Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis.
Keloids are defined as pathologically formed scars that exceed the boundary of the original wound . They are also deemed as benign dermal tumors that are unique to humans. Etiologically, keloids may occur because of minor skin injury, such as body piercing and insect bites. In addition, it is widely agreed that the incidence rate of keloid is significantly higher in populations with darker skin, such as Africans and Asians. The external ear is one of the most common sites for keloid formation . Many different treatment modalities such as surgical excision, intralesional corticosteroids, radiotherapy, and pressure earrings have been used for keloids [3, 4]. Although it has unclear etiology, the development of keloid could be considered as a process of abnormal wound healing, during which redundant extracellular collagen fibers as well as proteoglycans are deposited . It is known that various molecular factors contribute to this process, for example, growth factors [6,7], cytokines , and related gene pathways . Some among them maybe the key points that could stop or reverse this pathologic process. For example, transforming growth factor-[beta] (TGF-[beta]) receptor was recently reported to be a potential target in treating keloid . However, deeper understanding of the molecular mechanism of keloid formation is still required for detecting critical biological factors and for the further development of effective therapies.
It is known that 90% of the human genome is transcribed to RNAs that do not code proteins (noncoding RNAs). A lot of evidence suggests that long noncoding RNA (lncRNA; >200 nucleotides) regulates protein-coding genes at the transcriptional and posttranscriptional levels, as well as transcription control [11, 12]. It is known that lncRNAs play important roles in cellular differentiation, development, and disease [11, 12]. However, for earlobe keloids, the expression or function of lncRNAs has not been studied to date.
It the present study, global expression profiles of the lncRNAs and the mRNAs from 3 pairs of earlobe keloid specimens and normal skin tissues were detected using a microarray technique, from which significantly dysregulated lncRNAs and mRNAs were screened. These results indicated that the aberrant expression levels of lncRNAs may have important roles in the development of earlobe keloid and that knowing the differently expressed lncRNAs might provide useful biomarkers for earlobe keloid therapy and diagnosis.
2. Materials and Methods
2.1. Patients and Specimens. The study procedures were approved by the Ethics Review Board of Wuhan General Hospital of Guangzhou Military Command of the People's Liberation Army and it was carried out in accordance with the Declaration of Helsinki (2008) of the World Medical Association. Keloid was diagnosed by the overgrowth of a scar that obviously exceeded the boundary of the original wound. Demographic and clinical characteristics of the patients were extracted from their medical records. Earlobe keloid specimens were obtained from the resected keloid at our outpatient clinic. The normal skin specimens were obtained from the ear of the same patient. All patients were fully informed of the aim and protocol of the study and gave written informed consent to participate in the study.
2.2. RNA Isolation, Quantification, and Quality Control. Total RNA was extracted with the mirVana miRNA Isolation Kit (Applied Biosystems) and then eluted with 100 mL of nuclease-free water. Total RNA was quantified using a NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific) and the integrity of RNA was determined using an Agilent 2100 bioanalyzer and RNA 6000 Nano Kit (Agilent Technologies).
2.3. RNA Labeling and Array Hybridization. RNA sample preparation and microarray hybridization were performed according to Agilent One-Color Microarray-Based Gene Expression Analysis Protocol (Agilent Technologies, Santa Clara, CA, USA) with minor modifications. RNA was purified from 100 pg total RNA after removal of rRNA using RNeasy Mini Kit (Qiagen). After that, specimens were amplified and transcribed into cRNA, and cyanine-3-CTP was applied to label the cRNA (Quick Amp Labeling Kit: One-Color; Agilent). Labeled cRNA was once again purified with the RNeasy Mini Kit (Qiagen) and quantified using a NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific).
The cRNA was fragmented and hybridized using an Agilent Gene Expression Hybridization Kit (Agilent): 0.6 [micro]g labeled cRNA was fragmented by adding 5.0 [micro]L 10x blocking agent and 1.0 [micro]L 25x fragmentation buffer, and then the mixture was heated at 60[degrees]C for 30 minutes. After that, 25 [micro]L 2x GEx Hybridization Buffer was added to stop the fragmentation reaction. Finally, 50 mL hybridization solution was dispensed into the gasket slide and assembled to the lncRNA expression microarray slide. The slides were incubated for 17 hours at 65[degrees]C in an Agilent Hybridization Oven. The hybridized arrays were washed, fixed, and scanned with using the Agilent DNA Microarray Scanner (part number, G2505C).
