GrameneMart: the BioMart data portal for the Gramene project

Using knowledge graphs to infer gene expression in plants

Introduction

Climate change is already affecting ecosystems around the world and forcing us to adapt to meet societal needs. The speed with which climate change is progressing necessitates a massive scaling up of the number of species with understood genotype-environment-phenotype (G×E×P) dynamics in order to increase ecosystem and agriculture resilience. An important part of predicting phenotype is understanding the complex gene regulatory networks present in organisms. Previous work has demonstrated that knowledge about one species can be applied to another using ontologically-supported knowledge bases that exploit homologous structures and homologous genes. These types of structures that can apply knowledge about one species to another have the potential to enable the massive scaling up that is needed through in silico experimentation.

Methods

We developed one such structure, a knowledge graph (KG) using information from Planteome and the EMBL-EBI Expression Atlas that connects gene expression, molecular interactions, functions, and pathways to homology-based gene annotations. Our preliminary analysis uses data from gene expression studies in Arabidopsis thaliana and Populus trichocarpa plants exposed to drought conditions.

Results

A graph query identified 16 pairs of homologous genes in these two taxa, some of which show opposite patterns of gene expression in response to drought. As expected, analysis of the upstream cis-regulatory region of these genes revealed that homologs with similar expression behavior had conserved cis-regulatory regions and potential interaction with similar trans-elements, unlike homologs that changed their expression in opposite ways.

Discussion

This suggests that even though the homologous pairs share common ancestry and functional roles, predicting expression and phenotype through homology inference needs careful consideration of integrating cis and trans-regulatory components in the curated and inferred knowledge graph.

Gene Ontology Meta Annotator for Plants (GOMAP)

Annotating gene structures and functions to genome assemblies is necessary to make assembly resources useful for biological inference. Gene Ontology (GO) term assignment is the most used functional annotation system, and new methods for GO assignment have improved the quality of GO-based function predictions. The Gene Ontology Meta Annotator for Plants (GOMAP) is an optimized, high-throughput, and reproducible pipeline for genome-scale GO annotation of plants. We containerized GOMAP to increase portability and reproducibility and also optimized its performance for HPC environments. Here we report on the pipeline's availability and performance for annotating large, repetitive plant genomes and describe how GOMAP was used to annotate multiple maize genomes as a test case. Assessment shows that GOMAP expands and improves the number of genes annotated and annotations assigned per gene as well as the quality (based on [Formula: see text]) of GO assignments in maize. GOMAP has been deployed to annotate other species including wheat, rice, barley, cotton, and soy. Instructions and access to the GOMAP Singularity container are freely available online at https://bioinformapping.com/gomap/ . A list of annotated genomes and links to data is maintained at https://dill-picl.org/projects/gomap/ .

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.

The Medicago truncatula Genome: Genomic Data Availability

Medicago truncatula emerged in 1990 as a model for legumes, comprising the third largest land plant family. Most legumes form symbiotic nitrogen-fixing root nodules with compatible soil bacteria and thus are important contributors to the global nitrogen cycle and sustainable agriculture. Legumes and legume products are important sources for human and animal protein as well as for edible and industrial oils. In the years since M. truncatula was chosen as a legume model, many genetic, genomic, and molecular resources have become available, including reference quality genome sequences for two widely used genotypes. Accessibility of genomic data is important for many different types of studies with M. truncatula as well as for research involving crop and forage legumes. In this chapter, we discuss strategies to obtain archived M. truncatula genomic data originally deposited into custom databases that are no longer maintained but are now accessible in general databases. We also review key current genomic databases that are specific to M. truncatula as well as those that contain M. truncatula data in addition to data from other plants.

Comprehensive survey and evolutionary analysis of genome-wide miRNA genes from ten diploid Oryza species

BACKGROUND

MicroRNAs (miRNAs) are non-coding RNAs that play versatile roles in post-transcriptional gene regulation. Although much is known about their biogenesis, and gene regulation very little is known about their evolutionary relation among the closely related species.

