Genomics and bioinformatics resources for crop improvement

Functional characterization of plant specific Indeterminate Domain (IDD) transcription factors in tomato (Solanum lycopersicum L.)

Plant-specific transcription factors (TFs) are responsible for regulating the genes involved in the development of plant-specific organs and response systems for adaptation to terrestrial environments. This includes the development of efficient water transport systems, efficient reproductive organs, and the ability to withstand the effects of terrestrial factors, such as UV radiation, temperature fluctuations, and soil-related stress factors, and evolutionary advantages over land predators. In rice and Arabidopsis, INDETERMINATE DOMAIN (IDD) TFs are plant-specific TFs with crucial functions, such as development, reproduction, and stress response. However, in tomatoes, IDD TFs remain uncharacterized. Here, we examined the presence, distribution, structure, characteristics, and expression patterns of SlIDDs. Database searches, multiple alignments, and motif alignments suggested that 24 TFs were related to Arabidopsis IDDs. 18 IDDs had two characteristic C2H2 domains and two C2HC domains in their coding regions. Expression analyses suggest that some IDDs exhibit multi-stress responsive properties and can respond to specific stress conditions, while others can respond to multiple stress conditions in shoots and roots, either in a tissue-specific or universal manner. Moreover, co-expression database analyses suggested potential interaction partners within IDD family and other proteins. This study functionally characterized SlIDDs, which can be studied using molecular and bioinformatics methods for crop improvement.

Crop-GPA: an integrated platform of crop gene-phenotype associations

With the increasing availability of large-scale biology data in crop plants, there is an urgent demand for a versatile platform that fully mines and utilizes the data for modern molecular breeding. We present Crop-GPA ( https://crop-gpa.aielab.net ), a comprehensive and functional open-source platform for crop gene-phenotype association data. The current Crop-GPA provides well-curated information on genes, phenotypes, and their associations (GPAs) to researchers through an intuitive interface, dynamic graphical visualizations, and efficient online tools. Two computational tools, GPA-BERT and GPA-GCN, are specifically developed and integrated into Crop-GPA, facilitating the automatic extraction of gene-phenotype associations from bio-crop literature and predicting unknown relations based on known associations. Through usage examples, we demonstrate how our platform enables the exploration of complex correlations between genes and phenotypes in crop plants. In summary, Crop-GPA serves as a valuable multi-functional resource, empowering the crop research community to gain deeper insights into the biological mechanisms of interest.

Genetic Enhancement of Cereals Using Genomic Resources for Nutritional Food Security

Advances in genomics resources have facilitated the evolution of cereal crops with enhanced yield, improved nutritional values, and heightened resistance to various biotic and abiotic stresses. Genomic approaches present a promising avenue for the development of high-yielding varieties, thereby ensuring food and nutritional security. Significant improvements have been made within the omics domain, specifically in genomics, transcriptomics, and proteomics. The advent of Next-Generation Sequencing (NGS) techniques has yielded an immense volume of data, accompanied by substantial progress in bioinformatic tools for proficient analysis. The synergy between genomics and computational tools has been acknowledged as pivotal for unravelling the intricate mechanisms governing genome-wide gene regulation. Within this review, the essential genomic resources are delineated, and their harmonization in the enhancement of cereal crop varieties is expounded upon, with a paramount focus on fulfilling the nutritional requisites of humankind. Furthermore, an encompassing compendium of the available genomic resources for cereal crops is presented, accompanied by an elucidation of their judicious utilization in the advancement of crop attributes.

Advances in omics research on peanut response to biotic stresses

Peanut growth, development, and eventual production are constrained by biotic and abiotic stresses resulting in serious economic losses. To understand the response and tolerance mechanism of peanut to biotic and abiotic stresses, high-throughput Omics approaches have been applied in peanut research. Integrated Omics approaches are essential for elucidating the temporal and spatial changes that occur in peanut facing different stresses. The integration of functional genomics with other Omics highlights the relationships between peanut genomes and phenotypes under specific stress conditions. In this review, we focus on research on peanut biotic stresses. Here we review the primary types of biotic stresses that threaten sustainable peanut production, the multi-Omics technologies for peanut research and breeding, and the recent advances in various peanut Omics under biotic stresses, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics and phenomics, for identification of biotic stress-related genes, proteins, metabolites and their networks as well as the development of potential traits. We also discuss the challenges, opportunities, and future directions for peanut Omics under biotic stresses, aiming sustainable food production. The Omics knowledge is instrumental for improving peanut tolerance to cope with various biotic stresses and for meeting the food demands of the exponentially growing global population.

Transcriptomic profiling reveals candidate allelopathic genes in rice responsible for interactions with barnyardgrass

Echinochloa crus-galli (barnyardgrass) is one of the most damaging weeds in rice fields worldwide. Allelopathy has been considered a possible application for weed management. Thus understanding its molecular mechanisms is important for rice production. This study generated transcriptomes from rice under mono- and co-culture with barnyardgrass at two-time points to identify the candidate genes controlling allelopathic interactions between rice and barnyardgrass. A total of 5,684 differentially expressed genes (DEGs) were detected, amongst which 388 genes were transcription factors. These DEGs include genes associated with momilactone and phenolic acid biosynthesis, which play critical roles in allelopathy. Additionally, we found significantly more DEGs at 3 hours than at 3 days, suggesting a quick allelopathic response in rice. Up-regulated DEGs involve diverse biological processes, such as response to stimulus and pathways related to phenylpropanoid and secondary metabolites biosynthesis. Down-regulated DEGs were involved in developmental processes, indicating a balance between growth and stress response to allelopathy from barnyardgrass. Comparison of DEGs between rice and barnyardgrass shows few common genes, suggesting different mechanisms underlying allelopathic interaction in these two species. Our results offer an important basis for identifying of candidate genes responsible for rice and barnyardgrass interactions and contribute valuable resources for revealing its molecular mechanisms.

