scholarly journals Differential Expression of BARD1 Isoforms in Melanoma

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 320
Author(s):  
Lorissa I. McDougall ◽  
Ryan M. Powell ◽  
Magdalena Ratajska ◽  
Chi F. Lynch-Sutherland ◽  
Sultana Mehbuba Hossain ◽  
...  
Keyword(s):  
Long Range ◽  
Patient Outcomes ◽  
Splice Variants ◽  
Significant Proportion ◽  
Nanopore Sequencing ◽  
Rna Seq ◽  
Splice Isoforms ◽  
Tissue Samples ◽  
Multiple Transcripts ◽  
Mrna Variants

Melanoma comprises <5% of cutaneous malignancies, yet it causes a significant proportion of skin cancer-related deaths worldwide. While new therapies for melanoma have been developed, not all patients respond well. Thus, further research is required to better predict patient outcomes. Using long-range nanopore sequencing, RT-qPCR, and RNA sequencing analyses, we examined the transcription of BARD1 splice isoforms in melanoma cell lines and patient tissue samples. Seventy-six BARD1 mRNA variants were identified in total, with several previously characterised isoforms (γ, φ, δ, ε, and η) contributing to a large proportion of the expressed transcripts. In addition, we identified four novel splice events, namely, Δ(E3_E9), ▼(i8), IVS10+131▼46, and IVS10▼176, occurring in various combinations in multiple transcripts. We found that short-read RNA-Seq analyses were limited in their ability to predict isoforms containing multiple non-contiguous splicing events, as compared to long-range nanopore sequencing. These studies suggest that further investigations into the functional significance of the identified BARD1 splice variants in melanoma are warranted.

Single-molecule Real-time (SMRT) Isoform Sequencing (Iso-Seq) in Plants: The Status of the Bioinformatics Tools to Unravel the Transcriptome Complexity

2019 ◽  
Vol 14 (7) ◽  
pp. 566-573 ◽  
Author(s):  
Yubang Gao ◽  
Feihu Xi ◽  
Hangxiao zhang ◽  
Xuqing Liu ◽  
Huiyuan Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Single Molecule ◽  
Splice Variants ◽  
Alternative Polyadenylation ◽  
Full Length ◽  
Rna Seq ◽  
Bioinformatics Pipeline ◽  
Splice Isoforms ◽  
Bioinformatics Tools ◽  
Genome Annotations

Background: The advent of the Single-Molecule Real-time (SMRT) Isoform Sequencing (Iso-Seq) has paved the way to obtain longer full-length transcripts. This method was found to be much superior in identifying full-length splice variants and other post-transcriptional events as compared to the Next Generation Sequencing (NGS)-based short read sequencing (RNA-Seq). Several different bioinformatics tools to analyze the Iso-Seq data have been developed and some of them are still being refined to address different aspects of transcriptome complexity. However, a comprehensive summary of the available tools and their utility is still lacking. Objective: Here, we summarized the existing Iso-Seq analysis tools and presented an integrated bioinformatics pipeline for Iso-Seq analysis, which overcomes the limitations of NGS and generates long contiguous Full-Length Non-Chimeric (FLNC) reads for the analysis of posttranscriptional events. Results: In this review, we summarized recent applications of Iso-Seq in plants, which include improved genome annotations, identification of novel genes and lncRNAs, identification of fulllength splice isoforms, detection of novel Alternative Splicing (AS) and Alternative Polyadenylation (APA) events. In addition, we also discussed the bioinformatics pipeline for comprehensive Iso-Seq data analysis, including how to reduce the error rate in the reads and how to identify and quantify post-transcriptional events. Furthermore, the visualization approach of Iso-Seq was discussed as well. Finally, we discussed methods to combine Iso-Seq data with RNA-Seq for transcriptome quantification. Conclusion: Overall, this review demonstrates that the Iso-Seq is pivotal for analyzing transcriptome complexity and this new method offers unprecedented opportunities to comprehensively understand transcripts diversity.

scholarly journals Genetic Determinants for Prediction of Outcome of Patients with Papillary Thyroid Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2048
Author(s):  
Antónia Afonso Póvoa ◽  
Elisabete Teixeira ◽  
Maria Rosa Bella-Cueto ◽  
Rui Batista ◽  
Ana Pestana ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Patient Outcomes ◽  
Genetic Alterations ◽  
Papillary Thyroid ◽  
Tissue Samples ◽  
Primary Tumors ◽  
Persistent Disease ◽  
Increased Risk ◽  
Structural Disease

