Identification of novel tissue-specific genes by analysis of microarray databases: a human and mouse model

Atypical Modes of CTCF Binding Facilitate Tissue-Specific and Neuronal Activity-Dependent Gene Expression States

Multivalent binding of CTCF to variable DNA sequences is thought to underlie its ability to mediate diverse cellular functions. CTCF typically binds a 20 base-pair consensus DNA sequence, but the full diversity of CTCF binding sites (CBS) within the genome has not been interrogated. We assessed CTCF occupancy in cultured cortical neurons and observed surprisingly that ~ 22% of CBS lack the consensus CTCF motif. We report here that sequence diversity at most of these atypical CBS involves degeneracy at specific nucleotide positions within the consensus CTCF motif, which likely affect the binding of CTCF zinc fingers 6 and 7. This mode of atypical CTCF binding defines most CBS at gene promoters, as well as CBS that are dynamically altered during neural differentiation and following neuronal stimulation, revealing how atypical CTCF binding could influence gene activity. Dynamic CBS are distributed both within and outside loop anchors and TAD boundaries, suggesting both looping-dependent and independent roles for CTCF. Finally, we describe a second mode of atypical CTCF binding to DNA sequences that are completely unrelated to the consensus CTCF motif, which are enriched within the bodies of tissue-specific genes. These tissue-specific atypical CBS are also enriched in H3K27ac, which marks cis-regulatory elements within chromatin, including enhancers. Overall, these results indicate how atypical CBS could dynamically regulate gene activity patterns during differentiation, development, and in response to environmental cues.

Capture of circulating metastatic cancer cell clusters from a lung cancer patient can reveal a unique genomic profile and potential anti-metastatic molecular targets: A proof of concept study

Metastasis remains the leading cause of cancer deaths worldwide and lung cancer, known for its highly metastatic progression, remains among the most lethal of malignancies. The heterogeneous genomic profile of lung cancer metastases is often unknown. Since different metastatic events can selectively spread to multiple organs, strongly suggests more studies are needed to understand and target these different pathways. Unfortunately, access to the primary driver of metastases, the metastatic cancer cell clusters (MCCCs), remains difficult and limited. These metastatic clusters have been shown to be 100-fold more tumorigenic than individual cancer cells. Capturing and characterizing MCCCs is a key limiting factor in efforts to help treat and ultimately prevent cancer metastasis. Elucidating differentially regulated biological pathways in MCCCs will help uncover new therapeutic drug targets to help combat cancer metastases. We demonstrate a novel, proof of principle technology, to capture MCCCs directly from patients' whole blood. Our platform can be readily tuned for different solid tumor types by combining a biomimicry-based margination effect coupled with immunoaffinity to isolate MCCCs. Adopting a selective capture approach based on overexpressed CD44 in MCCCs provides a methodology that preferentially isolates them from whole blood. Furthermore, we demonstrate a high capture efficiency of more than 90% when spiking MCCC-like model cell clusters into whole blood. Characterization of the captured MCCCs from lung cancer patients by immunofluorescence staining and genomic analyses, suggests highly differential morphologies and genomic profiles., This study lays the foundation to identify potential drug targets thus unlocking a new area of anti-metastatic therapeutics.

Identification of metabolic biomarkers associated with nonalcoholic fatty liver disease

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for the diagnosis and treatment of NAFLD patients.

METHODS

GSE48452, GSE63067, and GSE89632 datasets including nonalcoholic steatohepatitis (NASH) and healthy controls (HC) analyzed in this study were retrieved from the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) between NASH and HC samples were obtained. Next, metabolism-related DEGs (MR-DEGs) were identified by overlapping DEGs and metabolism-related genes (MRG). Further, a protein-protein interaction (PPI) network was developed to show the interaction among MR-DEGs. Subsequently, the "Least absolute shrinkage and selection operator regression" and "Random Forest" algorithms were used to screen metabolism-related genes (MRGs) in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses (GSEA) were performed on these metabolism-related genes. Finally, the expression of metabolism-related gene was determined at the transcription level.

RESULTS

First, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1, were identified using machine learning algorithms. Moreover, a regulatory network consisting of four genes, 25 microRNAs (miRNAs), and 41 transcription factors (TFs) was constructed. Finally, a significant increase in FMO1 and LPL expression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the HC group.

CONCLUSION

Metabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD.

Chordin-like 1, a Novel Adipokine, Markedly Promotes Adipogenesis and Lipid Accumulation

White adipose tissue serves as a metabolically dynamic organ that can synthesize and secrete biologically active compounds such as adipokines as well as a caloric reservoir for maintaining energy homeostasis. Adipokines are involved in diverse biological and physiological processes and there have been extensive attempts to characterize the effects of over two dozen adipokines. However, many of these adipokines are produced by not only adipose tissue, but also other tissues. Therefore, investigations into the effects of adipokines on physiological functions have been challenged. In this regard, we aimed to identify a new secreted protein that is encoded by genes specifically expressed in white adipose tissue through analysis of multi-tissue transcriptome and protein expression. As a result, we report a novel adipokine that is encoded by the adipose-specific gene, chordin-like 1 (Chrdl1), which is specifically expressed in white adipose tissue in mice; this expression pattern was conserved in the human orthologous CHRDL1 gene. The expression of Chrdl1 was enriched in fat cells and developmentally regulated in vitro and in vivo, and moreover, its retrovirus-mediated overexpression and recombinant protein treatment led to markedly increased adipogenesis. Further pathway enrichment analysis revealed enriched pathways related to lipogenesis and adipogenic signaling. Our findings support a pro-adipogenic role of CHRDL1 as a new adipokine and pave the way toward animal studies and future research on its clinical implications and development of anti-obesity therapy.

