Plant Genome Research Research Articles

PGSB PlantsDB: updates to the database framework for comparative plant genome research.

PGSB (Plant Genome and Systems Biology: formerly MIPS) PlantsDB (http://pgsb.helmholtz-muenchen.de/plant/index.jsp) is a database framework for the comparative analysis and visualization of plant genome data. The resource has been updated with new data sets and types as well as specialized tools and interfaces to address user demands for intuitive access to complex plant genome data. In its latest incarnation, we have re-worked both the layout and navigation structure and implemented new keyword search options and a new BLAST sequence search functionality. Actively involved in corresponding sequencing consortia, PlantsDB has dedicated special efforts to the integration and visualization of complex triticeae genome data, especially for barley, wheat and rye. We enhanced CrowsNest, a tool to visualize syntenic relationships between genomes, with data from the wheat sub-genome progenitor Aegilops tauschii and added functionality to the PGSB RNASeqExpressionBrowser. GenomeZipper results were integrated for the genomes of barley, rye, wheat and perennial ryegrass and interactive access is granted through PlantsDB interfaces. Data exchange and cross-linking between PlantsDB and other plant genome databases is stimulated by the transPLANT project (http://transplantdb.eu/).

Research advances on analysis of medicinal plants transcriptome

The transcriptome represents the whole complement of RNA transcripts in cells or tissues and reflects the expressed genes at various life stages, tissue types, physiological states, and environmental conditions. Transcriptomics study concerning medicinal plants has become the most active area in medicinal plant genome research. Transcriptome analysis provides a comprehensive understanding of gene expression and its regulation. The study of its transcriptome has great significance in solving the questions of genetic evolution, genetic breeding, ecology and so on. Here we report the application status of transcriptomics in medicinal plants based on emergence, development and methodology of transcriptomics.

Plant Comparative and Functional Genomics.

Plant Comparative and Functional Genomics.

Whole-genome resequencing: changing the paradigms of SNP detection, molecular mapping and gene discovery

Next-generation sequencing (NGS) technologies open up a wealth of opportunities for plant breeding and genomic research and change the paradigms of DNA marker detection, genotyping, and gene discovery. Abundant genomic resources have been generated using a whole-genome resequencing (WGR) strategy and utilized in genome-wide association, genome diversity, and evolution studies in many crops with a reference genome such as rice and maize. The WGR-based quantitative trait loci mapping approach developed in soybean combines single nucleotide polymorphism (SNP) discovery, validation and genotyping and has the potential to identify candidate genes and causal SNPs without a time-consuming fine-mapping process. Given that this approach solves issues caused by genome duplications and repetitive sequences, it can be widely utilized in crops with a reference genome. The combination of WGR with bulked segregant analysis provides a rapid way to identify genes or causal mutations. Currently, DNA sequencing technologies are being improved rapidly. Third-generation sequencing platforms can overcome some inherent disadvantages of NGS and are expected to promote the application of WGR-based approaches and revolutionize plant breeding, genomic and genetic research.

Molecular Markers: An Excellent Tool for Genetic Analysis

The exploitation of DNA polymorphisms by an ever-increasing number of molecular marker technologies has begun to have an impact on animal and plant genome research and breeding. A large number of different molecular techniques for genetic diversity analysis are available and each of them differs in its informational content. These techniques not only helped in understanding the different structure and behavior of species genome, but also revolutionized and modernized the ability to characterize genetic variation. Identification of marker linked to useful traits has been based on complete linkage maps and bulked segregation analysis. Markers are therefore used to identify traits, their inheritance and characterize germplasm.

