Co-expression network of heat-response transcripts: A glimpse into how splicing factors impact rice basal thermotolerance.

To identify novel solutions to improve rice yield under rising temperatures, molecular components of thermotolerance must be better understood. Alternative splicing (AS) is a major post-transcriptional mechanism impacting plant tolerance against stresses, including heat stress (HS). AS is largely regulated by splicing factors (SFs) and recent studies have shown their involvement in temperature response. However, little is known about the splicing networks between SFs and AS transcripts in the HS response. To expand this knowledge, we constructed a co-expression network based on a publicly available RNA-seq dataset that explored rice basal thermotolerance over a time-course. Our analyses suggest that the HS-dependent control of the abundance of specific transcripts coding for SFs might explain the widespread, coordinated, complex, and delicate AS regulation of critical genes during a plant's inherent response to extreme temperatures. AS changes in these critical genes might affect many aspects of plant biology, from organellar functions to cell death, providing relevant regulatory candidates for future functional studies of basal thermotolerance.

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis.

BACKGROUND: Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. RESULTS: We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts-twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. CONCLUSIONS: AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

Experimental Design for Time-Series RNA-Seq Analysis of Gene Expression and Alternative Splicing.

RNA-sequencing (RNA-seq) is currently the method of choice for analysis of differential gene expression. To fully exploit the wealth of data generated from genome-wide transcriptomic approaches, the initial design of the experiment is of paramount importance. Biological rhythms in nature are pervasive and are driven by endogenous gene networks collectively known as circadian clocks. Measuring circadian gene expression requires time-course experiments which take into account time-of-day factors influencing variability in expression levels. We describe here an approach for characterizing diurnal changes in expression and alternative splicing for plants undergoing cooling. The method uses inexpensive everyday laboratory equipment and utilizes an RNA-seq application (3D RNA-seq) that can handle complex experimental designs and requires little or no prior bioinformatics expertise.

Reading between the Lines: RNA-seq Data Mining Reveals the Alternative Message of the Rice Leaf Transcriptome in Response to Heat Stress.

Rice (Oryza sativa L.) is a major food crop but heat stress affects its yield and grain quality. To identify mechanistic solutions to improve rice yield under rising temperatures, molecular responses of thermotolerance must be understood. Transcriptional and post-transcriptional controls are involved in a wide range of plant environmental responses. Alternative splicing (AS), in particular, is a widespread mechanism impacting the stress defence in plants but it has been completely overlooked in rice genome-wide heat stress studies. In this context, we carried out a robust data mining of publicly available RNA-seq datasets to investigate the extension of heat-induced AS in rice leaves. For this, datasets of interest were subjected to filtering and quality control, followed by accurate transcript-specific quantifications. Powerful differential gene expression (DE) and differential AS (DAS) identified 17,143 and 2162 heat response genes, respectively, many of which are novel. Detailed analysis of DAS genes coding for key regulators of gene expression suggests that AS helps shape transcriptome and proteome diversity in response to heat. The knowledge resulting from this study confirmed a widespread transcriptional and post-transcriptional response to heat stress in plants, and it provided novel candidates for rapidly advancing rice breeding in response to climate change.

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.

Cold-Dependent Expression and Alternative Splicing of Arabidopsis Long Non-coding RNAs.

Plants re-program their gene expression when responding to changing environmental conditions. Besides differential gene expression, extensive alternative splicing (AS) of pre-mRNAs and changes in expression of long non-coding RNAs (lncRNAs) are associated with stress responses. RNA-sequencing of a diel time-series of the initial response of Arabidopsis thaliana rosettes to low temperature showed massive and rapid waves of both transcriptional and AS activity in protein-coding genes. We exploited the high diversity of transcript isoforms in AtRTD2 to examine regulation and post-transcriptional regulation of lncRNA gene expression in response to cold stress. We identified 135 lncRNA genes with cold-dependent differential expression (DE) and/or differential alternative splicing (DAS) of lncRNAs including natural antisense RNAs, sORF lncRNAs, and precursors of microRNAs (miRNAs) and trans-acting small-interfering RNAs (tasiRNAs). The high resolution (HR) of the time-series allowed the dynamics of changes in transcription and AS to be determined and identified early and adaptive transcriptional and AS changes in the cold response. Some lncRNA genes were regulated only at the level of AS and using plants grown at different temperatures and a HR time-course of the first 3 h of temperature reduction, we demonstrated that the AS of some lncRNAs is highly sensitive to small temperature changes suggesting tight regulation of expression. In particular, a splicing event in TAS1a which removed an intron that contained the miR173 processing and phased siRNAs generation sites was differentially alternatively spliced in response to cold. The cold-induced reduction of the spliced form of TAS1a and of the tasiRNAs suggests that splicing may enhance production of the siRNAs. Our results identify candidate lncRNAs that may contribute to the regulation of expression that determines the physiological processes essential for acclimation and freezing tolerance.