Robust and rigorous identification of tissue-specific genes by statistically extending tau score

OBJECTIVES

In this study, we aimed to identify tissue-specific genes for various human tissues/organs more robustly and rigorously by extending the tau score algorithm.

INTRODUCTION

Tissue-specific genes are a class of genes whose functions and expressions are preferred in one or several tissues restrictedly. Identification of tissue-specific genes is essential for discovering multi-cellular biological processes such as tissue-specific molecular regulations, tissue development, physiology, and the pathogenesis of tissue-associated diseases.

MATERIALS AND METHODS

Gene expression data derived from five large RNA sequencing (RNA-seq) projects, spanning 96 different human tissues, were retrieved from ArrayExpress and ExpressionAtlas. The first step is categorizing genes using significant filters and tau score as a specificity index. After calculating tau for each gene in all datasets separately, statistical distance from the maximum expression level was estimated using a new meaningful procedure. Specific expression of a gene in one or several tissues was calculated after the integration of tau and statistical distance estimation, which is called as extended tau approach. Obtained tissue-specific genes for 96 different human tissues were functionally annotated, and some comparisons were carried out to show the effectiveness of the extended tau method.

RESULTS AND DISCUSSION

Categorization of genes based on expression level and identification of tissue-specific genes for a large number of tissues/organs were executed. Genes were successfully assigned to multiple tissues by generating the extended tau approach as opposed to the original tau score, which can assign tissue specificity to single tissue only.

Comparative single-cell analysis of the adult heart and coronary vasculature

The structure and function of the circulatory system, including the heart, have undergone substantial changes with the vertebrate evolution. Although the basic function of the heart is to pump blood through the body, its size, shape, speed, regeneration capacity, etc. vary considerably across species. Here, we address the differences among vertebrate hearts using a single-cell transcriptomics approach. Published datasets of macaque (Macaca fascicularis), mouse, and zebrafish hearts were integrated and compared to the human heart as a reference. While the three mammalian hearts integrated well, the zebrafish heart showed very little overlap with the other species. Our analysis revealed a mouse-specific cell subpopulation of ventricular cardiomyocytes (CM), represented by strikingly different expression patterns of specific genes related to high-energy metabolism. Interestingly, the observed differences between mouse and human CM coincided with actual biological differences between the two species. Smooth muscle and endothelial cells (EC) exhibited species-specific differences in clustering and gene expression, respectively, which we attribute to the tissues selected for sequencing, given different focuses of the original studies. Finally, we compared human and zebrafish heart-specific fibroblasts (FB) and identified a distinctively high expression of genes associated with heart regeneration following injury in zebrafish. Together, our results show that integration of numerous datasets of different species and different sequencing technologies is feasible and that this approach can identify species-specific differences and similarities in the heart.

Reproducible and sensitive micro-tissue RNA sequencing from formalin-fixed paraffin-embedded tissues for spatial gene expression analysis

Spatial transcriptome analysis of formalin-fixed paraffin-embedded (FFPE) tissues using RNA-sequencing (RNA-seq) provides interactive information on morphology and gene expression, which is useful for clinical applications. However, despite the advantages of long-term storage at room temperature, FFPE tissues may be severely damaged by methylene crosslinking and provide less gene information than fresh-frozen tissues. In this study, we proposed a sensitive FFPE micro-tissue RNA-seq method that combines the punching of tissue sections (diameter: 100 μm) and the direct construction of RNA-seq libraries. We evaluated a method using mouse liver tissues at two years after fixation and embedding and detected approximately 7000 genes in micro-punched tissue-spots (thickness: 10 μm), similar to that detected with purified total RNA (2.5 ng) equivalent to the several dozen cells in the spot. We applied this method to clinical FFPE specimens of lung cancer that had been fixed and embedded 6 years prior, and found that it was possible to determine characteristic gene expression in the microenvironment containing tumor and non-tumor cells of different morphologies. This result indicates that spatial gene expression analysis of the tumor microenvironment is feasible using FFPE tissue sections stored for extensive periods in medical facilities.

Retinol Binding Protein 7 Promotes Adipogenesis in vitro and Regulates Expression of Genes Involved in Retinol Metabolism

Retinol is an essential nutrient in animals. Its metabolites, specifically retinoic acid (RA), are crucial for cell differentiation, including adipogenesis. Retinol binding protein 7 (Rbp7) is under the control of PPARγ, the master regulator of adipogenesis. However, the role of RBP7 in adipogenesis is unclear. Our study showed that Rbp7 was abundantly expressed in white and brown mouse adipose tissues and had a higher expression in adipocytes than in stromal vascular fraction. Rbp7 overexpression promoted 3T3-L1 preadipocyte differentiation with increased triglyceride accumulation and up-regulation of Pparγ, Fabp4, C/ebpα, and AdipoQ. Rbp7 deficient adipocytes had opposite effects of the overexpression, which were rescued by RA supplementation. Indirect assessment of relative nuclear RA levels using RAR response element (RARE)-Luc reporter assay demonstrated that Rbp7 overexpression significantly increased RARE-Luc reporter activity. Rbp7 overexpression significantly increased expression of Raldh1, responsible for RA production, and up-regulation of Lrat and Cyp26a1, involved in retinol storage and RA catabolism, respectively, in 3T3-L1 adipocytes. Rbp7 deficient adipocytes had opposite effects of the overexpression of those genes involved in retinol metabolism. These data suggest that RBP7 increases transcriptional activity of RARE that may induce negative feedback responses via regulation of the gene expression for retinol homeostasis. Our data indicate critical RBP7 functions in adipocytes: regulation of transcriptional activity of RARE and adipocytes differentiation, potentially providing a new target for obesity therapy.