CRISPR/Cas9 technology as an innovative approach to enhancing the phytoremediation: Concepts and implications

Phytoremediation is currently an active field of research focusing chiefly on identifying and characterizing novel and high chelation action super-accumulators. In the last few years, molecular tools have been widely exploited to understand better metal absorption, translocation, cation, and tolerance mechanisms in plants. Recently more advanced CRISPR-Cas9 genome engineering technology is also employed to enhance detoxification efficiency. Further, advances in molecular science will trigger the understanding of adaptive phytoremediation ability plant production in current global warming conditions. The enhanced abilities of nucleases for genome modification can improve plant repair capabilities by modifying the genome, thereby achieving a sustainable ecosystem. The purpose of this manuscript focuses on biotechnology's fundamental principles and application to promote climate-resistant metal plants, especially the CRISPR-Cas9 genome editing system for enhancing the phytoremediation of harmful contamination and pollutants.

Multi-Omics and Integrative Approach towards Understanding Salinity Tolerance in Rice: A Review

Rice (Oryza sativa L.) plants are simultaneously encountered by environmental stressors, most importantly salinity stress. Salinity is the major hurdle that can negatively impact growth and crop yield. Understanding the salt stress and its associated complex trait mechanisms for enhancing salt tolerance in rice plants would ensure future food security. The main aim of this review is to provide insights and impacts of molecular-physiological responses, biochemical alterations, and plant hormonal signal transduction pathways in rice under saline stress. Furthermore, the review highlights the emerging breakthrough in multi-omics and computational biology in identifying the saline stress-responsive candidate genes and transcription factors (TFs). In addition, the review also summarizes the biotechnological tools, genetic engineering, breeding, and agricultural practicing factors that can be implemented to realize the bottlenecks and opportunities to enhance salt tolerance and develop salinity tolerant rice varieties. Future studies pinpointed the augmentation of powerful tools to dissect the salinity stress-related novel players, reveal in-depth mechanisms and ways to incorporate the available literature, and recent advancements to throw more light on salinity responsive transduction pathways in plants. Particularly, this review unravels the whole picture of salinity stress tolerance in rice by expanding knowledge that focuses on molecular aspects.

Root system architecture, physiological analysis and dynamic transcriptomics unravel the drought-responsive traits in rice genotypes

Drought is the major abiotic factors that limit crop productivity worldwide. To withstand stress conditions, plants alter numerous mechanisms for adaption and tolerance. Therefore, in the present study, 106 rice varieties were screened for drought tolerance phenotype via exposing different concentrations of polyethylene glycol 6000 (PEG) in the hydroponic nutrient medium at the time interval of 1, 3, and 7 days to evaluate the changes in their root system architecture. Further, based on root phenotype obtained after PEG-induced drought, two contrasting varieties drought-tolerant Heena and -sensitive Kiran were selected to study transcriptional and physiological alterations at the same stress durations. Physiological parameters (photosynthesis rate, stomatal conductance, transpiration), and non-enzymatic antioxidants (carotenoids, anthocyanins, total phenol content) production indicated better performance of Heena than Kiran. Comparatively higher accumulation of carotenoid and anthocyanin content and the increased photosynthetic rate was also observed in Heena. Root morphology (length, numbers of root hairs, seminal roots and adventitious roots) and anatomical data (lignin deposition, xylem area) enable tolerant variety Heena to better maintain membrane integrity and relative water content, which also contribute to comparatively higher biomass accumulation in Heena under drought. In transcriptome profiling, significant drought stress-associated differentially expressed genes (DEGs) were identified in both the varieties. A total of 1033 and 936 uniquely upregulated DEGs were found in Heena and Kiran respectively. The significant modulation of DEGs that were mainly associated with phytohormone signaling, stress-responsive genes (LEA, DREB), transcription factors (TFs) (AP2/ERF, MYB, WRKY, bHLH), and genes involved in photosynthesis and antioxidative mechanisms indicate better adaptive nature of Heena in stress tolerance. Additionally, the QTL-mapping analysis showed a very high number of DEGs associated with drought stress at AQHP069 QTL in Heena in comparison to Kiran which further distinguishes the drought-responsive traits at the chromosomal level in both the contrasting varieties. Overall, results support the higher capability of Heena over Kiran variety to induce numerous genes along with the development of better root architecture to endure drought stress.

Life-Course Monitoring of Endogenous Phytohormone Levels under Field Conditions Reveals Diversity of Physiological States among Barley Accessions

Agronomically important traits often develop during the later stages of crop growth as consequences of various plant-environment interactions. Therefore, the temporal physiological states that change and accumulate during the crop's life course can significantly affect the eventual phenotypic differences in agronomic traits among crop varieties. Thus, to improve productivity, it is important to elucidate the associations between temporal physiological responses during the growth of different crop varieties and their agronomic traits. However, data representing the dynamics and diversity of physiological states in plants grown under field conditions are sparse. In this study, we quantified the endogenous levels of five phytohormones - auxin, cytokinins (CKs), ABA, jasmonate and salicylic acid - in the leaves of eight diverse barley (Hordeum vulgare) accessions grown under field conditions sampled weekly over their life course to assess the ongoing fluctuations in hormone levels in the different accessions under field growth conditions. Notably, we observed enormous changes over time in the development-related plant hormones, such as auxin and CKs. Using 3' RNA-seq-based transcriptome data from the same samples, we investigated the expression of barley genes orthologous to known hormone-related genes of Arabidopsis throughout the life course. These data illustrated the dynamics and diversity of the physiological states of these field-grown barley accessions. Together, our findings provide new insights into plant-environment interactions, highlighting that there is cultivar diversity in physiological responses during growth under field conditions.

