Identification of differentially expressed protein‑coding genes in lung adenocarcinomas

The ubiquitin (Ub)–proteasome system (UPS) is an important regulatory component in colorectal cancer (CRC), and the cell cycle is also characterized to play a significant role in CRC. In this present study, we firstly identified UPS-associated differentially expressed genes and all the differentially expressed protein-coding genes in CRC through three differential analyses. UPS-associated genes were also further analyzed via survival analysis. A weighted gene co-expression network analysis (WGCNA) was used to identify the cell cycle-associated genes. We used protein–protein interaction (PPI) network to comprehensively mine the potential mechanism of the UPS–cell cycle regulatory axis. Moreover, we constructed a signature based on UPS-associated genes to predict the overall survival of CRC patients. Our research provides a novel insight view of the UPS and cell cycle system in CRC.

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Genome-wide identification and comparison of differentially expressed profiles of miRNAs and lncRNAs with associated ceRNA networks in the gonads of Chinese soft-shelled turtle, Pelodiscus sinensis

10.21203/rs.2.10525/v4 ◽

2020 ◽

Author(s):

Xiao Ma ◽

Shuangshuang Cen ◽

Luming Wang ◽

Chao Zhang ◽

Limin Wu ◽

...

Keyword(s):

Messenger Rna ◽

Target Genes ◽

Expression Profiles ◽

Differentially Expressed ◽

Integrated Analysis ◽

Pelodiscus Sinensis ◽

Specific Expression ◽

Protein Coding ◽

Reproductive Regulation ◽

Protein Coding Genes

Abstract Background: The gonad is the major factor affecting animal reproduction. The regulatory mechanism of the expression of protein-coding genes involved in reproduction still remains to be elucidated. Increasing evidence has shown that ncRNAs play key regulatory roles in gene expression in many life processes. The roles of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in reproduction have been investigated in some species. However, the regulatory patterns of miRNA and lncRNA in the sex biased expression of protein coding genes remains to be elucidated. In this study, we performed an integrated analysis of miRNA, messenger RNA (mRNA), and lncRNA expression profiles to explore their regulatory patterns in the female ovary and male testis of Chinese soft-shelled turtle, Pelodiscus sinensis.Results: We identified 10 446 mature miRNAs, 20 414 mRNAs and 28 500 lncRNAs in the ovaries and testes, and 633 miRNAs, 11 319 mRNAs, and 10 495 lncRNAs showed differential expression. A total of 2 814 target genes were identified for miRNAs. The predicted target genes of these differentially expressed (DE) miRNAs and lncRNAs included abundant genes related to reproductive regulation. Furthermore, we found that 189 DEmiRNAs and 5 408 DElncRNAs showed sex-specific expression. Of these, 3 DEmiRNAs and 917 DElncRNAs were testis-specific, and 186 DEmiRNAs and 4 491 DElncRNAs were ovary-specific. We further constructed complete endogenous lncRNA-miRNA-mRNA networks using bioinformatics, including 103 DEmiRNAs, 636 DEmRNAs, and 1 622 DElncRNAs. The target genes for the differentially expressed miRNAs and lncRNAs included abundant genes involved in gonadal development, including Wt1, Creb3l2, Gata4, Wnt2, Nr5a1, Hsd17, Igf2r, H2afz, Lin52, Trim71, Zar1, and Jazf1.Conclusions: In animals, miRNA and lncRNA as master regulators regulate reproductive processes by controlling the expression of mRNAs. Considering their importance, the identified miRNAs, lncRNAs, and their targets in P. sinensis might be useful for studying the molecular processes involved in sexual reproduction and genome editing to produce higher quality aquaculture animals. A thorough understanding of ncRNA-based cellular regulatory networks will aid in the improvement of P. sinensis reproductive traits for aquaculture.

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Gene Expression Profile in Responsive and Non-Responsive Chronic Myeloid Leukemia Patients Treated with Dasatinib.

Blood ◽

10.1182/blood.v114.22.3260.3260 ◽

2009 ◽

Vol 114 (22) ◽

pp. 3260-3260

Author(s):

Rosana A Silveira ◽

Angela A Fachel ◽

Yuri B Moreira ◽

Marcia T Delamain ◽

Carmino Antonio De Souza ◽

...