Screening and Identification of Muscle-Specific Candidate Genes via Mouse Microarray Data Analysis

Muscle tissue is involved with every stage of life activities and has roles in biological processes. For example, the blood circulation system needs the heart muscle to transport blood to all parts, and the movement cannot be separated from the participation of skeletal muscle. However, the process of muscle development and the regulatory mechanisms of muscle development are not clear at present. In this study, we used bioinformatics techniques to identify differentially expressed genes specifically expressed in multiple muscle tissues of mice as potential candidate genes for studying the regulatory mechanisms of muscle development. Mouse tissue microarray data from 18 tissue samples was selected from the GEO database for analysis. Muscle tissue as the treatment group, and the other 17 tissues as the control group. Genes expressed in the muscle tissue were different to those in the other 17 tissues and identified 272 differential genes with highly specific expression in muscle tissue, including 260 up-regulated genes and 12 down regulated genes. is the genes were associated with the myofibril, contractile fibers, and sarcomere, cytoskeletal protein binding, and actin binding. KEGG pathway analysis showed that the differentially expressed genes in muscle tissue were mainly concentrated in pathways for AMPK signaling, cGMP PKG signaling calcium signaling, glycolysis, and, arginine and proline metabolism. A PPI protein interaction network was constructed for the selected differential genes, and the MCODE module used for modular analysis. Five modules with Score > 3.0 are selected. Then the Cytoscape software was used to analyze the tissue specificity of differential genes, and the genes with high degree scores collected, and some common genes selected for quantitative PCR verification. The conclusion is that we have screened the differentially expressed gene set specific to mouse muscle to provide potential candidate genes for the study of the important mechanisms of muscle development.

Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

BACKGROUND

Liver hepatocellular carcinoma (HCC) is the third most common cause of death by cancer and has a high mortality world-widely. Approximately 75-85% of primary liver cancers are caused by HCC. Uncovering novel genes with prognostic significance would shed light on improving the HCC patient's outcome.

OBJECTIVE

In this research, we aim to identify novel prognostic biomarkers in hepatocellular carcinoma.

METHODS

Integrated proteomics and bioinformatics analysis were performed to investigate the expression landscape of prognostic biomarkers in 24 paired HCC patients.

RESULTS

As a result, eight key genes related to prognosis, including ACADS, HSD17B13, PON3, AMDHD1, CYP2C8, CYP4A11, SLC27A5, CYP2E1, were identified by comparing the weighted gene co-expression network analysis (WGCNA), proteomic differentially expressed genes (DEGs), proteomic turquoise module, The Cancer Genome Atlas (TCGA) cohort DEGs of HCC. Furthermore, we trained and validated eight pivotal genes integrating these independent clinical variables into a nomogram with superior accuracy in predicting progression events, and their lower expression was associated with a higher stage/risk score. The Gene Set Enrichment Analysis (GSEA) further revealed that these key genes showed enrichment in the HCC regulatory pathway.

CONCLUSION

All in all, we found that these eight genes might be the novel potential prognostic biomarkers for HCC and also provide promising insights into the pathogenesis of HCC at the molecular level.

The Utility of Resolving Asthma Molecular Signatures Using Tissue-Specific Transcriptome Data

An integrative analysis focused on multi-tissue transcriptomics has not been done for asthma. Tissue-specific DEGs remain undetected in many multi-tissue analyses, which influences identification of disease-relevant pathways and potential drug candidates. Transcriptome data from 609 cases and 196 controls, generated using airway epithelium, bronchial, nasal, airway macrophages, distal lung fibroblasts, proximal lung fibroblasts, CD4+ lymphocytes, CD8+ lymphocytes from whole blood and induced sputum samples, were retrieved from Gene Expression Omnibus (GEO). Differentially regulated asthma-relevant genes identified from each sample type were used to identify (a) tissue-specific and tissue-shared asthma pathways, (b) their connection to GWAS-identified disease genes to identify candidate tissue for functional studies, (c) to select surrogate sample for invasive tissues, and finally (d) to identify potential drug candidates via connectivity map analysis. We found that inter-tissue similarity in gene expression was more pronounced at pathway/functional level than at gene level with highest similarity between bronchial epithelial cells and lung fibroblasts, and lowest between airway epithelium and whole blood samples. Although public-domain gene expression data are limited by inadequately annotated per-sample demographic and clinical information which limited the analysis, our tissue-resolved analysis clearly demonstrated relative importance of unique and shared asthma pathways, At the pathway level, IL-1b signaling and ERK signaling were significant in many tissue types, while Insulin-like growth factor and TGF-beta signaling were relevant in only airway epithelial tissue. IL-12 (in macrophages) and Immunoglobulin signaling (in lymphocytes) and chemokines (in nasal epithelium) were the highest expressed pathways. Overall, the IL-1 signaling genes (inflammatory) were relevant in the airway compartment, while pro-Th2 genes including IL-13 and STAT6 were more relevant in fibroblasts, lymphocytes, macrophages and bronchial biopsies. These genes were also associated with asthma in the GWAS catalog. Support Vector Machine showed that DEGs based on macrophages and epithelial cells have the highest and lowest discriminatory accuracy, respectively. Drug (entinostat, BMS-345541) and genetic perturbagens (KLF6, BCL10, INFB1 and BAMBI) negatively connected to disease at multi-tissue level could potentially repurposed for treating asthma. Collectively, our study indicates that the DEGs, perturbagens and disease are connected differentially depending on tissue/cell types. While most of the existing literature describes asthma transcriptome data from individual sample types, the present work demonstrates the utility of multi-tissue transcriptome data. Future studies should focus on collecting transcriptomic data from multiple tissues, age and race groups, genetic background, disease subtypes and on the availability of better-annotated data in the public domain.

