scholarly journals Computational Evidence of NAGNAG Alternative Splicing in Human Large Intergenic Noncoding RNA

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaoyong Sun ◽  
Simon M. Lin ◽  
Xiaoyan Yan
Keyword(s):  
Alternative Splicing ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Data Sets ◽  
Posttranslational Regulation ◽  
Biological Processes ◽  
Rna Seq ◽  
Splice Site Selection ◽  
Protein Coding ◽  
Sequencing Studies

NAGNAG alternative splicing plays an essential role in biological processes and represents a highly adaptable system for posttranslational regulation of gene function. NAGNAG alternative splicing impacts a myriad of biological processes. Previous studies of NAGNAG largely focused on messenger RNA. To the best of our knowledge, this is the first study testing the hypothesis that NAGNAG alternative splicing is also operative in large intergenic noncoding RNA (lincRNA). The RNA-seq data sets from recent deep sequencing studies were queried to test our hypothesis. NAGNAG alternative splicing of human lincRNA was identified while querying two independent RNA-seq data sets. Within these datasets, 31 NAGNAG alternative splicing sites were identified in lincRNA. Notably, most exons of lincRNA containing NAGNAG acceptors were longer than those from protein-coding genes. Furthermore, presence of CAG coding appeared to participate in the splice site selection. Finally, expression of the isoforms of NAGNAG lincRNA exhibited tissue specificity. Together, this study improves our understanding of the NAGNAG alternative splicing in lincRNA.

scholarly journals Long Noncoding RNA Derived from LncRNA–mRNA Co-expression Networks Modulates the Locust Phase Change

2020 ◽  
Author(s):  
Ting Li ◽  
Bing Chen ◽  
Pengcheng Yang ◽  
Depin Wang ◽  
Baozhen Du ◽  
...  
Keyword(s):  
Phase Change ◽  
Animal Behavior ◽  
Noncoding Rna ◽  
Time Course ◽  
Empirical Studies ◽  
Expression Patterns ◽  
Rna Seq ◽  
Protein Coding ◽  
Migratory Locust ◽  
Functional Annotations

AbstractLong noncoding RNAs (lncRNAs) regulate various biological processes from gene expression to animal behavior. Although protein-coding genes, microRNAs, and neuropeptides play important roles in the regulation of phenotypic plasticity in migratory locust, empirical studies on the function of lncRNAs in the process remain limited. Here, we applied high-throughput RNA-seq to characterize the expression patterns of lncRNAs and mRNAs in the time course of the locust phase change. LncRNAs displayed more rapid response at the early stages of the time-course treatments than mRNA expression. Functional annotations demonstrated that early changed lncRNAs employed different pathways in isolation and crowding processes to cope up with the changes in population density. Finally, two overlapping hub lncRNA loci in the crowding and isolation networks were screened to be functionally verified. Experimental validation indicated that LNC1010057 could act as a potential regulator to modulate the locust phase change. This work offers new insights into the mechanism underlying the locust phase change and expands the scope of lncRNA functions in animal behavior.

scholarly journals Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization

2016 ◽  
Author(s):  
Xun Zhu ◽  
Travers Ching ◽  
Xinghua Pan ◽  
Sherman Weissman ◽  
Lana Garmire
Keyword(s):  
Single Cell ◽  
Hierarchical Clustering ◽  
Matrix Factorization ◽  
New Technology ◽  
Data Sets ◽  
Biological Processes ◽  
Rna Seq ◽  
Clustering Methods ◽  
Hematopoietic Stem ◽  
Non Negative Matrix Factorization

Single-cell RNA-Sequencing (scRNA-Seq) is a cutting edge technology that enables the understanding of biological processes at an unprecedentedly high resolution. However, well suited bioinformatics tools to analyze the data generated from this new technology are still lacking. Here we have investigated the performance of non-negative matrix factorization (NMF) method to analyze a wide variety of scRNA-Seq data sets, ranging from mouse hematopoietic stem cells to human glioblastoma data. In comparison to other unsupervised clustering methods including K-means and hierarchical clustering, NMF has higher accuracy even when the clustering results of K-means and hierarchical clustering are enhanced by t-SNE. Moreover, NMF successfully detect the subpopulations, such as those in a single glioblastoma patient. Furthermore, in conjugation with the modularity detection method FEM, it reveals unique modules that are indicative of clinical subtypes. In summary, we propose that NMF is a desirable method to analyze heterogeneous single-cell RNA-Seq data, and the NMFEM pipeline is suitable for modularity detection among single-cell RNA-Seq data.

