Microarray, SAGE and their applications to cardiovascular diseases

Lung Cell Atlases in Health and Disease

The human lung cellular portfolio, traditionally characterized by cellular morphology and individual markers, is highly diverse, with over 40 cell types and a complex branching structure highly adapted for agile airflow and gas exchange. While constant during adulthood, lung cellular content changes in response to exposure, injury, and infection. Some changes are temporary, but others are persistent, leading to structural changes and progressive lung disease. The recent advance of single-cell profiling technologies allows an unprecedented level of detail and scale to cellular measurements, leading to the rise of comprehensive cell atlas styles of reporting. In this review, we chronical the rise of cell atlases and explore their contributions to human lung biology in health and disease.

Identification of Key Non-coding RNAs and Transcription Factors in Calcific Aortic Valve Disease

Background

Calcific aortic valve disease (CAVD) is one of the most frequently occurring valvular heart diseases among the aging population. Currently, there is no known pharmacological treatment available to delay or reverse CAVD progression. The regulation of gene expression could contribute to the initiation, progression, and treatment of CAVD. Non-coding RNAs (ncRNAs) and transcription factors play essential regulatory roles in gene expression in CAVD; thus, further research is urgently needed.

Materials and Methods

The gene-expression profiles of GSE51472 and GSE12644 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) were identified in each dataset. A protein-protein-interaction (PPI) network of DEGs was then constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and functional modules were analyzed with ClusterOne plugin in Cytoscape. Furthermore, Gene Ontology-functional annotation and Kyoto Encyclopedia of Genes and Genomes-pathway analysis were conducted for each functional module. Most crucially, ncRNAs and transcription factors acting on each functional module were separately identified using the RNAInter and TRRUST databases. The expression of predicted transcription factors and key genes was validated using GSE51472 and GSE12644. Furthermore, quantitative real-time PCR (qRT-PCR) experiments were performed to validate the differential expression of most promising candidates in human CAVD and control samples.

Results

Among 552 DEGs, 383 were upregulated and 169 were downregulated. In the PPI network, 15 functional modules involving 182 genes and proteins were identified. After hypergeometric testing, 45 ncRNAs and 33 transcription factors were obtained. Among the predicted transcription factors, CIITA, HIF1A, JUN, POU2F2, and STAT6 were differentially expressed in both the training and validation sets. In addition, we found that key genes, namely, CD2, CD86, CXCL8, FCGR3B, GZMB, ITGB2, LY86, MMP9, PPBP, and TYROBP were also differentially expressed in both the training and validation sets. Among the most promising candidates, differential expressions of ETS1, JUN, NFKB1, RELA, SP1, STAT1, ANCR, and LOC101927497 were identified via qRT-PCR experiments.

Conclusion

In this study, we identified functional modules with ncRNAs and transcription factors involved in CAVD pathogenesis. The current results suggest candidate molecules for further research on CAVD.

Assessment of gene expression profiles in peripheral occlusive arterial disease

BACKGROUND

Molecular events responsible for the onset and progression of peripheral occlusive arterial disease (POAD) are incompletely understood. Gene expression profiling may point out relevant features of the disease.

METHODS

Tissue samples were collected as operatory waste from a total of 36 patients with (n = 18) and without (n = 18) POAD. The tissues were histologically evaluated, and the patients with POAD were classified according to Leriche-Fontaine (LF) classification: 11% with stage IIB, 22% with stage III, and 67% with stage IV. Total RNA was isolated from all samples and hybridized onto Agilent 4×44K Oligo microarray slides. The bioinformatic analysis identified genes differentially expressed between control and pathologic tissues. Ten genes with a fold change ≥ 2 (1 with a fold change ≥ 1.8) were selected for quantitative polymerase chain reaction validation (GPC3, CFD, GDF10, ITLN1, TSPAN8, MMP28, NNMT, SERPINA5, LUM, and FDXR). C-reactive protein (CRP) was assessed with a specific assay, while nicotinamide N-methyltransferase (NNMT) was evaluated in the patient serum by enzyme-linked immunosorbent assay.

RESULTS

A multiple regression analysis showed that the level of CRP in the serum is correlated with the POAD LF stages (r(2) = 0.22, P = 0.046) and that serum NNMT is higher in IV LF POAD patients (P = 0.005). The mRNA gene expression of LUM is correlated with the LF stage (r(2) = 0.45, P = 0.009), and the mRNA level of ITLN1 is correlated with the ankle-brachial index (r(2) = 0.42, P = 0.008).

