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

2019 ◽  
Vol 35 (21) ◽  
pp. 4469-4471 ◽  
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.

scholarly journals IsoformSwitchAnalyzeR: Analysis of changes in genome-wide patterns of alternative splicing and its functional consequences

2018 ◽  
Author(s):  
Kristoffer Vitting-Seerup ◽  
Albin Sandelin
Keyword(s):  
Alternative Splicing ◽  
Recent Work ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Genome Wide ◽  
Functional Consequences ◽  
Cancer Genome Atlas ◽  
Health And Disease ◽  
Genome Atlas

AbstractAlternative splicing is an important mechanism involved in both health and disease. Recent work highlights the importance of investigating genome-wide changes in patters of splicing and the subsequent functional consequences. Unfortunately current computational methods only support such analysis on a gene-by-gene basis. To fill this gap, we extended IsoformSwitchAnalyzeR thereby enabling analysis of genome-wide changes in both specific types of alternative splicing as well as the 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 both alternative splicing and the consequences of the associated isoform switches.AvailabilityWindows, Linux and Mac OS: http://bioconductor.org/packages/IsoformSwitchAnalyzeR.ContactKVS: [email protected], AS: [email protected]

scholarly journals LESSeq: Local event-based analysis of alternative splicing using RNA-Seq data

2019 ◽  
Author(s):  
Jing Leng ◽  
Christopher JF Cameron ◽  
Sunghee Oh ◽  
James P Noonan ◽  
Mark B Gerstein
Keyword(s):  
Alternative Splicing ◽  
Likelihood Estimation ◽  
Human Populations ◽  
Species Variation ◽  
Rna Seq ◽  
Data Set ◽  
Genome Wide ◽  
Alternative Splicing Events ◽  
Event Based ◽  
Splicing Patterns

Alternative splicing, which can be observed genome-wide by RNA-Seq, is important in cellular development and evolution. Comparative RNA-Seq experiments between different cellular conditions allow alternative splicing signatures to be detected. However, inferring alternative splicing signatures from short-read technology is unreliable and still presents many challenges before biologically significant signatures may be identified. To enable the robust discovery of differential alternative splicing, we developed the Local Event-based analysis of alternative Splicing using RNA-Seq (LESSeq) pipeline. LESSeq utilizes information of local splicing events (i.e., the partial structures in genes where transcript-splicing patterns diverge) to identify unambiguous alternative splicing. In addition, LESSeq quantifies the abundance of these alternative events using Maximum Likelihood Estimation (MLE) and provides their significance between different cellular conditions. The utility of LESSeq is demonstrated through two case studies relevant to human variation and evolution. Using an RNA-Seq data set of lymphoblastoid cell lines in two human populations, we examined within-species variation and discovered population-differential alternative splicing events. With an RNA-Seq data set of several tissues in human and rhesus macaque, we studied cross-species variation and identified lineage-differential alternative splicing events. LESSeq is implemented in C++ and R, and made publicly available on GitHub at: https://github.com/gersteinlab/LESSeq

Identification of Prognostic Alternative Splicing Signature in Gastric Cancer

2021 ◽  
Author(s):  
Zhiwu Wang ◽  
Qiong Wu ◽  
Yankun Liu ◽  
Jingwu Li
Keyword(s):  
Gastric Cancer ◽  
Alternative Splicing ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Splicing Factors ◽  
Rna Seq ◽  
Oncogenic Pathways ◽  
Splicing Variants ◽  
Cancer Genome Atlas

Abstract Aberrant alternative splicing (AS) events serve as prognostic indicators in a large number of malignancies, whereas comprehensive analysis of prognostic AS in gastric cancer (GC) has not yet been understood. To identify prognostic AS events and clarify the function of the splicing variants in GC. RNA-Seq data, clinical information and percent spliced in (PSI) values were available in the cancer genome atlas (TCGA) and TCGA SpliceSeq data portal. A three-step regression method was conducted to screen prognostic AS events and construct multi-AS-based signatures. The associations between prognostic AS events and splicing factors were also investigated. We identified a total of 1318 survival related AS events in GC, Parent genes of which were implicated in numerous oncogenic pathways. The final prognostic signatures stratified by seven types of AS events or not stratified performed well in risk prediction for GC patients. Moreover, five signatures base on AA, AD, AT, ES and RI events function as independent prognostic indicators after multivariate adjustment of clinicalpathological variables. Splicing network also showed marked correlation between the expression of splicing factors and PSI value of AS events in GC patients. The AS derived signatures allow to predict GC prognosis and might serve as potential therapeutic target for GC.