RESULT

All the orthologous miRNA genes of Oryza sativa (japonica) from 10 different Oryza species were identified, and the evolutionary changes among these genes were analysed. Significant differences in the expansion of miRNA gene families were observed across the Oryza species. Analysis of the nucleotide substitution rates indicated that the mature sequences show the least substitution rates among the different regions of miRNA genes, and also show a very much less substitution rates as compared to that of all protein-coding genes across the Oryza species. Evolution of miRNA genes was also found to be contributed by transposons. A non-neutral selection was observed at 80 different miRNA loci across Oryza species which were estimated to have lost ~87% of the sequence diversity during the domestication. The phylogenetic analysis revealed that O. longistaminata diverged first among the AA-genomes, whereas O. brachyantha and O. punctata appeared as the eminent out-groups. The miR1861 family organised into nine distinct compact clusters in the studied Oryza species except O. brachyantha. Further, the expression analysis showed that 11 salt-responsive miRNAs were differentially regulated between O. coarctata and O. glaberrima.

CONCLUSION

Our study provides the evolutionary dynamics in the miRNA genes of 10 different Oryza species which will support more investigations about the structural and functional organization of miRNA genes of Oryza species.

Gramene Database: Navigating Plant Comparative Genomics Resources

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.

From FHB Resistance QTLs to Candidate Genes Identification in Triticum aestivum L

Fusarium head blight (FHB) caused by Fusarium graminearum is a worldwide destructive disease affecting cereals such as wheat. FHB resistance is a quantitative trait, and information for FHB resistance QTLs in wheat is available. However, little is known about genes underlying the FHB resistance QTL regions. Using a computational approach in this study, we have mined eight FHB resistance QTLs in wheat and predicted the candidate genes falling within these QTL intervals based on the available sequences and markers. A total of 18 genomic scaffolds located at chromosomes 2AL, 2DL, 3B and 4BS were prioritized to harbor FHB-resistant candidate genes. These genes are mainly involved in plant defense response, immune regulation and cellular detoxification. We believe that our results constitute a starting point for further validation to improve FHB-resistant bread wheat varieties.

Gramene: A Resource for Comparative Analysis of Plants Genomes and Pathways

Gramene is an integrated informatics resource for accessing, visualizing, and comparing plant genomes and biological pathways. Originally targeting grasses, Gramene has grown to host annotations for economically important and research model crops, including wheat, potato, tomato, banana, grape, poplar, and Chlamydomonas. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. This chapter outlines system requirements for end users and database hosting, data types and basic navigation within Gramene, and provides examples of how to (1) view a phylogenetic tree for a family of transcription factors, (2) explore genetic variation in the orthologues of a gene with a known trait association, and (3) upload, visualize, and privately share end user data into a new genome browser track.Moreover, this is the first publication describing Gramene's new web interface-intended to provide a simplified portal to the most complete and up-to-date set of plant genome and pathway annotations.

Gramene 2016: comparative plant genomics and pathway resources

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to ∼ 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials.

The BioMart community portal: an innovative alternative to large, centralized data repositories

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

FASCIATED EAR4 encodes a bZIP transcription factor that regulates shoot meristem size in maize