Characterization and Identification of cis-Regulatory Elements in Arabidopsis Based on Single-Nucleotide Polymorphism Information

Identifying regulatory elements and revealing their role in gene expression regulation remains a central goal of plant genome research. We exploited the detailed genomic sequencing information of a large number of Arabidopsis (Arabidopsis thaliana) accessions to characterize known and to identify novel cis-regulatory elements in gene promoter regions of Arabidopsis by relying on conservation as the hallmark signal of functional relevance. Based on the genomic layout and the obtained density profiles of single-nucleotide polymorphisms (SNPs) in sequence regions upstream of transcription start sites, the average length of promoter regions in Arabidopsis could be established at 500 bp. Genes associated with high degrees of variability of their respective upstream regions are preferentially involved in environmental response and signaling processes, while low levels of promoter SNP density are common among housekeeping genes. Known cis-elements were found to exhibit a decreased SNP density than sequence regions not associated with known motifs. For 15 known cis-element motifs, strong positional preferences relative to the transcription start site were detected based on their promoter SNP density profiles. Five novel candidate cis-element motifs were identified as consensus motifs of 17 sequence hexamers exhibiting increased sequence conservation combined with evidence of positional preferences, annotation information, and functional relevance for inducing correlated gene expression. Our study demonstrates that the currently available resolution of SNP data offers novel ways for the identification of functional genomic elements and the characterization of gene promoter sequences.

MIPS PlantsDB: a database framework for comparative plant genome research

The rapidly increasing amount of plant genome (sequence) data enables powerful comparative analyses and integrative approaches and also requires structured and comprehensive information resources. Databases are needed for both model and crop plant organisms and both intuitive search/browse views and comparative genomics tools should communicate the data to researchers and help them interpret it. MIPS PlantsDB (http://mips.helmholtz-muenchen.de/plant/genomes.jsp) was initially described in NAR in 2007 [Spannagl,M., Noubibou,O., Haase,D., Yang,L., Gundlach,H., Hindemitt, T., Klee,K., Haberer,G., Schoof,H. and Mayer,K.F. (2007) MIPSPlantsDB–plant database resource for integrative and comparative plant genome research. Nucleic Acids Res., 35, D834–D840] and was set up from the start to provide data and information resources for individual plant species as well as a framework for integrative and comparative plant genome research. PlantsDB comprises database instances for tomato, Medicago, Arabidopsis, Brachypodium, Sorghum, maize, rice, barley and wheat. Building up on that, state-of-the-art comparative genomics tools such as CrowsNest are integrated to visualize and investigate syntenic relationships between monocot genomes. Results from novel genome analysis strategies targeting the complex and repetitive genomes of triticeae species (wheat and barley) are provided and cross-linked with model species. The MIPS Repeat Element Database (mips-REdat) and Catalog (mips-REcat) as well as tight connections to other databases, e.g. via web services, are further important components of PlantsDB.

Current state-of-art of sequencing technologies for plant genomics research

A number of next-generation sequencing (NGS) technologies such as Roche/454, Illumina and AB SOLiD have recently become available. These technologies are capable of generating hundreds of thousands or tens of millions of short DNA sequence reads at a relatively low cost. These NGS technologies, now referred as second-generation sequencing (SGS) technologies, are being utilized for de novo sequencing, genome re-sequencing, and whole genome and transcriptome analysis. Now, new generation of sequencers, based on the 'next-next' or third-generation sequencing (TGS) technologies like the Single-Molecule Real-Time (SMRT™) Sequencer, Heliscope™ Single Molecule Sequencer, and the Ion Personal Genome Machine™ are becoming available that are capable of generating longer sequence reads in a shorter time and at even lower costs per instrument run. Ever declining sequencing costs and increased data output and sample throughput for NGS and TGS sequencing technologies enable the plant genomics and breeding community to undertake genotyping-by-sequencing (GBS). Data analysis, storage and management of large-scale second or TGS projects, however, are essential. This article provides an overview of different sequencing technologies with an emphasis on forthcoming TGS technologies and bioinformatics tools required for the latest evolution of DNA sequencing platforms.

A Simple and Swift Method for Isolating High Quality RNA from Jute (Corchorus spp.)

High quality RNA extraction is a prerequisite for various types of genetic analyses. Many a time, the existing RNA isolation methods and commercial kits are either time consuming or fail to isolate high quality RNA from plants rich in polysaccharides, oil and other secondary metabolites since different plants contain different amounts of nucleic acids (Khan et al. 2004, Loomis 1974). This problem is particularly acute in case of jute (Corchorus spp.), which is rich in mucilage and other polysaccharides that tends to interfere with the downstream processes (Kundu et al. 2011, Pandey et al. 1996). Several guanidium salt based methods have been successful for RNA isolation from jute seedlings (Khan et al. 2004), but are often cumbersome and expensive; hence limit simultaneous processing of large number of samples. Here we report a simplified and swift protocol for isolating high quality RNA from jute by making key modifications in tissue denaturation and precipitation steps in the protocol described by Ghawana et al. (2011). The protocol allows consistent production of high quality RNA from different species, which makes it particularly suitable for comparative plant genome research. The extraction time has been reduced from two days (for standard guanidium-acid-phenol extraction protocols) to about one hour and the extracted RNA was suitable for downstream processes like cDNA synthesis and expression pattern analysis. Key words: Jute, Corchorus spp., Swift method, RNA isolation, RT-PCR D. O. I. 10.3329/ptcb.v21i2.10244 Plant Tissue Cult. & Biotech. 21(2): 207-211, 2011 (December) - Short communication

Reasons for lower transformation efficiency in indica rice using Agrobacterium tumefaciens-mediated transformation: lessons from transformation assays and genome-wide expression profiling

Agrobacterium tumefaciens-mediated genetic transformation has been routinely used in rice for more than a decade. However, the transformation efficiency of the indica rice variety is still unsatisfactory and much lower than that of japonica cultivars. Further improvement on the transformation efficiency lies in the genetic manipulation of the plant itself, which requires a better understanding of the underlying process accounting for the susceptibility of plant cells to Agrobacterium infection as well as the identification of plant genes involved in the transformation process. In this study, transient and stable transformation assays using different japonica and indica cultivars showed that the lower transformation efficiency in indica rice was mainly due to the low efficiency in T-DNA integration into the plant genome. Analyses of the global gene expression patterns across the transformation process in different varieties revealed major differences in the expression of genes responding to Agrobacterium within the first 6 h after infection and more differentially expressed genes were observed in the indica cultivar Zhenshan 97 (ZS), with a number of genes repressed early during infection. Microarray analysis revealed an important effect of plant defense response on Agrobacterium-mediated transformation. It has been shown that some genes which may be necessary for the transformation process were down-regulated in the indica cultivar ZS. This dataset provided a versatile resource for plant genomic research to understand the regulatory network of transformation process, and showed great promise for improving indica rice transformation using genetic manipulation of the rice genome.

Measurements of genomic GC content in plant genomes with flow cytometry: a test for reliability

• Knowledge of the phylogenetic pattern and biological relevance of the base composition of large eukaryotic genomes (including those of plants) is poor. With the use of flow cytometry (FCM), the amount of available data on the guanine + cytosine (GC) content of plants has nearly doubled in the last decade. However, skepticism exists concerning the reliability of the method because of uncertainty in some input parameters. • Here, we tested the reliability of FCM for estimating GC content by comparison with the biochemical method of DNA temperature melting analysis (TMA). We conducted measurements in 14 plant species with a maximum currently known GC content range (33.6-47.5% as measured by FCM). We also compared the estimations of the GC content by FCM with genomic sequences in 11 Oryza species. • FCM and TMA data exhibited a high degree of correspondence which remained stable over the relatively wide range of binding lengths (3.39-4.09) assumed for the base-specific dye used. A high correlation was also observed between FCM results and the sequence data in Oryza, although the latter GC contents were consistently lower. • Reliable estimates of the genomic base composition in plants by FCM are comparable with estimates obtained using other methods, and so wider application of FCM in future plant genomic research, although it would pose a challenge, would be supported by these findings.

Computable visually observed phenotype ontological framework for plants

BackgroundThe ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed.ResultsWe have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research.ConclusionsThe Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community.

Phenotypic and Genomic Analyses of a Fast Neutron Mutant Population Resource in Soybean

Mutagenized populations have become indispensable resources for introducing variation and studying gene function in plant genomics research. In this study, fast neutron (FN) radiation was used to induce deletion mutations in the soybean (Glycine max) genome. Approximately 120,000 soybean seeds were exposed to FN radiation doses of up to 32 Gray units to develop over 23,000 independent M2 lines. Here, we demonstrate the utility of this population for phenotypic screening and associated genomic characterization of striking and agronomically important traits. Plant variation was cataloged for seed composition, maturity, morphology, pigmentation, and nodulation traits. Mutants that showed significant increases or decreases in seed protein and oil content across multiple generations and environments were identified. The application of comparative genomic hybridization (CGH) to lesion-induced mutants for deletion mapping was validated on a midoleate x-ray mutant, M23, with a known FAD2-1A (for fatty acid desaturase) gene deletion. Using CGH, a subset of mutants was characterized, revealing deletion regions and candidate genes associated with phenotypes of interest. Exome resequencing and sequencing of PCR products confirmed FN-induced deletions detected by CGH. Beyond characterization of soybean FN mutants, this study demonstrates the utility of CGH, exome sequence capture, and next-generation sequencing approaches for analyses of mutant plant genomes. We present this FN mutant soybean population as a valuable public resource for future genetic screens and functional genomics research.

Construction, characterization, and preliminary BAC-end sequence analysis of a bacterial artificial chromosome library of the tea plant (Camellia sinensis).

We describe the construction and characterization of a publicly available BAC library for the tea plant, Camellia sinensis. Using modified methods, the library was constructed with the aim of developing public molecular resources to advance tea plant genomics research. The library consists of a total of 401,280 clones with an average insert size of 135 kb, providing an approximate coverage of 13.5 haploid genome equivalents. No empty vector clones were observed in a random sampling of 576 BAC clones. Further analysis of 182 BAC-end sequences from randomly selected clones revealed a GC content of 40.35% and low chloroplast and mitochondrial contamination. Repetitive sequence analyses indicated that LTR retrotransposons were the most predominant sequence class (86.93%–87.24%), followed by DNA retrotransposons (11.16%–11.69%). Additionally, we found 25 simple sequence repeats (SSRs) that could potentially be used as genetic markers.

MIPS: curated databases and comprehensive secondary data resources in 2010

The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38 000 000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de).

Implementing reverse genetics in Rosaceae: analysis of T-DNA flanking sequences of insertional mutant lines in the diploid strawberry, Fragaria vesca

Reverse genetics is used for functional genomics research in model plants. To establish a model system for the systematic reverse genetics research in the Rosaceae family, we analyzed genomic DNA flanking the T-DNA insertions in 191 transgenic plants of the diploid strawberry, Fragaria vesca. One hundred and seventy-six T-DNA flanking sequences were amplified from the right border (RB) and 37 from the left border (LB) by thermal asymmetric interlaced PCR. Analysis of the T-DNA nick positions revealed that T-DNA was most frequently nicked at the cleavage sites. Analysis of 11 T-DNA integration sites indicated that T-DNA was integrated into the F. vesca genome by illegitimate recombination, as reported in other model plants: Arabidopsis, rice and tobacco. First, deletion of DNA was found at T-DNA integration target sites in all transgenic plants tested. Second, microsimilarities of a few base pairs between the left and/or right ends of the T-DNA and genomic sites were found in all transgenic plants tested. Finally, filler DNA was identified in four break-points. Out of 191 transgenic plants, T-DNA flanking sequences of 79 plants (41%) showed significant similarity to genes, elements or proteins of other plant species and 67 (35%) of the sequences are still unknown strawberry gene fragments. T-DNA flanking sequences of 126 plants (66%) showed homology to plant ESTs. This is the first report of T-DNA integration in a sizeable population of a rosaceous species. We have shown in this paper that T-DNA integration in strawberry is not random but directed by sequence microsimilarities in the host genome.

Evolution of chromosome 6 of Solanum species revealed by comparative fluorescence in situ hybridization mapping

Comparative genetic linkage mapping using a common set of DNA markers in related species is an important methodology in plant genome research. Here, we demonstrate a comparative fluorescence in situ hybridization (FISH) mapping strategy in plants. A set of 13 bacterial artificial chromosome clones spanning the entire length of potato chromosome 6 was used for pachytene chromosome-based FISH mapping in seven distantly related Solanum species including potato, tomato, and eggplant. We discovered one paracentric inversion and one pericentric inversion within specific lineages of these species. The comparative FISH mapping data revealed the ancestral structure of this chromosome. We demonstrate that comparative FISH mapping is an efficient and powerful methodology to study chromosomal evolution among plant species diverged for up to 12 million years.