2.4. Data Analysis. Data were extracted with Agilent Feature Extraction software 184.108.40.206. GeneSpring GX 12.5 (Agilent Technologies) was used to normalize the quantiles of the raw data. The lncRNAs are carefully constructed using the quality-controlled, public transcriptome databases (RefSeq, UCSC Known Genes, lncRNAWiki, LNCipedia, NONCODE v4, fRNAdb v3.4, Broad lincRNA, GENCODE, etc.), as well as landmark publications. After that, lncRNAs and mRNAs with significant differential expression between the two groups were identified, and the volcano plot was drawn. Hierarchical clustering was performed using MeV 4.9.0 (http:// www.tm4.org/mev.html), and heat maps were obtained by this analysis. Gene Ontology (GO) analysis was performed based on Gene Ontology (www. geneontology.org), which provided three structured networks of defined terms that describe gene product functions. Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/) database was used for pathway analysis of the differentially expressed genes.
2.5. Quantitative Real-Time PCR (qRT-PCR). The total RNA was isolated using mirVana miRNA Isolation Kit (Applied Biosystems) and was then reverse-transcribed using Prime-Script RT reagent kit with gDNA Eraser (Perfect Real Time; TaKaRa). The expression of five upregulated lncRNAs and five downregulated lncRNAs was measured by qRT-PCR using SYBR Green assays (TaKaRa), and GAPDH was used as an internal control. The expression level of each lncRNA was represented as a fold change using 2- C methods. The expression levels of lncRNAs differentially expressed between earlobe keloid specimens and normal skin specimens were analyzed using Student's t-test with SPSS version 17.0 .
2.6. Statistics. Statistical analysis was performed with SPSS version 19.0. The differences in expression levels of tested lncRNAs and mRNAs between earlobe keloid and normal skin tissues were assessed using Student's t-test, and fold change [greater than or equal to] 2.0 and P < 0.05 were considered significant. Fisher's exact test was used for GO analysis and KEGG pathway analysis. P < 0.05 was considered significant.
3.1. Differentially Expressed lncRNAs. The baseline data for the 3 patients (3 pairs of specimens) included in the study are shown in Table 1. In order to compare the distributions of intensities from all samples, we used a box plot to visualize the distributions of a dataset. Box-whisker plotting suggested similar distribution of the data from six RNA gene chips (Figure 1(a)). The expression profiles of 2068 lncRNAs indicated that they were differentially expressed (fold change [greater than or equal to] 2.0 and P < 0.05) between earlobe keloid specimens and normal skin specimens (shown in the lncRNA profiling). Variations in lncRNA expression among specimens were shown by volcano plotting and scatter plotting (Figures 1(b) and 1(c)). Among these lncRNAs, 1290 were upregulated more than twofold in the earlobe keloid specimens compared to the normal skin specimens, while 778 lncRNAs were downregulated more than twofold. lncRNA expression data are deposited at Gene Expression Omnibus under accession number GSE83286. The top 20 differentially expressed lncRNAs are listed in Tables 2 and 3. Finally, to infer the relationships among specimens, hierarchical clustering was performed to show distinguishable lncRNA expression patterns among samples (Figure 1(d)).
3.2. Differentially Expressed mRNAs. A total of 1511 mRNAs were differentially expressed between the two tissues (fold change [greater than or equal to] 2.0 and P < 0.05). A total of 1092 of 1511 mRNAs were expressed significantly higher in earlobe keloid specimens and 419 mRNAs were expressed significantly lower compared to normal skin specimens (shown in the mRNA profiling). mRNA expression data are deposited at Gene Expression Omnibus under accession number GSE83286. The top 20 differentially expressed mRNAs are listed in Supplemental Tables 1 and 2 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/5893481. Variations in the mRNA expression among specimens were shown by volcano plotting and scatter plotting (Figures 2(a) and 2(b)). Hierarchical clustering showed that mRNA expression modes among samples were distinguishable (Figure 2(c)).