Keyword(s):

Gene Expression ◽

Human Genome ◽

Mononuclear Cells ◽

Cytogenetic Response ◽

Post Treatment ◽

Differentially Expressed ◽

Regulation Of Transcription ◽

Protein Coding ◽

Altered Expression ◽

Protein Coding Genes

Abstract Abstract 3260 Poster Board III-1 Background: CML treatment with tyrosine kinase inhibitors induces high and durable rates of complete cytogenetic response. Despite treatment efficacy, a significant proportion of patients develop resistance to these drugs. We measured gene expression profiles in an attempt to identify gene pathways that may be associated with dasatinib resistance. Patients and Methods: Mononuclear cells were separated from peripheral blood samples from seven CML patients resistant to imatinib, collected prior and after dasatinib treatment. Three patients who achieved partial cytogenetic response (Ph-positive cells: 1% - 35%) within twelve months were considered responders (R), whereas four patients who failed to achieve PCyR within 12 months of treatment were classified as non-responders. RNA samples prepared from peripheral mononuclear cells were hybridized to Agilent Technologies 4×44K Whole Human Genome Microarrays (WHGM) and 4×44K intronic-exonic custom oligoarrays. The latter was developed by Verjovski-Almeida's group (Nakaya et al, Genome Biology 2007, 8:R43) and contains sense and antisense probes that map to intronic regions in the human genome representing totally (TIN) and partially (PIN) intronic non-coding RNAs (ncRNAs), in addition to probes for the corresponding protein-coding genes of the same loci. Raw microarray data were normalized by the Affy package in statistical R language implemented in the Bioconductor platform. Each sample was labeled in replicate with Cy3 or Cy5 and the two were considered technical replicates. Two independent statistical approaches SAM (Significance Analysis of Microarrays) and Golub's discrimination score (SNR, Signal to Noise Ratio, with permutations) were performed to identify differentially expressed transcripts between responder and non-responder patients. For the intronic-exonic platform, the analysis parameters were FDR 10%, SNR>1.5 and p<0.01, and for WHGM platform parameters were FDR 5%, SNR>1.5 and p<0.001. For this latter platform, we also performed a patient leave-one-out analysis. Functions of transcripts differentially expressed were annotated and compared using GO Biological Process categories (www.genetools.microarray.ntu.no/egon). Results: We identified 34 ncRNAs with altered expression (26 over and 8 underexpressed in responders) in pre-treatment samples and 33 ncRNAs (20 over and 13 underexpressed in responders) in post-treatment samples. Functions associated with protein-coding genes from the same genomic loci as those of the intronic differentially expressed ncRNAs were: regulation of transcription (PRMT5, SOD2, SSBP3, BCL7A, MLL), signal transduction (PRKCB1, RASGRP2, NF1, PXN) and apoptosis (BCL2, PCSK6, TNFAIP8, EIF4G2). WHGM platform data analysis showed 63 and 250 protein-coding genes differentially expressed in pre and post-treatment samples, respectively. We observed a higher number of protein-coding genes with altered expression after treatment in the following functions: cell communication, immune response and metabolic process (p<0.02). Conclusions: Overall, these findings indicate that protein-coding genes and intronic ncRNAs may be related to dasatinib resistance and response to treatment. In particular, altered expression of ncRNAs transcribed from the introns of ‘regulation of transcription' genes could be part of an important alternative mechanism of gene expression control during emergence of resistance.Support: FAPESP (2005/60266-8) Disclosures: No relevant conflicts of interest to declare.

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Long Intergenic Non-Coding RNAs (lincRNA) Impacts Biology and Clinical Outcome in Multiple Myeloma

Blood ◽

10.1182/blood.v124.21.642.642 ◽

2014 ◽

Vol 124 (21) ◽

pp. 642-642

Author(s):

Mehmet Kemal Samur ◽

Naim Rashid ◽

Alice Cleynen ◽

Mariateresa Fulciniti ◽

Adam Sperling ◽

...

