the inherent advantages of single molecule platforms. Construction of the maize optical map represents the first physical map of a eukaryotic genome larger than 400 Mb that was created de novo from individual genomic DNA molecules.

Maize is a major cereal crop and an important model system for basic biological research. Knowledge gained from maize research can also be used to genetically improve its grass relatives such as sorghum, wheat, and rice. The primary objective of the Maize Genome Sequencing Consortium (MGSC) was to generate a reference genome sequence that was integrated with both the physical and genetic maps. Using a previously published integrated genetic and physical map, combined with in-coming maize genomic sequence, new sequence-based genetic markers, and an optical map, we dynamically picked a minimum tiling path (MTP) of 16,910 bacterial artificial chromosome (BAC) and fosmid clones that were used by the MGSC to sequence the maize genome. The final MTP resulted in a significantly improved physical map that reduced the number of contigs from 721 to 435, incorporated a total of 8,315 mapped markers, and ordered and oriented the majority of FPC contigs. The new integrated physical and genetic map covered 2,120 Mb (93%) of the 2,300-Mb genome, of which 405 contigs were anchored to the genetic map, totaling 2,103.4 Mb (99.2% of the 2,120 Mb physical map). More importantly, 336 contigs, comprising 94.0% of the physical map (∼1,993 Mb), were ordered and oriented. Finally we used all available physical, sequence, genetic, and optical data to generate a golden path (AGP) of chromosome-based pseudomolecules, herein referred to as the B73 Reference Genome Sequence version 1 (B73 RefGen_v1)., Author Summary Maize has been a cultural icon and staple food crop of Americans since the discovery of the new world in 1492. Contemporary society is now faced with growing demands for food and fuel in the face of global climate change and the potential for increased disease pressure. To provide a comprehensive foundation to systematically understand maize biology with the goal of breeding higher yielding, disease-resistant, and drought-tolerant cultivars, our consortium sequenced the B73 genome of maize. In this study, we used a comprehensive physical and genetic framework map to develop a minimum tiling path (MTP) of over 16,000 BAC clones across the genome. The MTP was generated dynamically and integrated numerous data types, such as in-coming genome sequence, over 8,000 sequence-based genetic markers, and the maize optical map. This allowed us to genetically anchor, order, and orient the majority of the maize physical map and genome sequence to the genetic map. Post-genome sequencing, we constructed a golden path (AGP) of sequence-based pseudomolecules representing the ten chromosomes of the maize B73 genome (B73 RefGen_v1). This unprecedented integration of genetic, physical, and genomic sequence into one framework will greatly facilitate all aspects of plant biological research.

The shoot apical meristem (SAM) maintains a pool of indeterminate cells within the SAM proper, while lateral organs are initiated from the SAM periphery. Laser microdissection–microarray technology was used to compare transcriptional profiles within these SAM domains to identify novel maize genes that function during leaf development. Nine hundred and sixty-two differentially expressed maize genes were detected; control genes known to be upregulated in the initiating leaf (P0/P1) or in the SAM proper verified the precision of the microdissections. Genes involved in cell division/growth, cell wall biosynthesis, chromatin remodeling, RNA binding, and translation are especially upregulated in initiating leaves, whereas genes functioning during protein fate and DNA repair are more abundant in the SAM proper. In situ hybridization analyses confirmed the expression patterns of six previously uncharacterized maize genes upregulated in the P0/P1. P0/P1-upregulated genes that were also shown to be downregulated in leaf-arrested shoots treated with an auxin transport inhibitor are especially implicated to function during early events in maize leaf initiation. Reverse genetic analyses of asceapen1 (asc1), a maize D4-cyclin gene upregulated in the P0/P1, revealed novel leaf phenotypes, less genetic redundancy, and expanded D4-CYCLIN function during maize shoot development as compared to Arabidopsis. These analyses generated a unique SAM domain-specific database that provides new insight into SAM function and a useful platform for reverse genetic analyses of shoot development in maize., Author Summary All the organs of plant shoots are derived from the shoot apical meristem (SAM), a pool of plant stem cells that are both organogenic and self-sustaining. These dual SAM functions take place in distinct yet adjacent meristematic domains; leaves are derived from the peripheral zone (PZ) of the SAM whereas cells lost during organogenesis are replenished from the central zone (CZ). Deciphering the global patterns of differential gene expression within these discrete SAM functional domains is integral toward understanding the molecular-signaling networks that regulate plant development. We utilized laser-microdissection technology to isolate tissues from the SAM crown and center (SAM-proper) and from initiating leaves (P0/P1) at the SAM periphery for use in microarray comparisons of gene expression within these SAM functional domains. Nine hundred and sixty-two maize genes were differentially expressed, confirming that the distinct functions of these meristematic domains involve widespread differences in gene expression. Genes involved in cell division, cell wall biosynthesis, chromatin structure, and RNA binding are especially upregulated in initiating leaves, whereas genes regulating protein stability and DNA repair are upregulated in the SAM proper. Mutations in a D-cyclin gene that was upregulated in the P0/P1 render narrow-leafed mutant plants with defective stomatal patterning, providing functional genetic data for a previously uncharacterized maize gene.

Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene–phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research.