Genome-wide association study of genetic variants related to anthracycline-induced cardiotoxicity in early breast cancer

We performed a genome‐wide association study to investigate the association between single nucleotide polymorphisms and anthracycline‐induced cardiotoxicity (ACT) in patients diagnosed with early breast cancer. From January 2000 to December 2015, 8490 patients underwent breast surgery at the National Cancer Center in Korea. Patients who received doxorubicin (cumulative dose 240 mg/m²‐300 mg/m²) with or without trastuzumab as a neoadjuvant/adjuvant therapy were included in our cohort. Sixty‐seven patients in our cohort were diagnosed with ACT. Clinical data, including age, body weight, height, cancer stage, trastuzumab treatment, comorbidities, and concomitant medications, were collected retrospectively. Patients were classified as having either persistent or transient ACT based on their clinical course. In total, 346 946 single nucleotide polymorphisms in 42 cases and 215 controls were tested in this study. Body mass index (BMI) ≥25 kg/m² [odds ratio (OR) = 2.45, 95% confidence interval (CI), 1.23‐4.88, P = .011] and trastuzumab use (OR = 2.40, 95% CI, 1.11‐5.17, P = .026) were identified as significant risk factors. We found 7 genetic variants for ACT including rs17530621 (SHISA3, P = 3.10E−06), rs11894115 (MPP4, P = 4.71E−06), rs58328254 (RPL7, P = 6.09E−06), and rs117299725 (PRUNE2, P = 8.53E−06), although none of these variants reached the Bonferroni‐corrected significance level when adjusted for BMI and trastuzumab use ( = α1.44E−07 based on 0.05/346 946). rs117299725 was a common variant when only the persistent ACT group was analyzed separately. It is meaningful that our study analyzed comprehensively the influence of genetic variation on ACT, along with some clinical factors in Asian breast cancer patients who received anthracycline with or without trastuzumab. Further research will be needed on candidate genetic variants found in this study.

Fetuin-a expression profile in mouse and human adipose tissue

Fetuin-A (Fet-A) was one of the first hepatokines to be reportedly linked to metabolic diseases. Fet-A was also suggested to be an adipokine, but its expression in the adipose tissue remains debatable. Here we compared the expression of Fet-A between human and mice adipose tissue biopsies as well as among human subcutaneous tissue and visceral adipose tissue primary cells, and mouse 3 T3-L1 cells at various stages of differentiation. Fet-A was expressed in mice biopsies and cells but not in human biopsies and cells, except in visceral adipose tissue primary cells following differentiation. Although the marginal expression of Fet-A in human visceral adipose tissue, a major contribution of Fet-A expression in human adipose tissue to systemic Fet-A levels is discounted, but it could indicate specific local Fet-A action in the visceral adipose tissue.

Comparative identification, nutritional, and physiological regulation of chicken liver-enriched genes

The liver performs a number of vital functions in the chicken. In order to identify unique gene expression patterns and link them to potential functions in the chicken liver, genes enriched in the liver of chickens needed to be investigated in a comparative manner. In this study, 41 liver-enriched genes were identified through chicken microarray, and many of them were validated through comparative analysis of mice and humans. Thirteen of them were unique in chickens, and their liver enhancement was confirmed by reverse transcription PCR. Furthermore, the expression of those 13 chicken liver-enriched genes was investigated, in response to nutritional and physiological challenges. Real-time PCR revealed that expression of PIT54 (P < 0.01), phosphoribosyl pyrophosphate synthetase 2 (PRPS2) (P < 0.05), sulfotransferase (SULT) (P < 0.05), and cytochrome P450 family 2 subfamily C, polypeptide 18 (CYP2C18) (P < 0.05) were significantly decreased in the liver during fasting compared to ad libitum control. During the post-laying stage, expression of GAL8 was significantly increased (P < 0.01), but CYP2C18 expression was significantly reduced (P < 0.05). Liver-enriched genes that were identified in this study and their expression patterns under fasting and the post-laying stage will serve as future targets to gain a better understanding of liver physiology, function and development in poultry.

Adipose-Specific Expression, Developmental and Nutritional Regulation of the Gene-Encoding Retinol-Binding Protein 7 in Pigs

Modulation of expression of adipose tissue-specific transcripts has been known to regulate adipogenesis and lipid metabolism. Recently, adipose-specific expression patterns and developmental regulation of the gene-encoding retinol-binding protein 7 (RBP7) was identified. However, its expression in adipose tissue of the porcine species has yet to be explored. In this study, adipose tissue-specific expression of porcine RBP7 was identified and conservation of the fatty acid-binding domains and evolutionary relationship of the RBP7 gene were verified comparatively across mammalian species. Our in vitro and in vivo analysis of gene expression revealed that RBP7 expression was significantly high in fat cell fraction compared to stromal vascular cells (p < 0.05) and increased during development (p < 0.05). The level of RBP7 expression was upregulated during a 24-h short-term fasting intervention and restored 6 h after refeeding (p < 0.05). Taken together, these studies provide insights into the role of RBP7 in adipose tissue of pigs during development and nutritional intervention and pave the way for future studies on the regulation of retinol homeostasis in porcine adipose tissue.

Insights from deconvolution of cell subtype proportions enhance the interpretation of functional genomic data

Cell subtype proportion variability between samples contributes significantly to the variation of functional genomic properties such as gene expression or DNA methylation. Although the impact of the variation of cell subtype composition on measured genomic quantities is recognized, and some innovative tools have been developed for the analysis of heterogeneous samples, most functional genomics studies using samples with mixed cell types still ignore the influence of cell subtype proportion variation, or just deal with it as a nuisance variable to be eliminated. Here we demonstrate how harvesting information about cell subtype proportions from functional genomics data can provide insights into cellular changes associated with phenotypes. We focused on two types of mixed cell populations, human blood and mouse kidney. Cell type prediction is well developed in the former, but not currently in the latter. Estimating the cellular repertoire is easier when a reference dataset from purified samples of all cell types in the tissue is available, as is the case for blood. However, reference datasets are not available for most other tissues, such as the kidney. In this study, we showed that the proportion of alterations attributable to changes in the cellular composition varies strikingly in the two disorders (asthma and systemic lupus erythematosus), suggesting that the contribution of cell subtype proportion changes to functional genomic properties can be disease-specific. We also showed that a reference dataset from a single-cell RNA-seq study successfully estimated the cell subtype proportions in mouse kidney and allowed us to distinguish altered cell subtype differences between two different knock-out mouse models, both of which had reported a reduced number of glomeruli compared to their wild-type counterparts. These findings demonstrate that testing for changes in cell subtype proportions between conditions can yield important insights in functional genomics studies.