scholarly journals Construction of competing endogenous RNA networks from paired RNA-seq data sets by pointwise mutual information

BMC Genomics ◽  
2019 ◽  
Vol 20 (S9) ◽  
Author(s):  
Chaowang Lan ◽  
Hui Peng ◽  
Gyorgy Hutvagner ◽  
Jinyan Li
Keyword(s):  
Breast Cancer ◽  
Mutual Information ◽  
Noncoding Rna ◽  
Regulation Mechanism ◽  
Data Sets ◽  
Rna Seq ◽  
Competing Endogenous Rna ◽  
Data Set ◽  
Cerna Network ◽  
Pointwise Mutual Information

Abstract Background A long noncoding RNA (lncRNA) can act as a competing endogenous RNA (ceRNA) to compete with an mRNA for binding to the same miRNA. Such an interplay between the lncRNA, miRNA, and mRNA is called a ceRNA crosstalk. As an miRNA may have multiple lncRNA targets and multiple mRNA targets, connecting all the ceRNA crosstalks mediated by the same miRNA forms a ceRNA network. Methods have been developed to construct ceRNA networks in the literature. However, these methods have limits because they have not explored the expression characteristics of total RNAs. Results We proposed a novel method for constructing ceRNA networks and applied it to a paired RNA-seq data set. The first step of the method takes a competition regulation mechanism to derive candidate ceRNA crosstalks. Second, the method combines a competition rule and pointwise mutual information to compute a competition score for each candidate ceRNA crosstalk. Then, ceRNA crosstalks which have significant competition scores are selected to construct the ceRNA network. The key idea, pointwise mutual information, is ideally suitable for measuring the complex point-to-point relationships embedded in the ceRNA networks. Conclusion Computational experiments and results demonstrate that the ceRNA networks can capture important regulatory mechanism of breast cancer, and have also revealed new insights into the treatment of breast cancer. The proposed method can be directly applied to other RNA-seq data sets for deeper disease understanding.

scholarly journals Robust Glycogene-Based Prognostic Signature for Proficient Mismatch Repair Colorectal Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yixi Li ◽  
Dehua Li ◽  
Yang Chen ◽  
Yongping Lu ◽  
Fangbin Zhou ◽  
...  
Keyword(s):  
Mismatch Repair ◽  
Regulatory Network ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Colorectal Adenocarcinoma ◽  
Prognostic Biomarkers ◽  
Rna Seq ◽  
Scale Free ◽  
New Strategy ◽  
Free Network

BackgroundProficient mismatch repair (pMMR) colorectal adenocarcinoma (CRAC) metastasizes to a greater extent than MMR-deficient CRAC. Prognostic biomarkers are preferred in clinical practice. However, traditional biomarkers screened directly from sequencing are often not robust and thus cannot be confidently utilized.MethodsTo circumvent the drawbacks of blind screening, we established a new strategy to identify prognostic biomarkers in the conserved and specific oncogenic pathway and its regulatory RNA network. We performed RNA sequencing (RNA-seq) for messenger RNA (mRNA) and noncoding RNA in six pMMR CRAC patients and constructed a glycosylation-related RNA regulatory network. Biomarkers were selected based on the network and their correlation with the clinicopathologic information and were validated in multiple centers (n = 775).ResultsWe constructed a competing endogenous RNA (ceRNA) regulatory network using RNA-seq. Genes associated with glycosylation pathways were embedded within this scale-free network. Moreover, we further developed and validated a seven-glycogene prognosis signature, GlycoSig (B3GNT6, GALNT3, GALNT8, ALG8, STT3B, SRD5A3, and ALG6) that prognosticate poor-prognostic subtype for pMMR CRAC patients. This biomarker set was validated in multicenter datasets, demonstrating its robustness and wide applicability. We constructed a simple-to-use nomogram that integrated the risk score of GlycoSig and clinicopathological features of pMMR CRAC patients.ConclusionsThe seven-glycogene signature served as a novel and robust prognostic biomarker set for pMMR CRAC, highlighting the role of a dysregulated glycosylation network in poor prognosis.

