3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists.

RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the '3D RNA-seq' App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

Insight on Genes Affecting Tuber Development in Potato upon Potato spindle tuber viroid (PSTVd) Infection.

Potato (Solanum tuberosum L) is a natural host of Potato spindle tuber viroid (PSTVd) which can cause characteristic symptoms on developing plants including stunting phenotype and distortion of leaves and tubers. PSTVd is the type species of the family Pospiviroidae, and can replicate in the nucleus and move systemically throughout the plant. It is not well understood how the viroid can affect host genes for successful invasion and which genes show altered expression levels upon infection. Our primary focus in this study is the identification of genes which can affect tuber formation since viroid infection can strongly influence tuber development and especially tuber shape. In this study, we used a large-scale method to identify differentially expressed genes in potato. We have identified defence, stress and sugar metabolism related genes having altered expression levels upon infection. Additionally, hormone pathway related genes showed significant up- or down-regulation. DWARF1/DIMINUTO, Gibberellin 7-oxidase and BEL5 transcripts were identified and validated showing differential expression in viroid infected tissues. Our study suggests that gibberellin and brassinosteroid pathways have a possible role in tuber development upon PSTVd infection.

Physiological, biochemical and molecular responses of the potato (Solanum tuberosum L.) plant to moderately elevated temperature.

Although significant work has been undertaken regarding the response of model and crop plants to heat shock during the acclimatory phase, few studies have examined the steady-state response to the mild heat stress encountered in temperate agriculture. In the present work, we therefore exposed tuberizing potato plants to mildly elevated temperatures (30/20 °C, day/night) for up to 5 weeks and compared tuber yield, physiological and biochemical responses, and leaf and tuber metabolomes and transcriptomes with plants grown under optimal conditions (22/16 °C). Growth at elevated temperature reduced tuber yield despite an increase in net foliar photosynthesis. This was associated with major shifts in leaf and tuber metabolite profiles, a significant decrease in leaf glutathione redox state and decreased starch synthesis in tubers. Furthermore, growth at elevated temperature had a profound impact on leaf and tuber transcript expression with large numbers of transcripts displaying a rhythmic oscillation at the higher growth temperature. RT-PCR revealed perturbation in the expression of circadian clock transcripts including StSP6A, previously identified as a tuberization signal. Our data indicate that potato plants grown at moderately elevated temperatures do not exhibit classic symptoms of abiotic stress but that tuber development responds via a diversity of biochemical and molecular signals.

Identification and characterization of miRNA transcriptome in potato by high-throughput sequencing.

Micro RNAs (miRNAs) represent a class of short, non-coding, endogenous RNAs which play important roles in post-transcriptional regulation of gene expression. While the diverse functions of miRNAs in model plants have been well studied, the impact of miRNAs in crop plant biology is poorly understood. Here we used high-throughput sequencing and bioinformatics analysis to analyze miRNAs in the tuber bearing crop potato (Solanum tuberosum). Small RNAs were analysed from leaf and stolon tissues. 28 conserved miRNA families were found and potato-specific miRNAs were identified and validated by RNA gel blot hybridization. The size, origin and predicted targets of conserved and potato specific miRNAs are described. The large number of miRNAs and complex population of small RNAs in potato suggest important roles for these non-coding RNAs in diverse physiological and metabolic pathways.

Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function.

Pollen, the male gametophyte of flowering plants, represents an ideal biological system to study developmental processes, such as cell polarity, tip growth, and morphogenesis. Upon hydration, the metabolically quiescent pollen rapidly switches to an active state, exhibiting extremely fast growth. This rapid switch requires relevant proteins to be stored in the mature pollen, where they have to retain functionality in a desiccated environment. Using a shotgun proteomics approach, we unambiguously identified approximately 3500 proteins in Arabidopsis pollen, including 537 proteins that were not identified in genetic or transcriptomic studies. To generate this comprehensive reference data set, which extends the previously reported pollen proteome by a factor of 13, we developed a novel deterministic peptide classification scheme for protein inference. This generally applicable approach considers the gene model-protein sequence-protein accession relationships. It allowed us to classify and eliminate ambiguities inherently associated with any shotgun proteomics data set, to report a conservative list of protein identifications, and to seamlessly integrate data from previous transcriptomics studies. Manual validation of proteins unambiguously identified by a single, information-rich peptide enabled us to significantly reduce the false discovery rate, while keeping valuable identifications of shorter and lower abundant proteins. Bioinformatic analyses revealed a higher stability of pollen proteins compared to those of other tissues and implied a protein family of previously unknown function in vesicle trafficking. Interestingly, the pollen proteome is most similar to that of seeds, indicating physiological similarities between these developmentally distinct tissues.