Transcriptome analysis to identify long non coding RNA (lncRNA) and characterize their functional role in back fat tissue of pig

Long non coding RNAs (lncRNA) have been previously found to be involved in important cellular activities like epigenetics, implantation, cell growth etc. in pigs. However, comprehensive analysis of lncRNA in back fat tissues at different developmental stages in pigs is still lacking. In this study we conducted transcriptome analysis in the back fat tissue of a F1 crossbred Korean Native Pig (KNP) × Yorkshire Pig to identify lncRNA. We investigated their role in 16 pigs at two different growth stages; stage 1 (10 weeks, n = 8) and stage 2 (26 weeks, n = 8). After quality assessment of sequencing reads, we got a total of 1,641,165 assembled transcripts out of eight paired end read from each stage. Among them, 6808 lncRNA transcripts were identified by filtering on the basis of multiple parameters like read length ≥ 200 nucleotides, exon numbers ≥2, FPKM ≥0.5, coding potential score < 0 etc. PFAM and RFAM were used to filter out all possible protein coding genes and housekeeping RNAs respectively. A total of 103 lncRNAs and 1057 mRNAs were found to be differentially expressed (DE) between the two stages (|log2FC| > 2, q < 0.05). We also identified 306 genes located around 100 kb upstream and 234 genes downstream around these DE lncRNA transcripts. The expression of top eleven DE lncRNAs (COL4A6, LY7S, MYH2, OXCT1, SMPDL3A, TMEM182, TTC36, RFOOOO4, RFOOO15, RFOOO45, CADM2) had been validating by qRT-PCR. Pathway and GO terms analysis showed that, positive regulation of biosynthetic process, Wnt signaling pathway, cellular protein modification process, and positive regulation of nitrogen compound were differentially enriched. Our results suggested that, KEGG pathways such as protein digestion and absorption, Arrhythmogenic right ventricular cardiomyopathy (ARVC) to be significantly enriched in both DE lncRNAs as well as DE mRNAs and involved in back fat tissues development. It also suggests that, identified lncRNAs are involved in regulation of important adipose tissues development pathways.

Analysis of Effect of Schisandra in the Treatment of Myocardial Infarction Based on Three-Mode Gene Ontology Network

Schisandra chinensis is a commonly used traditional Chinese medicine, which has been widely used in the treatment of acute myocardial infarction in China. However, it has been difficult to systematically clarify the major pharmacological effect of Schisandra, due to its multi-component complex mechanism. In order to solve this problem, a comprehensive network analysis method was established based-on “component–gene ontology–effect” interactions. Through the network analysis, reduction of cardiac preload and myocardial contractility was shown to be the major effect of Schisandra components, which was further experimentally validated. In addition, the expression of NCOR2 and NFAT in myocyte were experimentally confirmed to be associated with Schisandra in the treatment of AMI, which may be responsible for the preservation effect of myocardial contractility. In conclusion, the three-mode gene ontology network can be an effective network analysis workflow to evaluate the pharmacological effects of a multi-drug complex system.

Integrative Analysis Revealing Human Adipose-Specific Genes and Consolidating Obesity Loci

Identification of adipose-specific genes has contributed to an understanding of mechanisms underlying adipocyte development and obesity. Herein, our analyses of the recent Genotype-Tissue Expression (GTEx) database revealed 38 adipose-specific/enhanced protein coding genes, among which 3 genes were novel adipose-specific, and 414 highly differentially expressed genes (DEGs) between subcutaneous and omental adipose depots. By integrative analyses of genome-wide association studies (GWASs), 14 adipose-specific/enhanced genes and 60 DEGs were found to be associated with obesity-related traits and diseases, consolidating evidence for contribution of these genes to the regional fat distribution and obesity phenotypes. In addition, expression of HOXC cluster was up-regulated in subcutaneous adipose tissue, and the majority of the HOXB cluster was expressed highly in omental adipose tissue, indicating differential expression patterns of HOX clusters in adipose depots. Our findings on the distinct gene expression profiles in adipose tissue and their relation to obesity provide an important foundation for future functional biological studies and therapeutic targets in obesity and associated diseases.

Distinct gene signatures predict insulin resistance in young mice with high fat diet-induced obesity

Highly inbred C57BL/6 mice show wide variation in their degree of insulin resistance in response to diet-induced obesity even though they are almost genetically identical. Here we employed transcriptional profiling by RNA sequencing (RNA-Seq) of visceral adipose tissue (VAT) and liver in young mice to determine how gene expression patterns correlate with the later development of high-fat diet (HFD)-induced insulin resistance in adulthood. To accomplish this goal, we partially removed and banked tissues from pubertal mice. Mice subsequently received HFD followed by metabolic phenotyping to identify two well-defined groups of mice with either severe or mild insulin resistance. The remaining tissues were collected at study termination. We then applied RNA-Seq to generate transcriptome profiles associated with worsened insulin resistance before and after the initiation of HFD. We found 244 up- and 109 downregulated genes in VAT of the most insulin-resistant mice even before HFD exposure. Downregulated genes included serine protease inhibitor, major urinary protein, and complement genes; upregulated genes represented mostly muscle constituents. These gene families were also differentially expressed in VAT of mice with high or low insulin resistance after HFD. Inflammatory genes predicted insulin resistance in liver, but not in VAT. In contrast, when we compared VAT of all mice before and after HFD, differentially expressed genes were predominantly composed of immune response genes. These data show a distinct set of gene transcripts in young mice correlates with the severity of insulin resistance in adulthood, providing insight into the pathogenesis of insulin resistance in early life.

Human fetal heart specific coexpression network involves congenital heart disease/defect candidate genes

Heart development is a complex process requiring dynamic transcriptional regulation. Disturbance of this process will lead to severe developmental defects such as congenital heart disease/defect (CHD). CHD is a group of complex disorder with high genetic heterogeneity, common pathways associated with CHD remains largely unknown. In the manuscript, we focused on the tissue specific genes in human fetal heart samples to explore such pathways. We used the RNA microarray dataset of human fetal tissues from ENCODE project to identify genes with heart tissue specific expression. A transcriptional network was constructed for these genes based on the Pearson correlation coefficients of their expression levels. Function, selective constraints and disease associations of these genes were then examined. Our analysis identified a network consisted of 316 genes with human fetal heart specific expression. The network was highly co-regulated and showed evolutionary conserved tissue expression pattern in tetrapod. Genes in this network are enriched in CHD specific genes and disease mutations. Using the transcriptomic data, we discovered a highly concerted gene network that might reflect a common pathway associated with the etiology of CHD. Such analysis should be helpful for disease associated gene identification in clinical studies.

Comparative expression profiling of testis-enriched genes regulated during the development of spermatogonial cells

The testis has been identified as the organ in which a large number of tissue-enriched genes are present. However, a large portion of transcripts related to each stage or cell type in the testis still remains unknown. In this study, databases combined with confirmatory measurements were used to investigate testis-enriched genes, localization in the testis, developmental regulation, gene expression profiles of testicular disease, and signaling pathways. Our comparative analysis of GEO DataSets showed that 24 genes are predominantly expressed in testis. Cellular locations of 15 testis-enriched proteins in human testis have been identified and most of them were located in spermatocytes and round spermatids. Real-time PCR revealed that expressions of these 15 genes are significantly increased during testis development. Also, an analysis of GEO DataSets indicated that expressions of these 15 genes were significantly decreased in teratozoospermic patients and polyubiquitin knockout mice, suggesting their involvement in normal testis development. Pathway analysis revealed that most of those 15 genes are implicated in various sperm-related cell processes and disease conditions. This approach provides effective strategies for discovering novel testis-enriched genes and their expression patterns, paving the way for future characterization of their functions regarding infertility and providing new biomarkers for specific stages of spematogenesis.

Identification of the MUC2 Promoter as a Strong Promoter for Intestinal Gene Expression through Generation of Transgenic Quail Expressing GFP in Gut Epithelial Cells

Identification of tissue- and stage-specific gene promoters is valuable for delineating the functional roles of specific genes in genetically engineered animals. Here, through the comparison of gene expression in different tissues by analysis of a microarray database, the intestinal specificity of mucin 2 (MUC2) expression was identified in mice and humans, and further confirmed in chickens by RT-PCR (reverse transcription-PCR) analysis. An analysis of cis-acting elements in avian MUC2 gene promoters revealed conservation of binding sites, within a 2.9 kb proximal promoter region, for transcription factors such as caudal type homeobox 2 (CDX2), GATA binding protein 4 (GATA4), hepatocyte nuclear factor 4 α (HNF4A), and transcription factor 4 (TCF4) that are important for maintaining intestinal homeostasis and functional integrity. By generating transgenic quail, we demonstrated that the 2.9 kb chicken MUC2 promoter could drive green fluorescent protein (GFP) reporter expression exclusively in the small intestine, large intestine, and ceca. Fluorescence image analysis further revealed GFP expression in intestine epithelial cells. The GFP expression was barely detectable in the embryonic intestine, but increased during post-hatch development. The spatiotemporal expression pattern of the reporter gene confirmed that the 2.9 kb MUC2 promoter could retain the regulatory element to drive expression of target genes in intestinal tissues after hatching. This new transgene expression system, using the MUC2 promoter, will provide a new method of overexpressing target genes to study gene function in the avian intestine.

Robust multi-group gene set analysis with few replicates

Background

Competitive gene set analysis is a standard exploratory tool for gene expression data. Permutation-based competitive gene set analysis methods are preferable to parametric ones because the latter make strong statistical assumptions which are not always met. For permutation-based methods, we permute samples, as opposed to genes, as doing so preserves the inter-gene correlation structure. Unfortunately, up until now, sample permutation-based methods have required a minimum of six replicates per sample group.

Results

We propose a new permutation-based competitive gene set analysis method for multi-group gene expression data with as few as three replicates per group. The method is based on advanced sample permutation technique that utilizes all groups within a data set for pairwise comparisons. We present a comprehensive evaluation of different permutation techniques, using multiple data sets and contrast the performance of our method, mGSZm, with other state of the art methods. We show that mGSZm is robust, and that, despite only using less than six replicates, we are able to consistently identify a high proportion of the top ranked gene sets from the analysis of a substantially larger data set. Further, we highlight other methods where performance is highly variable and appears dependent on the underlying data set being analyzed.

Conclusions

Our results demonstrate that robust gene set analysis of multi-group gene expression data is permissible with as few as three replicates. In doing so, we have extended the applicability of such approaches to resource constrained experiments where additional data generation is prohibitively difficult or expensive. An R package implementing the proposed method and supplementary materials are available from the website http://ekhidna.biocenter.helsinki.fi/downloads/pashupati/mGSZm.html.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1403-0) contains supplementary material, which is available to authorized users.