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

2021 ◽  
Author(s):  
Mancini Estefania ◽  
Rabinovich Andres ◽  
Iserte Javier ◽  
Yanovsky Marcelo ◽  
Chernomoretz Ariel
Keyword(s):  
Alternative Splicing ◽  
Intron Retention ◽  
Real Data ◽  
Data Availability ◽  
Supplementary Information ◽  
Rna Seq ◽  
Sequencing Technologies ◽  
Reconstruction Methods ◽  
Genome Wide ◽  
Bioconductor Project

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.

scholarly journals psichomics: graphical application for alternative splicing quantification and analysis

2018 ◽  
Author(s):  
Nuno Saraiva-Agostinho ◽  
Nuno L. Barbosa-Morais
Keyword(s):  
Alternative Splicing ◽  
R Package ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Global Studies ◽  
Rna Seq ◽  
Cellular Processes ◽  
Cancer Genome Atlas ◽  
Downstream Analysis ◽  
User Friendly

Alternative pre-mRNA splicing generates functionally distinct transcripts from the same gene and is involved in the control of multiple cellular processes, with its dysregulation being associated with a variety of pathologies. The advent of next-generation sequencing has enabled global studies of alternative splicing in different physiological and disease contexts. However, current bioinformatics tools for alternative splicing analysis from RNA-seq data are not user-friendly, disregard available exon-exon junction quantification or have limited downstream analysis features. To overcome such limitations, we have developedpsichomics, an R package with an intuitive graphical interface for alternative splicing quantification and downstream dimensionality reduction, differential splicing and gene expression and survival analyses based on The Cancer Genome Atlas, the Genotype-Tissue Expression project and user-provided data. These integrative analyses can also incorporate clinical and molecular sample-associated features. We successfully usedpsichomicsto reveal alternative splicing signatures specific to stage I breast cancer and associated novel putative prognostic factors.

scholarly journals ICN: Extracting interconnected communities in gene Co-expression networks

2021 ◽  
Author(s):  
Qiong Wu ◽  
Tianzhou Ma ◽  
Qingzhi Liu ◽  
Donald K Milton ◽  
Yuan Zhang ◽  
...  
Keyword(s):  
Community Structure ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
Large Network ◽  
Rna Seq ◽  
Clustering Methods ◽  
Graph Norm ◽  
Immune Evasion Mechanism ◽  
Cancer Genome Atlas ◽  
Expression Matrix

Abstract Motivation The analysis of gene co-expression network (GCN) is critical in examining the gene-gene interactions and learning the underlying complex yet highly organized gene regulatory mechanisms. Numerous clustering methods have been developed to detect communities of co-expressed genes in the large network. The assumed independent community structure, however, can be oversimplified and may not adequately characterize the complex biological processes. Results We develop a new computational package to extract interconnected communities from gene co-expression network. We consider a pair of communities be interconnected if a subset of genes from one community is correlated with a subset of genes from another community. The interconnected community structure is more flexible and provides a better fit to the empirical co-expression matrix. To overcome the computational challenges, we develop efficient algorithms by leveraging advanced graph norm shrinkage approach. We validate and show the advantage of our method by extensive simulation studies. We then apply our interconnected community detection method to an RNA-seq data from The Cancer Genome Atlas (TCGA) Acute Myeloid Leukemia (AML) study and identify essential interacting biological pathways related to the immune evasion mechanism of tumor cells. Availability The software is available at Github: https://github.com/qwu1221/ICN and Figshare: https://figshare.com/articles/software/ICN-package/13229093. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

2021 ◽  
Vol 22 (11) ◽  
pp. 6091
Author(s):  
Kristina Daniunaite ◽  
Arnas Bakavicius ◽  
Kristina Zukauskaite ◽  
Ieva Rauluseviciute ◽  
Juozas Rimantas Lazutka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Practice ◽  
Promoter Methylation ◽  
Disease Recurrence ◽  
The Cancer Genome Atlas ◽  
Cancer Dataset ◽  
Protein Coding ◽  
Diagnosis And Prognosis ◽  
Genome Wide ◽  
Cancer Genome Atlas

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

scholarly journals PR/SET Domain Family and Cancer: Novel Insights from the Cancer Genome Atlas

2018 ◽  
Vol 19 (10) ◽  
pp. 3250 ◽  
Author(s):  
Anna Sorrentino ◽  
Antonio Federico ◽  
Monica Rienzo ◽  
Patrizia Gazzerro ◽  
Maurizio Bifulco ◽  
...  
Keyword(s):  
Family Members ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Gene ◽  
Rna Seq ◽  
Set Domain ◽  
Primary Tumors ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Genome Atlas

