Browsing by Subject "Gene regulatory networks"
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Item A modulator based regulatory network for ERα signaling pathway(Springer Nature, 2012) Wu, Heng-Yi; Zheng, Pengyue; Jiang, Guanglong; Liu, Yunlong; Nephew, Kenneth P.; Huang, Tim H. M.; Li, Lang; Center for Computational Biology and Bioinformatics, School of MedicineBackground: Estrogens control multiple functions of hormone-responsive breast cancer cells. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. ERα requires distinct co-regulator or modulators for efficient transcriptional regulation, and they form a regulatory network. Knowing this regulatory network will enable systematic study of the effect of ERα on breast cancer. Methods: To investigate the regulatory network of ERα and discover novel modulators of ERα functions, we proposed an analytical method based on a linear regression model to identify translational modulators and their network relationships. In the network analysis, a group of specific modulator and target genes were selected according to the functionality of modulator and the ERα binding. Network formed from targets genes with ERα binding was called ERα genomic regulatory network; while network formed from targets genes without ERα binding was called ERα non-genomic regulatory network. Considering the active or repressive function of ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on ERα, the ERα/modulator/target relationships were categorized into 27 classes. Results: Using the gene expression data and ERα Chip-seq data from the MCF-7 cell line, the ERα genomic/non-genomic regulatory networks were built by merging ERα/ modulator/target triplets (TF, M, T), where TF refers to the ERα, M refers to the modulator, and T refers to the target. Comparing these two networks, ERα non-genomic network has lower FDR than the genomic network. In order to validate these two networks, the same network analysis was performed in the gene expression data from the ZR-75.1 cell. The network overlap analysis between two cancer cells showed 1% overlap for the ERα genomic regulatory network, but 4% overlap for the non-genomic regulatory network. Conclusions: We proposed a novel approach to infer the ERα/modulator/target relationships, and construct the genomic/non-genomic regulatory networks in two cancer cells. We found that the non-genomic regulatory network is more reliable than the genomic regulatory network.Item Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis(Hindawi, 2022-02-07) Zhang, Hongliang; Chen, Tingting; Zhang, Yunyan; Lin, Jiangbo; Zhao, Wenjun; Shi, Yangyang; Lau, Huichong; Zhang, Yang; Yang, Minjun; Xu, Cheng; Tang, Lijiang; Xu, Baohui; Jiang, Jianjun; Chen, Xiaofeng; Radiation Oncology, School of MedicineBackground: Aortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis. Method: Nine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO). Results: DEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD. Conclusion: Our analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.Item The Direct Reprogramming of Somatic Cells: Establishment of a Novel System for Photoreceptor Derivation(2013-08-22) Steward, Melissa Mary; Meyer, Jason S.; Dai, Guoli; Randall, Stephen Karl, 1953-; Atkinson, SimonPhotoreceptors are a class of sensory neuronal cells that are deleteriously affected in many disorders and injuries of the visual system. Significant injury or loss of these cells often results in a partial or complete loss of vision. While previous studies have determined many necessary components of the gene regulatory network governing the establishment, development, and maintenance of these cells, the necessary and sufficient profile and timecourse of gene expression and/or silencing has yet to be elucidated. Arduous protocols do exist to derive photoreceptors in vitro utilizing pluripotent stem cells, but only recently have been able to yield cells that are disease- and/or patient-specific. The discovery that mammalian somatic cells can be directly reprogrammed to another terminally-differentiated cell phenotype has inspired an explosion of research demonstrating the successful genetic reprogramming of one cell type to another, a process which is typically both more timely and efficient than those used to derive the same cells from pluripotent stem cell sources. Therefore, the emphasis of this study was to establish a novel system to be used to determine a minimal transcriptional network capable of directly reprogramming mouse embryonic fibroblasts (MEFs) to rod photoreceptors. The tools, assays, and experimental design chosen and established herein were designed and characterized to facilitate this determination, and preliminary data demonstrated the utility of this approach for accomplishing this aim.Item From genes to networks: in systematic points of view(Springer Nature, 2011) Zhang, Ke; Liu, Yunlong; Yang, Jack Y.; Arabnia, Hamid R.; Niemierko, Andrzej; Ghafoor, Arif; Li, Weizhong; Deng, Youping; Medical and Molecular Genetics, School of MedicineWe present a report of the BIOCOMP'10 - The 2010 International Conference on Bioinformatics & Computational Biology and other related work in the area of systems biology.Item Intron retention-induced neoantigen load correlates with unfavorable prognosis in multiple myeloma(Springer Nature, 2021-10) Dong, Chuanpeng; Cesarano, Annamaria; Bombaci, Giuseppe; Reiter, Jill L.; Yu, Christina Y.; Wang, Yue; Jiang, Zhaoyang; Zaid, Mohammad Abu; Huang, Kun; Lu, Xiongbin; Walker, Brian A.; Perna, Fabiana; Liu, Yunlong; BioHealth Informatics, School of Informatics and ComputingNeoantigen peptides arising from genetic alterations may serve as targets for personalized cancer vaccines and as positive predictors of response to immune checkpoint therapy. Mutations in genes regulating RNA splicing are common in hematological malignancies leading to dysregulated splicing and intron retention (IR). In this study, we investigated IR as a potential source of tumor neoantigens in multiple myeloma (MM) patients and the relationship of IR-induced neoantigens (IR-neoAg) with clinical outcomes. MM-specific IR events were identified in RNA-sequencing data from the Multiple Myeloma Research Foundation CoMMpass study after removing IR events that also occurred in normal plasma cells. We quantified the IR-neoAg load by assessing IR-induced novel peptides that were predicted to bind to major histocompatibility complex (MHC) molecules. We found that high IR-neoAg load was associated with poor overall survival in both newly diagnosed and relapsed MM patients. Further analyses revealed that poor outcome in MM patients with high IR-neoAg load was associated with high expression levels of T-cell co-inhibitory molecules and elevated interferon signaling activity. We also found that MM cells exhibiting high IR levels had lower MHC-II protein abundance and treatment of MM cells with a spliceosome inhibitor resulted in increased MHC-I protein abundance. Our findings suggest that IR-neoAg may represent a novel biomarker of MM patient clinical outcome and further that targeting RNA splicing may serve as a potential therapeutic strategy to prevent MM immune escape and promote response to checkpoint blockade.Item IRIS-FGM: an integrative single-cell RNA-Seq interpretation system for functional gene module analysis(Oxford University Press, 2021) Chang, Yuzhou; Allen, Carter; Wan, Changlin; Chung, Dongjun; Zhang, Chi; Li, Zihai; Ma, Qin; Medical and Molecular Genetics, School of MedicineSummary: Single-cell RNA-Seq (scRNA-Seq) data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of condition-specific functional gene modules (FGM) can help to understand interactive gene networks and complex biological processes in different cell clusters. QUBIC2 is recognized as one of the most efficient and effective biclustering tools for condition-specific FGM identification from scRNA-Seq data. However, its limited availability to a C implementation restricted its application to only a few downstream analysis functionalities. We developed an R package named IRIS-FGM (Integrative scRNA-Seq Interpretation System for Functional Gene Module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can effectively identify condition-specific FGMs, predict cell types/clusters, uncover differentially expressed genes and perform pathway enrichment analysis. It is noteworthy that IRIS-FGM can also take Seurat objects as input, facilitating easy integration with the existing analysis pipeline. Availability and implementation: IRIS-FGM is implemented in the R environment (as of version 3.6) with the source code freely available at https://github.com/BMEngineeR/IRISFGM.Item Microgravity's effects on miRNA-mRNA regulatory networks in a mouse model of segmental bone defects(Public Library of Science, 2024-12-02) Gautam, Aarti; Chakraborty, Nabarun; Dimitrov, George; Hoke, Allison; Miller, Stacy Ann; Swift, Kevin; Sowe, Bintu; Conley, Carolynn; Kacena, Melissa A.; Hammamieh, Rasha; Orthopaedic Surgery, School of MedicineRehabilitation from musculoskeletal injuries (MSKI) complicate healing dynamics typically by sustained disuse of bone and muscles. Microgravity naturally allows limb disuse and thus an effective model to understand MSKI. The current study examined epigenetic changes in a segmental bone defect (SBD) mouse model in a prolonged unloading condition after spaceflight (FLT). We further connected potential miRNA-mRNA regulatory pathways impacting bone healing. Here, SBD surgery was performed on nine-week-old male mice that were launched into space for approximately 4 weeks. Sham with no surgery and ground controls were included in the study. The midshaft of the ipsilateral femur (with callus on the surgical mice) as well as the ipsilateral quadriceps tissue were used for analysis. Femur and quadriceps had a distinct miRNA profile. There was a stronger surgery effect as observed by miRNA expression when compared to microgravity effects. Leukopoiesis, granulopoiesis, myelopoiesis of leukocytes, differentiation of myeloid leukocytes, and differentiation of progenitor cells were all altered because of surgery in the femur. The