Decoding Plant-Environment Interactions That Influence Crop Agronomic Traits

To ensure food security in the face of increasing global demand due to population growth and progressive urbanization, it will be crucial to integrate emerging technologies in multiple disciplines to accelerate overall throughput of gene discovery and crop breeding. Plant agronomic traits often appear during the plants' later growth stages due to the cumulative effects of their lifetime interactions with the environment. Therefore, decoding plant-environment interactions by elucidating plants' temporal physiological responses to environmental changes throughout their lifespans will facilitate the identification of genetic and environmental factors, timing and pathways that influence complex end-point agronomic traits, such as yield. Here, we discuss the expected role of the life-course approach to monitoring plant and crop health status in improving crop productivity by enhancing the understanding of plant-environment interactions. We review recent advances in analytical technologies for monitoring health status in plants based on multi-omics analyses and strategies for integrating heterogeneous datasets from multiple omics areas to identify informative factors associated with traits of interest. In addition, we showcase emerging phenomics techniques that enable the noninvasive and continuous monitoring of plant growth by various means, including three-dimensional phenotyping, plant root phenotyping, implantable/injectable sensors and affordable phenotyping devices. Finally, we present an integrated review of analytical technologies and applications for monitoring plant growth, developed across disciplines, such as plant science, data science and sensors and Internet-of-things technologies, to improve plant productivity.

PeachVar-DB: A Curated Collection of Genetic Variations for the Interactive Analysis of Peach Genome Data

Applying next-generation sequencing (NGS) technologies to species of agricultural interest has the potential to accelerate the understanding and exploration of genetic resources. The storage, availability and maintenance of huge quantities of NGS-generated data remains a major challenge. The PeachVar-DB portal, available at http://hpc-bioinformatics.cineca.it/peach, is an open-source catalog of genetic variants present in peach (Prunus persica L. Batsch) and wild-related species of Prunus genera, annotated from 146 samples publicly released on the Sequence Read Archive (SRA). We designed a user-friendly web-based interface of the database, providing search tools to retrieve single nucleotide polymorphism (SNP) and InDel variants, along with useful statistics and information. PeachVar-DB results are linked to the Genome Database for Rosaceae (GDR) and the Phytozome database to allow easy access to other external useful plant-oriented resources. In order to extend the genetic diversity covered by the PeachVar-DB further, and to allow increasingly powerful comparative analysis, we will progressively integrate newly released data.

Surveying the Maize community for their diversity and pedigree visualization needs to prioritize tool development and curation

The Maize Genetics and Genomics Database (MaizeGDB) team prepared a survey to identify breeders’ needs for visualizing pedigrees, diversity data and haplotypes in order to prioritize tool development and curation efforts at MaizeGDB. The survey was distributed to the maize research community on behalf of the Maize Genetics Executive Committee in Summer 2015. The survey garnered 48 responses from maize researchers, of which more than half were self-identified as breeders. The survey showed that the maize researchers considered their top priorities for visualization as: (i) displaying single nucleotide polymorphisms in a given region for a given list of lines, (ii) showing haplotypes for a given list of lines and (iii) presenting pedigree relationships visually. The survey also asked which populations would be most useful to display. The following two populations were on top of the list: (i) 3000 publicly available maize inbred lines used in Romay et al. (Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol, 2013;14:R55) and (ii) maize lines with expired Plant Variety Protection Act (ex-PVP) certificates. Driven by this strong stakeholder input, MaizeGDB staff are currently working in four areas to improve its interface and web-based tools: (i) presenting immediate progenies of currently available stocks at the MaizeGDB Stock pages, (ii) displaying the most recent ex-PVP lines described in the Germplasm Resources Information Network (GRIN) on the MaizeGDB Stock pages, (iii) developing network views of pedigree relationships and (iv) visualizing genotypes from SNP-based diversity datasets. These survey results can help other biological databases to direct their efforts according to user preferences as they serve similar types of data sets for their communities.

Database URL

https://www.maizegdb.org.

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

Rice grain nutritional traits and their enhancement using relevant genes and QTLs through advanced approaches

BACKGROUND

Rice breeding program needs to focus on development of nutrient dense rice for value addition and helping in reducing malnutrition. Mineral and vitamin deficiency related problems are common in the majority of the population and more specific to developing countries as their staple food is rice.

RESULTS

Genes and QTLs are recently known for the nutritional quality of rice. By comprehensive literature survey and public domain database, we provided a critical review on nutritional aspects like grain protein and amino acid content, vitamins and minerals, glycemic index value, phenolic and flavonoid compounds, phytic acid, zinc and iron content along with QTLs linked to these traits. In addition, achievements through transgenic and advanced genomic approaches have been discussed. The information available on genes and/or QTLs involved in enhancement of micronutrient element and amino acids are summarized with graphical representation.

CONCLUSION

Compatible QTLs/genes may be combined together to design a desirable genotype with superior in multiple grain quality traits. The comprehensive review will be helpful to develop nutrient dense rice cultivars by integrating molecular markers and transgenic assisted breeding approaches with classical breeding.

Gene Overexpression Resources in Cereals for Functional Genomics and Discovery of Useful Genes

Identification and elucidation of functions of plant genes is valuable for both basic and applied research. In addition to natural variation in model plants, numerous loss-of-function resources have been produced by mutagenesis with chemicals, irradiation, or insertions of transposable elements or T-DNA. However, we may be unable to observe loss-of-function phenotypes for genes with functionally redundant homologs and for those essential for growth and development. To offset such disadvantages, gain-of-function transgenic resources have been exploited. Activation-tagged lines have been generated using obligatory overexpression of endogenous genes by random insertion of an enhancer. Recent progress in DNA sequencing technology and bioinformatics has enabled the preparation of genomewide collections of full-length cDNAs (fl-cDNAs) in some model species. Using the fl-cDNA clones, a novel gain-of-function strategy, Fl-cDNA OvereXpressor gene (FOX)-hunting system, has been developed. A mutant phenotype in a FOX line can be directly attributed to the overexpressed fl-cDNA. Investigating a large population of FOX lines could reveal important genes conferring favorable phenotypes for crop breeding. Alternatively, a unique loss-of-function approach Chimeric REpressor gene Silencing Technology (CRES-T) has been developed. In CRES-T, overexpression of a chimeric repressor, composed of the coding sequence of a transcription factor (TF) and short peptide designated as the repression domain, could interfere with the action of endogenous TF in plants. Although plant TFs usually consist of gene families, CRES-T is effective, in principle, even for the TFs with functional redundancy. In this review, we focus on the current status of the gene-overexpression strategies and resources for identifying and elucidating novel functions of cereal genes. We discuss the potential of these research tools for identifying useful genes and phenotypes for application in crop breeding.

Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley

Barley is one of the founder crops of Old world agriculture and has become the fourth most important cereal worldwide. Information on genome-scale DNA polymorphisms allows elucidating the evolutionary history behind domestication, as well as discovering and isolating useful genes for molecular breeding. Deep transcriptome sequencing enables the exploration of sequence variations in transcribed sequences; such analysis is particularly useful for species with large and complex genomes, such as barley. In this study, we performed RNA sequencing of 20 barley accessions, comprising representatives of several biogeographic regions and a wild ancestor. We identified 38,729 to 79,949 SNPs in the 19 domesticated accessions and 55,403 SNPs in the wild barley and revealed their genome-wide distribution using a reference genome. Genome-scale comparisons among accessions showed a clear differentiation between oriental and occidental barley populations. The results based on population structure analyses provide genome-scale properties of sub-populations grouped to oriental, occidental and marginal groups in barley. Our findings suggest that the oriental population of domesticated barley has genomic variations distinct from those in occidental groups, which might have contributed to barley’s domestication.

Bioinformatics Approach in Plant Genomic Research

The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity.

Computer aided gene mining for gingerol biosynthesis

Inspite of the large body of genomic data obtained from the transcriptome of Zingiber officinale, very few studies have focused on the identification and characterization of miRNAs in gingerol biosynthesis. Zingiber officinale transcriptome was analyzed using EST dataset (38169 total) deposited in public domains. In this paper computational functional annotation of the available ESTs and identification of genes which play a significant role in gingerol biosynthesis are described. Zingiber officinale transcriptome was analyzed using EST dataset (38169 total) from ncbi. ESTs were clustered and assembled, resulting in 8624 contigs and 8821 singletons. Assembled dataset was then submitted to the EST functional annotation workflow including blast, gene ontology (go) analysis, and pathway enrichment by kyoto encyclopedia of genes and genomes (kegg) and interproscan. The unigene datasets were further exploited to identify simple sequence repeats that enable linkage mapping. A total of 409 simple sequence repeats were identified from the contigs. Furthermore we examined the existence of novel miRNAs from the ESTs in rhizome, root and leaf tissues. EST analysis revealed the presence of single hypothetical miRNA in rhizome tissue. The hypothetical miRNA is warranted to play an important role in controlling genes involved in gingerol biosynthesis and hence demands experimental validation. The assembly and associated information of transcriptome data provides a comprehensive functional and evolutionary characterization of genomics of Zingiber officinale. As an effort to make the genomic and transcriptomic data widely available to the public domain, the results were integrated into a web-based Ginger EST database which is freely accessible at http://www.kaubic.in/gingerest/.

System approaches to study root hairs as a single cell plant model: current status and future perspectives

Our current understanding of plant functional genomics derives primarily from measurements of gene, protein and/or metabolite levels averaged over the whole plant or multicellular tissues. These approaches risk diluting the response of specific cells that might respond strongly to the treatment but whose signal is diluted by the larger proportion of non-responding cells. For example, if a gene is expressed at a low level, does this mean that it is indeed lowly expressed or is it highly expressed, but only in a few cells? In order to avoid these issues, we adopted the soybean root hair cell, derived from a single, differentiated root epidermal cell, as a single-cell model for functional genomics. Root hair cells are intrinsically interesting since they are major conduits for root water and nutrient uptake and are also the preferred site of infection by nitrogen-fixing rhizobium bacteria. Although a variety of other approaches have been used to study single plant cells or single cell types, the root hair system is perhaps unique in allowing application of the full repertoire of functional genomic and biochemical approaches. In this mini review, we summarize our published work and place this within the broader context of root biology, with a significant focus on understanding the initial events in the soybean-rhizobium interaction.

Genetic diversity in tef [Eragrostis tef (Zucc.) Trotter]

Tef [Eragrostis tef (Zucc.) Trotter] is a cereal crop resilient to adverse climatic and soil conditions, and possessing desirable storage properties. Although tef provides high quality food and grows under marginal conditions unsuitable for other cereals, it is considered to be an orphan crop because it has benefited little from genetic improvement. Hence, unlike other cereals such as maize and wheat, the productivity of tef is extremely low. In spite of the low productivity, tef is widely cultivated by over six million small-scale farmers in Ethiopia where it is annually grown on more than three million hectares of land, accounting for over 30% of the total cereal acreage. Tef, a tetraploid with 40 chromosomes (2n = 4x = 40), belongs to the family Poaceae and, together with finger millet (Eleusine coracana Gaerth.), to the subfamily Chloridoideae. It was originated and domesticated in Ethiopia. There are about 350 Eragrostis species of which E. tef is the only species cultivated for human consumption. At the present time, the gene bank in Ethiopia holds over five thousand tef accessions collected from geographical regions diverse in terms of climate and elevation. These germplasm accessions appear to have huge variability with regard to key agronomic and nutritional traits. In order to properly utilize the variability in developing new tef cultivars, various techniques have been implemented to catalog the extent and unravel the patterns of genetic diversity. In this review, we show some recent initiatives investigating the diversity of tef using genomics, transcriptomics and proteomics and discuss the prospect of these efforts in providing molecular resources that can aid modern tef breeding.

Crop improvement using life cycle datasets acquired under field conditions

Crops are exposed to various environmental stresses in the field throughout their life cycle. Modern plant science has provided remarkable insights into the molecular networks of plant stress responses in laboratory conditions, but the responses of different crops to environmental stresses in the field need to be elucidated. Recent advances in omics analytical techniques and information technology have enabled us to integrate data from a spectrum of physiological metrics of field crops. The interdisciplinary efforts of plant science and data science enable us to explore factors that affect crop productivity and identify stress tolerance-related genes and alleles. Here, we describe recent advances in technologies that are key components for data driven crop design, such as population genomics, chronological omics analyses, and computer-aided molecular network prediction. Integration of the outcomes from these technologies will accelerate our understanding of crop phenology under practical field situations and identify key characteristics to represent crop stress status. These elements would help us to genetically engineer "designed crops" to prevent yield shortfalls because of environmental fluctuations due to future climate change.

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.

Co-ordination and divergence of cell-specific transcription and translation of genes in arabidopsis root cells

BACKGROUND AND AIMS

A key challenge in biology is to systematically investigate and integrate the different levels of information available at the global and single-cell level. Recent studies have elucidated spatiotemporal expression patterns of root cell types in Arabidopsis thaliana, and genome-wide quantification of polysome-associated mRNA levels, i.e. the translatome, has also been obtained for corresponding cell types. Translational control has been increasingly recognized as an important regulatory step in protein synthesis. The aim of this study was to investigate coupled transcription and translation by use of publicly available root datasets.

METHODS

Using cell-type-specific datasets of the root transcriptome and translatome of arabidopsis, a systematic assessment was made of the degree of co-ordination and divergence between these two levels of cellular organization. The computational analysis considered correlation and variation of expression across cell types at both system levels, and also provided insights into the degree of co-regulatory relationships that are preserved between the two processes.

KEY RESULTS

The overall correlation of expression and translation levels of genes resemble an almost bimodal distribution (mean/median value of 0·08/0·12), with a second, less strongly pronounced 'mode' for negative Pearson's correlation coefficient values. The analysis conducted also confirms that previously identified key transcriptional activators of secondary cell wall development display highly conserved patterns of transcription and translation across the investigated cell types. Moreover, the biological processes that display conserved and divergent patterns based on the cell-type-specific expression and translation levels were identified.

CONCLUSIONS

In agreement with previous studies in animal cells, a large degree of uncoupling was found between the transcriptome and translatome. However, components and processes were also identified that are under co-ordinated transcriptional and translational control in plant root cells.

Systems responses to progressive water stress in durum wheat

Durum wheat is susceptible to terminal drought which can greatly decrease grain yield. Breeding to improve crop yield is hampered by inadequate knowledge of how the physiological and metabolic changes caused by drought are related to gene expression. To gain better insight into mechanisms defining resistance to water stress we studied the physiological and transcriptome responses of three durum breeding lines varying for yield stability under drought. Parents of a mapping population (Lahn x Cham1) and a recombinant inbred line (RIL2219) showed lowered flag leaf relative water content, water potential and photosynthesis when subjected to controlled water stress time transient experiments over a six-day period. RIL2219 lost less water and showed constitutively higher stomatal conductance, photosynthesis, transpiration, abscisic acid content and enhanced osmotic adjustment at equivalent leaf water compared to parents, thus defining a physiological strategy for high yield stability under water stress. Parallel analysis of the flag leaf transcriptome under stress uncovered global trends of early changes in regulatory pathways, reconfiguration of primary and secondary metabolism and lowered expression of transcripts in photosynthesis in all three lines. Differences in the number of genes, magnitude and profile of their expression response were also established amongst the lines with a high number belonging to regulatory pathways. In addition, we documented a large number of genes showing constitutive differences in leaf transcript expression between the genotypes at control non-stress conditions. Principal Coordinates Analysis uncovered a high level of structure in the transcriptome response to water stress in each wheat line suggesting genome-wide co-ordination of transcription. Utilising a systems-based approach of analysing the integrated wheat’s response to water stress, in terms of biological robustness theory, the findings suggest that each durum line transcriptome responded to water stress in a genome-specific manner which contributes to an overall different strategy of resistance to water stress.

Genetic control of functional traits related to photosynthesis and water use efficiency in Pinus pinaster Ait. drought response: integration of genome annotation, allele association and QTL detection for candidate gene identification

BACKGROUND

Understanding molecular mechanisms that control photosynthesis and water use efficiency in response to drought is crucial for plant species from dry areas. This study aimed to identify QTL for these traits in a Mediterranean conifer and tested their stability under drought.

RESULTS

High density linkage maps for Pinus pinaster were used in the detection of QTL for photosynthesis and water use efficiency at three water irrigation regimes. A total of 28 significant and 27 suggestive QTL were found. QTL detected for photochemical traits accounted for the higher percentage of phenotypic variance. Functional annotation of genes within the QTL suggested 58 candidate genes for the analyzed traits. Allele association analysis in selected candidate genes showed three SNPs located in a MYB transcription factor that were significantly associated with efficiency of energy capture by open PSII reaction centers and specific leaf area.

CONCLUSIONS

The integration of QTL mapping of functional traits, genome annotation and allele association yielded several candidate genes involved with molecular control of photosynthesis and water use efficiency in response to drought in a conifer species. The results obtained highlight the importance of maintaining the integrity of the photochemical machinery in P. pinaster drought response.

Genomic resources in fruit plants: an assessment of current status

The availability of many genomic resources such as genome sequences, functional genomics resources including microarrays and RNA-seq, sufficient numbers of molecular markers, express sequence tags (ESTs) and high-density genetic maps is causing a rapid acceleration of genetics and genomic research of many fruit plants. This is leading to an increase in our knowledge of the genes that are linked to many horticultural and agronomically important traits. Recently, some progress has also been made on the identification and functional analysis of miRNAs in some fruit plants. This is one of the most active research fields in plant sciences. The last decade has witnessed development of genomic resources in many fruit plants such as apple, banana, citrus, grapes, papaya, pears, strawberry etc.; however, many of them are still not being exploited. Furthermore, owing to lack of resources, infrastructure and research facilities in many lesser-developed countries, development of genomic resources in many underutilized or less-studied fruit crops, which grow in these countries, is limited. Thus, research emphasis should be given to those fruit crops for which genomic resources are relatively scarce. The development of genomic databases of these less-studied fruit crops will enable biotechnologists to identify target genes that underlie key horticultural and agronomical traits. This review presents an overview of the current status of the development of genomic resources in fruit plants with the main emphasis being on genome sequencing, EST resources, functional genomics resources including microarray and RNA-seq, identification of quantitative trait loci and construction of genetic maps as well as efforts made on the identification and functional analysis of miRNAs in fruit plants.

Detection of a Usp-like gene in Calotropis procera plant from the de novo assembled genome contigs of the high-throughput sequencing dataset

The wild plant species Calotropis procera (C. procera) has many potential applications and beneficial uses in medicine, industry and ornamental field. It also represents an excellent source of genes for drought and salt tolerance. Genes encoding proteins that contain the conserved universal stress protein (USP) domain are known to provide organisms like bacteria, archaea, fungi, protozoa and plants with the ability to respond to a plethora of environmental stresses. However, information on the possible occurrence of Usp in C. procera is not available. In this study, we uncovered and characterized a one-class A Usp-like (UspA-like, NCBI accession No. KC954274) gene in this medicinal plant from the de novo assembled genome contigs of the high-throughput sequencing dataset. A number of GenBank accessions for Usp sequences were blasted with the recovered de novo assembled contigs. Homology modelling of the deduced amino acids (NCBI accession No. AGT02387) was further carried out using Swiss-Model, accessible via the EXPASY. Superimposition of C. procera USPA-like full sequence model on Thermus thermophilus USP UniProt protein (PDB accession No. Q5SJV7) was constructed using RasMol and Deep-View programs. The functional domains of the novel USPA-like amino acids sequence were identified from the NCBI conserved domain database (CDD) that provide insights into sequence structure/function relationships, as well as domain models imported from a number of external source databases (Pfam, SMART, COG, PRK, TIGRFAM).

The Plant Organelles Database 3 (PODB3) update 2014: integrating electron micrographs and new options for plant organelle research

The Plant Organelles Database 2 (PODB2), which was first launched in 2006 as PODB, provides static image and movie data of plant organelles, protocols for plant organelle research and external links to relevant websites. PODB2 has facilitated plant organellar research and the understanding of plant organelle dynamics. To provide comprehensive information on plant organelles in more detail, PODB2 was updated to PODB3 (http://podb.nibb.ac.jp/Organellome/). PODB3 contains two additional components: the electron micrograph database and the perceptive organelles database. Through the electron micrograph database, users can examine the subcellular and/or suborganellar structures in various organs of wild-type and mutant plants. The perceptive organelles database provides information on organelle dynamics in response to external stimuli. In addition to the extra components, the user interface for access has been enhanced in PODB3. The data in PODB3 are directly submitted by plant researchers and can be freely downloaded for use in further analysis. PODB3 contains all the information included in PODB2, and the volume of data and protocols deposited in PODB3 continue to grow steadily. We welcome contributions of data from all plant researchers to enhance the utility and comprehensiveness of PODB3.

Unlocking Triticeae genomics to sustainably feed the future

The tribe Triticeae includes the major crops wheat and barley. Within the last few years, the whole genomes of four Triticeae species-barley, wheat, Tausch's goatgrass (Aegilops tauschii) and wild einkorn wheat (Triticum urartu)-have been sequenced. The availability of these genomic resources for Triticeae plants and innovative analytical applications using next-generation sequencing technologies are helping to revitalize our approaches in genetic work and to accelerate improvement of the Triticeae crops. Comparative genomics and integration of genomic resources from Triticeae plants and the model grass Brachypodium distachyon are aiding the discovery of new genes and functional analyses of genes in Triticeae crops. Innovative approaches and tools such as analysis of next-generation populations, evolutionary genomics and systems approaches with mathematical modeling are new strategies that will help us discover alleles for adaptive traits to future agronomic environments. In this review, we provide an update on genomic tools for use with Triticeae plants and Brachypodium and describe emerging approaches toward crop improvements in Triticeae.

Large-scale collection and analysis of full-length cDNAs from Brachypodium distachyon and integration with Pooideae sequence resources

A comprehensive collection of full-length cDNAs is essential for correct structural gene annotation and functional analyses of genes. We constructed a mixed full-length cDNA library from 21 different tissues of Brachypodium distachyon Bd21, and obtained 78,163 high quality expressed sequence tags (ESTs) from both ends of ca. 40,000 clones (including 16,079 contigs). We updated gene structure annotations of Brachypodium genes based on full-length cDNA sequences in comparison with the latest publicly available annotations. About 10,000 non-redundant gene models were supported by full-length cDNAs; ca. 6,000 showed some transcription unit modifications. We also found ca. 580 novel gene models, including 362 newly identified in Bd21. Using the updated transcription start sites, we searched a total of 580 plant cis-motifs in the −3 kb promoter regions and determined a genome-wide Brachypodium promoter architecture. Furthermore, we integrated the Brachypodium full-length cDNAs and updated gene structures with available sequence resources in wheat and barley in a web-accessible database, the RIKEN Brachypodium FL cDNA database. The database represents a “one-stop” information resource for all genomic information in the Pooideae, facilitating functional analysis of genes in this model grass plant and seamless knowledge transfer to the Triticeae crops.

Genome-wide discovery and information resource development of DNA polymorphisms in cassava

Cassava (Manihot esculenta Crantz) is an important crop that provides food security and income generation in many tropical countries, and is known for its adaptability to various environmental conditions. Its draft genome sequence and many expressed sequence tags are now publicly available, allowing the development of cassava polymorphism information. Here, we describe the genome-wide discovery of cassava DNA polymorphisms. Using the alignment of predicted transcribed sequences from the cassava draft genome sequence and ESTs from GenBank, we discovered 10,546 single-nucleotide polymorphisms and 647 insertions and deletions. To facilitate molecular marker development for cassava, we designed 9,316 PCR primer pairs to amplify the genomic region around each DNA polymorphism. Of the discovered SNPs, 62.7% occurred in protein-coding regions. Disease-resistance genes were found to have a significantly higher ratio of nonsynonymous-to-synonymous substitutions. We identified 24 read-through (changes of a stop codon to a coding codon) and 38 premature stop (changes of a coding codon to a stop codon) single-nucleotide polymorphisms, and found that the 5 gene ontology terms in biological process were significantly different in genes with read-through single-nucleotide polymorphisms compared with all cassava genes. All data on the discovered DNA polymorphisms were organized into the Cassava Online Archive database, which is available at http://cassava.psc.riken.jp/.

Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases

In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

De novo assembly and characterization of the Barnyardgrass (Echinochloa crus-galli) transcriptome using next-generation pyrosequencing

Background

Barnyardgrass (Echinochloa crus-galli) is an important weed that is a menace to rice cultivation and production. Rapid evolution of herbicide resistance in this weed makes it one of the most difficult to manage using herbicides. Since genome-wide sequence data for barnyardgrass is limited, we sequenced the transcriptomes of susceptible and resistant barnyardgrass biotypes using the 454 GS-FLX platform.

Results

454 pyrosequencing generated 371,281 raw reads with an average length of 341.8 bp, which made a total length of 126.89 Mb (SRX160526). De novo assembly produced 10,142 contigs (∼5.92 Mb) with an average length of 583 bp and 68,940 singletons (∼22.13 Mb) with an average length of 321 bp. About 244,653 GO term assignments to the biological process, cellular component and molecular function categories were obtained. A total of 6,092 contigs and singletons with 2,515 enzyme commission numbers were assigned to 151 predicted KEGG metabolic pathways. Digital abundance analysis using Illumina sequencing identified 78,124 transcripts among susceptible, resistant, herbicide-treated susceptible and herbicide-treated resistant barnyardgrass biotypes. From these analyses, eight herbicide target-site gene groups and four non-target-site gene groups were identified in the resistant biotype. These could be potential candidate genes involved in the herbicide resistance of barnyardgrass and could be used for further functional genomics research. C₄ photosynthesis genes including RbcS, RbcL, NADP-me and MDH with complete CDS were identified using PCR and RACE technology.

Conclusions

This is the first large-scale transcriptome sequencing of E. crus-galli performed using the 454 GS-FLX platform. Potential candidate genes involved in the evolution of herbicide resistance were identified from the assembled sequences. This transcriptome data may serve as a reference for further gene expression and functional genomics studies, and will facilitate the study of herbicide resistance at the molecular level in this species as well as other weeds.

Linking the potato genome to the conserved ortholog set (COS) markers

BACKGROUND

Conserved ortholog set (COS) markers are an important functional genomics resource that has greatly improved orthology detection in Asterid species. A comprehensive list of these markers is available at Sol Genomics Network (http://solgenomics.net/) and many of these have been placed on the genetic maps of a number of solanaceous species.

RESULTS

We amplified over 300 COS markers from eight potato accessions involving two diploid landraces of Solanum tuberosum Andigenum group (formerly classified as S. goniocalyx, S. phureja), and a dihaploid clone derived from a modern tetraploid cultivar of S. tuberosum and the wild species S. berthaultii, S. chomatophilum, and S. paucissectum. By BLASTn (Basic Local Alignment Search Tool of the NCBI, National Center for Biotechnology Information) algorithm we mapped the DNA sequences of these markers into the potato genome sequence. Additionally, we mapped a subset of these markers genetically in potato and present a comparison between the physical and genetic locations of these markers in potato and in comparison with the genetic location in tomato. We found that most of the COS markers are single-copy in the reference genome of potato and that the genetic location in tomato and physical location in potato sequence are mostly in agreement. However, we did find some COS markers that are present in multiple copies and those that map in unexpected locations. Sequence comparisons between species show that some of these markers may be paralogs.

CONCLUSIONS

The sequence-based physical map becomes helpful in identification of markers for traits of interest thereby reducing the number of markers to be tested for applications like marker assisted selection, diversity, and phylogenetic studies.

Genomics approaches for crop improvement against abiotic stress

As sessile organisms, plants are inevitably exposed to one or a combination of stress factors every now and then throughout their growth and development. Stress responses vary considerably even in the same plant species; stress-susceptible genotypes are at one extreme, and stress-tolerant ones are at the other. Elucidation of the stress responses of crop plants is of extreme relevance, considering the central role of crops in food and biofuel production. Crop improvement has been a traditional issue to increase yields and enhance stress tolerance; however, crop improvement against abiotic stresses has been particularly compelling, given the complex nature of these stresses. As traditional strategies for crop improvement approach their limits, the era of genomics research has arisen with new and promising perspectives in breeding improved varieties against abiotic stresses.

Salt-responsive ERF1 regulates reactive oxygen species-dependent signaling during the initial response to salt stress in rice

Early detection of salt stress is vital for plant survival and growth. Still, the molecular processes controlling early salt stress perception and signaling are not fully understood. Here, we identified salt-responsive ERF1 (SERF1), a rice (Oryza sativa) transcription factor (TF) gene that shows a root-specific induction upon salt and hydrogen peroxide (H2O2) treatment. Loss of SERF1 impairs the salt-inducible expression of genes encoding members of a mitogen-activated protein kinase (MAPK) cascade and salt tolerance-mediating TFs. Furthermore, we show that SERF1-dependent genes are H2O2 responsive and demonstrate that SERF1 binds to the promoters of MAPK kinase kinase6 (MAP3K6), MAPK5, dehydration-responsive element bindinG2A (DREB2A), and zinc finger protein179 (ZFP179) in vitro and in vivo. SERF1 also directly induces its own gene expression. In addition, SERF1 is a phosphorylation target of MAPK5, resulting in enhanced transcriptional activity of SERF1 toward its direct target genes. In agreement, plants deficient for SERF1 are more sensitive to salt stress compared with the wild type, while constitutive overexpression of SERF1 improves salinity tolerance. We propose that SERF1 amplifies the reactive oxygen species-activated MAPK cascade signal during the initial phase of salt stress and translates the salt-induced signal into an appropriate expressional response resulting in salt tolerance.