The PR/SET domain gene family (PRDM) encodes 19 different transcription factors that share a subtype of the SET domain [Su(var)3-9, enhancer-of-zeste and trithorax] known as the PRDF1-RIZ (PR) homology domain. This domain, with its potential methyltransferase activity, is followed by a variable number of zinc-finger motifs, which likely mediate protein–protein, protein–RNA, or protein–DNA interactions. Intriguingly, almost all PRDM family members express different isoforms, which likely play opposite roles in oncogenesis. Remarkably, several studies have described alterations in most of the family members in malignancies. Here, to obtain a pan-cancer overview of the genomic and transcriptomic alterations of PRDM genes, we reanalyzed the Exome- and RNA-Seq public datasets available at The Cancer Genome Atlas portal. Overall, PRDM2, PRDM3/MECOM, PRDM9, PRDM16 and ZFPM2/FOG2 were the most mutated genes with pan-cancer frequencies of protein-affecting mutations higher than 1%. Moreover, we observed heterogeneity in the mutation frequencies of these genes across tumors, with cancer types also reaching a value of about 20% of mutated samples for a specific PRDM gene. Of note, ZFPM1/FOG1 mutations occurred in 50% of adrenocortical carcinoma patients and were localized in a hotspot region. These findings, together with OncodriveCLUST results, suggest it could be putatively considered a cancer driver gene in this malignancy. Finally, transcriptome analysis from RNA-Seq data of paired samples revealed that transcription of PRDMs was significantly altered in several tumors. Specifically, PRDM12 and PRDM13 were largely overexpressed in many cancers whereas PRDM16 and ZFPM2/FOG2 were often downregulated. Some of these findings were also confirmed by real-time-PCR on primary tumors.

scholarly journals DoChaP: The Domain Change Presenter

2020 ◽  
Author(s):  
Shani T. Gal-Oz ◽  
Nimrod Haiat ◽  
Dana Eliyahu ◽  
Guy Shani ◽  
Tal Shay
Keyword(s):  
Alternative Splicing ◽  
Rna Splicing ◽  
Protein Domains ◽  
Visual Presentation ◽  
Structural Effect ◽  
Protein Isoforms ◽  
Multiple Transcripts ◽  
Genome Wide ◽  
Health And Disease ◽  
Specific Alternative

AbstractAlternative RNA splicing results in multiple transcripts of the same gene, possibly encoding for different protein isoforms with different protein domains and functionalities. Whereas it is possible to manually determine the effect of a specific alternative splicing event on the domain composition of a particular encoded protein, the process requires the tedious integration of several data sources; it is therefore error prone and its implementation is not feasible for genome-wide characterization of domains affected by differential splicing. To fulfill the need for an automated solution, we developed the Domain Change Presenter (DoChaP), a web server for the visualization of the exon–domain association. DoChaP visualizes all transcripts of a given gene, the domains of the proteins that they encode, and the exons encoding each domain. The visualization enables a comparison between the transcripts and between the protein isoforms they encode for. The organization and visual presentation of the information makes the structural effect of each alternative splicing event on the protein structure easily identified. To enable a study of the conservation of the exon structure, alternative splicing, and the effect of alternative splicing on protein domains, DoChaP also facilitates an inter-species comparison of domain–exon associations. DoChaP thus provides a unique and easy-to-use visualization of the exon–domain association and its conservation between transcripts and orthologous genes and will facilitate the study of the functional effects of alternative splicing in health and disease.

scholarly journals Visual Display of 5p-arm and 3p-arm miRNA Expression with a Mobile Application

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Chao-Yu Pan ◽  
Wei-Ting Kuo ◽  
Chien-Yuan Chiu ◽  
Wen-chang Lin
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Visual Display ◽  
Mature Mirnas ◽  
Mobile App ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
User Friendly

MicroRNAs (miRNAs) play important roles in human cancers. In previous studies, we have demonstrated that both 5p-arm and 3p-arm of mature miRNAs could be expressed from the same precursor and we further interrogated the 5p-arm and 3p-arm miRNA expression with a comprehensive arm feature annotation list. To assist biologists to visualize the differential 5p-arm and 3p-arm miRNA expression patterns, we utilized a user-friendly mobile App to display. The Cancer Genome Atlas (TCGA) miRNA-Seq expression information. We have collected over 4,500 miRNA-Seq datasets from 15 TCGA cancer types and further processed them with the 5p-arm and 3p-arm annotation analysis pipeline. In order to be displayed with the RNA-Seq Viewer App, annotated 5p-arm and 3p-arm miRNA expression information and miRNA gene loci information were converted into SQLite tables. In this distinct application, for any given miRNA gene, 5p-arm miRNA is illustrated on the top of chromosome ideogram and 3p-arm miRNA is illustrated on the bottom of chromosome ideogram. Users can then easily interrogate the differentially 5p-arm/3p-arm expressed miRNAs with their mobile devices. This study demonstrates the feasibility and utility of RNA-Seq Viewer App in addition to mRNA-Seq data visualization.

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