scholarly journals Integrative Analysis of lncRNA-mRNA Profile Reveals Potential Predictors for SAPHO Syndrome

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuxiu Sun ◽  
Chen Li ◽  
Qingyi Lu ◽  
Haixu Jiang ◽  
Mengmeng Zhu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Long Noncoding Rna ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Sapho Syndrome ◽  
Healthy Controls ◽  
Rna Seq ◽  
Expression Levels ◽  
Clinical Biomarkers ◽  
Mrna Profile

Synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome is known as a rare disease characterized by inflammatory lesions on bones and skin. Polymorphism of clinical manifestation and lack of molecular biomarkers have both limited its diagnosis. Our study performed RNA sequencing (RNA-seq) and integrative bioinformatics analysis of long noncoding RNA (lncRNA)-messenger RNA (mRNA) profile in patients with SAPHO syndrome and healthy controls. A total of 4,419 differentially expressed (DE) mRNAs and 2,713 lncRNAs were identified (p < 0.05, fold change > 2) and a coexpression network was constructed to further investigate their regulatory interactions. The DE lncRNAs were predicted to interact with mRNAs in both cis and trans manners. Functional prediction found that the lncRNA-targeted genes may function in SAPHO syndrome by participating in biological process such as adipocytokine signaling pathway, ErbB signaling pathway, FoxO signaling pathway, as well as production and function of miRNAs. The expression levels of three pairs of coexpressed lncRNA-mRNAs were validated by qRT-PCR, and their relative expression levels were consistent with the RNA-seq data. The deregulated RNAs GAS7 and lnc-CLLU1.1-1:2 may serve as potential diagnostic biomarkers, and the combined receiver operating characteristic (ROC) curve of the two showed more reliable diagnostic ability with an AUC value of 0.871 in distinguishing SAPHO patients from healthy controls. In conclusion, this study provides a first insight into long noncoding RNA transcriptome profile changes associated with SAPHO syndrome and inspiration for further investigation on clinical biomarkers and molecular regulators of this inadequately understood clinical entity.

scholarly journals RiceLncPedia: a comprehensive database of rice long non-coding RNAs

2020 ◽  
Author(s):  
Zhengfeng Zhang ◽  
Yao Xu ◽  
Fei Yang ◽  
Benze Xiao ◽  
Guoliang Li
Keyword(s):  
Experimental Validation ◽  
Developmental Stages ◽  
Data Sets ◽  
Omics Data ◽  
Biological Processes ◽  
Rna Seq ◽  
Current Version ◽  
Non Coding Rnas ◽  
Systematic Identification ◽  
Different Tissues

ABSTRACTLong non-coding RNAs (lncRNAs) play significant functions in various biological processes including differentiation, development and adaptation to different environments. Although multi research focused on lncRNAs in rice, the systematic identification and annotation of lncRNAs expressed in different tissues, developmental stages under diverse conditions are still scarce. This impacts the elucidation of their functional significance and the further research on them. Here, RiceLncPedia (http://218.199.68.191:10092/) is constructed including rice lncRNAs explored from 2313 publically available rice RNA-seq libraries and characterize them with multi-omics data sets. In the current version, RiceLncPedia shows 6978 lncRNAs with abundant features: (i) expression profile across 2313 rice RNA-seq libraries; (ii) an online genome browser for rice lncRNAs; (iii) genome SNPs in lncRNA transcripts; (iv) lncRNA associations with phenotype; (v) overlap of lncRNAs with transposons; and (vi) LncRNA-miRNA interactions and lncRNAs as the precursors of miRNAs. In total, RiceLncPedia imported numerous of rice lncRNAs during development under various environments as well as their features extracted from multi-omics data and thus serve as a fruitful resource for rice-related research communities. RiceLncPedia will be further updated with experimental validation, functions association and epigenetic characteristics to greatly facilitate future investigation on rice lncRNAs.

