Co-expression network analysis and genetic algorithms for gene prioritization in preeclampsia

TGFβ signalling: a nexus between inflammation, placental health and preeclampsia throughout pregnancy

BACKGROUND

The placenta is a unique and pivotal organ in reproduction, controlling crucial growth and cell differentiation processes that ensure a successful pregnancy. Placental development is a tightly regulated and dynamic process, in which the transforming growth factor beta (TGFβ) superfamily plays a central role. This family of pleiotropic growth factors is heavily involved in regulating various aspects of reproductive biology, particularly in trophoblast differentiation during the first trimester of pregnancy. TGFβ signalling precisely regulates trophoblast invasion and the cell transition from cytotrophoblasts to extravillous trophoblasts, which is an epithelial-to-mesenchymal transition-like process. Later in pregnancy, TGFβ signalling ensures proper vascularization and angiogenesis in placental endothelial cells. Beyond its role in trophoblasts and endothelial cells, TGFβ signalling contributes to the polarization and function of placental and decidual macrophages by promoting maternal tolerance of the semi-allogeneic foetus. Disturbances in early placental development have been associated with several pregnancy complications, including preeclampsia (PE) which is one of the severe complications. Emerging evidence suggests that TGFβ is involved in the pathogenesis of PE, thereby offering a potential target for intervention in the human placenta.

OBJECTIVE AND RATIONALE

This comprehensive review aims to explore and elucidate the roles of the major members of the TGFβ superfamily, including TGFβs, bone morphogenetic proteins (BMPs), activins, inhibins, nodals, and growth differentiation factors (GDFs), in the context of placental development and function. The review focusses on their interactions within the major cell types of the placenta, namely trophoblasts, endothelial cells, and immune cells, in both normal pregnancies and pregnancies complicated by PE throughout pregnancy.

SEARCH METHODS

A literature search was carried out using PubMed and Google Scholar, searching terms: 'TGF signalling preeclampsia', 'pregnancy TGF signalling', 'preeclampsia tgfβ', 'preeclampsia bmp', 'preeclampsia gdf', 'preeclampsia activin', 'endoglin preeclampsia', 'endoglin pregnancy', 'tgfβ signalling pregnancy', 'bmp signalling pregnancy', 'gdf signalling pregnancy', 'activin signalling pregnancy', 'Hofbauer cell tgfβ signalling', 'placental macrophages tgfβ', 'endothelial cells tgfβ', 'endothelium tgfβ signalling', 'trophoblast invasion tgfβ signalling', 'trophoblast invasion Smad', 'trophoblast invasion bmp', 'trophoblast invasion tgfβ', 'tgfβ preeclampsia', 'tgfβ placental development', 'TGFβ placental function', 'endothelial dysfunction preeclampsia tgfβ signalling', 'vascular remodelling placenta TGFβ', 'inflammation pregnancy tgfβ', 'immune response pregnancy tgfβ', 'immune tolerance pregnancy tgfβ', 'TGFβ pregnancy NK cells', 'bmp pregnancy NK cells', 'bmp pregnancy tregs', 'tgfβ pregnancy tregs', 'TGFβ placenta NK cells', 'TGFβ placenta tregs', 'NK cells preeclampsia', 'Tregs preeclampsia'. Only articles published in English until 2023 were used.

OUTCOMES

A comprehensive understanding of TGFβ signalling and its role in regulating interconnected cell functions of the main placental cell types provides valuable insights into the processes essential for successful placental development and growth of the foetus during pregnancy. By orchestrating trophoblast invasion, vascularization, immune tolerance, and tissue remodelling, TGFβ ligands contribute to the proper functioning of a healthy maternal-foetal interface. However, dysregulation of TGFβ signalling has been implicated in the pathogenesis of PE, where the shallow trophoblast invasion, defective vascular remodelling, decreased uteroplacental perfusion, and endothelial cell and immune dysfunction observed in PE, are all affected by an altered TGFβ signalling.

WIDER IMPLICATIONS

The dysregulation of TGFβ signalling in PE has important implications for research and clinical practice. Further investigation is required to understand the underlying mechanisms, including the role of different ligands and their regulation under pathophysiological conditions, in order to discover new therapeutic targets. Distinguishing between clinically manifested subtypes of PE and studying TGFβ signalling in different placental cell types holistically is an important first step. To put this knowledge into practice, pre-clinical animal models combined with new technologies are needed. This may also lead to improved human research models and identify potential therapeutic targets, ultimately improving outcomes for affected pregnancies and reducing the burden of PE.