CONCLUSIONS

Our analysis shows that NNMT, ITLN1, LUM, CFD, and TSPAN8 in combination with other known markers, such as CRP, could be evaluated as a panel of biomarkers of POAD.

SpliceAid 2: a database of human splicing factors expression data and RNA target motifs

Splicing is the most frequently altered biological process by mutations within gene regions. Information for splicing is recognized by several factors that bind pre-mRNA sequence and, through coordinated interaction, yield mature transcripts. Some in silico methods have been developed to predict if a mutation leads to aberrant splicing patterns. We previously created SpliceAid tool that is able to minimize false positive predictions because it adopts strictly experimental RNA target motifs bound by splicing proteins in humans. In order to improve prediction accuracy and better understand the splicing outcome, the tissue specificity of each splicing regulatory factor has to be taken into account. Here, we have developed SpliceAid 2 by adding the expression data related to the splicing factors extracted from the main proteomic and transcriptomic databases, true 5' and 3' splice sites, polypyrimidine tracts, and branch point sequences. The new version collects 2,220 target sites of 62 human splicing proteins and their expression data in 320 tissues per cell. SpliceAid 2 can be useful to foresee the splicing pattern alteration, to guide the identification of the molecular effect due to the mutations and to understand the tissue-specific alternative splicing. SpliceAid 2 is freely accessible at www.introni.it/spliceaid.html.

hSAGEing: an improved SAGE-based software for identification of human tissue-specific or common tumor markers and suppressors

BACKGROUND

SAGE (serial analysis of gene expression) is a powerful method of analyzing gene expression for the entire transcriptome. There are currently many well-developed SAGE tools. However, the cross-comparison of different tissues is seldom addressed, thus limiting the identification of common- and tissue-specific tumor markers.

METHODOLOGY/PRINCIPAL FINDINGS

To improve the SAGE mining methods, we propose a novel function for cross-tissue comparison of SAGE data by combining the mathematical set theory and logic with a unique "multi-pool method" that analyzes multiple pools of pair-wise case controls individually. When all the settings are in "inclusion", the common SAGE tag sequences are mined. When one tissue type is in "inclusion" and the other types of tissues are not in "inclusion", the selected tissue-specific SAGE tag sequences are generated. They are displayed in tags-per-million (TPM) and fold values, as well as visually displayed in four kinds of scales in a color gradient pattern. In the fold visualization display, the top scores of the SAGE tag sequences are provided, along with cluster plots. A user-defined matrix file is designed for cross-tissue comparison by selecting libraries from publically available databases or user-defined libraries.

CONCLUSIONS/SIGNIFICANCE

The hSAGEing tool provides a combination of friendly cross-tissue analysis and an interface for comparing SAGE libraries for the first time. Some up- or down-regulated genes with tissue-specific or common tumor markers and suppressors are identified computationally. The tool is useful and convenient for in silico cancer transcriptomic studies and is freely available at http://bio.kuas.edu.tw/hSAGEing.

Low birth weight and markers of inflammation and endothelial activation in adulthood: the ARIC study

BACKGROUND

To investigate the hypothesis that intrauterine growth restriction might produce a longstanding pro-inflammatory tendency, we investigated the association of low birth weight with blood levels of markers of inflammation and endothelial activation in middle-aged adults.

METHODS

The ARIC Study enrolled subjects aged 45-64 years sampled from four U.S. communities. An inflammation/endothelial activation score from 0 to 6 was created, one point being given for each above-median value of white blood cell count, fibrinogen, von Willebrand factor and Factor VIII, and for each below-median value of albumin and activated partial thromboplastin time.

RESULTS

Of the 9809 individuals reporting birth weight and having all inflammation/endothelial markers and covariates, 349 (3.6%) reported low birth weight (LBW). The mean (standard deviation) score was 3.5 (1.5) for those with and 3.1 (1.6) for those without LBW (p<0.001). In robust poisson regression models adjusting for gender, ethnicity, age, study center, educational level, and current drinking and smoking status and amount, those with LBW were more likely to have a high score (> or =4 points) (RR=1.16, 95% CI: 1.05-1.29).

CONCLUSION

In the ARIC Study, LBW predicted greater inflammation and endothelial activation, as indicated by the higher score of blood markers, consistent with the hypothesis that early life events may result in a hyper-responsive innate immune system. Such a pro-inflammatory tendency could help explain the association of low birth weight with elements of the metabolic syndrome and ischemic heart disease.