Missing data in open-data era – a barrier to multiomics integration

2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Monika Piwowar ◽  
Wiktor Jurkowski
Keyword(s):  
Quantitative Data ◽  
Open Data ◽  
Multidimensional Data ◽  
Data Sets ◽  
Biological Processes ◽  
Rna Seq ◽  
Data Set ◽  
Complex Interactions ◽  
Integrate Data ◽  
Generation Sequencing

AbstractThe exploration of complex interactions in biological systems is one of the main aims in nature science nowadays. Progress in this area is possible because of high-throughput omics technologies and the computational surge. The development of analytical methods “is trying to keep pace” with the development of molecular biology methods that provide increasingly large amounts of data – omics data. Specialized databases consist of ever-larger collections of experiments that are usually conducted by one next-generation sequencing technique (e.g. RNA-seq). Other databases integrate data by defining qualitative relationships between individual objects in the form of ontologies, interactions, and pathways (e.g. GO, KEGG, and String). However, there are no open-source complementary quantitative data sets for the biological processes studied, including information from many levels of the organism organization, which would allow the development of multidimensional data analysis methods (multiscale and insightful overviews of biological processes). In the paper, the lack of omics complementary quantitative data set, which would help integrate the defined qualitative biological relationships of individual biomolecules with statistical, computational methods, is discussed.

scholarly journals The Study of Alternative Splicing Events in Human Induced Pluripotent Stem Cells From a Down's Syndrome Patient

2021 ◽  
Vol 9 ◽  
Author(s):  
Yunjie Wang ◽  
Zexu Li ◽  
Guanheng Yang ◽  
Linlin Cai ◽  
Fan Yang ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Regulatory Networks ◽  
Potential Role ◽  
Down's Syndrome ◽  
Down’S Syndrome ◽  
Biological Processes ◽  
Protein Coding ◽  
Induced Pluripotent ◽  
Congenital Disabilities ◽  
Variable Penetrance

Down's syndrome (DS) is one of the most commonly known disorders with multiple congenital disabilities. Besides severe cognitive impairment and intellectual disability, individuals with DS also exhibit additional phenotypes of variable penetrance and severity, with one or more comorbid conditions, including Alzheimer's disease, congenital heart disease, or leukemia. Various vital genes and regulatory networks had been studied to reveal the pathogenesis of the disease. Nevertheless, very few studies have examined alternative splicing. Alternative splicing (AS) is a regulatory mechanism of gene expression when making one multi-exon protein-coding gene produce more than one unique mature mRNA. We employed the GeneChip Human Transcriptome Array 2.0 (HTA 2.0) for the global gene analysis with hiPSCs from DS and healthy individuals. Examining differentially expressed genes (DEGs) in these groups and focusing on specific transcripts with AS, 466 up-regulated and 722 down-regulated genes with AS events were identified. These genes were significantly enriched in biological processes, such as cell adhesion, cardiac muscle contraction, and immune response, through gene ontology (GO) analysis of DEGs. Candidate genes, such as FN1 were further explored for potentially playing a key role in DS. This study provides important insights into the potential role that AS plays in DS.

Bone Marrow Microenvironment Regulates Alternative Splicing Events in Myeloma Cells through Downregulation of RNA Binding Protein Fox2

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4714-4714
Author(s):  
Weihua Song ◽  
Chaolin Zhang ◽  
Yiguo Hu ◽  
Maria Gkotzamanidou ◽  
Parantu Shah ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Alternative Splicing ◽  
Cell Lines ◽  
Actin Polymerization ◽  
Rna Binding ◽  
Rna Binding Protein ◽  
Splicing Factor ◽  
Pcr Analysis ◽  
Rna Seq ◽  
Protein Coding