Papillary thyroid carcinoma (PTC) usually presents an excellent prognosis, but some patients present with aggressive metastatic disease. BRAF, RAS, and TERT promoter (TERTp) genes are altered in PTC, and their impact on patient outcomes remains controversial. We aimed to determine the role of genetic alterations in PTC patient outcomes (recurrent/persistent disease, structural disease, and disease-specific mortality (DSM)). The series included 241 PTC patients submitted to surgery, between 2002–2015, in a single hospital. DNA was extracted from tissue samples of 287 lesions (primary tumors and metastases). Molecular alterations were detected by Sanger sequencing. Primary tumors presented 143 BRAF, 16 TERTp, and 13 RAS mutations. Isolated TERTpmut showed increased risk of structural disease (HR = 7.0, p < 0.001) and DSM (HR = 10.1, p = 0.001). Combined genotypes, BRAFwt/TERTpmut (HR = 6.8, p = 0.003), BRAFmut/TERTpmut (HR = 3.2, p = 0.056) and BRAFmut/TERTpwt (HR = 2.2, p = 0.023) showed increased risk of recurrent/persistent disease. Patients with tumors BRAFwt/TERTpmut (HR = 24.2, p < 0.001) and BRAFmut/TERTpmut (HR = 11.5, p = 0.002) showed increased risk of structural disease. DSM was significantly increased in patients with TERTpmut regardless of BRAF status (BRAFmut/TERTpmut, log-rank p < 0.001; BRAFwt/TERTpmut, log-rank p < 0.001). Our results indicate that molecular markers may have a role in predicting PTC patients’ outcome. BRAFmut/TERTpwt tumors were prone to associate with local aggressiveness (recurrent/persistent disease), whereas TERTpmut tumors were predisposed to recurrent structural disease and DSM.

scholarly journals A Comprehensive RNA Sequencing Analysis of the Adeno-Associated Virus (AAV) Type 2 Transcriptome Reveals Novel AAV Transcripts, Splice Variants, and Derived Proteins

2015 ◽  
Vol 90 (3) ◽  
pp. 1278-1289 ◽  
Author(s):  
Catrin Stutika ◽  
Andreas Gogol-Döring ◽  
Laura Botschen ◽  
Mario Mietzsch ◽  
Stefan Weger ◽  
...  
Keyword(s):  
Life Cycle ◽  
Fusion Protein ◽  
Rna Sequencing ◽  
Splice Variants ◽  
Productive Infection ◽  
Minus Strand ◽  
Rna Seq ◽  
Adeno Associated Virus ◽  
Divergent Transcription ◽  
Productive Replication

ABSTRACTAdeno-associated virus (AAV) is recognized for its bipartite life cycle with productive replication dependent on coinfection with adenovirus (Ad) and AAV latency being established in the absence of a helper virus. The shift from latent to Ad-dependent AAV replication is mostly regulated at the transcriptional level. The current AAV transcription map displays highly expressed transcripts as found upon coinfection with Ad. So far, AAV transcripts have only been characterized on the plus strand of the AAV single-stranded DNA genome. The AAV minus strand is assumed not to be transcribed. Here, we apply Illumina-based RNA sequencing (RNA-Seq) to characterize the entire AAV2 transcriptome in the absence or presence of Ad. We find known and identify novel AAV transcripts, including additional splice variants, the most abundant of which leads to expression of a novel 18-kDa Rep/VP fusion protein. Furthermore, we identify for the first time transcription on the AAV minus strand with clustered reads upstream of the p5 promoter, confirmed by 5ˈ rapid amplification of cDNA ends and RNase protection assays. The p5 promoter displays considerable activity in both directions, a finding indicative of divergent transcription. Upon infection with AAV alone, low-level transcription of both AAV strands is detectable and is strongly stimulated upon coinfection with Ad.IMPORTANCENext-generation sequencing (NGS) allows unbiased genome-wide analyses of transcription profiles, used here for an in depth analysis of the AAV2 transcriptome during latency and productive infection. RNA-Seq analysis led to the discovery of novel AAV transcripts and splice variants, including a derived, novel 18-kDa Rep/VP fusion protein. Unexpectedly, transcription from the AAV minus strand was discovered, indicative of divergent transcription from the p5 promoter. This finding opens the door for novel concepts of the switch between AAV latency and productive replication. In the absence of a suitable animal model to study AAVin vivo, combinedin cellulaeandin silicostudies will help to forward the understanding of the unique, bipartite AAV life cycle.