3.3. GO Analysis. The GO project is a collaborative effort to construct and use ontologies to facilitate the biologically meaningful annotation of genes and their products in a wide variety of organisms . We performed GO analysis for lncRNAs to determine molecular function, biological processes, and cellular components. For molecular function (Figure 3(a)), calcium ion binding (GO:0005509) had the highest transcriptional domain coverage (TDC, 17.2%) in upregulated transcripts, while oxidoreductase activity (GO:0016491; TDC, 16.4%) was highest in downregulated transcripts. In biological processes (Figure 3(b)), it was found that upregulated genes were enriched most in the process of cell adhesion (GO:0007155; TDC, 18.8%). In contrast, downregulated genes were enriched most in the process of transmembrane transport (GO:0007155; TDC, 16.9%). In the cellular components (Figure 3(c)), it was detected that integral to membrane (GO:0016021) had the highest enrichment of upregulated genes (TDC, 39.5%), and mitochondria had the highest enrichment of downregulated genes (GO:0005886; TDC, 27.7%).
3.4. KEGG Analysis. KEGG pathway enrichment analysis was used for differentially expressed genes to identify pathways represented among the lncRNAs identified in the earlobe keloid gene expression signature. KEGG analysis suggested that 24 pathways were significantly correlated with upregulated gene expression. The focal adhesion pathway had the highest enrichment of increased transcription (TDC, 27.8%) and comprised 35 targets genes. Pathway analysis also revealed that 11 pathways corresponded to downregulated transcripts and that the most enriched network was metabolic pathways (TDC, 49.2%), which comprised 30 target genes (Figure 3(d)). Many of these pathways are reported to be associated with keloid, including the gene category focal adhesion pathway , TGF-[beta] signaling pathway [16-18], mitogen-activated protein kinase (MAPK) pathway , and gap junction pathway [20, 21].
3.5. QRT-PCR Validation. To verify the microarray data, five upregulated lncRNAs (NONHSAT120157, NONHSAT062994, NONHSAT016933, NR.024360.1, and FR39263) and five downregulated lncRNAs (NONHSAT053431, FR244962, ENST00000601148, TCONS_ 00022478, and XR244388.1) were randomly selected from the differentially expressed lncRNAs. We detected the expression levels of these lncRNAs in 10 earlobe keloids tissues and normal skin samples (Supplemental Table 3) using qRT-PCR. As shown in Figure 4, the qRT-PCR results and microarray data are consistent.
Emerging evidence shows that a set of noncoding RNAs (for example, miRNA) is involved in the mechanism of keloid formation [22-25]. lncRNAs are larger than miRNAs and have more complex structure. Deregulated expression of lncRNA disrupts cellular physiology and then leads to pathology [26-28]. Thus, we suggest that lncRNAs may play crucial roles in many biological processes and are vital to the formation of earlobe keloids. However, the profile and biological function of lncRNAs for earlobe keloid remain largely unknown. Thus, in the present study, we established the expression profile of lncRNAs in human earlobe keloids.
We analyzed lncRNA and mRNA expression profiles in the tissues of earlobe keloid and control tissues to reveal the potential roles of lncRNAs in the pathogenesis of earlobe keloid. High-throughput microarray techniques uncovered differential expression between 3 pairs of earlobe keloid and normal skin specimens. We identified that 1290 lncRNAs and 1092 mRNAs were upregulated and 778 lncRNAs and 419 mRNAs were downregulated in all 3 earlobe keloid and normal tissues (fold change [greater than or equal to] 2.0, P < 0.05). GO and KEGG pathway analysis were used to explore the possible biological functions and potential mechanisms of lncRNAs and mRNAs in earlobe keloids. In fact, Liang and colleagues have previously identified differential expression of lncRNAs and mRNAs between 3 pairs of keloid and normal skin tissue by microarray (32). Compared with their results, our study has several differences. First, tissues used here were earlobe keloid and normal specimens, and the expression profiles of lncRNAs were significantly different from the previous results. Second, to verify the microarray data, the expression levels of five upregulated lncRNAs and five downregulated lncRNAs were detected in 10 earlobe keloids tissues and normal skin samples using qRT-PCR, and the results were consistent with microarray data.