Abstract Alternative splicing is a crucial mechanism for gene regulation, which enhances the diversity of transcriptome and proteome. Misregulation of alternative splicing has been implicated in number of disease processes including cancer. Our data utilizing exon array profile from 170 uniformly treated newly diagnosed patients with MM confirms clinical relevance of splicing as demonstrated by impact of level and extent of alternate splicing on both progression free and overall survival. Fox2, a RNA splicing factor, is one of the most important genes predicting clinical outcome in these patients. We confirmed Fox2 expression in 10 MM cell lines at both RNA and protein levels. Immunohistochemistry staining showed a predominant nuclear localization of Fox2. Importantly, we also observed that MM cell - bone marrow stromal cells (BMSC) interaction led to significant inhibition of Fox2 expression in MM cells. Similar response was also observed using BMSC supernatants. While IL6 treatment significantly downregulated the expression of Fox2 in MM1S and RPMI8226 cells in a dose-dependent manner, IGF-1 treatment had no significant impact on Fox2 expression in MM cell lines. Since Fox2 has been described to plays a role in the maintenance of cell cytoskeleton, we therefore evaluated whether Fox2 might influence the migration and adhesion in MM cells. Transwell migration assay showed enhanced migration rate of Fox2-knocking down- MM1S and RPMI8226 cells versus controls. We also observed the increased cell adhesion to fibronetin in both cell lines upon Fox2 knockdown. Actin polymerization evaluated by Alexa488-conjugated phalloidin staining and confocal microscope analysis showed Fox2 knocking down cells with increased actin polymerization in both MM1S and RPMI8226 cell lines. Interstingly, we observed that Fox2 knockdown in MM cell lines did not affect the cell proliferation and survival. As Fox-2 is a splicing factor, we further evaluated the molecular impact of Fox2 expression in multiple myeloma by RNA-seq analysis. Our data revealed that Fox2 functions in regulating both protein-coding and non-coding RNA alternative splicing. Knockdown of Fox2 resulted in significant isoform up-regulation (60 in MM1S and 151 in RPMI8226) and down-regulation (70 in MM1S and 69 in RPMI8226). Gene enrichment analysis showed these genes are clustered in cell cytoskeleton regulation, microtubule-based movement, ATP binding, amongst others. Our study then focused on Fox2 knockdown-induced significant isoform switch in MM cell lines. We designed the primers testing the spliced exons and confirm the isoform switch in MM cells by PCR analysis (e.g. Pyk2 and PFDN6). Importantly, our RNA seq data showed that Fox2 regulates the expression of a series of microRNAs and long-noncoding RNAs (e.g. MALAT1 RPMI8226 CNT (58) vs Fox2 knockdown (108)), which provides us a new insight into impact of Fox2 on non-protein coding RNAs. We have also validated the RNA-seq data by Q-PCR analysis. In summary, our results identify Fox2 as a biologically important RNA binding protein that is regulated by bone marrow microenvironment interaction and with essential function and potential clinical implications in multiple myeloma. Disclosures No relevant conflicts of interest to declare.

scholarly journals Clinical and functional significance of circular RNAs in cytogenetically normal AML

2020 ◽  
Vol 4 (2) ◽  
pp. 239-251 ◽  
Author(s):  
Dimitrios Papaioannou ◽  
Stefano Volinia ◽  
Deedra Nicolet ◽  
Michał Świerniak ◽  
Andreas Petri ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Noncoding Rna ◽  
Prognostic Significance ◽  
High Sensitivity ◽  
Transcriptome Profiling ◽  
Circular Rnas ◽  
Data Sets ◽  
Validation Data ◽  
Molecular Features ◽  
Screening Experiments

Abstract Circular RNAs (circRNAs) are noncoding RNA molecules that display a perturbed arrangement of exons, called backsplicing. To examine the prognostic and biologic significance of circRNA expression in cytogenetically normal acute myeloid leukemia (CN-AML), we conducted whole-transcriptome profiling in 365 younger adults (age 18-60 years) with CN-AML. We applied a novel pipeline, called Massive Scan for circRNA, to identify and quantify circRNA expression. We validated the high sensitivity and specificity of our pipeline by performing RNase R treatment and RNA sequencing in samples of AML patients and cell lines. Unsupervised clustering analyses identified 3 distinct circRNA expression–based clusters with different frequencies of clinical and molecular features. After dividing our cohort into training and validation data sets, we identified 4 circRNAs (circCFLAR, circKLHL8, circSMC1A, and circFCHO2) that were prognostic in both data sets; high expression of each prognostic circRNA was associated with longer disease-free, overall, and event-free survival. In multivariable analyses, high circKLHL8 and high circFCHO2 expression were independently associated with better clinical outcome of CN-AML patients, after adjusting for other covariates. To examine the biologic relevance of circRNA expression, we performed knockdown screening experiments in a subset of prognostic and gene mutation–related candidate circRNAs. We identified circFBXW7, but not its linear messenger RNA, as a regulator of the proliferative capacity of AML blasts. In summary, our findings underscore the molecular associations, prognostic significance, and functional relevance of circRNA expression in CN-AML.

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