A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles-derived transcriptomic biomarkers in early-onset preeclampsia

Background

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%-8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies.

Objective

The objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways.

Methods/study design

We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions.

Results

Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways.

Conclusions

In this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.

eoPred: predicting the placental phenotype of early-onset preeclampsia using public DNA methylation data

Background: A growing body of literature has reported molecular and histological changes in the human placenta in association with preeclampsia (PE). Placental DNA methylation (DNAme) and transcriptomic patterns have revealed molecular subgroups of PE that are associated with placental histopathology and clinical phenotypes of the disease. However, the clinical and molecular heterogeneity of PE both across and within subtypes complicates the study of this disease. PE is most strongly associated with placental pathology and adverse fetal and maternal outcomes when it develops early in pregnancy. We focused on placentae from pregnancies affected by preeclampsia that were delivered before 34 weeks of gestation to develop eoPred, a predictor of the DNAme signature associated with the placental phenotype of early-onset preeclampsia (EOPE). Results: Public data from 83 placental samples (HM450K), consisting of 42 EOPE and 41 normotensive preterm birth (nPTB) cases, was used to develop eoPred-a supervised model that relies on a highly discriminative 45 CpG DNAme signature of EOPE in the placenta. The performance of eoPred was assessed using cross-validation (AUC = 0.95) and tested in an independent validation cohort (n = 49, AUC = 0.725). A subset of fetal growth restriction (FGR) and late-PE cases showed a similar DNAme profile at the 45 predictive CpGs, consistent with the overlap in placental pathology between these conditions. The relationship between the EOPE probability generated by eoPred and various phenotypic variables was also assessed, revealing that it is associated with gestational age, and it is not driven by cell composition differences. Conclusion: eoPred relies on a 45-CpG DNAme signature to predict a homogeneous placental phenotype of EOPE in a discrete or continuous manner. Using this classifier should 1) aid in the study of placental insufficiency and improve the consistency of future placental DNAme studies of PE, 2) facilitate identifying the placental phenotype of EOPE in public data sets and 3) importantly, standardize the placental diagnosis of EOPE to allow better cross-cohort comparisons. Lastly, classification of cases with eoPred will be useful for investigating the relationship between placental pathology and genetic or environmental variables.

BCL6, a key oncogene, in the placenta, pre-eclampsia and endometriosis

BACKGROUND

The key oncogene B-cell lymphoma 6 (BCL6) drives malignant progression by promoting proliferation, overriding DNA damage checkpoints and blocking cell terminal differentiation. However, its functions in the placenta and the endometrium remain to be defined.

OBJECTIVE AND RATIONALE

Recent studies provide evidence that BCL6 may play various roles in the human placenta and the endometrium. Deregulated BCL6 might be related to the pathogenesis of pre-eclampsia (PE) as well as endometriosis. In this narrative review, we aimed to summarize the current knowledge regarding the pathophysiological role of BCL6 in these two reproductive organs, discuss related molecular mechanisms, and underline associated research perspectives.

SEARCH METHODS

We conducted a comprehensive literature search using PubMed for human, animal and cellular studies published until October 2021 in the following areas: BCL6 in the placenta, in PE and in endometriosis, in combination with its functions in proliferation, fusion, migration, invasion, differentiation, stem/progenitor cell maintenance and lineage commitment.

OUTCOMES

The data demonstrate that BCL6 is important in cell proliferation, survival, differentiation, migration and invasion of trophoblastic cells. BCL6 may have critical roles in stem/progenitor cell survival and differentiation in the placenta and the endometrium. BCL6 is aberrantly upregulated in pre-eclamptic placentas and endometriotic lesions through various mechanisms, including changes in gene transcription and mRNA translation as well as post-transcriptional/translational modifications. Importantly, increased endometrial BCL6 is considered to be a non-invasive diagnostic marker for endometriosis and a predictor for poor outcomes of IVF. These data highlight that BCL6 is crucial for placental development and endometrium homeostasis, and its upregulation is associated with the pathogenesis of PE, endometriosis and infertility.

WIDER IMPLICATIONS

The lesson learned from studies of the key oncogene BCL6 reinforces the notion that numerous signaling pathways and regulators are shared by tumors and reproductive organs. Their alteration may promote the progression of malignancies as well as the development of gestational and reproductive disorders.