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

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.

Abstract 286: Long Noncoding RNAs Are Differentially Expressed in Heart Failure

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Emma L Robinson ◽  
Syed Haider ◽  
Hillary Hei ◽  
Richard T Lee ◽  
Roger S Foo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Significant Proportion ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Failing Heart ◽  
Novel Transcripts ◽  
Non Coding Rnas

Heart failure comprises of clinically distinct inciting causes but a consistent pattern of change in myocardial gene expression supports the hypothesis that unifying biochemical mechanisms underlie disease progression. The recent RNA-seq revolution has enabled whole transcriptome profiling, using deep-sequencing technologies. Up to 70% of the genome is now known to be transcribed into RNA, a significant proportion of which is long non-coding RNAs (lncRNAs), defined as polyribonucleotides of ≥200 nucleotides. This project aims to discover whether the myocardium expression of lncRNAs changes in the failing heart. Paired end RNA-seq from a 300-400bp library of ‘stretched’ mouse myocyte total RNA was carried out to generate 76-mer sequence reads. Mechanically stretching myocytes with equibiaxial stretch apparatus mimics pathological hypertrophy in the heart. Transcripts were assembled and aligned to reference genome mm9 (UCSC), abundance determined and differential expression of novel transcripts and alternative splice variants were compared with that of control (non-stretched) mouse myocytes. Five novel transcripts have been identified in our RNA-seq that are differentially expressed in stretched myocytes compared with non-stretched. These are regions of the genome that are currently unannotated and potentially are transcribed into non-coding RNAs. Roles of known lncRNAs include control of gene expression, either by direct interaction with complementary regions of the genome or association with chromatin remodelling complexes which act on the epigenome.Changes in expression of genes which contribute to the deterioration of the failing heart could be due to the actions of these novel lncRNAs, immediately suggesting a target for new pharmaceuticals. Changes in the expression of these novel transcripts will be validated in a larger sample size of stretched myocytes vs non-stretched myocytes as well as in the hearts of transverse aortic constriction (TAC) mice vs Sham (surgical procedure without the aortic banding). In vivo investigations will then be carried out, using siLNA antisense technology to silence novel lncRNAs in mice.

scholarly journals Reference transcriptome assembly and annotation for perennial ryegrass

Genome ◽  
2017 ◽  
Vol 60 (12) ◽  
pp. 1086-1088 ◽  
Author(s):  
Hiroshi Shinozuka ◽  
Noel O.I. Cogan ◽  
German C. Spangenberg ◽  
John W. Forster
Keyword(s):  
Perennial Ryegrass ◽  
Transcriptome Assembly ◽  
Genotyping By Sequencing ◽  
Whole Genome Sequence ◽  
Grass Species ◽  
Rna Seq ◽  
Pasture Grass ◽  
Tissue Samples ◽  
Genome Sequence Assembly ◽  
Transcriptome Resource

RNA-Seq methodology has been used to generate a comprehensive transcriptome sequence resource for perennial ryegrass, an important temperate pasture grass species. A total of 931 547 255 reads were obtained from libraries corresponding to 19 distinct tissue samples, including both vegetative and reproductive stages of development. Assembly of data generated a final filtered reference set of 48 713 contigs and scaffolds. The transcriptome resource will support whole genome sequence assembly, comparative genomics, implementation of genotyping-by-sequencing (GBS) methods based on transcript sampling, and identification of candidate genes for multiple biological functions.