Identification of lung-specific genes by meta-analysis of multiple tissue RNA-seq data

Lung-specific genes play critically important roles in lung development, lung physiology, and pathogenesis of lung-associated diseases. We performed a meta-analysis of multiple tissue RNA-seq data to identify lung-specific genes in order to better investigate their lung-specific functions and pathological roles. We identified 83 lung-specific genes consisting of 62 protein-coding genes, five pseudogenes and 16 noncoding RNA genes. About 49.4% of lung-specific genes were implicated in the pathogenesis of lung diseases and 21.7% were involved with lung development. The identification of genes with enriched expression in the lung will facilitate the elucidation of lung-specific functions and their roles in disease pathogenesis.

The Arabidopsis NADPH oxidases RbohD and RbohF display differential expression patterns and contributions during plant immunity

Plant NADPH oxidases, also known as respiratory burst oxidase homologues (RBOHs), produce reactive oxygen species (ROS) that perform a wide range of functions. RbohD and RbohF, two of the 10 Rboh genes present in Arabidopsis, are pleiotropic and mediate diverse physiological processes including the response to pathogens. We hypothesized that the spatio-temporal control of RbohD and RbohF gene expression might be critical in determining their multiplicity of functions. Transgenic Arabidopsis plants with RbohD and RbohF promoter fusions to β-glucuronidase and Luciferase reporter genes were generated. Analysis of these plants revealed a differential expression pattern for RbohD and RbohF throughout plant development and during immune responses. RbohD and RbohF gene expression was differentially modulated by pathogen-associated molecular patterns. Histochemical stains and in vivo expression analysis showed a correlation between the level of RbohD and RbohF promoter activity, H2O2 accumulation and the amount of cell death in response to the pathogenic bacterium Pseudomonas syringae pv. tomato DC3000 and the necrotrophic fungus Plectosphaerella cucumerina. A promoter-swap strategy revealed that the promoter region of RbohD was required to drive production of ROS by this gene in response to pathogens. Moreover, RbohD promoter was activated during Arabidopsis interaction with a non-virulent P. cucumerina isolate, and susceptibility tests with the double mutant rbohD rbohF uncovered a new function for these oxidases in basal resistance. Altogether, our results suggest that differential spatio-temporal expression of the Rboh genes contributes to fine-tune RBOH/NADPH oxidase-dependent ROS production and signaling in Arabidopsis immunity.

Deep sequencing-generated modules demonstrate coherent expression patterns for various cardiac diseases

As sequencing technology rapidly develops, gene annotations have also become increasingly sophisticated with incorporation of information regarding the temporal-spatial context of alternative splicing patterns, developmental stages, and tissue specificity. The present study aimed to identify the heart-enriched genes based on next-generation sequencing data and to investigate the gene modules demonstrating coherent expression patterns for various cardiac disease-related perturbations. Seven gene modules, including 382 heart-enriched genes, were identified. At least two modules containing differentially expressed genes were experimentally confirmed to be highly sensitive to various cardiac diseases. Transcription factors regulating the gene modules were then analyzed based on knowledgebase information; the expression of eight transcription factors changed significantly during pressure-overload cardiac hypertrophy, suggesting possible regulation of the modules by the identified transcription factors. Collectively, our results contribute to the classification of heart-enriched genes and their modules and would aid in identification of the transcription factors involved in cardiac pathogenesis in the future.

MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data

Background

Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases.

Results

We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI’s Gene Expression Omnibus public repository encompassing samples for similar sets of five human tissues (brain, heart, kidney, liver, and lung). Comparison with another tool for tissue-specific gene identification and validation with literature-derived established tissue markers established functionality, accuracy and simplicity of our tool. Furthermore, top ranked marker genes were experimentally validated by reverse transcriptase-polymerase chain reaction (RT-PCR). The sets of predicted marker genes associated with the five selected tissues comprised well-known genes of particular importance in these tissues. The tool is freely available from the Bioconductor web site, and it is also provided as an online application integrated into the CellFinder platform (http://cellfinder.org/analysis/marker).

Conclusions

MGFM is a useful tool to predict tissue/cell type marker genes using microarray gene expression data. The implementation of the tool as an R-package as well as an application within CellFinder facilitates its use.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1785-9) contains supplementary material, which is available to authorized users.

Differential expression of cyclin G2, cyclin-dependent kinase inhibitor 2C and peripheral myelin protein 22 genes during adipogenesis

Increase of fat cells (FCs) in adipose tissue is attributed to proliferation of preadipocytes or immature adipocytes in the early stage, as well as adipogenic differentiation in the later stage of adipose development. Although both events are involved in the FC increase, they are contrary to each other, because the former requires cell cycle activity, whereas the latter requires cell cycle withdrawal. Therefore, appropriate regulation of cell cycle inhibition is critical to adipogenesis. In order to explore the important cell cycle inhibitors and study their expression in adipogenesis, we adopted a strategy combining the Gene Expression Omnibus (GEO) database available on the NCBI website and the results of quantitative real-time PCR (qPCR) data in porcine adipose tissue. Three cell cycle inhibitors - cyclin G2 (CCNG2), cyclin-dependent kinase inhibitor 2C (CDKN2C) and peripheral myelin protein (PMP22) - were selected for study because they are relatively highly expressed in adipose tissue compared with muscle, heart, lung, liver and kidney in humans and mice based on two GEO DataSets (GDS596 and GDS3142). In the latter analysis, they were found to be more highly expressed in differentiating/ed preadipocytes than in undifferentiated preadipocytes in human and mice as shown respectively by GDS2366 and GDS2743. In addition, GDS2659 also suggested increasing expression of the three cell cycle inhibitors during differentiation of 3T3-L1 cells. Further study with qPCR in Landrace pigs did not confirm the high expression of these genes in adipose tissue compared with other tissues in market-age pigs, but confirmed higher expression of these genes in FCs than in the stromal vascular fraction, as well as increasing expression of these genes during in vitro adipogenic differentiation and in vivo development of adipose tissue. Moreover, the relatively high expression of CCNG2 in adipose tissue of market-age pigs and increasing expression during development of adipose tissue was also confirmed at the protein level by western blot analysis. Based on the analysis of the GEO DataSets and results of qPCR and Western blotting we conclude that all three cell cycle inhibitors may inhibit adipocyte proliferation, but promote adipocyte differentiation and hold a differentiated state by inducing and maintaining cell cycle inhibition. Therefore, their expression in adipose tissue is positively correlated with age and mature FC number. By regulating the expression of these genes, we may be able to control FC number, and, thus, reduce excessive fat tissue in animals and humans.

