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

Transcriptome analysis of two isolates of the tomato pathogen Cladosporium fulvum, uncovers genome-wide patterns of alternative splicing during a host infection cycle

Alternative splicing (AS) is a key element of eukaryotic gene expression that increases transcript and proteome diversity in cells, thereby altering their responses to external stimuli and stresses. While AS has been intensively researched in plants and animals, its frequency, conservation, and putative impact on virulence, are relatively still understudied in plant pathogenic fungi. Here, we profiled the AS events occurring in genes of Cladosporium fulvum isolates Race 5 and Race 4, during nearly a complete compatible infection cycle on their tomato host. Our studies revealed extensive heterogeneity in the transcript isoforms assembled from different isolates, infections, and infection timepoints, as over 80% of the transcript isoforms were singletons that were detected in only a single sample. Despite that, nearly 40% of the protein-coding genes in each isolate were predicted to be recurrently AS across the disparate infection timepoints, infections, and the two isolates. Of these, 37.5% were common to both isolates and 59% resulted in multiple protein isoforms, thereby putatively increasing proteome diversity in the pathogen by 31% during infections. An enrichment analysis showed that AS mostly affected genes likely to be involved in the transport of nutrients, regulation of gene expression, and monooxygenase activity, suggesting a role for AS in finetuning adaptation of C. fulvum on its tomato host during infections. Tracing the location of the AS genes on the fungal chromosomes showed that they were mostly located in repeat-rich regions of the core chromosomes, indicating a causal connection between gene location on the genome and propensity to AS. Finally, multiple cases of differential isoform usage in AS genes of C. fulvum were identified, suggesting that modulation of AS at different infection stages may be another way by which pathogens refine infections on their hosts.

LsRTDv1, a reference transcript dataset for accurate transcript-specific expression analysis in lettuce

Accurate quantification of gene and transcript-specific expression, with the underlying knowledge of precise transcript isoforms, is crucial to understanding many biological processes. Analysis of RNA sequencing data has benefited from the development of alignment-free algorithms which enhance the precision and speed of expression analysis. However, such algorithms require a reference transcriptome. Here we generate a reference transcript dataset (LsRTDv1) for lettuce (cv. Saladin), combining long- and short-read sequencing with publicly available transcriptome annotations, and filtering to keep only transcripts with high-confidence splice junctions and transcriptional start and end sites. LsRTDv1 identifies novel genes (mostly long non-coding RNAs) and increases the number of transcript isoforms per gene in the lettuce genome from 1.4 to 2.7. We show that LsRTDv1 significantly increases the mapping rate of RNA-seq data from a lettuce time-series experiment (mock- and Botrytis cinerea-inoculated) and enables detection of genes that are differentially alternatively spliced in response to infection as well as transcript-specific expression changes. LsRTDv1 is a valuable resource for investigation of transcriptional and alternative splicing regulation in lettuce.

Geneapp: A web application for visualizing alternative splicing for biomedicine

Alternative Splicing (AS) is an essential mechanism for eukaryotes. However, the consequences of deleting a single exon can be dramatic for the organism and can lead to cancer in humans. Additionally, alternative 5' and 3' splice sites, which define the boundaries of exons, also play key roles to human disorders. Therefore, Investigating AS events is crucial for understanding the molecular basis of human diseases and developing therapeutic strategies. Workflow for AS event analysis can be sampling followed by data analysis with bioinformatics to identify the different AS events in the control and case samples, data visualization for curation, and selection of relevant targets for experimental validation. The raw output of the analysis software does not favor the inspection of events by bioinformaticians requiring custom scripts for data visualization. In this work, we propose the Geneapp application with three modules: GeneappScript, GeneappServer, and GeneappExplorer. GeneappScript is a wrapper that assists in identifying AS in samples compared in two different approaches, while GeneappServer integrates data from AS analysis already performed by the user. In GeneappExplorer, the user visualizes the previous dataset by exploring AS events in genes with functional annotation. This targeted screens that Geneapp allows to perform helps in the identification of targets for experimental validation to confirm the hypotheses under study. The Geneapp is freely available for non-commercial use at https://geneapp.net to advance research on AS for bioinformatics.

Comprehensive deciphering the alternative splicing patterns involved in leaf morphogenesis of Liriodendron chinense

Alternative splicing (AS), a pivotal post-transcriptional regulatory mechanism, profoundly amplifies diversity and complexity of transcriptome and proteome. Liriodendron chinense (Hemsl.) Sarg., an excellent ornamental tree species renowned for its distinctive leaf shape, which resembles the mandarin jacket. Despite the documented potential genes related to leaf development of L. chinense, the underlying post-transcriptional regulatory mechanisms remain veiled. Here, we conducted a comprehensive analysis of the transcriptome to clarify the genome-wide landscape of the AS pattern and the spectrum of spliced isoforms during leaf developmental stages in L. chinense. Our investigation unveiled 50,259 AS events, involving 10,685 genes (32.9%), with intron retention as the most prevalent events. Notably, the initial stage of leaf development witnessed the detection of 804 differentially AS events affiliated with 548 genes. Although both differentially alternative splicing genes (DASGs) and differentially expressed genes (DEGs) were enriched into morphogenetic related pathways during the transition from fishhook (P2) to lobed (P7) leaves, there was only a modest degree of overlap between DASGs and DEGs. Furthermore, we conducted a comprehensively AS analysis on homologous genes involved in leaf morphogenesis, and most of which are subject to post-transcriptional regulation of AS. Among them, the AINTEGUMENTA-LIKE transcript factor LcAIL5 was characterization in detailed, which experiences skipping exon (SE), and two transcripts displayed disparate expression patterns across multiple stages. Overall, these findings yield a comprehensive understanding of leaf development regulation via AS, offering a novel perspective for further deciphering the mechanism of plant leaf morphogenesis.

Comprehensive benchmark of differential transcript usage analysis for static and dynamic conditions

RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimental factors such as the availability of single- or paired-end and bulk or single-cell data. To help users select the most promising tool for their task, we performed a comprehensive benchmark of DTU detection tools. We cover a wide array of experimental settings, using simulated bulk and single-cell RNA-seq data as well as real transcriptomics datasets, including time-series data. Our results suggest that DEXSeq, edgeR, and LimmaDS are better choices for paired-end data, while DSGseq and DEXSeq can be used for single-end data. In single-cell simulation settings, we showed that satuRn performs better than DTUrtle. In addition, we showed that Spycone is optimal for time series DTU/IS analysis based on the evidence provided using GO terms enrichment analysis.

REVEILLE2 thermosensitive splicing: a molecular basis for the integration of nocturnal temperature information by the Arabidopsis circadian clock

Cold stress is one of the major environmental factors that limit growth and yield of plants. However, it is still not fully understood how plants account for daily temperature fluctuations, nor how these temperature changes are integrated with other regulatory systems such as the circadian clock. We demonstrate that REVEILLE2 undergoes alternative splicing after chilling that increases accumulation of a transcript isoform encoding a MYB-like transcription factor. We explore the biological function of REVEILLE2 in Arabidopsis thaliana using a combination of molecular genetics, transcriptomics, and physiology. Disruption of REVEILLE2 alternative splicing alters regulatory gene expression, impairs circadian timing, and improves photosynthetic capacity. Changes in nuclear gene expression are particularly apparent in the initial hours following chilling, with chloroplast gene expression subsequently upregulated. The response of REVEILLE2 to chilling extends our understanding of plants immediate response to cooling. We propose that the circadian component REVEILLE2 restricts plants responses to nocturnal reductions in temperature, thereby enabling appropriate responses to daily environmental changes.

The coordinated regulation of early meiotic stages is dominated by non-coding RNAs and stage-specific transcription in wheat

Reproductive success hinges on precisely coordinated meiosis, yet our understanding of how structural rearrangements of chromatin and phase transitions during meiosis are transcriptionally regulated is limited. In crop plants, detailed analysis of the meiotic transcriptome could identify regulatory genes and epigenetic regulators that can be targeted to increase recombination rates and broaden genetic variation, as well as provide a resource for comparison among eukaryotes of different taxa to answer outstanding questions about meiosis. We conducted a meiotic stage-specific analysis of messenger RNA (mRNA), small non-coding RNA (sncRNA), and long intervening/intergenic non-coding RNA (lincRNA) in wheat (Triticum aestivum L.) and revealed novel mechanisms of meiotic transcriptional regulation and meiosis-specific transcripts. Amidst general repression of mRNA expression, significant enrichment of ncRNAs was identified during prophase I relative to vegetative cells. The core meiotic transcriptome was comprised of 9309 meiosis-specific transcripts, 48 134 previously unannotated meiotic transcripts, and many known and novel ncRNAs differentially expressed at specific stages. The abundant meiotic sncRNAs controlled the reprogramming of central metabolic pathways by targeting genes involved in photosynthesis, glycolysis, hormone biosynthesis, and cellular homeostasis, and lincRNAs enhanced the expression of nearby genes. Alternative splicing was not evident in this polyploid species, but isoforms were switched at phase transitions. The novel, stage-specific regulatory controls uncovered here challenge the conventional understanding of this crucial biological process and provide a new resource of requisite knowledge for those aiming to directly modulate meiosis to improve crop plants. The wheat meiosis transcriptome dataset can be queried for genes of interest using an eFP browser located at https://bar.utoronto.ca/efp_wheat/cgi-bin/efpWeb.cgi?dataSource=Wheat_Meiosis.

Transcription Factor Dynamics in Cross-Regulation of Plant Hormone Signaling Pathways

Cross-regulation between hormone signaling pathways is indispensable for plant growth and development. However, the molecular mechanisms by which multiple hormones interact and co-ordinate activity need to be understood. Here, we generated a cross-regulation network explaining how hormone signals are integrated from multiple pathways in etiolated Arabidopsis (Arabidopsis thaliana) seedlings. To do so we comprehensively characterized transcription factor activity during plant hormone responses and reconstructed dynamic transcriptional regulatory models for six hormones; abscisic acid, brassinosteroid, ethylene, jasmonic acid, salicylic acid and strigolactone/karrikin. These models incorporated target data for hundreds of transcription factors and thousands of protein-protein interactions. Each hormone recruited different combinations of transcription factors, a subset of which were shared between hormones. Hub target genes existed within hormone transcriptional networks, exhibiting transcription factor activity themselves. In addition, a group of MITOGEN-ACTIVATED PROTEIN KINASES (MPKs) were identified as potential key points of cross-regulation between multiple hormones. Accordingly, the loss of function of one of these (MPK6) disrupted the global proteome, phosphoproteome and transcriptome during hormone responses. Lastly, we determined that all hormones drive substantial alternative splicing that has distinct effects on the transcriptome compared with differential gene expression, acting in early hormone responses. These results provide a comprehensive understanding of the common features of plant transcriptional regulatory pathways and how cross-regulation between hormones acts upon gene expression.

Systematic analysis of alternative splicing in time course data using Spycone

MOTIVATION

During disease progression or organism development, alternative splicing may lead to isoform switches that demonstrate similar temporal patterns and reflect the alternative splicing co-regulation of such genes. Tools for dynamic process analysis usually neglect alternative splicing.

RESULTS

Here, we propose Spycone, a splicing-aware framework for time course data analysis. Spycone exploits a novel IS detection algorithm and offers downstream analysis such as network and gene set enrichment. We demonstrate the performance of Spycone using simulated and real-world data of SARS-CoV-2 infection.

AVAILABILITY AND IMPLEMENTATION

The Spycone package is available as a PyPI package. The source code of Spycone is available under the GPLv3 license at https://github.com/yollct/spycone and the documentation at https://spycone.readthedocs.io/en/latest/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

ESRP1-regulated isoform switching of LRRFIP2 determines metastasis of gastric cancer

Although accumulating evidence indicates that alternative splicing is aberrantly altered in many cancers, the functional mechanism remains to be elucidated. Here, we show that epithelial and mesenchymal isoform switches of leucine-rich repeat Fli-I-interacting protein 2 (LRRFIP2) regulated by epithelial splicing regulatory protein 1 (ESRP1) correlate with metastatic potential of gastric cancer cells. We found that expression of the splicing variants of LRRFIP2 was closely correlated with that of ESRP1. Surprisingly, ectopic expression of the mesenchymal isoform of LRRFIP2 (variant 3) dramatically increased liver metastasis of gastric cancer cells, whereas deletion of exon 7 of LRRFIP2 by the CRISPR/Cas9 system caused an isoform switch, leading to marked suppression of liver metastasis. Mechanistically, the epithelial LRRFIP2 isoform (variant 2) inhibited the oncogenic function of coactivator-associated arginine methyltransferase 1 (CARM1) through interaction. Taken together, our data reveals a mechanism of LRRFIP2 isoform switches in gastric cancer with important implication for cancer metastasis.

Temporal Dynamic Analysis of Alternative Splicing During Embryonic Development in Zebrafish

Alternative splicing is pervasive in mammalian genomes and involved in embryo development, whereas research on crosstalk of alternative splicing and embryo development was largely restricted to mouse and human and the alternative splicing regulation during embryogenesis in zebrafish remained unclear. We constructed the alternative splicing atlas at 18 time-course stages covering maternal-to-zygotic transition, gastrulation, somitogenesis, pharyngula stages, and post-fertilization in zebrafish. The differential alternative splicing events between different developmental stages were detected. The results indicated that abundance alternative splicing and differential alternative splicing events are dynamically changed and remarkably abundant during the maternal-to-zygotic transition process. Based on gene expression profiles, we found splicing factors are expressed with specificity of developmental stage and largely expressed during the maternal-to-zygotic transition process. The better performance of cluster analysis was achieved based on the inclusion level of alternative splicing. The biological function analysis uncovered the important roles of alternative splicing during embryogenesis. The identification of isoform switches of alternative splicing provided a new insight into mining the regulated mechanism of transcript isoforms, which always is hidden by gene expression. In conclusion, we inferred that alternative splicing activation is synchronized with zygotic genome activation and discovered that alternative splicing is coupled with transcription during embryo development in zebrafish. We also unveiled that the temporal expression dynamics of splicing factors during embryo development, especially co-orthologous splicing factors. Furthermore, we proposed that the inclusion level of alternative splicing events can be employed for cluster analysis as a novel parameter. This work will provide a deeper insight into the regulation of alternative splicing during embryogenesis in zebrafish.

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.

High transcriptome plasticity drives phosphate starvation responses in tomato

Tomato is an important vegetable crop and fluctuating available soil phosphate (Pi) level elicits several morpho-physiological responses driven by underlying molecular responses. Therefore, understanding these molecular responses at the gene and isoform levels has become critical in the quest for developing crops with improved Pi use efficiency. A quantitative time-series RNA-seq analysis was performed to decipher the global transcriptomic changes that accompany Pi starvation in tomato. Apart from changes in the expression levels of genes, there were also alterations in the expression of alternatively-spliced transcripts. Physiological responses such as anthocyanin accumulation, reactive oxygen species generation and cell death are obvious 7 days after Pi deprivation accompanied with the maximum amount of transcriptional change in the genome making it an important stage for in-depth study while studying Pi stress responses (PSR). Our study demonstrates that transcriptomic changes under Pi deficiency are dynamic and complex in tomato. Overall, our study dwells on the dynamism of the transcriptome in eliciting a response to adapt to low Pi stress and lays it bare. Findings from this study will prove to be an invaluable resource for researchers using tomato as a model for understanding nutrient deficiency.

Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability

Current expression quantification methods suffer from a fundamental but undercharacterized type of error: the most likely estimates for transcript abundances are not unique. This means multiple estimates of transcript abundances generate the observed RNA-seq reads with equal likelihood, and the underlying true expression cannot be determined. This is called nonidentifiability in probabilistic modeling. It is further exacerbated by incomplete reference transcriptomes where reads may be sequenced from unannotated transcripts. Graph quantification is a generalization to transcript quantification, accounting for the reference incompleteness by allowing exponentially many unannotated transcripts to express reads. We propose methods to calculate a "confidence range of expression" for each transcript, representing its possible abundance across equally optimal estimates for both quantification models. This range informs both whether a transcript has potential estimation error due to nonidentifiability and the extent of the error. Applying our methods to the Human Body Map data, we observe that 35%-50% of transcripts potentially suffer from inaccurate quantification caused by nonidentifiability. When comparing the expression between isoforms in one sample, we find that the degree of inaccuracy of 20%-47% transcripts can be so large that the ranking of expression between the transcript and other isoforms from the same gene cannot be determined. When comparing the expression of a transcript between two groups of RNA-seq samples in differential expression analysis, we observe that the majority of detected differentially expressed transcripts are reliable with a few exceptions after considering the ranges of the optimal expression estimates.

Barley (Hordeum Vulgare) Anther and Meiocyte RNA Sequencing: Mapping Sequencing Reads and Downstream Data Analyses

RNA sequencing (RNA-seq) data is by now the most common method to study differential gene expression. Here we present a pipeline from RNA-seq generation to analysis with examples based on our own barley anther and meiocyte transcriptome. The bioinformatics pipeline will give everyone, from a beginner to a more experienced user, the possibility to analyze their datasets and identify significantly differentially expressed genes. It also allows differential alternative splicing analysis which will become increasingly common due to the high regulatory impact on the gene expression. We describe use of the Galaxy interface for RNA-seq read quantification and the 3D RNA-seq app for the downstream data analysis.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

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.

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.

A dynamic intron retention program regulates the expression of several hundred genes during pollen meiosis

Intron retention is a stage-specific mechanism of functional attenuation of a subset of co-regulated, functionally related genes during early stages of pollen development. To improve our understanding of the gene regulatory mechanisms that drive developmental processes, we performed a genome-wide study of alternative splicing and isoform switching during five key stages of pollen development in field mustard, Brassica rapa. Surprisingly, for several hundred genes (12.3% of the genes analysed), isoform switching results in stage-specific expression of intron-retaining transcripts at the meiotic stage of pollen development. In such cases, we report temporally regulated switching between expression of a canonical, translatable isoform and an intron-retaining transcript that is predicted to produce a truncated and presumably inactive protein. The results suggest a new pervasive mechanism underlying modulation of protein levels in a plant developmental program. The effect is not based on gene expression induction but on the type of transcript produced. We conclude that intron retention is a stage-specific mechanism of functional attenuation of a subset of co-regulated, functionally related genes during meiosis, especially genes related to ribosome biogenesis, mRNA transport and nuclear envelope architecture. We also propose that stage-specific expression of a non-functional isoform of Brassica rapa BrSDG8, a non-redundant member of histone methyltransferase gene family, linked to alternative splicing regulation, may contribute to the intron retention observed.

Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.

Rice Transcriptome Analysis Reveals Nitrogen Starvation Modulates Differential Alternative Splicing and Transcript Usage in Various Metabolism-Related Genes

Nitrogen (N) is crucial for plant growth and development; however, excessive use of N fertilizers cause many problems including environmental damage, degradation of soil fertility, and high cost to the farmers. Therefore, immediate implementation is required to develop N efficient crop varieties. Rice being low nitrogen use efficiency (NUE) and a high demand staple food across the world has become a favorite crop to study the NUE trait. In the current study, we used the publicly available transcriptome data generated from the root and shoot tissues of two rice genotypes IR-64 and Nagina-22 (N-22) under optimum N supply (N+) and chronic N-starvation (N-). A stringent pipeline was applied to detect differentially expressed genes (DEGs), alternatively spliced (DAS) genes, differentially expressed transcripts (DETs) and differential transcript usage (DTU) transcripts in both the varieties and tissues under N+ and N- conditions. The DAS genes and DTU transcripts identified in the study were found to be involved in several metabolic and biosynthesis processes. We suggest alternative splicing (AS) plays an important role in fine-tuning the regulation of metabolic pathways related genes in genotype, tissue, and condition-dependent manner. The current study will help in understanding the transcriptional dynamics of NUE traits in the future.

Exploring transcriptional switches from pairwise, temporal and population RNA-Seq data using deepTS

Transcriptional switch (TS) is a widely observed phenomenon caused by changes in the relative expression of transcripts from the same gene, in spatial, temporal or other dimensions. TS has been associated with human diseases, plant development and stress responses. Its investigation is often hampered by a lack of suitable tools allowing comprehensive and flexible TS analysis for high-throughput RNA sequencing (RNA-Seq) data. Here, we present deepTS, a user-friendly web-based implementation that enables a fully interactive, multifunctional identification, visualization and analysis of TS events for large-scale RNA-Seq datasets from pairwise, temporal and population experiments. deepTS offers rich functionality to streamline RNA-Seq-based TS analysis for both model and non-model organisms and for those with or without reference transcriptome. The presented case studies highlight the capabilities of deepTS and demonstrate its potential for the transcriptome-wide TS analysis of pairwise, temporal and population RNA-Seq data. We believe deepTS will help research groups, regardless of their informatics expertise, perform accessible, reproducible and collaborative TS analyses of large-scale RNA-Seq data.

Integrated multi-omics framework of the plant response to jasmonic acid

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways.

Omics Playground: a comprehensive self-service platform for visualization, analytics and exploration of Big Omics Data

As the cost of sequencing drops rapidly, the amount of 'omics data increases exponentially, making data visualization and interpretation-'tertiary' analysis a bottleneck. Specialized analytical tools requiring technical expertise are available. However, consolidated and multi-faceted tools that are easy to use for life scientists is highly needed and currently lacking. Here we present Omics Playground, a user-friendly and interactive self-service bioinformatics platform for the in-depth analysis, visualization and interpretation of transcriptomics and proteomics data. It provides a large number of different tools in which special attention has been paid to single cell data. With Omics Playground, life scientists can easily perform complex data analysis and visualization without coding, and significantly reduce the time to discovery.

Integrated multi-omics framework of the plant response to jasmonic acid

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways.

Dynamic Alternative Splicing During Mouse Preimplantation Embryo Development

The mechanism of alternative pre-mRNA splicing (AS) during preimplantation development is largely unknown. In order to capture the dynamic changes of AS occurring during embryogenesis, we carried out bioinformatics analysis based on scRNA-seq data over the time-course preimplantation development in mouse. We detected numerous previously-unreported differentially expressed genes at specific developmental stages and investigated the nature of AS at both minor and major zygotic genome activation (ZGA). The AS and differential AS atlas over preimplantation development were established. The differentially alternatively spliced genes (DASGs) are likely to be key splicing factors (SFs) during preimplantation development. We also demonstrated that there is a regulatory cascade of AS events in which some key SFs are regulated by differentially AS of their own gene transcripts. Moreover, 212 isoform switches (ISs) during preimplantation development were detected, which may be critical for decoding the mechanism of early embryogenesis. Importantly, we uncovered that zygotic AS activation (ZASA) is in conformity with ZGA and revealed that AS is coupled with transcription during preimplantation development. Our results may provide a deeper insight into the regulation of early embryogenesis.

Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat

Wheat (Triticum aestivum L.), a globally important crop, is challenged by increasing temperatures (heat stress, HS). However its polyploid nature, the incompleteness of its genome sequences and annotation, the lack of comprehensive HS-responsive transcriptomes and the unexplored heat sensing and signaling of wheat hinder our full understanding of its adaptations to HS. The recently released genome sequences of wheat, as well as emerging single-molecular sequencing technologies, provide an opportunity to thoroughly investigate the molecular mechanisms of the wheat response to HS. We generated a high-resolution spatio-temporal transcriptome map of wheat flag leaves and filling grain under HS at 0 min, 5 min, 10 min, 30 min, 1 h and 4 h by combining full-length single-molecular sequencing and Illumina short reads sequencing. This hybrid sequencing newly discovered 4947 loci and 70 285 transcripts, generating the comprehensive and dynamic list of HS-responsive full-length transcripts and complementing the recently released wheat reference genome. Large-scale analysis revealed a global landscape of heat adaptations, uncovering unexpected rapid heat sensing and signaling, significant changes of more than half of HS-responsive genes within 30 min, heat shock factor-dependent and -independent heat signaling, and metabolic alterations in early HS-responses. Integrated analysis also demonstrated the differential responses and partitioned functions between organs and subgenomes, and suggested a differential pattern of transcriptional and alternative splicing regulation in the HS response. This study provided comprehensive data for dissecting molecular mechanisms of early HS responses in wheat and highlighted the genomic plasticity and evolutionary divergence of polyploidy wheat.

Temporal Splicing Switches in Elements of the TNF-Pathway Identified by Computational Analysis of Transcriptome Data for Human Cell Lines

Alternative splicing plays an important role in numerous cellular processes and aberrant splice decisions are associated with cancer. Although some studies point to a regulation of alternative splicing and its effector mechanisms in a time-dependent manner, the extent and consequences of such a regulation remains poorly understood. In the present work, we investigated the time-dependent production of isoforms in two Hodgkin lymphoma cell lines of different progression stages (HD-MY-Z, stage IIIb and L-1236, stage IV) compared to a B lymphoblastoid cell line (LCL-HO) with a focus on tumour necrosis factor (TNF) pathway-related elements. For this, we used newly generated time-course RNA-sequencing data from the mentioned cell lines and applied a computational pipeline to identify genes with isoform-switching behaviour in time. We analysed the temporal profiles of the identified events and evaluated in detail the potential functional implications of alterations in isoform expression for the selected top-switching genes. Our data indicate that elements within the TNF pathway undergo a time-dependent variation in isoform production with a putative impact on cell migration, proliferation and apoptosis. These include the genes TRAF1, TNFRSF12A and NFKB2. Our results point to a role of temporal alternative splicing in isoform production, which may alter the outcome of the TNF pathway and impact on tumorigenesis.

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.

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.

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.

Genome-wide characterization of differential transcript usage in Arabidopsis thaliana

Alternative splicing and the usage of alternate transcription start- or stop sites allows a single gene to produce multiple transcript isoforms. Most plant genes express certain isoforms at a significantly higher level than others, but under specific conditions this expression dominance can change, resulting in a different set of dominant isoforms. These events of differential transcript usage (DTU) have been observed for thousands of Arabidopsis thaliana, Zea mays and Vitis vinifera genes, and have been linked to development and stress response. However, neither the characteristics of these genes, nor the implications of DTU on their protein coding sequences or functions, are currently well understood. Here we present a dataset of isoform dominance and DTU for all genes in the AtRTD2 reference transcriptome based on a protocol that was benchmarked on simulated data and validated through comparison with a published reverse transciptase-polymerase chain reaction panel. We report DTU events for 8148 genes across 206 public RNA-Seq samples, and find that protein sequences are affected in 22% of the cases. The observed DTU events show high consistency across replicates, and reveal reproducible patterns in response to treatment and development. We also demonstrate that genes with different evolutionary ages, expression breadths and functions show large differences in the frequency at which they undergo DTU, and in the effect that these events have on their protein sequences. Finally, we showcase how the generated dataset can be used to explore DTU events for genes of interest or to find genes with specific DTU in samples of interest.