biological functions such as apoptosis, necrosis, and activation of cell migration and viability were altered because of surgery in quadriceps. Integrating the transcriptome and microRNA data indicated pronounced changes because of microgravity. According to pathway analysis, microgravity had a greater impact on the quadriceps tissue than the bone tissue in the absence of surgery. The altered biological functions resulting from microgravity were validated by integrating limited proteomics data to miRNA-mRNA. Thus, this study highlights the importance of dynamic interplay of gene-epigene regulations as they appear to be intrinsically interconnected and influence in combination for the biological outcome.Item Mutational landscape of RNA-binding proteins in human cancers(Taylor & Francis, 2018-01-02) Neelamraju, Yaseswini; Gonzalez-Perez, Abel; Bhat-Nakshatri, Poornima; Nakshatri, Harikrishna; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and ComputingRNA Binding Proteins (RBPs) are a class of post-transcriptional regulatory molecules which are increasingly documented to be dysfunctional in cancer genomes. However, our current understanding of these alterations is limited. Here, we delineate the mutational landscape of ∼1300 RBPs in ∼6000 cancer genomes. Our analysis revealed that RBPs have an average of ∼3 mutations per Mb across 26 cancer types. We identified 281 RBPs to be enriched for mutations (GEMs) in at least one cancer type. GEM RBPs were found to undergo frequent frameshift and inframe deletions as well as missense, nonsense and silent mutations when compared to those that are not enriched for mutations. Functional analysis of these RBPs revealed the enrichment of pathways associated with apoptosis, splicing and translation. Using the OncodriveFM framework, we also identified more than 200 candidate driver RBPs that were found to accumulate functionally impactful mutations in at least one cancer. Expression levels of 15% of these driver RBPs exhibited significant difference, when transcriptome groups with and without deleterious mutations were compared. Functional interaction network of the driver RBPs revealed the enrichment of spliceosomal machinery, suggesting a plausible mechanism for tumorogenesis while network analysis of the protein interactions between RBPs unambiguously revealed the higher degree, betweenness and closeness centrality for driver RBPs compared to non-drivers. Analysis to reveal cancer-specific Ribonucleoprotein (RNP) mutational hotspots showed extensive rewiring even among common drivers between cancer types. Knockdown experiments on pan-cancer drivers such as SF3B1 and PRPF8 in breast cancer cell lines, revealed cancer subtype specific functions like selective stem cell features, indicating a plausible means for RBPs to mediate cancer-specific phenotypes. Hence, this study would form a foundation to uncover the contribution of the mutational spectrum of RBPs in dysregulating the post-transcriptional regulatory networks in different cancer types.Item Network analysis identifies strain-dependent response to tau and tau seeding-associated genes(Rockefeller University Press, 2023) Acri, Dominic J.; You, Yanwen; Tate, Mason D.; Karahan, Hande; Martinez, Pablo; McCord, Brianne; Sharify, A. Daniel; John, Sutha; Kim, Byungwook; Dabin, Luke C.; Philtjens, Stéphanie; Wijeratne, H. R. Sagara; McCray, Tyler J.; Smith, Daniel C.; Bissel, Stephanie J.; Lamb, Bruce T.; Lasagna-Reeves, Cristian A.; Kim, Jungsu; Anatomy, Cell Biology and Physiology, School of MedicinePrevious research demonstrated that genetic heterogeneity is a critical factor in modeling amyloid accumulation and other Alzheimer's disease phenotypes. However, it is unknown what mechanisms underlie these effects of genetic background on modeling tau aggregate-driven pathogenicity. In this study, we induced tau aggregation in wild-derived mice by expressing MAPT. To investigate the effect of genetic background on the action of tau aggregates, we performed RNA sequencing with brains of C57BL/6J, CAST/EiJ, PWK/PhJ, and WSB/EiJ mice (n = 64) and determined core transcriptional signature conserved in all genetic backgrounds and signature unique to wild-derived backgrounds. By measuring tau seeding activity using the cortex, we identified 19 key genes associated with tau seeding and amyloid response. Interestingly, microglial pathways were strongly associated with tau seeding activity in CAST/EiJ and PWK/PhJ backgrounds. Collectively, our study demonstrates that mouse genetic context affects tau-mediated alteration of transcriptome and tau seeding. The gene modules associated with tau seeding provide an important resource to better model tauopathy.Item PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology(Oxford Academic, 2018-01-04) Yue, Zongliang; Zheng, Qi; Neylon, Michael T.; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon; Chen, Jake Yue; BioHealth Informatics, School of Informatics and ComputingIntegrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug-gene, miRNA-gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/.