Plant architecture is dictated by precise control of meristematic activity. In the shoot, an imbalance in positive or negative maintenance signals can result in a fasciated or enlarged meristem phenotype. fasciated ear4 (fea4) is a semidwarfed mutant with fasciated ears and tassels as well as greatly enlarged vegetative and inflorescence meristems. We identified FEA4 as a bZIP transcription factor, orthologous to Arabidopsis thaliana PERIANTHIA. FEA4 was expressed in the peripheral zone of the vegetative shoot apical meristem and in the vasculature of immature leaves and conspicuously excluded from the stem cell niche at the tip of the shoot apical meristem and from incipient leaf primordia. Following the transition to reproductive fate, FEA4 was expressed throughout the entire inflorescence and floral meristems. Native expression of a functional YFP:FEA4 fusion recapitulated this pattern of expression. We used chromatin immunoprecipitation-sequencing to identify 4060 genes proximal to FEA4 binding sites, including ones that were potentially bound and modulated by FEA4 based on transcriptional changes in fea4 mutant ears. Our results suggest that FEA4 promotes differentiation in the meristem periphery by regulating auxin-based responses and genes associated with leaf differentiation and polarity, potentially in opposition to factors such as KNOTTED1 and WUSCHEL.

MOROKOSHI: transcriptome database in Sorghum bicolor

In transcriptome analysis, accurate annotation of each transcriptional unit and its expression profile is essential. A full-length cDNA (FL-cDNA) collection facilitates the refinement of transcriptional annotation, and accurate transcription start sites help to unravel transcriptional regulation. We constructed a normalized FL-cDNA library from eight growth stages of aerial tissues in Sorghum bicolor and isolated 37,607 clones. These clones were Sanger sequenced from the 5' and/or 3' ends and in total 38,981 high-quality expressed sequence tags (ESTs) were obtained. About one-third of the transcripts of known genes were captured as FL-cDNA clone resources. In addition to these, we also annotated 272 novel genes, 323 antisense transcripts and 1,672 candidate isoforms. These clones are available from the RIKEN Bioresource Center. After obtaining accurate annotation of transcriptional units, we performed expression profile analysis. We carried out spikelet-, seed- and stem-specific RNA sequencing (RNA-Seq) analysis and confirmed the expression of 70.6% of the newly identified genes. We also downloaded 23 sorghum RNA-Seq samples that are publicly available and these are shown on a genome browser together with our original FL-cDNA and RNA-Seq data. Using our original and publicly available data, we made an expression profile of each gene and identified the top 20 genes with the most similar expression. In addition, we visualized their relationships in gene co-expression networks. Users can access and compare various transcriptome data from S, bicolor at http://sorghum.riken.jp.

POEAS: Automated Plant Phenomic Analysis Using Plant Ontology

Biological enrichment analysis using gene ontology (GO) provides a global overview of the functional role of genes or proteins identified from large-scale genomic or proteomic experiments. Phenomic enrichment analysis of gene lists can provide an important layer of information as well as cellular components, molecular functions, and biological processes associated with gene lists. Plant phenomic enrichment analysis will be useful for performing new experiments to better understand plant systems and for the interpretation of gene or proteins identified from high-throughput experiments. Plant ontology (PO) is a compendium of terms to define the diverse phenotypic characteristics of plant species, including plant anatomy, morphology, and development stages. Adoption of this highly useful ontology is limited, when compared to GO, because of the lack of user-friendly tools that enable the use of PO for statistical enrichment analysis. To address this challenge, we introduce Plant Ontology Enrichment Analysis Server (POEAS) in the public domain. POEAS uses a simple list of genes as input data and performs enrichment analysis using Ontologizer 2.0 to provide results in two levels, enrichment results and visualization utilities, to generate ontological graphs that are of publication quality. POEAS also offers interactive options to identify user-defined background population sets, various multiple-testing correction methods, different enrichment calculation methods, and resampling tests to improve statistical significance. The availability of such a tool to perform phenomic enrichment analyses using plant genes as a complementary resource will permit the adoption of PO-based phenomic analysis as part of analytical workflows. POEAS can be accessed using the URL http://caps.ncbs.res.in/poeas.