Identification of CTLA2A, DEFB29, WFDC15B, SERPINA1F and MUP19 as Novel Tissue-Specific Secretory Factors in Mouse

Secretory factors in animals play an important role in communication between different cells, tissues and organs. Especially, the secretory factors with specific expression in one tissue may reflect important functions and unique status of that tissue in an organism. In this study, we identified potential tissue-specific secretory factors in the fat, muscle, heart, lung, kidney and liver in the mouse by analyzing microarray data from NCBI’s Gene Expression Omnibus (GEO) public repository and searching and predicting their subcellular location in GeneCards and WoLF PSORT, and then confirmed tissue-specific expression of the genes using semi-quantitative PCR reactions. With this approach, we confirmed 11 lung, 7 liver, 2 heart, 1 heart and muscle, 7 kidney and 2 adipose and liver-specific secretory factors. Among these genes, 1 lung-specific gene - CTLA2A (cytotoxic T lymphocyte-associated protein 2 alpha), 3 kidney-specific genes - SERPINA1F (serpin peptidase inhibitor, Clade A, member 1F), WFDC15B (WAP four-disulfide core domain 15B) and DEFB29 (defensin beta 29) and 1 liver-specific gene - MUP19 (major urinary protein 19) have not been reported as secretory factors. These genes were tagged with hemagglutinin at the 3’end and then transiently transfected to HEK293 cells. Through protein detection in cell lysate and media using Western blotting, we verified secretion of the 5 genes and predicted the potential pathways in which they may participate in the specific tissue through data analysis of GEO profiles. In addition, alternative splicing was detected in transcripts of CTLA2A and SERPINA1F and the corresponding proteins were found not to be secreted in cell culture media. Identification of novel secretory factors through the current study provides a new platform to explore novel secretory factors and a general direction for further study of these genes in the future.

Identification of the avian RBP7 gene as a new adipose-specific gene and RBP7 promoter-driven GFP expression in adipose tissue of transgenic quail

The discovery of an increasing number of new adipose-specific genes has significantly contributed to our understanding of adipose tissue biology and the etiology of obesity and its related diseases. In the present study, comparison of gene expression profiles among various tissues was performed by analysis of chicken microarray data, leading to identification of RBP7 as a novel adipose-specific gene in chicken. Adipose-specific expression of RBP7 in the avian species was further confirmed at the protein and mRNA levels. Examination of the transcription factor binding sites within the chicken RBP7 promoter by Matinspector software revealed potential binding sites for adipogenic transcription factors. This led to the hypothesis that the RBP7 promoter can be utilized to overexpress a transgene in adipose tissue in order to further investigate the function of a transgene in adipose tissue. Several lines of transgenic quail containing a green fluorescent protein (GFP) gene under the control of the RBP7 promoter were generated using lentivirus-mediated gene transfer. The GFP expression in transgenic quail was specific to adipose tissue and increased after adipocyte differentiation. This expression pattern was consistent with endogenous RBP7 expression, suggesting the RBP7 promoter is sufficient to overexpress a gene of interest in adipose tissue at later developmental stages. These findings will lead to the establishment of a novel RBP7 promoter cassette which can be utilized for overexpressing genes of interest in adipose tissue in vivo to study the function of genes in adipose tissue development and lipid metabolism.

Skeletal muscle characterization of Japanese quail line selectively bred for lower body weight as an avian model of delayed muscle growth with hypoplasia

This study was designed to extensively characterize the skeletal muscle development in the low weight (LW) quail selected from random bred control (RBC) Japanese quail in order to provide a new avian model of impaired and delayed growth in physically normal animals. The LW line had smaller embryo and body weights than the RBC line in all age groups (P<0.05). During 3 to 42 d post-hatch, the LW line exhibited approximately 60% smaller weight of pectoralis major muscle (PM), mainly resulting from lower fiber numbers compared to the RBC line (P<0.05). During early post-hatch period when myotubes are still actively forming, the LW line showed impaired PM growth with prolonged expression of Pax7 and lower expression levels of MyoD, Myf-5, and myogenin (P<0.05), likely leading to impairment of myogenic differentiation and consequently, reduced muscle fiber formation. Additionally, the LW line had delayed transition of neonatal to adult myosin heavy chain isoform, suggesting delayed muscle maturation. This is further supported by the finding that the LW line continued to grow unlike the RBC line; difference in the percentages of PMW to body weights between both quail lines diminished with increasing age from 42 to 75 d post-hatch. This delayed muscle growth in the LW line is accompanied by higher levels of myogenin expression at 42 d (P<0.05), higher percentage of centered nuclei at 42 d (P<0.01), and greater rate of increase in fiber size between 42 and 75 d post-hatch (P<0.001) compared to the RBC line. Analysis of physiological, morphological, and developmental parameters during muscle development of the LW quail line provided a well-characterized avian model for future identification of the responsible genes and for studying mechanisms of hypoplasia and delayed muscle growth.