Patrick Xuechun Zhao

psRNATarget: a plant small RNA target analysis server

Plant endogenous non-coding short small RNAs (20–24 nt), including microRNAs (miRNAs) and a subset of small interfering RNAs (ta-siRNAs), play important role in gene expression regulatory networks (GRNs). For example, many transcription factors and development-related genes have been reported as targets of these regulatory small RNAs. Although a number of miRNA target prediction algorithms and programs have been developed, most of them were designed for animal miRNAs which are significantly different from plant miRNAs in the target recognition process. These differences demand the development of separate plant miRNA (and ta-siRNA) target analysis tool(s). We present psRNATarget, a plant small RNA target analysis server, which features two important analysis functions: (i) reverse complementary matching between small RNA and target transcript using a proven scoring schema, and (ii) target-site accessibility evaluation by calculating unpaired energy (UPE) required to ‘open’ secondary structure around small RNA’s target site on mRNA. The psRNATarget incorporates recent discoveries in plant miRNA target recognition, e.g. it distinguishes translational and post-transcriptional inhibition, and it reports the number of small RNA/target site pairs that may affect small RNA binding activity to target transcript. The psRNATarget server is designed for high-throughput analysis of next-generation data with an efficient distributed computing back-end pipeline that runs on a Linux cluster. The server front-end integrates three simplified user-friendly interfaces to accept user-submitted or preloaded small RNAs and transcript sequences; and outputs a comprehensive list of small RNA/target pairs along with the online tools for batch downloading, key word searching and results sorting. The psRNATarget server is freely available at http://plantgrn.noble.org/psRNATarget/.

A gene expression atlas of the model legume Medicago truncatula

Legumes played central roles in the development of agriculture and civilization, and today account for approximately one-third of the worlds primary crop production. Unfortunately, most cultivated legumes are poor model systems for genomic research. Therefore, Medicago truncatula, which has a relatively small diploid genome, has been adopted as a model species for legume genomics. To enhance its value as a model, we have generated a gene expression atlas that provides a global view of gene expression in all major organ systems of this species, with special emphasis on nodule and seed development. The atlas reveals massive differences in gene expression between organs that are accompanied by changes in the expression of key regulatory genes, such as transcription factor genes, which presumably orchestrate genetic reprogramming during development and differentiation. Interestingly, many legume-specific genes are preferentially expressed in nitrogen-fixing nodules, indicating that evolution endowed them with special roles in this unique and important organ. Comparative transcriptome analysis of Medicago versus Arabidopsis revealed significant divergence in developmental expression profiles of orthologous genes, which indicates that phylogenetic analysis alone is insufficient to predict the function of orthologs in different species. The data presented here represent an unparalleled resource for legume functional genomics, which will accelerate discoveries in legume biology.

Large‐scale insertional mutagenesis using the Tnt1 retrotransposon in the model legume Medicago truncatula

Medicago truncatula is a fast-emerging model for the study of legume functional biology. We used the tobacco retrotransposon Tnt1 to tag the Medicago genome and generated over 7600 independent lines representing an estimated 190,000 insertion events. Tnt1 inserted on average at 25 different locations per genome during tissue culture, and insertions were stable during subsequent generations in soil. Analysis of 2461 Tnt1 flanking sequence tags (FSTs) revealed that Tnt1 appears to prefer gene-rich regions. The proportion of Tnt1 insertion in coding sequences was 34.1%, compared to the expected 15.9% if random insertions were to occur. However, Tnt1 showed neither unique target site specificity nor strong insertion hot spots, although some genes were more frequently tagged than others. Forward-genetic screening of 3237 R(1) lines resulted in identification of visible mutant phenotypes in approximately 30% of the regenerated lines. Tagging efficiency appears to be high, as all of the 20 mutants examined so far were found to be tagged. Taking the properties of Tnt1 into account and assuming 1.7 kb for the average M. truncatula gene size, we estimate that approximately 14,000-16,000 lines would be sufficient for 90% gene tagging coverage in M. truncatula. This is in contrast to more than 500,000 lines required to achieve the same saturation level using T-DNA tagging. Our data demonstrate that Tnt1 is an efficient insertional mutagen in M. truncatula, and could be a primary choice for other plant species with large genomes.

Transcript and proteomic analysis of developing white lupin (Lupinus albus L.) roots

BackgroundWhite lupin (Lupinus albus L.) roots efficiently take up and accumulate (heavy) metals, adapt to phosphate deficiency by forming cluster roots, and secrete antimicrobial prenylated isoflavones during development. Genomic and proteomic approaches were applied to identify candidate genes and proteins involved in antimicrobial defense and (heavy) metal uptake and translocation.ResultsA cDNA library was constructed from roots of white lupin seedlings. Eight thousand clones were randomly sequenced and assembled into 2,455 unigenes, which were annotated based on homologous matches in the NCBInr protein database. A reference map of developing white lupin root proteins was established through 2-D gel electrophoresis and peptide mass fingerprinting. High quality peptide mass spectra were obtained for 170 proteins. Microsomal membrane proteins were separated by 1-D gel electrophoresis and identified by LC-MS/MS. A total of 74 proteins were putatively identified by the peptide mass fingerprinting and the LC-MS/MS methods. Genomic and proteomic analyses identified candidate genes and proteins encoding metal binding and/or transport proteins, transcription factors, ABC transporters and phenylpropanoid biosynthetic enzymes.ConclusionThe combined EST and protein datasets will facilitate the understanding of white lupins response to biotic and abiotic stresses and its utility for phytoremediation. The root ESTs provided 82 perfect simple sequence repeat (SSR) markers with potential utility in breeding white lupin for enhanced agronomic traits.

Genome-wide analysis of phenylpropanoid defence pathways

Phenylpropanoids can function as preformed and inducible antimicrobial compounds, as well as signal molecules, in plant-microbe interactions. Since we last reviewed the field 8 years ago, there has been a huge increase in our understanding of the genes of phenylpropanoid biosynthesis and their regulation, brought about largely by advances in genome technology, from whole-genome sequencing to massively parallel gene expression profiling. Here, we present an overview of the biosynthesis and roles of phenylpropanoids in plant defence, together with an analysis of confirmed and predicted phenylpropanoid pathway genes in the sequenced genomes of 11 plant species. Examples are provided of phylogenetic and expression clustering analyses, and the large body of underlying genomic data is provided through a website accessible from the article.

Terpene Biosynthesis in Glandular Trichomes of Hop

Hop (Humulus lupulus L. Cannabaceae) is an economically important crop for the brewing industry, where it is used to impart flavor and aroma to beer, and has also drawn attention in recent years due to its potential pharmaceutical applications. Essential oils (mono- and sesquiterpenes), bitter acids (prenylated polyketides), and prenylflavonoids are the primary phytochemical components that account for these traits, and all accumulate at high concentrations in glandular trichomes of hop cones. To understand the molecular basis for terpene accumulation in hop trichomes, a trichome cDNA library was constructed and 9,816 cleansed expressed sequence tag (EST) sequences were obtained from random sequencing of 16,152 cDNA clones. The ESTs were assembled into 3,619 unigenes (1,101 contigs and 2,518 singletons). Putative functions were assigned to the unigenes based on their homology to annotated sequences in the GenBank database. Two mono- and two sesquiterpene synthases identified from the EST collection were expressed in Escherichia coli. Hop MONOTERPENE SYNTHASE2 formed the linear monterpene myrcene from geranyl pyrophosphate, whereas hop SESQUITERPENE SYNTHASE1 (HlSTS1) formed both caryophyllene and humulene from farnesyl pyrophosphate. Together, these enzymes account for the production of the major terpene constituents of the hop trichomes. HlSTS2 formed the minor sesquiterpene constituent germacrene A, which was converted to β-elemene on chromatography at elevated temperature. We discuss potential functions for other genes expressed at high levels in developing hop trichomes.

The Medicago truncatula gene expression atlas web server

BackgroundLegumes (Leguminosae or Fabaceae) play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA) web server for this purpose.DescriptionThe Medicago truncatula Gene Expression Atlas (MtGEA) web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible at: http://bioinfo.noble.org/gene-atlas/.ConclusionsThe MtGEA web server has a well managed rich data set, and offers data retrieval and analysis tools provided in the web platform. Its proven to be a powerful resource for plant biologists to effectively and efficiently identify Medicago transcripts of interest from a multitude of aspects, formulate hypothesis about gene function, and overall interpret the Medicago genome from a systematic point of view.

Computational analysis of miRNA targets in plants: current status and challenges

Plant microRNAs (miRNA) target recognition mechanism was once thought to be simple and straightforward, i.e. through perfect reverse complementary matching; therefore, very few target prediction tools and algorithms were developed for plants as compared to those for animals. However, the discovery of transcription suppression and the more recent observation of widespread translational regulation by miRNAs highlight the enormous diversity and complexity of gene regulation in plant systems. This, in turn, necessitates the need for advanced computational tools/algorithms for comprehensive miRNA target analysis to help understand miRNA regulatory mechanisms. Yet, advanced/comprehensive plant miRNA target analysis tools are still lacking despite the desirability and importance of such tools, especially the ability of predicting translational inhibition and integrating transcriptome data. This review focuses on recent progress in plant miRNA target recognition mechanism, principles of target prediction based on these understandings, comparison of current prediction tools and algorithms for plant miRNA target analysis and the outlook for future directions in the development of plant miRNA target tools and algorithms.

TrichOME: A Comparative Omics Database for Plant Trichomes

Plant secretory trichomes have a unique capacity for chemical synthesis and secretion and have been described as biofactories for the production of natural products. However, until recently, most trichome-specific metabolic pathways and genes involved in various trichome developmental stages have remained unknown. Furthermore, only a very limited amount of plant trichome genomics information is available in scattered databases. We present an integrated “omics” database, TrichOME, to facilitate the study of plant trichomes. The database hosts a large volume of functional omics data, including expressed sequence tag/unigene sequences, microarray hybridizations from both trichome and control tissues, mass spectrometry-based trichome metabolite profiles, and trichome-related genes curated from published literature. The expressed sequence tag/unigene sequences have been annotated based upon sequence similarity with popular databases (e.g. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Transporter Classification Database). The unigenes, metabolites, curated genes, and probe sets have been mapped against each other to enable comparative analysis. The database also integrates bioinformatics tools with a focus on the mining of trichome-specific genes in unigenes and microarray-based gene expression profiles. TrichOME is a valuable and unique resource for plant trichome research, since the genes and metabolites expressed in trichomes are often underrepresented in regular non-tissue-targeted cDNA libraries. TrichOME is freely available at http://www.planttrichome.org/.

Genomic Inventory and Transcriptional Analysis of Medicago truncatula Transporters

Transporters move hydrophilic substrates across hydrophobic biological membranes and play key roles in plant nutrition, metabolism, and signaling and, consequently, in plant growth, development, and responses to the environment. To initiate and support systematic characterization of transporters in the model legume Medicago truncatula, we identified 3,830 transporters and classified 2,673 of these into 113 families and 146 subfamilies. Analysis of gene expression data for 2,611 of these transporters identified 129 that are expressed in an organ-specific manner, including 50 that are nodule specific and 36 specific to mycorrhizal roots. Further analysis uncovered 196 transporters that are induced at least 5-fold during nodule development and 44 in roots during arbuscular mycorrhizal symbiosis. Among the nodule- and mycorrhiza-induced transporter genes are many candidates for known transport activities in these beneficial symbioses. The data presented here are a unique resource for the selection and functional characterization of legume transporters.