Background Barley has one of the largest and most complex genomes of all economically important food crops. The rise of new short read sequencing technologies such as Illumina/Solexa permits such large genomes to be effectively sampled at relatively low cost. Based on the corresponding sequence reads a Mathematically Defined Repeat (MDR) index can be generated to map repetitive regions in genomic sequences. Results We have generated 574 Mbp of Illumina/Solexa sequences from barley total genomic DNA, representing about 10% of a genome equivalent. From these sequences we generated an MDR index which was then used to identify and mark repetitive regions in the barley genome. Comparison of the MDR plots with expert repeat annotation drawing on the information already available for known repetitive elements revealed a significant correspondence between the two methods. MDR-based annotation allowed for the identification of dozens of novel repeat sequences, though, which were not recognised by hand-annotation. The MDR data was also used to identify gene-containing regions by masking of repetitive sequences in eight de-novo sequenced bacterial artificial chromosome (BAC) clones. For half of the identified candidate gene islands indeed gene sequences could be identified. MDR data were only of limited use, when mapped on genomic sequences from the closely related species Triticum monococcum as only a fraction of the repetitive sequences was recognised. Conclusion An MDR index for barley, which was obtained by whole-genome Illumina/Solexa sequencing, proved as efficient in repeat identification as manual expert annotation. Circumventing the labour-intensive step of producing a specific repeat library for expert annotation, an MDR index provides an elegant and efficient resource for the identification of repetitive and low-copy (i.e. potentially gene-containing sequences) regions in uncharacterised genomic sequences. The restriction that a particular MDR index can not be used across species is outweighed by the low costs of Illumina/Solexa sequencing which makes any chosen genome accessible for whole-genome sequence sampling.

Background The challenges of accurate gene prediction and enumeration are further aggravated in large genomes that contain highly repetitive transposable elements (TEs). Yet TEs play a substantial role in genome evolution and are themselves an important subject of study. Repeat annotation, based on counting occurrences of k-mers, has been previously used to distinguish TEs from low-copy genic regions; but currently available software solutions are impractical due to high memory requirements or specialization for specific user-tasks. Results Here we introduce the Tallymer software, a flexible and memory-efficient collection of programs for k-mer counting and indexing of large sequence sets. Unlike previous methods, Tallymer is based on enhanced suffix arrays. This gives a much larger flexibility concerning the choice of the k-mer size. Tallymer can process large data sizes of several billion bases. We used it in a variety of applications to study the genomes of maize and other plant species. In particular, Tallymer was used to index a set of whole genome shotgun sequences from maize (B73) (total size 109 bp.). We analyzed k-mer frequencies for a wide range of k. At this low genome coverage (≈ 0.45×) highly repetitive 20-mers constituted 44% of the genome but represented only 1% of all possible k-mers. Similar low-complexity was seen in the repeat fractions of sorghum and rice. When applying our method to other maize data sets, High-C 0 t derived sequences showed the greatest enrichment for low-copy sequences. Among annotated TEs, the most highly repetitive were of the Ty3/gypsy class of retrotransposons, followed by the Ty1/copia class, and DNA transposons. Among expressed sequence tags (EST), a notable fraction contained high-copy k-mers, suggesting that transposons are still active in maize. Retrotransposons in Mo17 and McC cultivars were readily detected using the B73 20-mer frequency index, indicating their conservation despite extensive rearrangement across cultivars. Among one hundred annotated bacterial artificial chromosomes (BACs), k-mer frequency could be used to detect transposon-encoded genes with 92% sensitivity, compared to 96% using alignment-based repeat masking, while both methods showed 92% specificity. Conclusion The Tallymer software was effective in a variety of applications to aid genome annotation in maize, despite limitations imposed by the relatively low coverage of sequence available. For more information on the software, see http://www.zbh.uni-hamburg.de/Tallymer.

To date, variation in nectar chemistry of flowering plants has not been studied in detail. Such variation exerts considerable influence on pollinator-plant interactions, as well as on flower traits that play important roles in the selection of a plant for visitation by specific pollinators. Over the past 60 years the Aquilegia genus has been used as a key model for speciation studies. In this study, we defined the metabolomic profiles of flower samples of two Aquilegia species, A. Canadensis and A. pubescens. We identified a total of 75 metabolites that were classified into six main categories: organic acids, fatty acids, amino acids, esters, sugars, and unknowns. The mean abundances of 25 of these metabolites were significantly different between the two species, providing insights into interspecies variation in floral chemistry. Using the PlantSEED biochemistry database, we found that the majority of these metabolites are involved in biosynthetic pathways. Finally, we explored the annotated genome of A. coerulea, using the PlantSEED pipeline and reconstructed the metabolic network of Aquilegia. This network, which contains the metabolic pathways involved in generating the observed chemical variation, is now publicly available from the DOE Systems Biology Knowledge Base (KBase; http://kbase.us).

Gramene is a well-established resource for plant comparative genome analysis. Data are generated through automated and curated analyses and made available through web interfaces such as GrameneMart. The Gramene project was an early adopter of the BioMart software, which remains an integral and well-used component of the Gramene website. BioMart accessible data sets include plant gene annotations, plant variation catalogues, genetic markers, physical mapping entities, public DNA/mRNA sequences of various types and curated quantitative trait loci for various species. DATABASE URL: http://www.gramene.org/biomart/martview.

Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one-hybrid (Y1H) and two-hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue-specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered.