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Excessive generation of reactive oxygen species (ROS) due to environmental stresses critically effects plant development and productivity. Plants efficiently detoxify ROS by both non-enzymatic and enzymatic mechanisms. Plant glutathione peroxidases (GPXs) are non-haeme thiol peroxidases that catalyze the reduction of HO (or organic hydroperoxides) to water or the respective alcohols using reduced glutathione or thioredoxin. Genome-wide analysis of the known GPXs from rice and Arabidopsis genomes revealed their gene structure, conserved motifs, localization and tissue-specific and/or organ-specific expression profiles in response to various abiotic stresses. Among the eight genes that encoded GPX proteins from Arabidopsis, AtGPX3 showed two alternate spliced forms that spread over four chromosomes. Five genes encoded for rice GPX proteins, while OsGPX1 showed three spliced variants that were distributed on five chromosomes. Utilizing the publicly available microarray and massively parallel signature sequencing (MPSS) data, the GPXs revealed stress-responsive, tissue-specific and/or organ-specific expression profiles. Presence of important cis-regulatory elements analyzed in the GPX promoter sequences revealed their overlapping or specific responsiveness to different abiotic stresses. Co-expression data of Arabidopsis GPX genes suggested that various protein kinase family members and stress-responsive proteins co-expressed with the GPX proteins. Transcript profile of rice GPX genes by qRT-PCR validated their functional roles in signal transduction and stress pathways. Results revealed that plant GPXs play a crucial role in response to stress and significantly contribute towards their growth and development. [ABSTRACT FROM AUTHOR]

Background: Milling yield and eating quality are two important grain quality traits in rice. To identify the genes involved in these two traits, we performed a deep transcriptional analysis of developing seeds using both massively parallel signature sequencing (MPSS) and sequencing-by-synthesis (SBS). Five MPSS and five SBS libraries were constructed from 6-day-old developing seeds of Cypress (high milling yield), LaGrue (low milling yield), Ilpumbyeo (high eating quality), YR15965 (low eating quality), and Nipponbare (control). Results: The transcriptomes revealed by MPSS and SBS had a high correlation co-efficient (0.81 to 0.90), and about 70% of the transcripts were commonly identified in both types of the libraries. SBS, however, identified 30% more transcripts than MPSS. Among the highly expressed genes in Cypress and Ilpumbyeo, over 100 conserved cis regulatory elements were identified. Numerous specifically expressed transcription factor (TF) genes were identified in Cypress (282), LaGrue (312), Ilpumbyeo (363), YR15965 (260), and Nipponbare (357). Many key grain quality-related genes (i.e., genes involved in starch metabolism, aspartate amino acid metabolism, storage and allergenic protein synthesis, and seed maturation) that were expressed at high levels underwent alternative splicing and produced antisense transcripts either in Cypress or Ilpumbyeo. Further, a time course RT-PCR analysis confirmed a higher expression level of genes involved in starch metabolism such as those encoding ADP glucose pyrophosphorylase (AGPase) and granule bound starch synthase I (GBSS I) in Cypress than that in LaGrue during early seed development. Conclusion: This study represents the most comprehensive analysis of the developing seed transcriptome of rice available to date. Using two high throughput sequencing methods, we identified many differentially expressed genes that may affect milling yield or eating quality in rice. Many of the identified genes are involved in the biosynthesis of starch, aspartate family amino acids, and storage proteins. Some of the differentially expressed genes could be useful for the development of molecular markers if they are located in a known QTL region for milling yield or eating quality in the rice genome. Therefore, our comprehensive and deep survey of the developing seed transcriptome in five rice cultivars has provided a rich genomic resource for further elucidating the molecular basis of grain quality in rice. [ABSTRACT FROM AUTHOR]

Abstract: Several methods now exist for identifying and quantifying many biological events in parallel and in a relatively unbiased fashion. For gene expression experiments, cloning approaches have been supplemented with microarray platforms over the past few years. The focus of this review is on deep sequencing, a new set of techniques that can be used to both identify RNA species and quantify them in a massively parallel fashion. Deep sequencing has some advantages over other methods, driven largely by the high depth of coverage for any library of nucleic acids. This allows, for example, estimates of alternative splicing and untranslated region utilization. We will discuss how deep sequencing methods are being applied to characterization of gene expression in the brain and how these technologies might develop over the next few years. [Copyright &y& Elsevier]

Our limited understanding of plant promoters does not allow us to recognize any core promoter elements for the majority of plant promoters. To understand the promoter architecture of Arabidopsis, we used the combined approach of in silico detection of novel core promoter elements and large-scale determination of transcription start sites (TSSs). To this end, we developed a novel methodology for TSS identification, using a combination of the cap-trapper and massively parallel signature sequencing methods. This technique, CT–MPSS, allowed us to identify 158 237 Arabidopsis TSS tags corresponding to 38 311 TSS loci, which provides an opportunity for quantitative analysis of plant promoters. The expression characteristics of these promoters were analyzed with respect to core promoter elements detected by our in silico analyses, revealing that Arabidopsis promoters contain two main types of elements with exclusive characteristics, the TATA type and the GA type. The TATA-type promoters tend to be associated with the Y Patch and the Inr motif, and cause high expression with sharp-peak TSS clusters. By contrast, the GA type produces broad-type TSS clusters. Unlike mammalian promoters, plant promoters are not associated with CpG islands. However, plant-specific GA-type promoters share some characteristics with mammalian CpG-type promoters. [ABSTRACT FROM AUTHOR]

Transcription factors play a key role in integrating and modulating biological information. In this study, we comprehensively measured the changing abundances of mRNAs over a time course of activation of human peripheral-blood-derived mononuclear cells (‘macrophages’) with lipopolysaccharide. Global and dynamic analysis of transcription factors in response to a physiological stimulus has yet to be achieved in a human system, and our efforts significantly advanced this goal. We used multiple global high-throughput technologies for measuring mRNA levels, including massively parallel signature sequencing and GeneChip microarrays. We identified 92 of 1,288 known human transcription factors as having significantly measurable changes during our 24-h time course. At least 42 of these changes were previously unidentified in this system. Our data demonstrate that some transcription factors operate in a functional range below 10 transcripts per cell, whereas others operate in a range three orders of magnitude greater. The highly reproducible response of many mRNAs indicates feedback control. A broad range of activation kinetics was observed; thus, combinatorial regulation by small subsets of transcription factors would permit almost any timing input to cis-regulatory elements controlling gene transcription. [ABSTRACT FROM AUTHOR]

The massively parallel signature sequencing (MPSS) provides a greater depth of coverage than expressed sequence tag scan or microarray and provides a comprehensive expression profile. We used the MPSS technology to uncover gene expression profiling in the early embryonic gonads and primordial germ cells (PGCs) in the chicken. Total numbers of sequenced signatures were 1,012,533 and 995,676 for the PGCs and gonad, respectively. Using a noise distribution model, we found that 1.67% of all signatures are expressed at a higher level in PCGs and 2.81% of all signatures are expressed at a higher level in the gonad. The MPSS data are presented via an interactive web interface available at http://snugenome.snu.ac.kr/MPSS. The MPSS data have been submitted to the Gene Expression Omnibus of the National Center for Biotechnology Information (accession number GSM137300 and GSM137301 for PGCs and gonad, respectively). [ABSTRACT FROM AUTHOR]

Small RNAs play pivotal roles in regulating gene expression in higher eukaryotes. Among them, trans-acting siRNAs (ta-siRNAs) are a class of small RNAs that regulate plant development. The biogenesis of ta-siRNA depends on microRNA-targeted cleavage followed by the DCL4-mediated production of small RNAs phased in 21-nt increments relative to the cleavage site on both strands. To find TAS genes, we have used these characteristics to develop the first computational algorithm that allows for a comprehensive search and statistical evaluation of putative TAS genes from any given small RNA database. A search in Arabidopsis small RNA massively parallel signature sequencing (MPSS) databases with this algorithm revealed both known and previously unknown ta-siRNA-producing loci. We experimentally validated the biogenesis of ta-siRNAs from two PPR genes and the trans-acting activity of one of the ta-siRNAs. The production of ta-siRNAs from the identified PPR genes was directed by the cleavage of a TAS2-derived ta-siRNA instead of by microRNAs as was reported previously for TAS1a, -b, -c, TAS2, and TAS3 genes. Our results indicate the existence of a small RNA regulatory cascade initiated by miR173-directed cleavage and followed by the consecutive production of ta-siRNAs from two TAS genes. [ABSTRACT FROM AUTHOR]

The past few years have seen remarkable progress in our understanding of stem cell biology. The wealth of genomic data and the multiplicity of sources have enabled researchers to begin to profile stem cells in detail. In this paper we describe the biological and technical controls necessary to obtain reliable data and the relative merits of various large-scale analytical techniques including microarray, expressed sequence tag enumeration, serial analysis of gene expression and massively parallel signature sequencing. We suggest that while much has been learned, additional information remains to be gleaned by meta-analysis of existing data. Copyright © 2006 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Cytokinins have been implicated in developmental and growth processes in plants including cell division, chloroplast biogenesis, shoot meristem initiation and senescence. The regulation of these processes requires changes in cytokinin-responsive gene expression. Here, we induced the expression of a bacterial isopentenyl transferase gene, IPT, in transgenic Arabidopsis thaliana seedlings to study the regulation of genome-wide gene expression in response to endogenous cytokinin. Using MPSS (massively parallel signature sequencing) we identified 823 and 917 genes that were up- and downregulated, respectively, following 24 h of IPT induction. When comparing the response to cytokinin after 6 and 24 h, we identified different clusters of genes showing a similar course of regulation. Our study provides researchers with the opportunity to rapidly assess whether genes of interest are regulated by cytokinins. [Copyright &y& Elsevier]

Massively parallel signature sequencing (MPSS) is one of the newest tools available for conducting in-depth expression profiling. MPSS is an open-ended platform that analyses the level of expression of virtually all genes in a sample by counting the number of individual mRNA molecules produced from each gene. There is no requirement that genes be identified and characterised prior to conducting an experiment. MPSS has a routine sensitivity at a level of a few molecules of mRNA per cell, and the datasets are in a digital format that simplifies the management and analysis of the data. Therefore, of the various microarray and non-microarray technologies currently available, MPSS provides many advantages for generating the type of complete datasets that will help to facilitate hypothesis-driven experiments in the era of digital biology. [ABSTRACT FROM PUBLISHER]