An integrative method including pathway was developed to identify possible functional relationships between the different RNA molecules. Based on the differentially expressed mRNAs, pathway analysis revealed which biological functions and mechanisms were involved in earlobe keloid formation. Our results suggest that different biological processes, such as cell-cell adhesion, cell migration, cell death, cell junction formation, epithelial to mesenchymal transition (EMT), TGF-[beta], and MAPK, are among the significantly enriched mRNAs. Most of these pathways are involved in the process of tissue fibrosis. For example, studies in a wide range of experimental models have revealed that TGF-[beta] is a central mediator of keloid fibrogenesis. It is reported that Loureirin B attenuated the contraction of fibroblasts which was induced by TGF-[beta] in hypertrophic scar formation (33). Yan et al. have reported that EMT plays crucial roles in keloid formation . Gobin et al. have shown that emodin-loaded liposomes decrease survival rate of keloids which express high levels of receptor tyrosine kinase (RTK) (included in the focal adhesion pathway) . Among these related pathways, we found that focal adhesion, extracellular matrix receptor interaction, cell adhesion molecules, and gap junction-associated pathway showed significant changes in upregulated and downregulated mRNAs. For example, 35 differentially expressed mRNAs were involved in the focal adhesion pathway and 16 differentially expressed mRNAs were enriched in cell adhesion molecules. Otherwise, 7 of which were downregulated in the tight junction related pathway. These results indicated that cell adhesion and tight associated signaling may play an important role in the mechanism of earlobe keloid formation, which is not identified by other researches.
Our study used microarray data to analyze systematically and comprehensively differentially expressed lncRNAs and mRNAs between normal skin and earlobe keloid tissues. Many differentially expressed lncRNAs could play a vital role in regulating earlobe keloid formation through various pathways. In our present study, we found that TGF-[beta], MAPK, cell tight, and adhesion related signaling series mRNAs may interact with IncRNAs. Previous reports demonstrated that ADAM proteins are involved in cell adhesion, cell fusion, cell signaling, and proteolysis. ADAM33 is a member of ADAM family that is associated with keloid scars in the northeastern Chinese population (36). ADAM12 are reluctant to adhere to fibronectin, a key ECM protein in keloids (37). Patients suffering from collagen VI related myopathies caused by mutations in COL6A1, COL6A2, and COL6A3 often also display skin abnormalities, like formation of keloids or "cigarette paper" scars, dry skin, striae rubrae, and keratosis pilaris (follicular keratosis) (38). Keloid fibroblasts were propagated in culture and their proliferative behaviour and response to the epidermal growth factor (EGF) were studied (39). Our results found that NONHSAT016934, NONHSAT016933, NONHSAT016928, and NONHSAT077639 expressions were increased, whereas NONHSAT097800 expression was decreased in earlobe keloid and normal tissues. These lncRNAs were associated with the related genes of keloid (ADAM12, COL6A3, and EGF). We will carry out further studies of these differentially expressed lncRNAs to establish their functions in earlobe keloid formation.
In conclusion, we studied the differential expression profile of lncRNAs and mRNAs in earlobe keloid and normal skin tissues. Our microarray analysis indicated that lncRNAs are involved in the pathological process of earlobe keloid formation. Therefore, subgroup analysis of lncRNAs should be performed to explore this relationship in the future. In addition, we will select numbers of samples to deepen the research into the lncRNA molecular mechanism and biochemical function in order to provide a novel accurate method for therapy of earlobe keloid.
All the authors declare that they have no competing interests to disclose.
Liang Guo and Kai Xu contributed equally to this study.
This work was supported by a grant from the National Natural Science Foundation of China (Grant nos. 81301638 and 81301639) and a grant from the Natural Science Foundation ofHubei Province (Grant no. 2012FFB06808).
