Computational Analysis of RNA-seq

2012 ◽  
pp. 201-219 ◽  
Author(s):  
Scott A. Givan ◽  
Christopher A. Bottoms ◽  
William G. Spollen
Keyword(s):  
Computational Analysis ◽  
Rna Seq

Immunophenotype and proliferation to predict for response to neoadjuvant chemotherapy in TNBC: Results from BrighTNess phase III study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 510-510 ◽  
Author(s):  
Otto Metzger Filho ◽  
Daniel G. Stover ◽  
Sarah Asad ◽  
Peter J Ansell ◽  
Mark Watson ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Computational Analysis ◽  
Pathologic Complete Response ◽  
Complete Response ◽  
Phase Iii ◽  
Rna Seq ◽  
Immune Signature ◽  
T Cell Infiltration ◽  
Phase Iii Study ◽  
Clinical Trial Information

510 Background: In TNBC, the interplay between immunophenotype, tumor proliferation (prolif) and achievement of pathologic complete response (pCR) with neoadjuvant chemotherapy (NAC) remains unknown. Methods: RNA seq was performed on pre-tx research biopsies of stage II/III TNBC enrolled in BrighTNess. NAC regimens included paclitaxel alone or with carboplatin (Cb) or Cb plus veliparib, followed by AC. Computational analysis included subtyping (i.e. PAM50, Pietenpol), prolif (PAM50) and GeparSixto immune signature (GSIS). Cb-containing arms were combined due to similar pCR. Results: High quality RNA seq data was obtained from 482 of 634 pts. PAM50 classified 80.1% of tumors as basal-like. TNBC subtypes were mostly BL1 or BL2 (23.3%), IM (22.4%) or M/MSL (31.7%); 6% were LAR. pCR was higher for basal vs non-basal tumors (52.3% vs 35.4%, p = 0.003). IM had the highest pCR rate (64.2%, 95% CI 59.9%,68.5%). Basal-like was not a significant predictor for Cb benefit (p-interaction = 0.8). Prolif (OR = 0.30 p < 0.001) and GSIS (OR 0.68 p < 0.001) were significantly correlated with pCR but did not correlate with each other (Pearson’s r2 = 0.027). In multivariate analysis, prolif (HR = 0.36 95% CI, 0.21-0.61 p = 0.0002) and GSIS (HR = 0.62 95% CI, 0.49-0.79 p < 0.0001) increased the ability to predict pCR beyond standard clinico-pathologic variables (likelihood ratio = 14.9, p = 0.0001115). Among all pts, those above the median for both prolif. and GSIS had the highest pCR (67%; 84/125) while those below the median for both had the lowest pCR rate (34%; 42/125). Tumors with higher inferred CD8+ T-cell infiltration demonstrated greater benefit from Cb using either TIMER (HR = 0.83 [0.73-0.95]) or CIBERSORT (HR = 0.83 [0.76-0.91]). Tumors with higher inferred total macrophages, particularly immune suppressive M2 macrophages had a higher pCR rate on the non-Cb arm (AC-T) using CIBERSORT (HR = 1.27 [1.07,1.50]). Conclusions: Immunophenotype and proliferation are independent predictors of pCR to standard NAC regimens in TNBC. PAM50 is not a significant predictor of Cb benefit. Exploratory findings suggest that tumor infiltrating immunophenotype (i.e. CD8 T cells and macrophages) may predict response to specific NAC regimens in TNBC. Clinical trial information: NCT02032277.

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

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.

scholarly journals READemption - A tool for the computational analysis of deep-sequencing-based transcriptome data

2014 ◽  
Author(s):  
Konrad Ulrich Förstner ◽  
Jörg Vogel ◽  
Cynthia Mira Sharma
Keyword(s):  
Data Processing ◽  
Deep Sequencing ◽  
Computational Analysis ◽  
Command Line ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Command Line Interface ◽  
Parallel Data ◽  
Full Power ◽  
Computationally Intensive

Summary: RNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. In order to draw biological conclusions based on RNA-Seq data, several steps some of which are computationally intensive, have to betaken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes, RNA immunoprecipitated with proteins, not only from bacteria, but also from eukaryotes and archaea. Availability and Implementation: READemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).

scholarly journals Computational analysis of bacterial RNA-Seq data

2013 ◽  
Vol 41 (14) ◽  
pp. e140-e140 ◽  
Author(s):  
Ryan McClure ◽  
Divya Balasubramanian ◽  
Yan Sun ◽  
Maksym Bobrovskyy ◽  
Paul Sumby ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Rna Seq ◽  
Bacterial Rna

scholarly journals The Erythroid Intron Retention Program Encompasses Developmentally Stable and Dynamic Networks and Regulates Diverse Gene Classes

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3331-3331
Author(s):  
Harold Pimentel ◽  
Marilyn Parra ◽  
Sherry Gee ◽  
Narla Mohandas ◽  
Lior Pachter ◽  
...  
Keyword(s):  
Metal Ion ◽  
Computational Analysis ◽  
Conflicts Of Interest ◽  
Intron Retention ◽  
Dynamic Networks ◽  
Pcr Analysis ◽  
Mrna Levels ◽  
Rna Seq ◽  
Metal Ion Binding ◽  
Dynamic Regulation

