ASpli: integrative analysis of splicing landscapes through RNA-Seq assays

Abstract Motivation Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons. Results In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals. Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms. Availability and implementation ASpli is freely available from the Bioconductor project site https://doi.org/doi:10.18129/B9.bioc.ASpli. Supplementary information Supplementary data are available at Bioinformatics online.

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ASpli2: Integrative analysis of splicing landscapes through RNA-Seq assays

10.1101/2020.06.21.162891 ◽

2020 ◽

Author(s):

Estefania Mancini ◽

Andres Rabinovich ◽

Javier Iserte ◽

Marcelo Yanovsky ◽

Ariel Chernomoretz

Keyword(s):

Alternative Splicing ◽

Real Data ◽

Data Availability ◽

Rna Seq ◽

Genome Wide Analysis ◽

Sequencing Technologies ◽

Genome Wide ◽

Analysis Workflow ◽

Sophisticated Analysis ◽

Generation Sequencing

AbstractGenome-wide analysis of alternative splicing has been a very active field of research since the early days of NGS (Next generation sequencing) technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. However, independently of the considered quantification methodology, very often changes in variant concentration profiles can be hard to disentangle. In order to tackle this problem we present ASpli2, a computational suite implemented in R, that allows the identification of changes in both, annotated and novel alternative splicing events, and can deal with complex experimental designs.Our analysis workflow relies on the analysis of differential usage of subgenic features in combination with a junction-based description of local splicing changes. Analyzing simulated and real data we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While junction-based signals allowed us to uncover annotated as well and non-annotated events, bin-associated signals notably increased recall capabilities at a very competitive performance in terms of precision.

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IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences

Bioinformatics ◽

10.1093/bioinformatics/btz247 ◽

2019 ◽

Vol 35 (21) ◽

pp. 4469-4471 ◽

Cited By ~ 21

Author(s):

Kristoffer Vitting-Seerup ◽

Albin Sandelin

Keyword(s):

Alternative Splicing ◽

The Cancer Genome Atlas ◽

Supplementary Information ◽

Rna Seq ◽

Genome Wide ◽

Functional Consequences ◽

Cancer Genome Atlas ◽

Health And Disease ◽

Splicing Patterns

Abstract Summary Alternative splicing is an important mechanism involved in health and disease. Recent work highlights the importance of investigating genome-wide changes in splicing patterns and the subsequent functional consequences. Current computational methods only support such analysis on a gene-by-gene basis. Therefore, we extended IsoformSwitchAnalyzeR R library to enable analysis of genome-wide changes in specific types of alternative splicing and predicted functional consequences of the resulting isoform switches. As a case study, we analyzed RNA-seq data from The Cancer Genome Atlas and found systematic changes in alternative splicing and the consequences of the associated isoform switches. Availability and implementation Windows, Linux and Mac OS: http://bioconductor.org/packages/IsoformSwitchAnalyzeR. Supplementary information Supplementary data are available at Bioinformatics online.

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Consistent Reanalysis of Genome-wide Imprinting Studies in Plants Using Generalized Linear Models Increases Concordance across Datasets

10.1101/180745 ◽

2017 ◽

Author(s):

Stefan Wyder ◽

Michael T. Raissig ◽

Ueli Grossniklaus

Keyword(s):

Linear Models ◽

Real Data ◽

Rna Seq ◽

Sequence Coverage ◽

Reciprocal Crosses ◽

Sequencing Technologies ◽

Genome Wide ◽

Allelic Bias ◽

Generation Sequencing ◽

Made In

ABSTRACTGenomic imprinting leads to different expression levels of maternally and paternally derived alleles. Over the last years, major progress has been made in identifying novel imprinted candidate genes in plants, owing to affordable next-generation sequencing technologies. However, reports on sequencing the transcriptome of hybrid F1 seed tissues strongly disagree about how many and which genes are imprinted. This raises questions about the relative impact of biological, environmental, technical, and analytic differences or biases. Here, we adopt a statistical approach, frequently used in RNA-seq data analysis, which properly models count overdispersion and considers replicate information of reciprocal crosses. We show that our statistical pipeline outperforms other methods in identifying imprinted genes in simulated and real data. Accordingly, reanalysis of genome-wide imprinting studies in Arabidopsis and maize shows that, at least for the Arabidopsis dataset, an increased agreement across datasets can be observed. For maize, however, consistent reanalysis did not yield in a larger overlap between the datasets. This suggests that the discrepancy across publications might be partially due to different analysis pipelines but that technical, biological, and environmental factors underlie much of the discrepancy between datasets. Finally, we show that the set of genes that can be characterized regarding allelic bias by all studies with minimal confidence is small (~8,000/27,416 genes for Arabidopsis and ~12,000/39,469 for maize). In conclusion, we propose to use biologically replicated reciprocal crosses, high sequence coverage, and a generalized linear model approach to identify differentially expressed alleles in developing seeds.

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Plant buffering against the high-light stress-induced accumulation of CsGA2ox8 transcripts via alternative splicing to finely tune gibberellin levels and maintain hypocotyl elongation

Horticulture Research ◽

10.1038/s41438-020-00430-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Bin Liu ◽

Shuo Zhao ◽

Pengli Li ◽

Yilu Yin ◽

Qingliang Niu ◽

...

Keyword(s):

Alternative Splicing ◽

Light Intensity ◽

Intron Retention ◽

Light Stress ◽

Photosynthetic Photon Flux Density ◽

Photon Flux ◽

Photon Flux Density ◽

Rna Seq ◽

Multiple Transcripts ◽

Novel Transcript

AbstractIn plants, alternative splicing (AS) is markedly induced in response to environmental stresses, but it is unclear why plants generate multiple transcripts under stress conditions. In this study, RNA-seq was performed to identify AS events in cucumber seedlings grown under different light intensities. We identified a novel transcript of the gibberellin (GA)-deactivating enzyme Gibberellin 2-beta-dioxygenase 8 (CsGA2ox8). Compared with canonical CsGA2ox8.1, the CsGA2ox8.2 isoform presented intron retention between the second and third exons. Functional analysis proved that the transcript of CsGA2ox8.1 but not CsGA2ox8.2 played a role in the deactivation of bioactive GAs. Moreover, expression analysis demonstrated that both transcripts were upregulated by increased light intensity, but the expression level of CsGA2ox8.1 increased slowly when the light intensity was >400 µmol·m−2·s−1 PPFD (photosynthetic photon flux density), while the CsGA2ox8.2 transcript levels increased rapidly when the light intensity was >200 µmol·m−2·s−1 PPFD. Our findings provide evidence that plants might finely tune their GA levels by buffering against the normal transcripts of CsGA2ox8 through AS.

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Alternative Splicing During the Chlamydomonasreinhardtii Cell Cycle

G3 Genes|Genome|Genetics ◽

10.1534/g3.120.401622 ◽

2020 ◽

Vol 10 (10) ◽

pp. 3797-3810

Author(s):