Identification of candidate mRNAs associated with gonadotropin-induced maturation of murine cumulus oocyte complexes using serial analysis of gene expression

In cultured cumulus oocyte complexes (COC), FSH induces gene transcription required for germinal vesicle breakdown (GVBD). Experiments were performed to determine the critical period when gene transcription is required for GVBD and to identify candidate mRNAs involved. Experiment I: murine COC were cultured 4 h in the presence of FSH with 5,6-dichloro-1-β-d-ribofuranosylbenzimidazole (DRB) added at different intervals after the start of culture. COC cultured with FSH underwent GVBD (82 ± 7%). When DRB was added at 0, 5, or 10 min after culture initiation, oocyte maturation was blocked (17 ± 7, 14 ± 6, and 21 ± 6% GVBD, respectively). When DRB was added after 15, 20, or 30 min, progressively more COC underwent GVBD (37 ± 6, 39 ± 6, and 66 ± 6%, respectively). The critical period of transcription required for GVBD occurred between 15 and 30 min after culture initiation. Experiment II: COC were cultured for 25 min in the presence (plusDRB) or absence (minusDRB) of DRB. SAGE libraries were generated from COC RNA of each treatment group. A total of 48,431 and 45,367 tags were sequenced for the plusDRB and minusDRB libraries, respectively. Criteria used to identify transcripts of interest included a total tag count of at least 10 across both libraries and a threefold or greater difference in expression between libraries. Using these criteria, 39 and 27 transcripts were identified as differentially expressed at the P ≤ 0.01 and P ≤ 0.001 levels, respectively. Differentially expressed transcripts were classed into major categories that included cell growth, development, and regulation of gene expression. Differentially expressed transcripts represent candidates potentially involved in regulating maturation of murine COC.

SAGE reveals expression of Wnt signalling pathway members during mouse prostate development

To identify genes and pathways not previously implicated in the mesenchymal-epithelial (M/E) interactions that are critical for normal mouse prostate development, we constructed six serial analysis of gene expression (SAGE) libraries. Bioinformatic analyses revealed expression of various members of numerous signalling pathways and the differential expression of several members of the wingless-related MMTV integration site (Wnt) signalling pathway. This pathway has not been previously implicated in prostate development thus expression of selected Wnt pathway members in the developing prostate was confirmed by RT-qPCR. Of particular interest, an antagonist of the Wnt pathway, secreted frizzled related protein 2 (Sfrp2), was highly expressed in the early prostate libraries and down regulated at later developmental stages. The expression levels of four Wnt ligands reported to interact with Sfrp2 were, therefore, examined by RT-qPCR. We found that only Wnt4 transcripts were detectable in the developing prostate. Expression of Sfrp2 was validated using RT-qPCR and localization of Sfrp2 transcripts and protein was carried out using in situ hybridization and immunofluorescence, respectively. These studies provide the first evidence that Wnt pathway members are expressed in the developing prostate. Functional analyses are now required to establish the biological significance of this observation.

Design, preparation and testing of suitable probe-receptors for RNA biosensing

Absolute measurements of a given RNA in a cheap, easy, rapid and reproducible manner using biosensors technology could overcome many of the operative and analytical limits of conventional molecular biology methods. To this end, an integrated approach for the design, synthesis, and connection of RNA probes to the transducing surface of a microgravimetric biosensor has been developed. Suitable probes to be used as the bioreceptors in RNA biosensor were successfully designed by using a purposely developed computational method whose selection criteria are based on the accessibility of target region to probe, on pairing stability of probe-target duplex and on the uniqueness of selected targets over all known expressed sequences from a genome data base. Automated chemical synthesis of selected probes was performed and the oligonucleotides produced were covalently conjugated to the sensing surface of a quartz microbalance. The microgravimetric sensor was tested in a flow chamber by measuring the variation of resonance frequency due to the binding of synthetic target substrates. Specific dose dependent binding was observed. Furthermore, the binding of a transcribed full-length mRNA substrate was successfully monitored under similar conditions.