The bimodal distribution of genic GC content is ancestral to monocot species

In grasses such as rice or maize, the distribution of genic GC content is well known to be bimodal. It is mainly driven by GC content at third codon positions (GC3 for short). This feature is thought to be specific to grasses as closely related species like banana have a unimodal GC3 distribution. GC3 is associated with numerous genomics features and uncovering the origin of this peculiar distribution will help understanding the potential roles and consequences of GC3 variations within and between genomes. Until recently, the origin of the peculiar GC3 distribution in grasses has remained unknown. Thanks to the recent publication of several complete genomes and transcriptomes of nongrass monocots, we studied more than 1,000 groups of one-to-one orthologous genes in seven grasses and three outgroup species (banana, palm tree, and yam). Using a maximum likelihood-based method, we reconstructed GC3 at several ancestral nodes. We found that the bimodal GC3 distribution observed in extant grasses is ancestral to both grasses and most monocot species, and that other species studied here have lost this peculiar structure. We also found that GC3 in grass lineages is globally evolving very slowly and that the decreasing GC3 gradient observed from 5′ to 3′ along coding sequences is also conserved and ancestral to monocots. This result strongly challenges the previous views on the specificity of grass genomes and we discuss its implications for the possible causes of the evolution of GC content in monocots.

Gramene 2013: comparative plant genomics resources

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

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the computational prediction of CPEs across eight plant genomes to help better understand the transcription initiation complex assembly. The distribution of thirteen known CPEs across four monocots (Brachypodium distachyon, Oryza sativa ssp. japonica, Sorghum bicolor, Zea mays) and four dicots (Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera, Glycine max) reveals the structural organization of the core promoter in relation to the TATA-box as well as with respect to other CPEs. The distribution of known CPE motifs with respect to transcription start site (TSS) exhibited positional conservation within monocots and dicots with slight differences across all eight genomes. Further, a more refined subset of annotated genes based on orthologs of the model monocot (O. sativa ssp. japonica) and dicot (A. thaliana) genomes supported the positional distribution of these thirteen known CPEs. DNA free energy profiles provided evidence that the structural properties of promoter regions are distinctly different from that of the non-regulatory genome sequence. It also showed that monocot core promoters have lower DNA free energy than dicot core promoters. The comparison of monocot and dicot promoter sequences highlights both the similarities and differences in the core promoter architecture irrespective of the species-specific nucleotide bias. This study will be useful for future work related to genome annotation projects and can inspire research efforts aimed to better understand regulatory mechanisms of transcription.

WikiPathways for plants: a community pathway curation portal and a case study in rice and arabidopsis seed development networks

BACKGROUND

Next-generation sequencing and 'omics' platforms are used extensively in plant biology research to unravel new genomes and study their interactions with abiotic and biotic agents in the growth environment. Despite the availability of a large and growing number of genomic data sets, there are only limited resources providing highly-curated and up-to-date metabolic and regulatory networks for plant pathways.

RESULTS

Using PathVisio, a pathway editor tool associated with WikiPathways, we created a gene interaction network of 430 rice (Oryza sativa) genes involved in the seed development process by curating interactions reported in the published literature. We then applied an InParanoid-based homology search to these genes and used the resulting gene clusters to identify 351 Arabidopsis thaliana genes. Using this list of homologous genes, we constructed a seed development network in Arabidopsis by processing the gene list and the rice network through a Perl utility software called Pathway GeneSWAPPER developed by us. In order to demonstrate the utility of these networks in generating testable hypotheses and preliminary analysis prior to more in-depth downstream analysis, we used the expression viewer and statistical analysis features of PathVisio to analyze publicly-available and published microarray gene expression data sets on diurnal photoperiod response and the seed development time course to discover patterns of coexpressed genes found in the rice and Arabidopsis seed development networks. These seed development networks described herein, along with other plant pathways and networks, are freely available on the plant pathways portal at WikiPathways (http://plants.wikipathways.org).

CONCLUSION

In collaboration with the WikiPathways project we present a community curation and analysis platform for plant biologists where registered users can freely create, edit, share and monitor pathways supported by published literature. We describe the curation and annotation of a seed development network in rice, and the projection of a similar, gene homology-based network in Arabidopsis. We also demonstrate the utility of the Pathway GeneSWAPPER (PGS) application in saving valuable time and labor when a reference network in one species compiled in GPML format is used to project a similar network in another species based on gene homology.