Editorial [Hot topic: Plant Genomics in the 21st Century (Guest Editor: Chhandak Basu)

It is my great pleasure as a Guest Editor of the journal Current Genomics to present you with a ‘hot topic issue’ on plant genomics. The complete sequence of genome of model plant Arabidopsis thaliana was a boost for plant genomics research. Following the path of Arabidopsis sequencing, hundreds of plant genomes are being sequenced and we have ocean of sequence data. It is a challenge for us to interpret the functions of thousands of genes. Surely, computational biology will be a great help in predicting functions of plant genes. Publicly available web based sequence annotation softwares are another resource to annotate and characterize plant genes. It is a challenge and responsibility for plant biologists to provide food, fiber and fuel for this exponentially increasing population. Sequences of model plants and crop plants will help us to understand the genome architectures of the plants and will help us to identify economically important genes. It is a well-established fact that a great alternative for whole genome sequencing is development of an EST (Expressed Sequence Tags) database. The ESTs will give us a snapshot of whole genome with a small percentage of cost of whole genome sequencing. The next generation sequencing including 454 sequencing (Roche Applied Sciences), Solexa system (Illumina) and SOliD system (Applied Biosystems) are also great resources for plant genomicists. These technologies will generate enormous amount of sequencing data, which will be beneficial to understand the basic physiology of plants.

Challenges and Strategies for Next Generation Sequencing (NGS) Data Analysis

Next Generation Sequencing (NGS) technologies enable the resequencing of entire - genomes or the sampling of entire transcriptomes more effi ciently and economically and with greater depth than ever before. Rather than sequencing individual genomes, now it is possible to sequence hundreds or even thousands of related genomes to sample genetic diversity within and between germplasm pools. Identifying and tracking genetic variation is now so effi cient and precise that thousands of variants can be tracked within large populations. While NGS technologies have signifi cant implications on crop breeding, optimization and availability of appropriate methodologies and tools to analyze, visualize and intrepret NGS data are still in their infancy. With an objective to help crop genetics and breeding community to utilize NGS data for crop improvement, Generation Challenge Programme, Mexico and ICRISAT, India organized an international workshop entitled “Next Generation Sequencing (NGS) Data Analysis” during Jul 21-23, 2009. More than 30 scientists from nine countries (USA, UK, France, Korea, Japan, Australia, Mexico, Philippines and India) participated in the workshop. The workshop had four technical sessions and two brainstorming sessions in which participants shared their experience/views on data generation and analysis by using NGS technologies for accelerating plant genome research to understand genome dynamics as well as to facilitate crop breeding. This article presents a report on this international workshop. All presentations made in this workshop have been made available online (http:// www.icrisat.org/bt-publicdomain-ngs.htm).

A dynamic gene expression atlas covering the entire life cycle of rice

Growth and development of a plant are controlled by programmed expression of suits of genes at the appropriate time, tissue and abundance. Although genomic resources have been developed rapidly in recent years in rice, a model plant for cereal genome research, data of gene expression profiling are still insufficient to relate the developmental processes to transcriptomes, leaving a large gap between the genome sequence and phenotype. In this study, we generated genome-wide expression data by hybridizing 190 Affymetrix GeneChip Rice Genome Arrays with RNA from 39 tissues collected throughout the life cycle of the rice plant from two varieties, Zhenshan 97 and Minghui 63. Analyses of the global transcriptomes revealed many interesting features of dynamic patterns of gene expression across the tissues and stages. In total, 38 793 probe sets were detected as expressed and 69% of the expressed transcripts showed significantly variable expression levels among tissues/organs. We found that similarity of transcriptomes among organs corresponded well to their developmental relatedness. About 5.2% of the expressed transcripts showed tissue-specific expression in one or both varieties and 22.7% of the transcripts exhibited constitutive expression including 19 genes with high and stable expression in all the tissues. This dataset provided a versatile resource for plant genomic research, which can be used for associating the transcriptomes to the developmental processes, understanding the regulatory network of these processes, tracing the expression profile of individual genes and identifying reference genes for quantitative expression analyses.