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Liang Guo, (1) Kai Xu, (1) Hongbo Yan, (1) Haifeng Feng, (1) Linlin Chai, (2) and Guozheng Xu (3)
(1) Department of Plastic Surgery, Wuhan General Hospital of Guangzhou Military Command of Chinese PLA, Wuhan, Hubei, China
(2) Department of Plastic and Reconstructive Surgery, Southwestern Hospital, Third Military Medical University, Chongqing, China
(3) Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Command of Chinese PLA, Wuhan, Hubei, China
Correspondence should be addressed to Linlin Chai; email@example.com and Guozheng Xu; firstname.lastname@example.org
Received 8 July 2016; Revised 14 September 2016; Accepted 1 November 2016
Academic Editor: Kui Li
Caption: Figure 1: Expression profiles of lncRNAs in earlobe keloid and normal skin specimens. (a) Box-whisker plots of lncRNAs showed the distributions of intensities from all samples. (b) Volcano plots showed variation in lncRNA expression. The vertical lines correspond to 2.0-fold upregulation and downregulation and the horizontal line represents a P value of 0.05. (c) Scatter plots show variation in lncRNA expression. (d) Hierarchical clustering shows lncRNA expression profiling. Cluster analysis arranges samples into groups based on their expression levels, which allows us to hypothesize the relationships among samples. "Red" indicates highly relative expression, and "green" indicates lowly relative expression.
Caption: Figure 2: Expression profiles of mRNAs in earlobe keloid and normal skin specimens. (a and b) Volcano and scatter plots show differences in expression. The vertical green lines delimit 2.0-fold upregulation and downregulation. Red plots represent mRNAs with >2.0-fold change and corrected P value < 0.05. (c) Hierarchical clustering shows mRNA expression profiling. Cluster analysis arranges samples into groups based on their expression levels, which allows us to hypothesize the relationships among samples. "Red" indicates highly relative expression, and "green" indicates lowly relative expression.
Caption: Figure 4: Quantitative RT-PCR validation of 10 differentially expressed lncRNAs. (a) Comparison of fold change [[log.sub.10](S/N)] oflncRNAs between microarray and quantitative RT-PCR results (S: earlobe keloid specimens; N: normal skin specimens). (b) Relative expression levels of lncRNAs in 10 other pairs of earlobe keloid and normal skin specimens (P < 0.05).
Table 1: Baseline data of included patients. Case Age Gender Reason of Size of keloid History of (years) skin injury (cm x cm x cm) keloid (months) 1 21 Female Earlobe 2.0 x 1.3 x 0.8 10 piercing 2 34 Female Earlobe 1.8 x 1.5 x 1.2 14 piercing 3 24 Female Earlobe 2.7 x 2.0 x 1.5 17 piercing Table 2: The top 20 upregulated lncRNAs. Seq. name Source Fold change Chrom. Strad. NONHSAT120157 NONCODE v4 302.566 chr7 -- NONHSAT062994 NONCODE v4 198.76 chr19 -- ENST00000424523 Ensembl 1878763 chr7 + NONHSAT016934 NONCODE v4 121.1942 chr10 -- NONHSAG007229 NONCODE v4 98.20973 chr10 -- NONHSAT135001 NONCODE v4 85.73119 chr9 + NONHSAT016933 NONCODE v4 66.81899 chr10 -- NONHSAT033754 NONCODE v4 59.65379 chr13 + NONHSAT102388 NONCODE v4 57.30576 chr5 + NONHSAT016928 NONCODE v4 56.89644 chr10 -- NONHSAT076769 NONCODE v4 55.34357 chr2 + NONHSAT033252 NONCODE v4 45.90168 chr13 -- NONHSAG013256 NONCODE v4 45.0158 chr13 -- ENST00000557618 Ensembl 40.71083 