EPCO-33. CELL-TYPE PROPORTION DECONVOLUTION OF PEDIATRIC CENTRAL NERVOUS SYSTEM TUMORS FROM SINGLE NUCLEI RNA-seq UNCOVERS UNDERLYING TRANSCRIPTOMIC CHANGES FROM BULK TUMOR RNA-seq COMPARED TO NORMAL BRAIN

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi9-vi9
Author(s):  
Min Kyung Lee ◽  
Nasim Azizgolshani ◽  
Fred Kolling ◽  
Lananh Nguyen ◽  
George Zanazzi ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Rna Sequencing ◽  
Differentially Expressed ◽  
Normal Brain ◽  
Rna Seq ◽  
Cell Type ◽  
Tissue Samples ◽  
Pediatric Brain ◽  
Bulk Tissue ◽  
Unadjusted Analysis

Abstract Identifying transcriptomic alterations in pediatric central nervous system (pCNS) tumors often relies on transcriptomic profiles from bulk tissue RNA-sequencing that can be confounded by varying cell type proportions across tumor and normal brain tissues. We utilized single nuclei RNA-sequencing (snRNA-seq) and bulk RNA-seq in 33 pCNS tumors and 3 non-diseased pediatric brain tissue samples collected from the Norris Cotton Cancer Center to identify variation in gene expression in bulk tissue attributed to overrepresentation of specific cell-type populations when determining differentially expressed genes comparing pCNS tumors to normal pediatric brain tissues. snRNA-seq of 43,515 nuclei (mean = 1,209 nuclei/sample) revealed large proportions of astrocytes (median = 0.45, range = 0.24–0.93) and oligodendrocytes (median = 0.37, range = 0.00–0.66) in pCNS tumors. Compared to normal pediatric brain, proportions of astrocytes were significantly higher (P = 9.2E-03) and neurons were significantly lower (P = 9.4E-03) in pCNS tumors. Differential expression analyses comparing bulk RNA-sequencing data from pCNS tumors to normal pediatric brain identified 902 additional differentially expressed genes (# DE genes = 1,802) when adjusting for astrocyte and neuron proportions compared with unadjusted analysis (# DE genes = 900). In cell-type proportion unadjusted analysis, top DE genes included astrocyte-specific markers, GFAP and CIITA, both of which were found to be not significantly differentially expressed in cell-type proportion adjusted analysis. Indeed, pathways enrichment analysis revealed DE genes in unadjusted models were associated with processes of the neurons and astrocytes such as interferon signaling and postsynaptic signal transmission. After adjustment for astrocyte and neuron proportions, DE genes were associated with defensins and DNA replication-related processes. Our results highlight new potential biological pathways essential in pCNS tumors and indicate the significance of the distribution of varying cell types in tissue samples when conducting studies to investigate transcriptomic alterations in bulk tissue of pCNS tumors.

scholarly journals Bayesian Framework for Detecting Gene Expression Outliers in Individual Samples

2020 ◽  
pp. 160-170
Author(s):  
John Vivian ◽  
Jordan M. Eizenga ◽  
Holly C. Beale ◽  
Olena M. Vaske ◽  
Benedict Paten
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Rna Seq ◽  
Single Patient ◽  
Tissue Samples ◽  
Composite Tissue ◽  
Patient Sample ◽  
Statistical Framework ◽  
Therapeutic Leads ◽  
Upregulated Genes

PURPOSE Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most natural comparison set is unaffected samples from the matching tissue, but there are often too few available unaffected samples to overcome high intersample variance. Moreover, some cancer samples have misidentified tissues of origin or even composite-tissue phenotypes. Even if an appropriate comparison set can be identified, most differential expression tools are not designed to accommodate comparisons to a single patient sample. METHODS We propose a Bayesian statistical framework for gene expression outlier detection in single samples. Our method uses all available data to produce a consensus background distribution for each gene of interest without requiring the researcher to manually select a comparison set. The consensus distribution can then be used to quantify over- and underexpression. RESULTS We demonstrate this method on both simulated and real gene expression data. We show that it can robustly quantify overexpression, even when the set of comparison samples lacks ideally matched tissue samples. Furthermore, our results show that the method can identify appropriate comparison sets from samples of mixed lineage and rediscover numerous known gene-cancer expression patterns. CONCLUSION This exploratory method is suitable for identifying expression outliers from comparative RNA sequencing (RNA-seq) analysis for individual samples, and Treehouse, a pediatric precision medicine group that leverages RNA-seq to identify potential therapeutic leads for patients, plans to explore this method for processing its pediatric cohort.

scholarly journals Identification of a molecular signature of prognostic subtypes in diffuse-type gastric cancer