Comprehensive transcriptome mining identified the gene expression signature and differentially regulated pathways of the late-onset preeclampsia

Preeclampsia (PE) is categorized as a pregnancy-related hypertensive disorder and is a serious concern in pregnancies. Several factors, including genetic factors (placenta gene expression, and imprinting), oxidative stress, the inaccurate immune response of the mother, and the environmental factors are responsible for PE development, but still, the exact mechanism of the pathogenesis has remained unknown. The main aim of the present study is to identify the gene expression signature in placenta tissue, to unveil disease etiology mechanisms. The GEO, PubMed, and ArrayExpress databases have selected to identify gene expression datasets on placenta samples of both preeclampsia and the normotensive controls. A comprehensive gene expression meta-analysis of fourteen publicly available microarray data of preeclampsia disease has performed to identify gene expression signature and responsible biological pathways and processes. Using two different meta-analysis pipeline (in-house and INMEX) we have identified a total of 1234 differentially expressed genes (DEGs) with in-house method, including 713 overexpressed and 356 under-expressed genes whereas 272 DEGs (131 over and 141 under-expressed) have identified with INMEX, across PEs and healthy controls. Comprehensive functional enrichment and pathway analysis was performed by EnrichR library, whic revealed "Asparagine N-linked glycosylation Homo sapiens", "Nef and signal transduction", "Hemostasis", and "immune system" among the most enriched terms. The present study sets out to explain a novel database of candidate genetic markers and biological pathways that play a critical role in PE development, which might aid in the identification of diagnostic, prognostic, and therapeutic informative molecules.

Ortho_Sim_Loc: Essential protein prediction using orthology and priority-based similarity approach

Proteins are the essential macro-molecules of living organism. But all proteins cannot be considered as essential in different relevant studies. Essentiality of a protein is thus computed by computation methods rather than biological experiments which in turn save both time and effort. Different computational approaches are already predicted to select essential proteins successfully with different biological significances by researchers. Most of the experimental approaches return higher false negative outcomes with respect to others. In order to retain the prediction accuracy level, a novel methodology "Ortho_Sim_Loc"has been proposed which is a combined approach of Orthology, Similarity (using clustering and priority based GO-Annotation) and Subcellular localization. Ortho_Sim_Loc can predict enriched functional set essential proteins. The predicted results are validated with other existing methods like different centrality measures, LIDC. The validation results exhibits better performance of Ortho_Sim_Loc in compare to other existing computational approaches.

ANXA7 regulates trophoblast proliferation and apoptosis in preeclampsia

PROBLEM

Preeclampsia (PE) is a unique gestational disorder leading to maternal and neonatal morbidity and mortality. AnnexinA7 (ANXA7) is a calcium-dependent phospholipid-binding protein that promotes membrane fusion during exocytosis. However, the function of ANXA7 in placental trophoblast is poorly understood. The present study aimed to investigate a possible association between ANXA7 and human trophoblast apoptosis.

METHODS

We collected human placental tissues from patients with PE and normal pregnant women to elucidate the expression level of ANXA7. The ANXA7-knockdown and ANXA7-overexpressing HTR8/SVneo cells were utilized for studying the function of ANXA7 in trophoblast. The proliferation and apoptosis levels of trophoblast were examined with Western blot assay, flow cytometry, Cell Counting Kit-8 assay, and immunohistochemistry.

RESULTS

ANXA7 expression was significantly lower in placentas from patients with PE patients compared with that in from normal pregnant controls. Knockdown of ANXA7 induced cell apoptosis and inhibited cell proliferation in HTR-8 via by downregulating BCL2 protein levels. Overexpression of ANXA7 reduced apoptosis and promoted HTR8 proliferation. Further analyses showed that ANXA7 knockdown inhibited the activation of the JAK1/STAT3 pathway in HTR-8 cells.

CONCLUSION

Our findings revealed a new regulatory pathway of ANXA7/JAK1/STAT3 in trophoblast apoptosis in preeclampsia, suggesting that ANXA7 is a potential therapeutic target for preeclampsia.

Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis

Consensus strategy was proved to be highly efficient in the recognition of gene-disease association. Therefore, the main objective of this study was to apply theoretical approaches to explore genes and communities directly involved in breast cancer (BC) pathogenesis. We evaluated the consensus between 8 prioritization strategies for the early recognition of pathogenic genes. A communality analysis in the protein-protein interaction (PPi) network of previously selected genes was enriched with gene ontology, metabolic pathways, as well as oncogenomics validation with the OncoPPi and DRIVE projects. The consensus genes were rationally filtered to 1842 genes. The communality analysis showed an enrichment of 14 communities specially connected with ERBB, PI3K-AKT, mTOR, FOXO, p53, HIF-1, VEGF, MAPK and prolactin signaling pathways. Genes with highest ranking were TP53, ESR1, BRCA2, BRCA1 and ERBB2. Genes with highest connectivity degree were TP53, AKT1, SRC, CREBBP and EP300. The connectivity degree allowed to establish a significant correlation between the OncoPPi network and our BC integrated network conformed by 51 genes and 62 PPi. In addition, CCND1, RAD51, CDC42, YAP1 and RPA1 were functional genes with significant sensitivity score in BC cell lines. In conclusion, the consensus strategy identifies both well-known pathogenic genes and prioritized genes that need to be further explored.

Candidate Gene, Genome-Wide Association and Bioinformatic Studies in Pre-eclampsia: a Review

PURPOSE OF REVIEW

Regardless of the familial linkage reported in pre-eclampsia development, understanding the polymorphic genes associated with pre-eclampsia remains limited. Hence, this review aims to outline the main genetic factors that have been investigated in respect to pre-eclampsia development.

RECENT FINDINGS

It is apparent that different genes show significance in varying populations. Notably, it is reported that apolipoprotein-1 gene polymorphisms are associated with pre-eclampsia development in an African-American population, which may be worthwhile to investigate in a Black South African cohort. Despite the research attention that is focused on this surreptitious syndrome, a definitive cause eludes scientists and physicians, alike. Genetic studies can fulfil a dual purpose of suggesting novel hypotheses through genome-wide screening and testing these hypotheses via candidate gene studies. However, publications to date have only presented inconsistent and conflicting results regarding candidate gene analysis.

Identification of Disease Critical Genes Using Collective Meta-heuristic Approaches: An Application to Preeclampsia

Identifying a small subset of disease critical genes out of a large size of microarray gene expression data is a challenge in computational life sciences. This paper has applied four meta-heuristic algorithms, namely, honey bee mating optimization (HBMO), harmony search (HS), differential evolution (DE) and genetic algorithm (basic version GA) to find disease critical genes of preeclampsia which affects women during gestation. Two hybrid algorithms, namely, HBMO-kNN and HS-kNN have been newly proposed here where kNN (k nearest neighbor classifier) is used for sample classification. Performances of these new approaches have been compared with other two hybrid algorithms, namely, DE-kNN and SGA-kNN. Three datasets of different sizes have been used. In a dataset, the set of genes found common in the output of each algorithm is considered here as disease critical genes. In different datasets, the percentage of classification or classification accuracy of meta-heuristic algorithms varied between 92.46 and 100%. HBMO-kNN has the best performance (99.64-100%) in almost all data sets. DE-kNN secures the second position (99.42-100%). Disease critical genes obtained here match with clinically revealed preeclampsia genes to a large extent.

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis

BACKGROUND

Preeclampsia is a multifactorial disease with unknown pathogenesis. Even when recent studies explored this disease using several bioinformatics tools, the main objective was not directed to pathogenesis. Additionally, consensus prioritization was proved to be highly efficient in the recognition of genes-disease association. However, not information is available about the consensus ability to early recognize genes directly involved in pathogenesis. Therefore our aim in this study is to apply several theoretical approaches to explore preeclampsia; specifically those genes directly involved in the pathogenesis.

METHODS

We firstly evaluated the consensus between 12 prioritization strategies to early recognize pathogenic genes related to preeclampsia. A communality analysis in the protein-protein interaction network of previously selected genes was done including further enrichment analysis. The enrichment analysis includes metabolic pathways as well as gene ontology. Microarray data was also collected and used in order to confirm our results or as a strategy to weight the previously enriched pathways.

RESULTS

The consensus prioritized gene list was rationally filtered to 476 genes using several criteria. The communality analysis showed an enrichment of communities connected with VEGF-signaling pathway. This pathway is also enriched considering the microarray data. Our result point to VEGF, FLT1 and KDR as relevant pathogenic genes, as well as those connected with NO metabolism.