Alternative Splicing of Circadian Clock Genes Correlates With Temperature in Field-Grown Sugarcane.

Alternative Splicing (AS) is a mechanism that generates different mature transcripts from precursor mRNAs (pre-mRNAs) of the same gene. In plants, a wide range of physiological and metabolic events are related to AS, as well as fast responses to changes in temperature. AS is present in around 60% of intron-containing genes in Arabidopsis, 46% in rice, and 38% in maize and it is widespread among the circadian clock genes. Little is known about how AS influences the circadian clock of C4 plants, like commercial sugarcane, a C4 crop with a complex hybrid genome. This work aims to test if the daily dynamics of AS forms of circadian clock genes are regulated by environmental factors, such as temperature, in the field. A systematic search for AS in five sugarcane clock genes, ScLHY, ScPRR37, ScPRR73, ScPRR95, and ScTOC1 using different organs of sugarcane sampled during winter, with 4 months old plants, and during summer, with 9 months old plants, revealed temperature- and organ-dependent expression of at least one alternatively spliced isoform in all genes. Expression of AS isoforms varied according to the season. Our results suggest that AS events in circadian clock genes are correlated with temperature.

High-Resolution RT-PCR Analysis of Alternative Barley Transcripts.

Assembly of the barley genome and extensive use of RNA-seq has resulted in an abundance of gene expression data and the recognition of wide-scale production of alternatively spliced transcripts. Here, we describe in detail a high-resolution reverse transcription-PCR based panel (HR RT-PCR) that confirms the accuracy of alternatively spliced transcripts from RNA-seq and allows quantification of changes in the proportion of splice isoforms between different experimental conditions, time points, tissues, genotypes, ecotypes, and treatments. By validating a selection of barley genes, use of the panel gives confidence or otherwise to the genome-wide global changes in alternatively spliced transcripts reported by RNA-seq. This simple assay can readily be applied to perform detailed transcript isoform analysis for any gene in any species.

Rapid and Dynamic Alternative Splicing Impacts the Arabidopsis Cold Response Transcriptome.

Plants have adapted to tolerate and survive constantly changing environmental conditions by reprogramming gene expression The dynamics of the contribution of alternative splicing (AS) to stress responses are unknown. RNA-sequencing of a time-series of Arabidopsis thaliana plants exposed to cold determines the timing of significant AS changes. This shows a massive and rapid AS response with coincident waves of transcriptional and AS activity occurring in the first few hours of temperature reduction and further AS throughout the cold. In particular, hundreds of genes showed changes in expression due to rapidly occurring AS in response to cold ("early AS" genes); these included numerous novel cold-responsive transcription factors and splicing factors/RNA binding proteins regulated only by AS. The speed and sensitivity to small temperature changes of AS of some of these genes suggest that fine-tuning expression via AS pathways contributes to the thermo-plasticity of expression. Four early AS splicing regulatory genes have been shown previously to be required for freezing tolerance and acclimation; we provide evidence of a fifth gene, U2B"-LIKE Such factors likely drive cascades of AS of downstream genes that, alongside transcription, modulate transcriptome reprogramming that together govern the physiological and survival responses of plants to low temperature.

How does temperature affect splicing events? Isoform switching of splicing factors regulates splicing of LATE ELONGATED HYPOCOTYL (LHY).

One of the ways in which plants can respond to temperature is via alternative splicing (AS). Previous work showed that temperature changes affected the splicing of several circadian clock gene transcripts. Here, we investigated the role of RNA-binding splicing factors (SFs) in temperature-sensitive AS of the clock gene LATE ELONGATED HYPOCOTYL (LHY). We characterized, in wild type plants, temperature-associated isoform switching and expression patterns for SF transcripts from a high-resolution temperature and time series RNA-seq experiment. In addition, we employed quantitative RT-PCR of SF mutant plants to explore the role of the SFs in cooling-associated AS of LHY. We show that the splicing and expression of several SFs responds sufficiently, rapidly, and sensitively to temperature changes to contribute to the splicing of the 5'UTR of LHY. Moreover, the choice of splice site in LHY was altered in some SF mutants. The splicing of the 5'UTR region of LHY has characteristics of a molecular thermostat, where the ratio of transcript isoforms is sensitive to temperature changes as modest as 2 °C and is scalable over a wide dynamic range of temperature. Our work provides novel insight into SF-mediated coupling of the perception of temperature to post-transcriptional regulation of the clock.

