Rank-in: enabling integrative analysis across microarray and RNA-seq for cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Tang K
PROVIDER: S-EPMC8464058 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gene expression profiling of psoriasis has driven research advances and may soon provide the basis for clinical applications. For expression profiling studies, RNA-seq is now a competitive technology, but RNA-seq results may differ from those obtained by microarray. We therefore compared findings obtained by RNA-seq with those from eight microarray studies of psoriasis. RNA-seq and microarray datasets identified similar numbers of differentially expressed genes (DEGs), with certain genes uniquely identified by each technology. Correspondence between platforms and the balance of increased to decreased DEGs was influenced by mRNA abundance, GC content, and gene length. Weakly expressed genes, genes with low GC content, and long genes were all biased toward decreased expression in psoriasis lesions. The strength of these trends differed among array datasets, most likely due to variations in RNA quality. Gene length bias was by far the strongest trend and was evident in all datasets regardless of the expression profiling technology. The effect was due to differences between lesional and uninvolved skin with respect to the genome-wide correlation between gene length and gene expression, which was consistently more negative in psoriasis lesions. These findings demonstrate the complementary nature of RNA-seq and microarray technology and show that integrative analysis of both data types can provide a richer view of the transcriptome than strict reliance on a single method alone. Our results also highlight factors affecting correspondence between technologies, and we have established that gene length is a major determinant of differential expression in psoriasis lesions.
| S-EPMC4121624 | biostudies-literature
Project description:Our previous integrative study in gastric cancer discovered cryptic promoter activation events that drive the expression of important developmental genes. However, it was unclear if such cancer-associated epigenetic changes occurred in cancer cells or other cell types in bulk tissue samples. An integrative analysis consisting of RNA-Seq and H3K4me3 ChIP-Seq was used. This workflow was applied to a set of matched normal lung tissues and non-small cell lung cancer (NSCLC) tissues, for which the stroma and tumor cell parts could be isolated by laser-microdissection microscopy (LMD). RNA-Seq analysis showed subtype-specific differential expressed genes and enriched pathways in NSCLC. ChIP-Seq analysis results suggested that the proximal altered H3K4me3 regions were located at differentially expressed genes involved in cancer-related pathways, while altered distal H3K4me3 regions were annotated with enhancer activity of cancer regulatory genes. Interestingly, integration with ENCODE data revealed that proximal tumor-gained promoters were associated with EZH2 and SUZ12 occupancies, which are the core components of polycomb repressive complex 2 (PRC2). This study used LMD on clinical samples for an integrative analysis to overcome the tissue heterogeneity problem in cancer research. The results also contribute to the overall understanding of genetic and epigenetic dysregulation of lung malignancy.
| S-EPMC8038546 | biostudies-literature
Project description:BackgroundDeregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.ResultsWe observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.ConclusionOur data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.
| S-EPMC3961325 | biostudies-literature
Project description:RNA-seq is currently the technology of choice for global measurement of transcript abundances in cells. Despite its successes, isoform-level quantification remains difficult because short RNA-seq reads are often compatible with multiple alternatively spliced isoforms. Existing methods rely heavily on uniquely mapping reads, which are not available for numerous isoforms that lack regions of unique sequence. To improve quantification accuracy in such difficult cases, we developed a novel computational method, prior-enhanced RSEM (pRSEM), which uses a complementary data type in addition to RNA-seq data. We found that ChIP-seq data of RNA polymerase II and histone modifications were particularly informative in this approach. In qRT-PCR validations, pRSEM was shown to be superior than competing methods in estimating relative isoform abundances within or across conditions. Data-driven simulations suggested that pRSEM has a greatly decreased false-positive rate at the expense of a small increase in false-negative rate. In aggregate, our study demonstrates that pRSEM transforms existing capacity to precisely estimate transcript abundances, especially at the isoform level.
| S-EPMC4971760 | biostudies-literature
Project description:PurposeCorneal epithelial homeostasis is maintained by coordinated gene expression across distinct cell populations, but the gene regulatory programs underlying this cellular diversity remain to be characterized. Here we applied single-cell multi-omics analysis to delineate the gene regulatory profile of mouse corneal epithelial cells under normal homeostasis.MethodsSingle cells isolated from the cornea epithelium (with marginal conjunctiva) of adult mice were subjected to scRNA-seq and scATAC-seq using the 10×Genomics platform. Cell types were clustered by the graph-based visualization method uniform manifold approximation and projection and unbiased computational informatics analysis. The scRNA-seq and scATAC-seq datasets were integrated following the integration pipeline described in ArchR and Seurat.ResultsWe characterized diverse corneal epithelial cell types based on gene expression signatures and chromatin accessibility. We found that cell type-specific accessibility regions were mainly located at distal regions, suggesting essential roles of distal regulatory elements in determining corneal epithelial cell diversity. Trajectory analyses revealed a continuum of cell state transition and higher coordination between transcription factor (TF) motif accessibility and gene expression during corneal epithelial cell differentiation. By integrating transcriptomic and chromatin accessibility analysis, we identified cell type-specific and shared gene regulation programs. We also uncovered critical TFs driving corneal epithelial cell differentiation, such as nuclear factor I (NFI) family members, Rarg, Elf3. We found that nuclear factor-κB (NF-κB) family members were positive TFs in limbal cells and some superficial cells, but they were involved in regulating distinct biological processes.ConclusionsOur study presents a comprehensive gene regulatory landscape of mouse cornea epithelial cells, and provides valuable foundations for future investigation of corneal epithelial homeostasis in the context of cornea pathologies and regenerative medicine.
| S-EPMC10043503 | biostudies-literature
Project description:BackgroundSkeletal muscle development is a multistep process whose understanding is central in a broad range of fields and applications, from the potential medical value to human society, to its economic value associated with improvement of agricultural animals. Skeletal muscle initiates in the somites, with muscle precursor cells generated in the dermomyotome and dermomyotome-derived myotome before muscle differentiation ensues, a developmentally regulated process that is well characterized in model organisms. However, the regulation of skeletal muscle ontogeny during embryonic development remains poorly defined in farm animals, for instance in pig. Here, we profiled gene expression and chromatin accessibility in developing pig somites and myotomes at single-cell resolution.ResultsWe identified myogenic cells and other cell types and constructed a differentiation trajectory of pig skeletal muscle ontogeny. Along this trajectory, the dynamic changes in gene expression and chromatin accessibility coincided with the activities of distinct cell type-specific transcription factors. Some novel genes upregulated along the differentiation trajectory showed higher expression levels in muscular dystrophy mice than that in healthy mice, suggesting their involvement in myogenesis. Integrative analysis of chromatin accessibility, gene expression data, and in vitro experiments identified EGR1 and RHOB as critical regulators of pig embryonic myogenesis.ConclusionsCollectively, our results enhance our understanding of the molecular and cellular dynamics in pig embryonic myogenesis and offer a high-quality resource for the further study of pig skeletal muscle development and human muscle disease.
| S-EPMC9893630 | biostudies-literature
Project description:Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets.To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments.GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.
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Project description:Molecular heterogeneity has great significance in the disease biology of multiple myeloma (MM). Thus, the analysis combined single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data were performed to investigate the clonal evolution characteristics and to find novel prognostic targets in MM. The scRNA-seq data were analyzed by the Seurat pipeline and Monocle 2 to identify MM cell branches with different differentiation states. Marker genes in each branch were uploaded to the STRING database to construct the Protein-Protein Interaction (PPI) network, followed by the detection of hub genes by Cytoscape software. Using bulk RNA-seq data, Kaplan-Meier (K-M) survival analysis was then carried out to determine prognostic biomarkers in MM. A total of 342 marker genes in two branches with different differentiation states were identified, and the top 20 marker genes with the highest scores in the network calculated by the MCC algorithm were selected as hub genes in MM. Furthermore, K-M survival analysis revealed that higher NDUFB8, COX6C, NDUFA6, USMG5, and COX5B expression correlated closely with a worse prognosis in MM patients. Moreover, ssGSEA and Pearson analyses showed that their expression had a significant negative correlation with the proportion of Tcm (central memory cell) immune cells. Our findings identified NDUFB8, COX6C, NDUFA6, USMG5, and COX5B as novel prognostic biomarkers in MM, and also revealed the significance of genetic heterogeneity during cell differentiation in MM prognosis.
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Project description:The immune microenvironment is a culmination of the collaborative effort of immune cells and is important in cancer development. The underlying mechanisms of the tumor immune microenvironment in regulating prostate cancer (PRAD) are unclear. In the current study, 144 natural killer cell-related genes were identified using differential expression, single-sample gene set enrichment analysis, and weighted gene coexpression network analysis. Furthermore, VCL, ACTA2, MYL9, MYLK, MYH11, TPM1, ACTG2, TAGLN, and FLNC were selected as hub genes via the protein-protein interaction network. Based on the expression patterns of the hub genes, endothelial, epithelial, and tissue stem cells were identified as key cell subpopulations, which could regulate PRAD via immune response, extracellular signaling, and protein formation. Moreover, 27 genes were identified as prognostic signatures and used to construct the risk score model. Receiver operating characteristic curves revealed the good performance of the risk score model in both the training and testing datasets. Different chemotherapeutic responses were observed between the low- and high-risk groups. Additionally, a nomogram based on the risk score and other clinical features was established to predict the 1-, 3-, and 5-year progression-free interval of patients with PRAD. This study provides novel insights into the molecular mechanisms of the immune microenvironment and its role in the pathogenesis of PARD. The identification of key cell subpopulations has a potential therapeutic and prognostic use in PRAD.
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Project description:Luchuan pig is a typical obese pig breed in China, and the diameter and area of its longissimus dorsi muscle fibers are significantly smaller than those of Duroc (lean) pig. Skeletal muscle fiber characteristics are related to meat quality of livestock. There is a significant correlation between the quality of different breeds of pork and the characteristics of muscle fiber, which is an important factor affecting the quality of pork. The diameter and area of muscle fibers are related to muscle growth and development. Therefore, we used the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing (RNA-seq) analysis to investigate the potential mechanism underlying the difference in skeletal muscle growth and development between the two types of pigs. First, transposase-accessible chromatin was analyzed to map the landscape of open chromatin regions and transcription factor binding sites. We identified several transcription factors that potentially affected muscle growth and development, including TFAP4, MAX, NHLH1, FRX5, and TGIF1. We also found that transcription factors with basic helix-loop-helix structures had a preference for binding to genes involved in muscle development. Then, by integrating ATAC-seq and RNA-seq, we found that the Wnt signaling pathway, the mTOR signaling pathway, and other classical pathways regulate skeletal muscle development. In addition, some pathways that might regulate skeletal muscle growth, such as parathyroid hormone synthesis, secretion, and action, synthesis and degradation of ketone bodies, and the thyroid hormone signaling pathway, which were significantly enriched. After further study, we identified a number of candidate genes (ASNS, CARNS1, G0S2, PPP1R14C, and SH3BP5) that might be associated with muscle development. We also found that the differential regulation of chromatin openness at the level of some genes was contrary to the differential regulation at the level of transcription, suggesting that transcription factors and transcriptional repressors may be involved in the regulation of gene expression. Our study provided an in-depth understanding of the mechanism behind the differences in muscle fibers from two species of pig and provided an important foundation for further research on improving the quality of pork.
| S-EPMC8511529 | biostudies-literature