2019 ◽  
Vol 23 (3) ◽  
pp. 473-482 ◽  
Author(s):  
Seon-Kyu Kim ◽  
Hee-Jin Kim ◽  
Jong-Lyul Park ◽  
Haejeong Heo ◽  
Seon-Young Kim ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Tissue Microarray ◽  
Microarray Analysis ◽  
Cox Regression ◽  
Molecular Signature ◽  
Diffuse Type ◽  
Rna Seq ◽  
Tissue Samples ◽  
Diffuse Type Gastric Cancer ◽  
Tissue Microarray Analysis

Abstract Background Although recent advances in high-throughput technology have provided many insights into gastric cancer (GC), few reliable biomarkers for diffuse-type GC have been identified. Here, we aim to identify a prognostic and predictive signature of diffuse-type GC heterogeneity. Methods We analyzed RNA-seq-based transcriptome data to identify a molecular signature in 150 gastric tissue samples including 107 diffuse-type GCs. The predictive value of the signature was verified using other diffuse-type GC samples in three independent cohorts (n = 466). Log-rank and Cox regression analyses were used to estimate the association between the signature and prognosis. The signature was also characterized by somatic variant analyses and tissue microarray analysis between diffuse-type GC subtypes. Results Transcriptomic profiling of RNA-seq data identified a signature which revealed distinct subtypes of diffuse-type GC: the intestinal-like (INT) and core diffuse-type (COD) subtypes. The signature showed high predictability and independent clinical utility in diffuse-type GC prognosis in other patient cohorts (HR 2.058, 95% CI 1.53–2.77, P = 1.76 × 10–6). Integrative mutational and gene expression analyses demonstrated that the COD subtype was responsive to chemotherapy, whereas the INT subtype was responsive to immunotherapy with an immune checkpoint inhibitor (ICI). Tissue microarray analysis showed the practical utility of IGF1 and NXPE2 for predicting diffuse-type GC heterogeneity. Conclusions We present a molecular signature that can identify diffuse-type GC patients who display different clinical behaviors as well as responses to chemotherapy or ICI treatment.

scholarly journals Real-Time RT-PCR Quantification of Human Telomerase Reverse Transcriptase Splice Variants in Tumor Cell Lines and Non–Small Cell Lung Cancer

2007 ◽  
Vol 53 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Eleni Mavrogiannou ◽  
Areti Strati ◽  
Aliki Stathopoulou ◽  
Emily G Tsaroucha ◽  
Loukas Kaklamanis ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Real Time ◽  
Cell Lines ◽  
Splice Variant ◽  
Splice Variants ◽  
Telomerase Activity ◽  
Tumor Cell Lines ◽  
Rt Pcr ◽  
Human Telomerase Reverse Transcriptase ◽  
Tissue Samples

Abstract Background: We developed and validated a real-time reverse transcription (RT)–PCR for the quantification of 4 individual human telomerase reverse transcriptase (TERT) splice variants (α+β+, α−β+, α+β−, α−β−) in tumor cell lines and non–small cell lung cancer (NSCLC). Methods: We used in silico designed primers and a common TaqMan probe for highly specific amplification of each TERT splice variant, PCR transcript–specific DNA external standards as calibrators, and the MCF-7 cell line for the development and validation of the method. We then quantified TERT splice variants in 6 tumor cell lines and telomerase activity and TERT splice variant expression in cancerous and paired noncancerous tissue samples from 28 NSCLC patients. Results: In most tumor cell lines, we observed little variation in the proportion of TERT splice variants. The α+β− splice variant showed the highest expression and α−β+ and α−β− the lowest. Quantification of the 4 TERT splice variants in NSCLC and surrounding nonneoplastic tissues showed the highest expression percentage for the α+β− variant in both NSCLC and adjacent nonneoplastic tissue samples, followed by α+β+, with the α−β+ and α−β− splice variants having the lowest expression. In the NSCLC tumors, the α+β+ variant had higher expression than other splice variants, and its expression correlated with telomerase activity, overall survival, and disease-free survival. Conclusions: Real-time RT-PCR quantification is a specific, sensitive, and rapid method that can elucidate the biological role of TERT splice variants in tumor development and progression. Our results suggest that the expression of the TERT α+β+ splice variant may be an independent negative prognostic factor for NSCLC patients.

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