TSIS: an R package to infer alternative splicing isoform switches for time-series data.

SUMMARY: An alternative splicing isoform switch is where a pair of transcript isoforms reverse their relative expression abundances in response to external or internal stimuli. Although computational methods are available to study differential alternative splicing, few tools for detection of isoform switches exist and these are based on pairwise comparisons. Here, we provide the TSIS R package, which is the first tool for detecting significant transcript isoform switches in time-series data. The main steps of TSIS are to search for the isoform switch points in the time-series, characterize the switches and filter the results with user input parameters. All the functions are integrated into a Shiny App for ease of implementation of the analysis. AVAILABILITY AND IMPLEMENTATION: The TSIS package is available on GitHub: https://github.com/wyguo/TSIS. CONTACT: runxuan.zhang@hutton.ac.uk.

Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size.

BACKGROUND: Co-expression has been widely used to identify novel regulatory relationships using high throughput measurements, such as microarray and RNA-seq data. Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes. For large networks, simulated expression data usually consist of hundreds or thousands of profiles with different perturbations or knock-outs, which is uncommon in real experiments due to their cost and the amount of work required. Thus, the performances of co-expression network analysis methods on large co-expression networks consisting of a few thousand nodes, with only a small number of profiles with a single perturbation, which more accurately reflect normal experimental conditions, are generally uncharacterized and unknown. METHODS: We proposed a novel network inference methods based on Relevance Low order Partial Correlation (RLowPC). RLowPC method uses a two-step approach to select on the high-confidence edges first by reducing the search space by only picking the top ranked genes from an intial partial correlation analysis and, then computes the partial correlations in the confined search space by only removing the linear dependencies from the shared neighbours, largely ignoring the genes showing lower association. RESULTS: We selected six co-expression-based methods with good performance in evaluation studies from the literature: Partial correlation, PCIT, ARACNE, MRNET, MRNETB and CLR. The evaluation of these methods was carried out on simulated time-series data with various network sizes ranging from 100 to 3000 nodes. Simulation results show low precision and recall for all of the above methods for large networks with a small number of expression profiles. We improved the inference significantly by refinement of the top weighted edges in the pre-inferred partial correlation networks using RLowPC. We found improved performance by partitioning large networks into smaller co-expressed modules when assessing the method performance within these modules. CONCLUSIONS: The evaluation results show that current methods suffer from low precision and recall for large co-expression networks where only a small number of profiles are available. The proposed RLowPC method effectively reduces the indirect edges predicted as regulatory relationships and increases the precision of top ranked predictions. Partitioning large networks into smaller highly co-expressed modules also helps to improve the performance of network inference methods. The RLowPC R package for network construction, refinement and evaluation is available at GitHub: https://github.com/wyguo/RLowPC .

A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing.

Alternative splicing generates multiple transcript and protein isoforms from the same gene and thus is important in gene expression regulation. To date, RNA-sequencing (RNA-seq) is the standard method for quantifying changes in alternative splicing on a genome-wide scale. Understanding the current limitations of RNA-seq is crucial for reliable analysis and the lack of high quality, comprehensive transcriptomes for most species, including model organisms such as Arabidopsis, is a major constraint in accurate quantification of transcript isoforms. To address this, we designed a novel pipeline with stringent filters and assembled a comprehensive Reference Transcript Dataset for Arabidopsis (AtRTD2) containing 82,190 non-redundant transcripts from 34 212 genes. Extensive experimental validation showed that AtRTD2 and its modified version, AtRTD2-QUASI, for use in Quantification of Alternatively Spliced Isoforms, outperform other available transcriptomes in RNA-seq analysis. This strategy can be implemented in other species to build a pipeline for transcript-level expression and alternative splicing analyses.

High-quality reference transcript datasets hold the key to transcript-specific RNA-sequencing analysis in plants.

525 I. 525 II. 526 III. 527 IV. 527 V. 529 VI. 529 529 References 529 SUMMARY: Re-programming of the transcriptome involves both transcription and alternative splicing (AS). Some genes are regulated only at the AS level with no change in expression at the gene level. AS data must be incorporated as an essential aspect of the regulation of gene expression. RNA-sequencing (RNA-seq) can deliver both transcriptional and AS information, but accurate methods to analyse the added complexity in RNA-seq data are needed. The construction of a comprehensive reference transcript dataset (RTD) for a specific plant species, variety or accession, from all available sequence data, will immediately allow more robust analysis of RNA-seq data. RTDs will continually evolve and improve, a process that will be more efficient if resources across a community are shared and pooled.

Alternative Splicing of Barley Clock Genes in Response to Low Temperature.