CONCLUSION

Our results revealed that consensus strategy improve the detection and initial enrichment of pathogenic genes, at least in preeclampsia condition. Moreover the combination of the first percent of the prioritized genes with protein-protein interaction network followed by communality analysis reduces the gene space. This approach actually identifies well known genes related with pathogenesis. However, genes like HSP90, PAK2, CD247 and others included in the first 1% of the prioritized list need to be further explored in preeclampsia pathogenesis through experimental approaches.

Placental transcriptome co-expression analysis reveals conserved regulatory programs across gestation

BACKGROUND

Mammalian development in utero is absolutely dependent on proper placental development, which is ultimately regulated by the placental genome. The regulation of the placental genome can be directly studied by exploring the underlying organisation of the placental transcriptome through a systematic analysis of gene-wise co-expression relationships.

RESULTS

In this study, we performed a comprehensive analysis of human placental co-expression using RNA sequencing and intergrated multiple transcriptome datasets spanning human gestation. We identified modules of co-expressed genes that are preserved across human gestation, and also identifed modules conserved in the mouse indicating conserved molecular networks involved in placental development and gene expression patterns more specific to late gestation. Analysis of co-expressed gene flanking sequences indicated that conserved co-expression modules in the placenta are regulated by a core set of transcription factors, including ZNF423 and EBF1. Additionally, we identified a gene co-expression module enriched for genes implicated in the pregnancy pathology preeclampsia. By using an independnet transcriptome dataset, we show that these co-expressed genes are differentially expressed in preeclampsia.

CONCLUSIONS

This study represents a comprehensive characterisation of placental co-expression and provides insight into potential transcriptional regulators that govern conserved molecular programs fundamental to placental development.

Identifying miRNA regulatory mechanisms in preeclampsia by systems biology approaches

BACKGROUND

Preeclampsia (PE) is the major cause of maternal and fetal morbidity and mortality, affecting 3-8% of all pregnancies around the globe. miRNAs are small, noncoding RNA molecules, which negatively regulate gene expression. Abnormally expressed miRNAs contribute to pregnancy complications such as PE. The aim of our study was to find possible regulatory mechanisms by system biology approaches, which are connected to the pathogenesis of PE.

METHODS

We integrated publicly available miRNA and gene expression profiles and created a network from the significant miRNA-mRNA pairs with the help of MAGIA and Cytoscape softwares. Two subnetworks were expanded by adding protein-protein interactions. Differentially expressed miRNAs were identified for the evaluation of their regulatory effect. We analyzed the miRNAs and their targets using different bioinformatics tools and through literature research.

RESULTS

Altogether, 52,603 miRNA-mRNA interactions were generated by the MAGIA web tool. The top 250 interactions were visualized and pairs with q < 0.0001 were analyzed, which included 85 nodes and 80 edges signalizing the connections between 52 regulated genes and 33 miRNAs. A total of 11 of the regulated genes are PE related and 9 of them were targeted by multiple miRNAs. A total of 8 miRNAs were associated with PE before, and 13 miRNAs regulated more than 1 mRNA. Hsa-mir-210 was the highest degree node in the network and its role in PE is well established.

CONCLUSIONS

We identified several miRNA-mRNA regulatory mechanisms which may contribute to the pathogenesis of PE. Further investigations are needed to validate these miRNA-mRNA interactions and to enlighten the possibilities of developing potential therapeutic targets.

A curated transcriptome dataset collection to investigate the development and differentiation of the human placenta and its associated pathologies

Compendia of large-scale datasets made available in public repositories provide a precious opportunity to discover new biomedical phenomena and to fill gaps in our current knowledge. In order to foster novel insights it is necessary to ensure that these data are made readily accessible to research investigators in an interpretable format. Here we make a curated, public, collection of transcriptome datasets relevant to human placenta biology available for further analysis and interpretation via an interactive data browsing interface. We identified and retrieved a total of 24 datasets encompassing 759 transcriptome profiles associated with the development of the human placenta and associated pathologies from the NCBI Gene Expression Omnibus (GEO) and present them in a custom web-based application designed for interactive query and visualization of integrated large-scale datasets ( http://placentalendocrinology.gxbsidra.org/dm3/landing.gsp). We also performed quality control checks using relevant biological markers. Multiple sample groupings and rank lists were subsequently created to facilitate data query and interpretation. Via this interface, users can create web-links to customized graphical views which may be inserted into manuscripts for further dissemination, or e-mailed to collaborators for discussion. The tool also enables users to browse a single gene across different projects, providing a mechanism for  developing new perspectives on the role of a molecule of interest across multiple biological states. The dataset collection we created here is available at: http://placentalendocrinology.gxbsidra.org/dm3.