chr14 + ENST00000597626 Ensembl 37.49051 chr21 + NONHSAG030448 NONCODE v4 36.29881 chr2 -- NONHSAT056875 NONCODE v4 34.17572 chr18 + NONHSAG052055 NONCODE v4 32.53344 chr9 + NONHSAT100815 NONCODE v4 31.91256 chr5 + NONHSAT077639 NONCODE v4 30.05823 chr2 -- Seq. name txStrat txEnd Associated gene name NONHSAT120157 37946864 37949441 SFRP4 NONHSAT062994 18896928 18897844 COMP ENST00000424523 92484223 92546465 NONHSAT016934 127823937 127843874 ADAM12 NONHSAG007229 134634754 134637851 TTC40 NONHSAT135001 131745793 131747541 NUP188 NONHSAT016933 127779305 127798357 ADAM12 NONHSAT033754 50191636 50192101 NONHSAT102388 79377827 79379011 THBS4 NONHSAT016928 127700956 127703336 ADAM12 NONHSAT076769 216476099 216669548 LINC00607 NONHSAT033252 38137358 38144948 postn NONHSAG013256 38136835 38145672 postn ENST00000557618 60981837 61021634 ENST00000597626 35287852 35341659 NONHSAG030448 216232403 216237205 FN1 NONHSAT056875 907552 909671 ADCYAP1 NONHSAG052055 34084331 34096676 DCAF12 NONHSAT100815 28524293 28602803 NONHSAT077639 238241611 238243429 COL6A3 Table 3: The top 20 downregulated lncRNAs. Seq. name Source Fold change Chrom. Strad. NONHSAT053431 NONCODE v4 22.78803 chr17 + NONHSAT030286 NONCODE v4 17.52123 chr12 + FR244962 fRNAdb v3.4 16.8388 chr7 + ENST00000601148 Ensembl 15.31924 chr19 + TCONSJ2.00026076 Broad lincRNA 13.31326 chr7 + FR193036 fRNAdb v3.4 12.53563 chr19 -- NONHSAT125631 NONCODE v4 12.31555 chr8 + TCONSJ2.00016248 Broad lincRNA 12.02637 chr20 + NONHSAT030224 NONCODE v4 12.02533 chr12 -- NONHSAT076673 NONCODE v4 11.6689 chr2 -- NONHSAT137402 NONCODE v4 11.66708 chrX + ENST00000580420 Ensembl 11.61363 chr18 + FR174595 fRNAdb v3.4 11.10483 chr6 + NONHSAT077942 NONCODE v4 11.03293 chr2 -- NONHSAT060814 NONCODE v4 10.87916 chr19 + NONHSAT097800 NONCODE v4 10.56074 chr4 + NONHSAT070090 NONCODE v4 10.32572 chr2 + TCONS_00022478 Broad lincRNA 10.21703 chr14 + ENST00000556024 Ensembl 9.802968 chr14 -- NONHSAT102735 NONCODE v4 9.773005 chr5 + Seq. name txStrat txEnd Associated gene name NONHSAT053431 37395854 37400623 FBXL20 NONHSAT030286 101988749 102021958 MYBPC1 FR244962 31551811 31552010 ENST00000601148 51843949 51847370 TCONSJ2.00026076 80804833 80828289 FR193036 56526608 56527152 NONHSAT125631 25398695 25408293 TCONSJ2.00016248 37230676 37256614 NONHSAT030224 100560001 100562998 GOLGA2P5 NONHSAT076673 211074313 211081443 ACADL NONHSAT137402 69454505 69457167 AWAT1 ENST00000580420 29522538 29524119 FR174595 118888744 118889041 NONHSAT077942 242455829 242457154 NONHSAT060814 7410710 7411049 NONHSAT097800 110897243 110898692 EGF NONHSAT070090 36991437 36993016 vit TCONS_00022478 38205181 38208450 ENST00000556024 38025363 38036300 NONHSAT102735 90142207 90144638 GPR98 Figure 3: (a) Top 12 enriched GO terms for differentially expressed mRNAs for molecular function. The bar plot shows the transcriptional domain coverage. (b) Top 12 enriched GO terms for differentially expressed mRNAs for biological processes. The bar plot shows the transcriptional domain coverage. (c) Top 12 enriched GO terms for differentially expressed mRNAs for cellular components. The bar plot shows the transcriptional domain coverage. (d) The results of KEGG pathway enrichment analysis. The bar plot shows the transcriptional domain coverage of the enrichment pathway. Transcriptional domain coverage (%) (a) GO molecular function Upregulated transcript