Alternative splicing (AS) is a regulated mechanism that generates multiple transcripts from individual genes. It is widespread in eukaryotic genomes and provides an effective way to control gene expression. At low temperatures, AS regulates Arabidopsis clock genes through dynamic changes in the levels of productive mRNAs. We examined AS in barley clock genes to assess whether temperature-dependent AS responses also occur in a monocotyledonous crop species. We identify changes in AS of various barley core clock genes including the barley orthologues of Arabidopsis AtLHY and AtPRR7 which showed the most pronounced AS changes in response to low temperature. The AS events modulate the levels of functional and translatable mRNAs, and potentially protein levels, upon transition to cold. There is some conservation of AS events and/or splicing behaviour of clock genes between Arabidopsis and barley. In addition, novel temperature-dependent AS of the core clock gene HvPPD-H1 (a major determinant of photoperiod response and AtPRR7 orthologue) is conserved in monocots. HvPPD-H1 showed a rapid, temperature-sensitive isoform switch which resulted in changes in abundance of AS variants encoding different protein isoforms. This novel layer of low temperature control of clock gene expression, observed in two very different species, will help our understanding of plant adaptation to different environments and ultimately offer a new range of targets for plant improvement.

Exome sequencing of geographically diverse barley landraces and wild relatives gives insights into environmental adaptation.

After domestication, during a process of widespread range extension, barley adapted to a broad spectrum of agricultural environments. To explore how the barley genome responded to the environmental challenges it encountered, we sequenced the exomes of a collection of 267 georeferenced landraces and wild accessions. A combination of genome-wide analyses showed that patterns of variation have been strongly shaped by geography and that variant-by-environment associations for individual genes are prominent in our data set. We observed significant correlations of days to heading (flowering) and height with seasonal temperature and dryness variables in common garden experiments, suggesting that these traits were major drivers of environmental adaptation in the sampled germplasm. A detailed analysis of known flowering-associated genes showed that many contain extensive sequence variation and that patterns of single- and multiple-gene haplotypes exhibit strong geographical structuring. This variation appears to have substantially contributed to range-wide ecogeographical adaptation, but many factors key to regional success remain unidentified.

Monitoring Alternative Splicing Changes in Arabidopsis Circadian Clock Genes.

Posttranscriptional control makes an important contribution to circadian regulation of gene expression. In higher plants, alternative splicing is particularly prevalent upon abiotic and biotic stress and in the circadian system. Here we describe in detail a high-resolution reverse transcription-PCR based panel (HR RT-PCR) to monitor alternative splicing events. The use of the panel allows the quantification of changes in the proportion of splice isoforms between different samples, e.g., different time points, different tissues, genotypes, ecotypes, or treatments.

AtRTD - a comprehensive reference transcript dataset resource for accurate quantification of transcript-specific expression in Arabidopsis thaliana.

RNA-sequencing (RNA-seq) allows global gene expression analysis at the individual transcript level. Accurate quantification of transcript variants generated by alternative splicing (AS) remains a challenge. We have developed a comprehensive, nonredundant Arabidopsis reference transcript dataset (AtRTD) containing over 74 000 transcripts for use with algorithms to quantify AS transcript isoforms in RNA-seq. The AtRTD was formed by merging transcripts from TAIR10 and novel transcripts identified in an AS discovery project. We have estimated transcript abundance in RNA-seq data using the transcriptome-based alignment-free programmes Sailfish and Salmon and have validated quantification of splicing ratios from RNA-seq by high resolution reverse transcription polymerase chain reaction (HR RT-PCR). Good correlations between splicing ratios from RNA-seq and HR RT-PCR were obtained demonstrating the accuracy of abundances calculated for individual transcripts in RNA-seq. The AtRTD is a resource that will have immediate utility in analysing Arabidopsis RNA-seq data to quantify differential transcript abundance and expression.

Evolutionary relationships among barley and Arabidopsis core circadian clock and clock-associated genes.

The circadian clock regulates a multitude of plant developmental and metabolic processes. In crop species, it contributes significantly to plant performance and productivity and to the adaptation and geographical range over which crops can be grown. To understand the clock in barley and how it relates to the components in the Arabidopsis thaliana clock, we have performed a systematic analysis of core circadian clock and clock-associated genes in barley, Arabidopsis and another eight species including tomato, potato, a range of monocotyledonous species and the moss, Physcomitrella patens. We have identified orthologues and paralogues of Arabidopsis genes which are conserved in all species, monocot/dicot differences, species-specific differences and variation in gene copy number (e.g. gene duplications among the various species). We propose that the common ancestor of barley and Arabidopsis had two-thirds of the key clock components identified in Arabidopsis prior to the separation of the monocot/dicot groups. After this separation, multiple independent gene duplication events took place in both monocot and dicot ancestors.