Sequencing and de novo transcriptome assembly of Brachypodium sylvaticum (Poaceae)

PREMISE OF THE STUDY

We report the de novo assembly and characterization of the transcriptomes of Brachypodium sylvaticum (slender false-brome) accessions from native populations of Spain and Greece, and an invasive population west of Corvallis, Oregon, USA. •

METHODS AND RESULTS

More than 350 million sequence reads from the mRNA libraries prepared from three B. sylvaticum genotypes were assembled into 120,091 (Corvallis), 104,950 (Spain), and 177,682 (Greece) transcript contigs. In comparison with the B. distachyon Bd21 reference genome and GenBank protein sequences, we estimate >90% exome coverage for B. sylvaticum. The transcripts were assigned Gene Ontology and InterPro annotations. Brachypodium sylvaticum sequence reads aligned against the Bd21 genome revealed 394,654 single-nucleotide polymorphisms (SNPs) and >20,000 simple sequence repeat (SSR) DNA sites. •

CONCLUSIONS

To our knowledge, this is the first report of transcriptome sequencing of invasive plant species with a closely related sequenced reference genome. The sequences and identified SNP variant and SSR sites will provide tools for developing novel genetic markers for use in genotyping and characterization of invasive behavior of B. sylvaticum.

STIFDB2: an updated version of plant stress-responsive transcription factor database with additional stress signals, stress-responsive transcription factor binding sites and stress-responsive genes in Arabidopsis and rice

Understanding the principles of abiotic and biotic stress responses, tolerance and adaptation remains important in plant physiology research to develop better varieties of crop plants. Better understanding of plant stress response mechanisms and application of knowledge derived from integrated experimental and bioinformatics approaches are gaining importance. Earlier, we showed that compiling a database of stress-responsive transcription factors and their corresponding target binding sites in the form of Hidden Markov models at promoter, untranslated and upstream regions of stress-up-regulated genes from expression analysis can help in elucidating various aspects of the stress response in Arabidopsis. In addition to the extensive content in the first version, STIFDB2 is now updated with 15 stress signals, 31 transcription factors and 5,984 stress-responsive genes from three species (Arabidopsis thaliana, Oryza sativa subsp. japonica and Oryza sativa subsp. indica). We have employed an integrated biocuration and genomic data mining approach to characterize the data set of transcription factors and consensus binding sites from literature mining and stress-responsive genes from the Gene Expression Omnibus. STIFDB2 currently has 38,798 associations of stress signals, stress-responsive genes and transcription factor binding sites predicted using the Stress-responsive Transcription Factor (STIF) algorithm, along with various functional annotation data. As a unique plant stress regulatory genomics data platform, STIFDB2 can be utilized for targeted as well as high-throughput experimental and computational studies to unravel principles of the stress regulome in dicots and gramineae. STIFDB2 is available from the URL: http://caps.ncbs.res.in/stifdb2.

BioMart: a data federation framework for large collaborative projects

BioMart is a freely available, open source, federated database system that provides a unified access to disparate, geographically distributed data sources. It is designed to be data agnostic and platform independent, such that existing databases can easily be incorporated into the BioMart framework. BioMart allows databases hosted on different servers to be presented seamlessly to users, facilitating collaborative projects between different research groups. BioMart contains several levels of query optimization to efficiently manage large data sets and offers a diverse selection of graphical user interfaces and application programming interfaces to ensure that queries can be performed in whatever manner is most convenient for the user. The software has now been adopted by a large number of different biological databases spanning a wide range of data types and providing a rich source of annotation available to bioinformaticians and biologists alike.

BioMart Central Portal: an open database network for the biological community

BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities.