HBA-DEALS: accurate and simultaneous identification of differential expression and splicing using hierarchical Bayesian analysis

Transcriptomics in the era of long-read sequencing

Transcriptome sequencing revolutionized the analysis of gene expression, providing an unbiased approach to gene detection and quantification that enabled the discovery of novel isoforms, alternative splicing events and fusion transcripts. However, although short-read sequencing technologies have surpassed the limited dynamic range of previous technologies such as microarrays, they have limitations, for example, in resolving full-length transcripts and complex isoforms. Over the past 5 years, long-read sequencing technologies have matured considerably, with improvements in instrumentation and analytical methods, enabling their application to RNA sequencing (RNA-seq). Benchmarking studies are beginning to identify the strengths and limitations of long-read RNA-seq, although there remains a need for comprehensive resources to guide newcomers through the intricacies of this approach. In this Review, we provide a comprehensive overview of the long-read RNA-seq workflow, from library preparation and sequencing challenges to core data processing, downstream analyses and emerging developments. We present an extensive inventory of experimental and analytical methods and discuss current challenges and prospects.

Bioinformatics analysis and validation of RNA methylation-related genes in osteogenic and adipogenic differentiation of rat bone marrow mesenchymal stem cells

BACKGROUND

The regulatory mechanisms of RNA methylation during the processes of osteogenic and adipogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) have yet to be fully understood. The objective of our study was to analyze and validate the contribution of RNA methylation regulators to the mechanisms underlying the osteogenic and adipogenic differentiation of rat BMSCs.

METHODS

We downloaded the GSE186026 from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened using the DESeq2 package in R software (version 3.6.3). A total of 50 RNA methylation genes obtained from literature review and summary were intersected with the previous DEGs to obtain RNA methylation genes, which have different expressions (RM-DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were utilized to reveal the functional enrichment. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate RM-DEGs. Protein-protein interaction network (PPI) analysis and visual analysis were performed using STRING and Cytoscape. RM-DEGs regulatory network was constructed to analyze the top 10 hub genes. The relationship between RM-DEGs, some enriched GO and pathways was also been analyzed. The miRNAs and RM-DEGs regulatory networks were established by using miRWalk and TargetScan.

RESULTS

As part of our research, we detected varying levels of expression for m6A regulators Mettl3 and Rbm15, as well as m7G regulators Mettl1 and Wdr4, in relation to osteogenic differentiation, along with m6A regulator Fmr1 in adipogenic differentiation. The protein-protein interaction (PPI) networks were constructed for 49 differentially expressed genes (DEGs) related to RNA methylation during the process of osteogenic differentiation, and 13 DEGs for adipogenic differentiation. Moreover, top10 hub genes were calculated. In osteogenic differentiation, Mettl3 regulated the Wnt pathway and Hippo pathway by regulating Smad3, Rbm15 regulated the Notch pathway by Notch1, Mettl1 regulated the PI3K-Akt pathway by Gnb4. In adipogenic differentiation, Fmr1 regulated the PI3K-Akt pathway by Egfr. M6A methylation sites of Smad3, Notch1 and Gnb4 were predicted, and the results showed that all three genes were possibly methylated by m6A, and more than 9 sites per gene were possibly methylated. Finally, we constructed the regulatory networks of Mettl3, Rbm15, Mettl1, and Wdr4 and 109 miRNAs in osteogenic differentiation, Fmr1 and 118 miRNAs in adipogenic differentiation.

CONCLUSIONS

Mettl3(m6A), Rbm15(m6A), Wdr4 and Mettl1(m7G) were differentially expressed in osteogenic differentiation, while Fmr1(m6A) was differentially expressed in adipogenic differentiation. These findings offered potential candidates for further research on the involvement of RNA methylation in the osteogenic and adipogenic differentiation of BMSCs.

IsopretGO-analysing and visualizing the functional consequences of differential splicing

Gene Ontology overrepresentation analysis (GO-ORA) is a standard approach towards characterizing salient functional characteristics of sets of differentially expressed genes (DGE) in RNA sequencing (RNA-seq) experiments. GO-ORA compares the distribution of GO annotations of the DGE to that of all genes or all expressed genes. This approach has not been available to characterize differential alternative splicing (DAS). Here, we introduce a desktop application called isopretGO for visualizing the functional implications of DGE and DAS that leverages our previously published machine-learning predictions of GO annotations for individual isoforms. We show based on an analysis of 100 RNA-seq datasets that DAS and DGE frequently have starkly different functional profiles. We present an example that shows how isopretGO can be used to identify functional shifts in RNA-seq data that can be attributed to differential splicing.

ASpediaFI: Functional Interaction Analysis of Alternative Splicing Events

Alternative splicing (AS) regulates biological processes governing phenotypes and diseases. Differential AS (DAS) gene test methods have been developed to investigate important exonic expression from high-throughput datasets. However, the DAS events extracted using statistical tests are insufficient to delineate relevant biological processes. In this study, we developed a novel application, Alternative Splicing Encyclopedia: Functional Interaction (ASpediaFI), to systemically identify DAS events and co-regulated genes and pathways. ASpediaFI establishes a heterogeneous interaction network of genes and their feature nodes (i.e., AS events and pathways) connected by co-expression or pathway gene set knowledge. Next, ASpediaFI explores the interaction network using the random walk with restart algorithm and interrogates the proximity from a query gene set. Finally, ASpediaFI extracts significant AS events, genes, and pathways. To evaluate the performance of our method, we simulated RNA sequencing (RNA-seq) datasets to consider various conditions of sequencing depth and sample size. The performance was compared with that of other methods. Additionally, we analyzed three public datasets of cancer patients or cell lines to evaluate how well ASpediaFI detects biologically relevant candidates. ASpediaFI exhibits strong performance in both simulated and public datasets. Our integrative approach reveals that DAS events that recognize a global co-expression network and relevant pathways determine the functional importance of spliced genes in the subnetwork. ASpediaFI is publicly available at https://bioconductor.org/packages/ASpediaFI.

Betacoronavirus-specific alternate splicing

Viruses can subvert a number of cellular processes including splicing in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection, datasets from the betacoronaviruses SARS-CoV and MERS, as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification, and have a smaller number of exons as compared with differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by differential alternative splicing and gene expression in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS. The alternative splicing changes observed in betacoronaviruses infection potentially modify a broad range of cellular functions, via changes in the functions of the products of a diverse set of genes involved in different biological processes.

Alternative splicing regulation appears to play a crucial role in grape berry development and is also potentially involved in adaptation responses to the environment

BACKGROUND

Alternative splicing (AS) produces transcript variants playing potential roles in proteome diversification and gene expression regulation. AS modulation is thus essential to respond to developmental and environmental stimuli. In grapevine, a better understanding of berry development is crucial for implementing breeding and viticultural strategies allowing adaptation to climate changes. Although profound changes in gene transcription have been shown to occur in the course of berry ripening, no detailed study on splicing modifications during this period has been published so far. We report here on the regulation of gene AS in developing berries of two grapevine (Vitis vinifera L.) varieties, Gewurztraminer (Gw) and Riesling (Ri), showing distinctive phenotypic characteristics. Using the software rMATS, the transcriptomes of berries at four developmental steps, from the green stage to mid-ripening, were analysed in pairwise comparisons between stages and varieties.

RESULTS

A total of 305 differential AS (DAS) events, affecting 258 genes, were identified. Interestingly, 22% of these AS events had not been reported before. Among the 80 genes that underwent the most significant variations during ripening, 22 showed a similar splicing profile in Gw and Ri, which suggests their involvement in berry development. Conversely, 23 genes were subjected to splicing regulation in only one variety. In addition, the ratios of alternative isoforms were different in Gw and Ri for 35 other genes, without any change during ripening. This last result indicates substantial AS differences between the two varieties. Remarkably, 8 AS events were specific to one variety, due to the lack of a splice site in the other variety. Furthermore, the transcription rates of the genes affected by stage-dependent splicing regulation were mostly unchanged, identifying AS modulation as an independent way of shaping the transcriptome.

CONCLUSIONS

The analysis of AS profiles in grapevine varieties with contrasting phenotypes revealed some similarity in the regulation of several genes with developmental functions, suggesting their involvement in berry ripening. Additionally, many splicing differences were discovered between the two varieties, that could be linked to phenotypic specificities and distinct adaptive capacities. Together, these findings open perspectives for a better understanding of berry development and for the selection of grapevine genotypes adapted to climate change.

Betacoronavirus-specific alternate splicing

Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection as well as datasets from the betacoronaviruses SARS-CoV and MERS as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification and a smaller number of exons than differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by DAS and DGE in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS, potentially modifying a broad range of cellular functions and affecting a diverse set of genes and biological functions.

Molecular Tools for Adapting Viticulture to Climate Change

Adaptation of viticulture to climate change includes exploration of new geographical areas, new training systems, new management practices, or new varieties, both for rootstocks and scions. Molecular tools can be defined as molecular approaches used to study DNAs, RNAs, and proteins in all living organisms. We present here the current knowledge about molecular tools and their potential usefulness in three aspects of grapevine adaptation to the ongoing climate change. (i) Molecular tools for understanding grapevine response to environmental stresses. A fine description of the regulation of gene expression is a powerful tool to understand the physiological mechanisms set up by the grapevine to respond to abiotic stress such as high temperatures or drought. The current knowledge on gene expression is continuously evolving with increasing evidence of the role of alternative splicing, small RNAs, long non-coding RNAs, DNA methylation, or chromatin activity. (ii) Genetics and genomics of grapevine stress tolerance. The description of the grapevine genome is more and more precise. The genetic variations among genotypes are now revealed with new technologies with the sequencing of very long DNA molecules. High throughput technologies for DNA sequencing also allow now the genetic characterization at the same time of hundreds of genotypes for thousands of points in the genome, which provides unprecedented datasets for genotype-phenotype associations studies. We review the current knowledge on the genetic determinism of traits for the adaptation to climate change. We focus on quantitative trait loci and molecular markers available for developmental stages, tolerance to water stress/water use efficiency, sugar content, acidity, and secondary metabolism of the berries. (iii) Controlling the genome and its expression to allow breeding of better-adapted genotypes. High-density DNA genotyping can be used to select genotypes with specific interesting alleles but genomic selection is also a powerful method able to take into account the genetic information along the whole genome to predict a phenotype. Modern technologies are also able to generate mutations that are possibly interesting for generating new phenotypes but the most promising one is the direct editing of the genome at a precise location.