Abstract Computational analysis of RNA-seq data from highly purified human erythroblasts has been instrumental in revealing changes in pre-mRNA splicing during terminal erythropoiesis. Here we report updated studies of intron retention (IR), a type of alternative splicing in which specific introns are retained in otherwise efficiently-processed transcripts, allowing post-transcriptional modulation of cellular mRNA levels. Differences in differentiation stage-specificity, degree of retention, nuclear/cytoplasmic localization, and sensitivity to nonsense-mediated decay (NMD) suggest the existence of multiple classes of erythroblast IR subject to distinct regulatory controls. Two clusters comprising ~470 "developmentally dynamic" introns in 354 genes exhibit more efficient splicing in proerythroblasts, but elevated intron retention in orthochromatic erythroblasts prior to enucleation. Dynamic regulation of late erythroblast IR parallels previously described splicing switches involving alternative exons. Gene ontology analysis revealed that the dynamic intron group is highly enriched in genes with RNA processing functions. Among these are several spliceosomal factors including SF3B1, a commonly mutated gene in myelodysplasia patients. We also identified several clusters of "developmentally stable" introns whose IR levels are not substantially modulated during erythropoiesis. Among this latter type are two clusters containing 294 introns that are enriched in functions related to metal ion binding. Key genes include mitoferrin-1 (SC25A37; IR~50%) and mitoferrin-2 (SLC25A28; IR~20-30%), mitochondrial iron importers essential for heme biosynthesis. We observed a correlation between splice site strength and percent IR among developmentally stable but not dynamic intron clusters, indicating that splicing regulatory mechanism(s) for the latter must require additional sequence features. A search for such features revealed that IR was significantly higher adjacent to alternative 'PTC' exons containing premature termination codons than it was adjacent to other exons; moreover, by direct RT-PCR analysis we discovered novel (unannotated) PTC exons in additional retained introns. The proposed role of PTC exons in IR is being studied experimentally using an array of minigene splicing reporter constructs. Finally, we noted that while specific IR events are erythroid specific, e.g., in the alpha spectrin gene SPTA1, computational analysis of public RNA-seq data demonstrated that most erythroblast IR events were also observed in granulocytes and in 16 other tissues surveyed by the human BodyMap project. Intron retention is likely to play critical roles in gene regulation in both hematological and non-hematological tissues. Disclosures No relevant conflicts of interest to declare.

scholarly journals Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors

2013 ◽  
Vol 42 (5) ◽  
pp. 2856-2869 ◽  
Author(s):  
Zhenqing Ye ◽  
Zhong Chen ◽  
Xun Lan ◽  
Stephen Hara ◽  
Benjamin Sunkel ◽  
...  
Keyword(s):  
Computational Analysis ◽  
De Novo ◽  
Exon Skipping ◽  
K562 Cells ◽  
Computational Method ◽  
Rna Seq ◽  
Splice Sites ◽  
Epigenetic Factors ◽  
Multiple Transcripts ◽  
The Impact

Abstract Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting mature mRNA. Both transcript isoforms from this skipping event site, i.e. in which the exon is either included (inclusion isoform) or excluded (skipping isoform), are typically present in one cell, and maintain a subtle balance that is vital to cellular function and dynamics. However, how the prevailing conditions dictate which isoform is expressed and what biological factors might influence the regulation of this process remain areas requiring further exploration. In this study, we have developed a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium and experimentally validated several skipping site predictions by RT-PCR. Furthermore, we integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. Our computational analysis found that splice sites within the skipping-isoform-dominated group (SIDG) tended to exhibit weaker MaxEntScan-calculated splice site strength around middle, ‘skipping’, exons compared to those in the inclusion-isoform-dominated group (IIDG). We further showed the positional preference pattern of splicing factors, characterized by enrichment in the intronic splice sites immediately bordering middle exons. Finally, our analysis suggested that different epigenetic factors may introduce a variable obstacle in the process of exon–intron boundary establishment leading to skipping events.

scholarly journals A Computational Analysis of Alternative Splicing across Mammalian Tissues Reveals Circadian and Ultradian Rhythms in Splicing Events

2019 ◽  
Vol 20 (16) ◽  
pp. 3977 ◽  
Author(s):  
Rukeia El-Athman ◽  
Dora Knezevic ◽  
Luise Fuhr ◽  
Angela Relógio
Keyword(s):  
Alternative Splicing ◽  
Circadian Clock ◽  
Computational Analysis ◽  
Tumour Progression ◽  
Primary Tumour ◽  
Expression Patterns ◽  
Rna Seq ◽  
Ultradian Rhythms ◽  
Mammalian Tissues

Mounting evidence points to a role of the circadian clock in the temporal regulation of post-transcriptional processes in mammals, including alternative splicing (AS). In this study, we carried out a computational analysis of circadian and ultradian rhythms on the transcriptome level to characterise the landscape of rhythmic AS events in published datasets covering 76 tissues from mouse and olive baboon. Splicing-related genes with 24-h rhythmic expression patterns showed a bimodal distribution of peak phases across tissues and species, indicating that they might be controlled by the circadian clock. On the output level, we identified putative oscillating AS events in murine microarray data and pairs of differentially rhythmic splice isoforms of the same gene in baboon RNA-seq data that peaked at opposing times of the day and included oncogenes and tumour suppressors. We further explored these findings using a new circadian RNA-seq dataset of human colorectal cancer cell lines. Rhythmic isoform expression patterns differed between the primary tumour and the metastatic cell line and were associated with cancer-related biological processes, indicating a functional role of rhythmic AS that might be implicated in tumour progression. Our data shows that rhythmic AS events are widespread across mammalian tissues and might contribute to a temporal diversification of the proteome.

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