The yeast noncoding RNA interaction network.
Ontology highlight
ABSTRACT:
SUBMITTER: Panni S
PROVIDER: S-EPMC5602107 | biostudies-literature | 2017 Oct
REPOSITORIES: biostudies-literature
Publications
The yeast noncoding RNA interaction network.
Panni Simona S Prakash Ananth A Bateman Alex A Orchard Sandra S
RNA (New York, N.Y.) 20170712 10
This article describes the creation of the first expert manually curated noncoding RNA interaction networks for <i>S. cerevisiae</i> The RNA-RNA and RNA-protein interaction networks have been carefully extracted from the experimental literature and made available through the IntAct database (www.ebi.ac.uk/intact). We provide an initial network analysis and compare their properties to the much larger protein-protein interaction network. We find that the proteins that bind to ncRNAs in the network ...[more]
Similar Datasets
Project description:BackgroundLong noncoding RNAs (lncRNAs) are related to different biological processes in non-small cell lung cancer (NSCLC). However, the possible molecular mechanisms underlying the effects of the long noncoding RNA HOXA11-AS (HOXA11 antisense RNA) in NSCLC are unknown.MethodsHOXA11-AS was knocked down in the NSCLC A549 cell line and a high throughput microarray assay was applied to detect changes in the gene profiles of the A549 cells. Bioinformatics analyses (gene ontology (GO), pathway, Kyoto Encyclopedia of Genes and Genomes (KEGG), and network analyses) were performed to investigate the potential pathways and networks of the differentially expressed genes. The molecular signatures database (MSigDB) was used to display the expression profiles of these differentially expressed genes. Furthermore, the relationships between the HOXA11-AS, de-regulated genes and clinical NSCLC parameters were verified by using NSCLC patient information from The Cancer Genome Atlas (TCGA) database. In addition, the relationship between HOXA11-AS expression and clinical diagnostic value was analyzed by receiver operating characteristic (ROC) curve.ResultsAmong the differentially expressed genes, 277 and 80 genes were upregulated and downregulated in NSCLC, respectively (fold change ≥2.0, P < 0.05 and false discovery rate (FDR) < 0.05). According to the degree of the fold change, six upregulated and three downregulated genes were selected for further investigation. Only four genes (RSPO3, ADAMTS8, DMBT1, and DOCK8) were reported to be related with the development or progression of NSCLC based on a PubMed search. Among all possible pathways, three pathways (the PI3K-Akt, TGF-beta and Hippo signaling pathways) were the most likely to be involved in NSCLC development and progression. Furthermore, we found that HOXA11-AS was highly expressed in both lung adenocarcinoma and squamous cell carcinoma based on TCGA database. The ROC curve showed that the area under curve (AUC) of HOXA11-AS was 0.727 (95% CI 0.663-0.790) for lung adenocarcinoma and 0.933 (95% CI 0.906-0.960) for squamous cell carcinoma patients. Additionally, the original data from TCGA verified that ADAMTS8, DMBT1 and DOCK8 were downregulated in both lung adenocarcinoma and squamous cell carcinoma, whereas RSPO3 expression was upregulated in lung adenocarcinoma and downregulated in lung squamous cell carcinoma. For the other five genes (STMN2, SPINK6, TUSC3, LOC100128054, and C8orf22), we found that STMN2, TUSC3 and C8orf22 were upregulated in squamous cell carcinoma and that STMN2 and USC3 were upregulated in lung adenocarcinoma. Furthermore, we compared the correlation between HOXA11-AS and de-regulated genes in NSCLC based on TCGA. The results showed that the HOXA11-AS expression was negatively correlated with DOCK8 in squamous cell carcinoma (r = -0.124, P = 0.048) and lung adenocarcinoma (r = -0.176, P = 0.005). In addition, RSPO3, ADAMTS8 and DOCK8 were related to overall survival and disease-free survival (all P < 0.05) of lung adenocarcinoma patients in TCGA.ConclusionsOur results showed that the gene profiles were significantly changed after HOXA11-AS knock-down in NSCLC cells. We speculated that HOXA11-AS may play an important role in NSCLC development and progression by regulating the expression of various pathways and genes, especially DOCK8 and TGF-beta pathway. However, the exact mechanism should be verified by functional experiments.
| S-EPMC5133743 | biostudies-literature
Project description:Noncoding RNAs (ncRNAs) are emerging as key regulators of cellular function. We have exploited the recently developed barcoded ncRNA gene deletion strain collections in the yeast Saccharomyces cerevisiae to investigate the numerous ncRNAs in yeast with no known function. The ncRNA deletion collection contains deletions of tRNAs, snoRNAs, snRNAs, stable unannotated transcripts (SUTs), cryptic unstable transcripts (CUTs) and other annotated ncRNAs encompassing 532 different individual ncRNA deletions. We have profiled the fitness of the diploid heterozygous ncRNA deletion strain collection in six conditions using batch and continuous liquid culture, as well as the haploid ncRNA deletion strain collections arrayed individually onto solid rich media. These analyses revealed many novel environmental-specific haplo-insufficient and haplo-proficient phenotypes providing key information on the importance of each specific ncRNA in every condition. Co-fitness analysis using fitness data from the heterozygous ncRNA deletion strain collection identified two ncRNA groups required for growth during heat stress and nutrient deprivation. The extensive fitness data for each ncRNA deletion strain has been compiled into an easy to navigate database called Yeast ncRNA Analysis (YNCA). By expanding the original ncRNA deletion strain collection we identified four novel essential ncRNAs; SUT527, SUT075, SUT367 and SUT259/691. We defined the effects of each new essential ncRNA on adjacent gene expression in the heterozygote background identifying both repression and induction of nearby genes. Additionally, we discovered a function for SUT527 in the expression, 3' end formation and localization of SEC4, an essential protein coding mRNA. Finally, using plasmid complementation we rescued the SUT075 lethal phenotype revealing that this ncRNA acts in trans. Overall, our findings provide important new insights into the function of ncRNAs.