Cytokine activity 4.1% Collagen binding 4.4% Integrin binding 4.7% Metalloendopeptidase activity 5% Sugar binding 5.5% Heparin binding 5.5% GTPase activity 5.5% Receptor binding 6.1% Extracellular matrix structural constituent 6.7% GTP binding 8.5% Peptidase activity 11.7% Calcium ion binding 17.2% Downregulated transcripts Alpha-tubulin binding 1.8% Hydrolase activity 2.7% ATPase activity 2.7% Calcium channel activity 2.7% Oxygen binding 2.7% Aromatase activity 3.6% Monooxygenase activity 3.6% Flavin adenine dinucleotide binding 5.5% GTPase activator activity 6.4% Structural constituent of ribosome 9.1% Binding 14.5% Oxidoreductase activity 16.4% Transcriptional domain coverage (%) (b) GO biological process Upregulated transcript Small GTPase mediated signal transduction 5.4% Platelet activation 5.6% Positive regulation of cell proliferation 6.5% Negative regulation of cell proliferation 6.7% Skeletal system development 6.7% Axon guidance 8.1% Nervous system development 8.1% Blood coagulation 8.7% Proteolysis 9% Multicellular organismal development 13.9% Signal transduction 15.9% Cell adhesion 18.8% Downregulated transcripts Response to hypoxia 5.1% Cellular nitrogen compound metabolic process 5.9% Endocrine pancreas development 7.6% Viral transcription 7.6% Viral infectious cycle 7.6% Translational elongation 7.6% Translational termination 8.5% Viral reproduction 9.3% Translation 10.2% Gene expression 11% Cellular protein metabolic process 11% Transmembrane transport 16.9% Transcriptional domain coverage (%) (c) GO cellular component Upregulated transcripts Golgi membrane 5.1% Cell surface 5.6% Extracellular matrix 6.8% Proteinaceous extracellular matrix 7.8% Endoplasmic reticulum 11.3% Integral to plasma membrane 11.6% Golgi apparatus 11.9% Extracellular space 13.8% Extracellular region 29.2% Membrane 35% Plasma membrane 35.5% Integral to membrane 39.5% Downregulated transcripts Synaptic vesicle 2.7% Spectrin 2.7% Cytosolic small ribosomal subunit 3.6% Keratin filament 4.5% Nucleosome 4.5% Tight junction 4.5% Cell cortex 6.2% Mitochondrial matrix 7.1% Microsome 8.9% Endoplasmic reticulum membrane 14.3% Integral to plasma membrane 23.2% Mitochondrion 27.7% Transcriptional domain coverage (%) (d) KEGG Upregulated transcript TGF-beta signaling pathway 9.5% Arrhythmogenic right ventricular cardiomyopathy (ARVC) 9.5% Axon guidance 10.3% Hypertrophic cardiomyopathy (HCM) 11.1% Protein digestion and absorption 11.1% Gap junction 11.1% Amoebiasis 11.9% Dilated cardiomyopathy 11.9% Cell adhesion molecules (CAMs) 12.7% Phagosome 14.3% ECM-receptor interaction 18.3% Focal adhesion 27.8% Downregulated transcripts Butirosin and neomycin biosynthesis 3.3% Glyoxylate and dicarboxylate metabolism 3.3% Aldosterone-regulated sodium reabsorption 4.9% Carbohydrate digestion and absorption 4.9% Linoleic acid metabolism 4.9% Fructose and mannose metabolism 6.6% Long-term depression 6.6% Tight junction 11.5% Ribosome 14.8% Systemic lupus erythematosus 16.4% Metabolic pathways 49.2% Note: Table made from bar graph.
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|Title Annotation:||Research Article|
|Author:||Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng; Chai, Linlin; Xu, Guozheng|
|Publication:||BioMed Research International|
|Article Type:||Clinical report|
|Date:||Jan 1, 2017|
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