Efficient and biologically relevant consensus strategy for Parkinson's disease gene prioritization

BACKGROUND

The systemic information enclosed in microarray data encodes relevant clues to overcome the poorly understood combination of genetic and environmental factors in Parkinson's disease (PD), which represents the major obstacle to understand its pathogenesis and to develop disease-modifying therapeutics. While several gene prioritization approaches have been proposed, none dominate over the rest. Instead, hybrid approaches seem to outperform individual approaches.

METHODS

A consensus strategy is proposed for PD related gene prioritization from mRNA microarray data based on the combination of three independent prioritization approaches: Limma, machine learning, and weighted gene co-expression networks.

RESULTS

The consensus strategy outperformed the individual approaches in terms of statistical significance, overall enrichment and early recognition ability. In addition to a significant biological relevance, the set of 50 genes prioritized exhibited an excellent early recognition ability (6 of the top 10 genes are directly associated with PD). 40 % of the prioritized genes were previously associated with PD including well-known PD related genes such as SLC18A2, TH or DRD2. Eight genes (CCNH, DLK1, PCDH8, SLIT1, DLD, PBX1, INSM1, and BMI1) were found to be significantly associated to biological process affected in PD, representing potentially novel PD biomarkers or therapeutic targets. Additionally, several metrics of standard use in chemoinformatics are proposed to evaluate the early recognition ability of gene prioritization tools.

CONCLUSIONS

The proposed consensus strategy represents an efficient and biologically relevant approach for gene prioritization tasks providing a valuable decision-making tool for the study of PD pathogenesis and the development of disease-modifying PD therapeutics.

The Gene Expression Omnibus Database

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

Identification of hub genes of pneumocyte senescence induced by thoracic irradiation using weighted gene co‑expression network analysis

Irradiation commonly causes pneumocyte senescence, which may lead to severe fatal lung injury characterized by pulmonary dysfunction and respiratory failure. However, the molecular mechanism underlying the induction of pneumocyte senescence by irradiation remains to be elucidated. In the present study, weighted gene co-expression network analysis (WGCNA) was used to screen for differentially expressed genes, and to identify the hub genes and gene modules, which may be critical for senescence. A total of 2,916 differentially expressed genes were identified between the senescence and non-senescence groups following thoracic irradiation. In total, 10 gene modules associated with cell senescence were detected, and six hub genes were identified, including B-cell scaffold protein with ankyrin repeats 1, translocase of outer mitochondrial membrane 70 homolog A, actin filament-associated protein 1, Cd84, Nuf2 and nuclear factor erythroid 2. These genes were markedly associated with cell proliferation, cell division and cell cycle arrest. The results of the present study demonstrated that WGCNA of microarray data may provide further insight into the molecular mechanism underlying pneumocyte senescence.

Genome-Wide Mapping of 5mC and 5hmC Identified Differentially Modified Genomic Regions in Late-Onset Severe Preeclampsia: A Pilot Study

Preeclampsia (PE) is a leading cause of perinatal morbidity and mortality. However, as a common form of PE, the etiology of late-onset PE is elusive. We analyzed 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) levels in the placentas of late-onset severe PE patients (n = 4) and normal controls (n = 4) using a (hydroxy)methylated DNA immunoprecipitation approach combined with deep sequencing ([h]MeDIP-seq), and the results were verified by (h)MeDIP-qPCR. The most significant differentially methylated regions (DMRs) were verified by MassARRAY EppiTYPER in an enlarged sample size (n = 20). Bioinformatics analysis identified 714 peaks of 5mC that were associated with 403 genes and 119 peaks of 5hmC that were associated with 61 genes, thus showing significant differences between the PE patients and the controls (>2-fold, p<0.05). Further, only one gene, PTPRN2, had both 5mC and 5hmC changes in patients. The ErbB signaling pathway was enriched in those 403 genes that had significantly different5mC level between the groups. This genome-wide mapping of 5mC and 5hmC in late-onset severe PE and normal controls demonstrates that both 5mC and 5hmC play epigenetic roles in the regulation of the disease, but work independently. We reveal the genome-wide mapping of DNA methylation and DNA hydroxymethylation in late-onset PE placentas for the first time, and the identified ErbB signaling pathway and the gene PTPRN2 may be relevant to the epigenetic pathogenesis of late-onset PE.