Transcriptional profiling of tissue plasticity: role of shifts in gene expression and technical limitations

Reprogramming of gene expression has been recognized as a main instructive modality for the adjustments of tissues to various kinds of stress. The recent application of gene expression profiling has provided a powerful tool to elucidate the molecular pathways underlying such tissue remodeling. However, the biological interpretations of expression profiling results critically depend on normalization of transcript signals to mRNA standards before statistical evaluation. A hypothesis is proposed whereby the “fluctuating nature” of gene expression represents an inherent limitation of the test system used to quantify RNA levels. Misinterpretation of gene expression data occurs when RNA quantities are normalized to a subset of mRNAs that are subject to strong regulation. The contention of contradictory biological outcomes using different RNA-normalization schemes is demonstrated in two models of skeletal muscle plasticity with data from custom-designed microarrays and biochemical and ultrastructural evidence for correspondingly altered RNA content and nucleolar activity. The prevalence of these biological constraints is underlined by a literature survey in different models of tissue plasticity with emphasis on the unique malleability of skeletal muscle. Finally, recommendations on the optimal experimental layout are given to control biological and technical variability in microarray and RT-PCR studies. It is proposed to approach normalization of transcript signals by measuring total RNA and DNA content per sample weight and by correcting for concurrently estimated endogenous standards such as major ribosomal RNAs and spiked RNA and DNA species. This allows for later conversion to diverse tissue-relevant references and should improve the physiological interpretations of phenotypic plasticity.

Reproducibility, bioinformatic analysis and power of the SAGE method to evaluate changes in transcriptome

The serial analysis of gene expression (SAGE) method is used to study global gene expression in cells or tissues in various experimental conditions. However, its reproducibility has not yet been definitively assessed. In this study, we have evaluated the reproducibility of the SAGE method and identified the factors that affect it. The determination coefficient (R²) for the reproducibility of SAGE is 0.96. However, there are some factors that can affect the reproducibility of SAGE, such as the replication of concatemers and ditags, the number of sequenced tags and double PCR amplification of ditags. Thus, corrections for these factors must be made to ensure the reproducibility and accuracy of SAGE results. A bioinformatic analysis of SAGE data is also presented in order to eliminate these artifacts. Finally, the current study shows that increasing the number of sequenced tags improves the power of the method to detect transcripts and their regulation by experimental conditions.

Gene expression changes in an in vitro model of chondroinduction: a comparison of two methods

There are many useful technologies to describe patterns of gene expression that occur during tissue repair and regeneration. Results from different methods used in one experimental setting are not often compared. In this case study of chondrogenesis, we compare two methods to identify differentially expressed genes, representational difference analysis and targeted macroarray analysis, as a model for investigating genes that may be relevant to tissue repair. We sought to identify genes whose expression was altered when human dermal fibroblasts were cultured in a three-dimensional, porous collagen sponge with the chondroinductive agent, demineralized bone. Both representational difference analysis and macroarray experiments revealed several functional families of genes as up-regulated or down-regulated in chondroinduced fibroblasts. An advantage of representational difference analysis is that altered expression of specific mRNA transcripts can be revealed. In this example, representational difference analysis uncovered the up-regulation of a specific transcript of Wnt5a in fibroblasts cultured with demineralized bone. Representational difference analysis is limited, however, as there can be false negatives for genes not readily amplified by polymerase chain reaction. We conclude that small arrays containing functional classes of genes can be used to ask specific, hypothesis-driven questions at minimal cost. It may be prudent, however, to use more than one method to survey differences in gene expression in order to validate and expand findings.

Identification of ABA-responsive genes in rice shoots via cDNA macroar-

Phytohormone abscisic acid (ABA) was critical for many plant growth and developmental processes including seed maturation, germination and response to environmental factors. With the purpose to detect the possible ABA related signal transduction pathways, we tried to isolate ABA-regulated genes through cDNA macroarray technology using ABA-treated rice seedling as materials (under treatment for 2, 4, 8 and 12 h). Of 6144 cDNA clones tested, 37 differential clones showing induction or suppression for at least one time, were isolated. Of them 30 and 7 were up- or down-regulated respectively. Sequence analyses revealed that the putative encoded proteins were involved in different possible processes, including transcription, metabolism and resistance, photosynthesis, signal transduction, and seed maturation. 6 cDNA clones were found to encode proteins with unknown functions. Regulation by ABA of 7 selected clones relating to signal transduction or metabolism was confirmed by reverse transcription PCR. In addition, some clones were further shown to be regulated by other plant growth regulators including auxin and brassinosteroid, which, however, indicated the complicated interactions of plant hormones. Possible signal transduction pathways involved in ABA were discussed.