RiceSRTFDB: a database of rice transcription factors containing comprehensive expression, cis-regulatory element and mutant information to facilitate gene function analysis

Rice is one of the most important crop plants, representing the staple food for more than half the world’s population. However, its productivity is challenged by various stresses, including drought and salinity. Transcription factors (TFs) represent a regulatory component of the genome and are the most important targets for engineering stress tolerance. Here, we constructed a database, RiceSRTFDB, which provides comprehensive expression information for rice TFs during drought and salinity stress conditions and various stages of development. This information will be useful to identify the target TF(s) involved in stress response at a particular stage of development. The curated information for cis-regulatory elements present in their promoters has also been provided, which will be important to study the binding proteins. In addition, we have provided the available mutants and their phenotype information for rice TFs. All these information have been integrated in the database to facilitate the selection of target TFs of interest for functional analysis. This database aims to accelerate functional genomics research of rice TFs and understand the regulatory mechanisms underlying abiotic stress responses.

Database URL:http://www.nipgr.res.in/RiceSRTFDB.html

Genomic resources for functional analyses of the rice genome

With the availability of the rice genome sequence, rice research communities are entering a new era of plant functional genomics. The last decade has seen rapid worldwide progress on establishing platforms for rice functional genomic research. These platforms offer practical toolkits and genomic resources for high-throughput identification of genes and pathways. In this review, we summarize available genomic resources for functional analyses of the rice genome. These genomic resources include high-quality bacterial artificial chromosome libraries, large-scale expression sequence tags, full-length cDNA collections, large amounts of data on global expression profiles, various mutant libraries and integrated bioinformatics databases. We not only present the current status of genomic resources but also discuss their usage in elucidating gene functions of the rice genome.

A review of the "Omics" approach to biomarkers of oxidative stress in Oryza sativa

Physiological and ecological constraints that cause the slow growth and depleted production of crops have raised a major concern in the agriculture industry as they represent a possible threat of short food supply in the future. The key feature that regulates the stress signaling pathway is always related to the reactive oxygen species (ROS). The accumulation of ROS in plant cells would leave traces of biomarkers at the genome, proteome, and metabolome levels, which could be identified with the recent technological breakthrough coupled with improved performance of bioinformatics. This review highlights the recent breakthrough in molecular strategies (comprising transcriptomics, proteomics, and metabolomics) in identifying oxidative stress biomarkers and the arising opportunities and obstacles observed in research on biomarkers in rice. The major issue in incorporating bioinformatics to validate the biomarkers from different omic platforms for the use of rice-breeding programs is also discussed. The development of powerful techniques for identification of oxidative stress-related biomarkers and the integration of data from different disciplines shed light on the oxidative response pathways in plants.

TreeTFDB: an integrative database of the transcription factors from six economically important tree crops for functional predictions and comparative and functional genomics

Crop plants, whose productivity is affected by a wide range of growing and environmental conditions, are grown for economic purposes. Transcription factors (TFs) play central role in regulation of many biological processes, including plant development and responses to environmental stimuli, by activating or repressing spatiotemporal gene expression. Here, we describe the TreeTFDB (http://treetfdb.bmep.riken.jp/index.pl) that houses the TF repertoires of six economically important tree crop species: Jatropha curcas, papaya, cassava, poplar, castor bean and grapevine. Among these, the TF repertoire of J. curcas has not been reported by any other TF databases. In addition to their basic information, such as sequence and domain features, domain alignments, gene ontology assignment and sequence comparison, information on available full-length cDNAs, identity and positions of all types of known cis-motifs found in the promoter regions, gene expression data are provided. With its newly designed and friendly interface and its unique features, TreeTFDB will enable research community to predict the functions and provide access to available genetic resources for performing comparative and functional genomics of the crop TFs, either individually or at whole family level, in a comprehensive and convenient manner.

Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics

The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics.

PRIMe Update: innovative content for plant metabolomics and integration of gene expression and metabolite accumulation

PRIMe (http://prime.psc.riken.jp/), the Platform for RIKEN Metabolomics, is a website that was designed and implemented to support research and analyses ranging from metabolomics to transcriptomics. To achieve functional genomics and annotation of unknown metabolites, we established the following PRIMe contents: MS2T, a library comprising >1 million entries of untargeted tandem mass spectrometry (MS/MS) data of plant metabolites; AtMetExpress LC-MS, a database of transcriptomics and metabolomics approaches in Arabidopsis developmental stages (AtMetExpress Development LC-MS) and a data set of the composition of secondary metabolites among 20 Arabidopsis ecotypes (AtMetExpress 20 ecotypes LC-MS); and ReSpect, hybrid reference MS/MS data resources (acquisitions and literature). PRIMeLink is a new web application that allows access to the innovative data resources of PRIMe. The MS2T library was generated from a set of MS/MS spectra acquired using the automatic data acquisition function of mass spectrometry. To increase the understanding of mechanisms driving variations in metabolic profiles among plant tissues, we further provided the AtMetExpress Development LC-MS database in PRIMe, facilitating the investigation of relationships between gene expression and metabolite accumulation. This information platform therefore provides an integrative analysis resource by linking Arabidopsis transcriptome and metabolome data. Moreover, we developed the ReSpect database, a plant-specific MS/MS data resource, which allows users to identify candidate structures from the suite of complex phytochemical structures. Finally, we integrated the three databases into PRIMeLink and established a walk-through link between transcriptome and metabolome information. PRIMeLink offers a bi-directional searchable function, from the gene and the metabolite perspective, to search for targets seamlessly and effectively.

Plant metabolomics: from experimental design to knowledge extraction

Metabolomics is one of the most recent additions to the functional genomics approaches. It involves the use of analytical chemistry techniques to provide high-density data of metabolic profiles. Data is then analyzed using advanced statistics and databases to extract biological information, thus providing the metabolic phenotype of an organism. Large variety of metabolites produced by plants through the complex metabolic networks and their dynamic changes in response to various perturbations can be studied using metabolomics. Here, we describe the basic features of plant metabolic diversity and analytical methods to describe this diversity, which includes experimental workflows starting from experimental design, sample preparation, hardware and software choices, combined with knowledge extraction methods. Finally, we describe a scenario for using these workflows to identify differential metabolites and their pathways from complex biological samples.