| S-EPMC5864082 | biostudies-literature
Project description:A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein-protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70-80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).
| S-EPMC3337474 | biostudies-literature
Project description:To study the evolution of the yeast protein interaction network, we first classified yeast proteins by their evolutionary histories into isotemporal categories, then analyzed the interaction tendencies within and between the categories, and finally reconstructed the main growth path. We found that two proteins tend to interact with each other if they are in the same or similar categories, but tended to avoid each other otherwise, and that network evolution mirrors the universal tree of life. These observations suggest synergistic selection during network evolution and provide insights into the hierarchical modularity of cellular networks.
| S-EPMC240702 | biostudies-literature
Project description:Glioma is considered to be the most common brain malignancy in the central nervous system. At present, the aetiology of glioma is not clear. Due to its rapidly growth and easily recurrence, the prognosis of patients with glioma is very poor. N6-methyladenosine (m6A) methylation is an internal reversible modification in most RNAs, including messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). Recent studies have shown that the m6A regulators are abnormal expressed, and are extensively involved in the progression of glioma by targeting ncRNAs. Moreover, as the most important epigenetic regulators, ncRNAs can also affect the function of m6A regulators in glioma. This review summarized the expression and function of certain common m6A regulators in glioma. Also, the current review sum up the mutual interactions between m6A regulators and ncRNAs in glioma.
| S-EPMC9187709 | biostudies-literature
Project description:1. Evaluate the diagnostic value of long noncoding RNA (CCAT1) expression by RT-PCR in peripheral blood in colorectal cancer patients versus normal healthy control personal.
2. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in diagnosis of colorectal cancer patients & its relation to tumor staging.
3. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in precancerous colorectal diseases.
4. Compare long noncoding RNA (CCAT1) expression with traditional marker; carcinoembryonic antigen (CEA) and Carbohydrate antigen 19-9 (CA19-9) in diagnosis of colorectal cancer.
| 2330122 | ecrin-mdr-crc
Project description:Telomerase is a ribonucleoprotein that maintains the ends of linear chromosomes in most eukaryotes. Loss of telomerase activity results in shortening of telomeric DNA and eventually a specific G2/M cell-cycle arrest known as senescence. In humans, telomere shortening occurs during aging, while inappropriate activation of telomerase is associated with approximately 90% of cancers. Previous studies have identified several classes of noncoding RNAs (ncRNA) also associated with aging-related senescence and cancer, but whether ncRNAs are also involved in short-telomere-induced senescence in yeast is unknown. Here, we report 112 putative novel lncRNAs in the yeast Saccharomyces cerevisiae, 41 of which are only expressed in telomerase-negative yeast. Expression of approximately half of the lncRNAs is strongly correlated with that of adjacent genes, suggesting this subset may influence transcription of neighboring genes. Our results reveal a new potential mechanism governing adaptive changes in senescing and post-senescent survivor yeast cells.
| S-EPMC4726298 | biostudies-literature
Project description:Many cellular functions are mediated by protein-protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment-dependent protein complex dynamics, we used a DNA-barcode-based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that "concerted" protein-centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass-action-based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.
| S-EPMC5527849 | biostudies-literature
Project description:BackgroundThe recently emerged protein interaction network paradigm can provide novel and important insights into the innerworkings of a cell. Yet, the heavy burden of both false positive and false negative protein-protein interaction data casts doubt on the broader usefulness of these interaction sets. Approaches focusing on one-protein-at-a-time have been powerfully employed to demonstrate the high degree of conservation of proteins participating in numerous interactions; here, we expand his 'node' focused paradigm to investigate the relative persistence of 'link' based evolutionary signals in a protein interaction network of S. cerevisiae and point out the value of this relatively untapped source of information.ResultsThe trend for highly connected proteins to be preferably conserved in evolution is stable, even in the context of tremendous noise in the underlying protein interactions as well as in the assignment of orthology among five higher eukaryotes. We find that local clustering around interactions correlates with preferred evolutionary conservation of the participating proteins; furthermore the correlation between high local clustering and evolutionary conservation is accompanied by a stable elevated degree of coexpression of the interacting proteins. We use this conserved interaction data, combined with P. falciparum/Yeast orthologs, as proof-of-principle that high-order network topology can be used comparatively to deduce local network structure in non-model organisms.ConclusionHigh local clustering is a criterion for the reliability of an interaction and coincides with preferred evolutionary conservation and significant coexpression. These strong and stable correlations indicate that evolutionary units go beyond a single protein to include the interactions among them. In particular, the stability of these signals in the face of extreme noise suggests that empirical protein interaction data can be integrated with orthologous clustering around these protein interactions to reliably infer local network structures in non-model organisms.
| S-EPMC1395346 | biostudies-literature
Project description:Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.
| S-EPMC9132594 | biostudies-literature