Manishi Pandey ◽

Gary D. Stormo ◽

Susan K. Dutcher

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Alternative Splicing ◽

Chlamydomonas Reinhardtii ◽

Intron Retention ◽

Exon Skipping ◽

Dark Phase ◽

Periodic Patterns ◽

Genome Wide ◽

Splicing Pattern

Genome-wide analysis of transcriptome data in Chlamydomonas reinhardtii shows periodic patterns in gene expression levels when cultures are grown under alternating light and dark cycles so that G1 of the cell cycle occurs in the light phase and S/M/G0 occurs during the dark phase. However, alternative splicing, a process that enables a greater protein diversity from a limited set of genes, remains largely unexplored by previous transcriptome based studies in C. reinhardtii. In this study, we used existing longitudinal RNA-seq data obtained during the light-dark cycle to investigate the changes in the alternative splicing pattern and found that 3277 genes (19.75% of 17,746 genes) undergo alternative splicing. These splicing events include Alternative 5′ (Alt 5′), Alternative 3′ (Alt 3′) and Exon skipping (ES) events that are referred as alternative site selection (ASS) events and Intron retention (IR) events. By clustering analysis, we identified a subset of events (26 ASS events and 10 IR events) that show periodic changes in the splicing pattern during the cell cycle. About two-thirds of these 36 genes either introduce a pre-termination codon (PTC) or introduce insertions or deletions into functional domains of the proteins, which implicate splicing in altering gene function. These findings suggest that alternative splicing is also regulated during the Chlamydomonas cell cycle, although not as extensively as changes in gene expression. The longitudinal changes in the alternative splicing pattern during the cell cycle captured by this study provides an important resource to investigate alternative splicing in genes of interest during the cell cycle in Chlamydomonas reinhardtii and other eukaryotes.

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RNA-Seq Analysis Reveals Localization-Associated Alternative Splicing across 13 Cell Lines

Genes ◽

10.3390/genes11070820 ◽

2020 ◽

Vol 11 (7) ◽

pp. 820 ◽

Cited By ~ 1

Author(s):

Chao Zeng ◽

Michiaki Hamada

Keyword(s):

Alternative Splicing ◽

Subcellular Localization ◽

Cell Lines ◽

Biological Diversity ◽

Rna Binding ◽

Regulatory Mechanism ◽

Intron Retention ◽

Rna Seq ◽

Motif Analysis ◽

Structurally Stable

Alternative splicing, a ubiquitous phenomenon in eukaryotes, is a regulatory mechanism for the biological diversity of individual genes. Most studies have focused on the effects of alternative splicing for protein synthesis. However, the transcriptome-wide influence of alternative splicing on RNA subcellular localization has rarely been studied. By analyzing RNA-seq data obtained from subcellular fractions across 13 human cell lines, we identified 8720 switching genes between the cytoplasm and the nucleus. Consistent with previous reports, intron retention was observed to be enriched in the nuclear transcript variants. Interestingly, we found that short and structurally stable introns were positively correlated with nuclear localization. Motif analysis reveals that fourteen RNA-binding protein (RBPs) are prone to be preferentially bound with such introns. To our knowledge, this is the first transcriptome-wide study to analyze and evaluate the effect of alternative splicing on RNA subcellular localization. Our findings reveal that alternative splicing plays a promising role in regulating RNA subcellular localization.

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Alternative Splicing in the Obligate Biotrophic Oomycete Pathogen Pseudoperonospora cubensis

Molecular Plant-Microbe Interactions ◽

10.1094/mpmi-09-14-0300-fi ◽

2015 ◽

Vol 28 (3) ◽

pp. 298-309 ◽

Cited By ~ 10

Author(s):

Alyssa Burkhardt ◽

Alex Buchanan ◽

Jason S. Cumbie ◽

Elizabeth A. Savory ◽

Jeff H. Chang ◽

...

Keyword(s):

Alternative Splicing ◽

Intron Retention ◽

Draft Genome ◽

Pseudoperonospora Cubensis ◽

Rna Seq ◽

Transcriptome Regulation ◽

Oomycete Pathogen ◽

Alternatively Spliced ◽

Genome Annotations ◽

Obligate Pathogen

Pseudoperonospora cubensis is an obligate pathogen and causative agent of cucurbit downy mildew. To help advance our understanding of the pathogenicity of P. cubensis, we used RNA-Seq to improve the quality of its reference genome sequence. We also characterized the RNA-Seq dataset to inventory transcript isoforms and infer alternative splicing during different stages of its development. Almost half of the original gene annotations were improved and nearly 4,000 previously unannotated genes were identified. We also demonstrated that approximately 24% of the expressed genome and nearly 55% of the intron-containing genes from P. cubensis had evidence for alternative splicing. Our analyses revealed that intron retention is the predominant alternative splicing type in P. cubensis, with alternative 5′- and alternative 3′-splice sites occurring at lower frequencies. Representatives of the newly identified genes and predicted alternatively spliced transcripts were experimentally validated. The results presented herein highlight the utility of RNA-Seq for improving draft genome annotations and, through this approach, we demonstrate that alternative splicing occurs more frequently than previously predicted. In total, the current study provides evidence that alternative splicing plays a key role in transcriptome regulation and proteome diversification in plant-pathogenic oomycetes.

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Splatter: simulation of single-cell RNA sequencing data

10.1101/133173 ◽

2017 ◽

Cited By ~ 8

Author(s):

Luke Zappia ◽

Belinda Phipson ◽

Alicia Oshlack

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Real Data ◽

Cell Types ◽

Rna Seq ◽

Sequencing Data ◽

Sequencing Technologies ◽

Simulation Based ◽

Single Cell Rna Sequencing ◽

Multiple Cell

AbstractAs single-cell RNA sequencing technologies have rapidly developed, so have analysis methods. Many methods have been tested, developed and validated using simulated datasets. Unfortunately, current simulations are often poorly documented, their similarity to real data is not demonstrated, or reproducible code is not available.Here we present the Splatter Bioconductor package for simple, reproducible and well-documented simulation of single-cell RNA-seq data. Splatter provides an interface to multiple simulation methods including Splat, our own simulation, based on a gamma-Poisson distribution. Splat can simulate single populations of cells, populations with multiple cell types or differentiation paths.

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Genome-wide transcriptome analysis identifies alternative splicing regulatory network and key splicing factors in mouse and human psoriasis

10.1101/259291 ◽

2018 ◽

Author(s):

Jin Li ◽

Peng Yu

Keyword(s):

Alternative Splicing ◽

Computational Analysis ◽

Potential Role ◽

Exon Skipping ◽

Chronic Inflammatory Disease ◽

Splicing Factors ◽

The Novel ◽

Rna Seq ◽

Genome Wide

AbstractPsoriasis is a chronic inflammatory disease that affects the skin, nails, and joints. For understanding the mechanism of psoriasis, though, alternative splicing analysis has received relatively little attention in the field. Here, we developed and applied several computational analysis methods to study psoriasis. Using psoriasis mouse and human datasets, our differential alternative splicing analyses detected hundreds of differential alternative splicing changes. Our analysis of conservation revealed many exon-skipping events conserved between mice and humans. In addition, our splicing signature comparison analysis using the psoriasis datasets and our curated splicing factor perturbation RNA-Seq database, SFMetaDB, identified nine candidate splicing factors that may be important in regulating splicing in the psoriasis mouse model dataset. Three of the nine splicing factors were confirmed upon analyzing the human data. Our computational methods have generated predictions for the potential role of splicing in psoriasis. Future experiments on the novel candidates predicted by our computational analysis are expected to provide a better understanding of the molecular mechanism of psoriasis and to pave the way for new therapeutic treatments.

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Customized de novo mutation detection for any variant calling pipeline: SynthDNM

Bioinformatics ◽

10.1093/bioinformatics/btab225 ◽

2021 ◽

Author(s):

Aojie Lian ◽

James Guevara ◽

Kun Xia ◽

Jonathan Sebat

Keyword(s):

Mutation Detection ◽

De Novo ◽

Variant Calling ◽

Real Data ◽

Supplementary Information ◽

De Novo Mutation ◽

Flexible Approach ◽

Sequencing Technologies ◽

Training Examples ◽

Simulated Training

Abstract Motivation As sequencing technologies and analysis pipelines evolve, de novo mutation (DNM) calling tools must be adapted. Therefore, a flexible approach is needed that can accurately identify DNMs from genome or exome sequences from a variety of datasets and variant calling pipelines. Results Here, we describe SynthDNM, a random-forest based classifier that can be readily adapted to new sequencing or variant-calling pipelines by applying a flexible approach to constructing simulated training examples from real data. The optimized SynthDNM classifiers predict de novo SNPs and indels with robust accuracy across multiple methods of variant calling. Availabilityand implementation SynthDNM is freely available on Github (https://github.com/james-guevara/synthdnm). Supplementary information Supplementary data are available at Bioinformatics online.

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