Keyword(s):

Clinical Outcome ◽

Regression Model ◽

Cox Regression ◽

Differentially Expressed ◽

P Value ◽

Relapse Free Survival ◽

Protein Coding ◽

Free Survival ◽

Protein Coding Genes ◽

Regulatory Functions

Abstract RNA has a diverse sets of regulatory functions besides being a messenger between DNA and protein. Recent analysis of RNA repertoire has identified a large numbers of non-coding transcripts. One of which, long intergenic non-coding RNA (lincRNA) with transcripts longer than 200 nucleotides, are located between the protein coding genes and do not overlap exons of either protein-coding or other non-lincRNA genes. lincRNAs have been considered to provide regulatory functions, however, their precise role in cellular biology remains unclear. Here, we have evaluated the lincRNA profile and their clinical role in MM. We performed RNA-seq on CD138+ MM cells from 320 patients and 18 normal bone marrow plasma cells (NBM) and analyzed for lincRNA. Data from Unstranded 50 bp paired-end RNAseq reads were mapped to the human genome and evaluated for frequency and type of lncRNA. Patient data for MM characteristics, cytogenetic and FISH as well as clinical survival outcomes were also analyzed and correlated with lncRNA data. We compared differentially expressed lincRNAs and protein coding genes in MM versus NBM samples. lincRNA and protein coding genes that have more than 2 reads/million reads for at least 50 samples (~15%) were included in the analysis. We identified 192 significantly expressed lincRNA (adj p value <0.05). We evaluated neighborhood protein coding genes for lincRNA within 500kb up/down stream and identified 298 genes within the region, 134 of these also differentially expressed between MM and NBM. Gene enrichment analysis to recognize possible biological processes that may be affected by lincRNAs and genes enriched by several Gene Ontology(GO) terms identified DNA binding, transcription, cell proliferation, and regulation of lymphocyte function. We applied unsupervised clustering method to the differentially expressed lincRNA that are neighbor of these 134 protein-coding genes. We identified four distinct clusters which are being investigated for correlation with clinical subtypes of MM. Finally we checked correlation between lincRNAs and clinical outcome including response and relapse free survival. We compared differentially expressed lincRNA between patients achieving complete response (CR) versus others and identified 16 lincRNAs with significantly different expression values (p value < 0.05). Using univariate cox regression model, 26 lincRNAs were identified as having significant correlation (cox p value < 0.05) with event-free survival (EFS). Three of these lincRNAs were also related with response prediction suggesting high level of functional and biological importance. We have developed a multivariate cox regression model utilizing these individually significant lincRNAs able to predict relapse free survival (Overall Wald test p value = 6.736e-07). Using a training set of 171 patients, we developed a cox regression multivariate survival model and created a risk score. The high and low risk based on lincRNA was validated using this model in 85 independent patients (log-rank p = 0.04). We are in the process of now integrating the gene expression data with lincRNA data to develop an integrated survival model. In summary, we report the first differential lincRNA expression in MM showing a significant role in disease biology as well as clinical outcome. lincRNAs are still functionally poorly characterized and our ongoing integrative approach will provide a link between lincRNAs and protein coding genes in MM. Disclosures Anderson: Celgene: Consultancy; Sanofi-Aventis: Consultancy; Onyx: Consultancy; Acetylon: Scientific Founder, Scientific Founder Other; Oncoprep: Scientific Founder Other; Gilead Sciences: Consultancy.

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Differentially Expressed and Prognostically Significant Lincrnas May Impact Immune System and Tumor Progression in Multiple Myeloma (MM)

Blood ◽

10.1182/blood.v126.23.2989.2989 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2989-2989 ◽

Cited By ~ 3

Author(s):

Mehmet K Samur ◽

Annamaria Gulla ◽

Alice Cleynen ◽

Florence Magrangeas ◽

Stephane Minvielle ◽

...

Keyword(s):

Immune System ◽

Board Of Directors ◽

Differentially Expressed ◽

Support Vector ◽

Strongly Correlated ◽

Advisory Committees ◽

Protein Coding ◽

Free Survival ◽

Protein Coding Genes ◽

Highly Correlated

Abstract Long intergenic non-coding RNA (lincRNA) are transcripts longer than 200 nucleotides which have a diverse sets of regulatory functions but do not get translated into protein. lincRNAs are located between the protein coding genes and do not overlap exons of either protein-coding or other non-lincRNA. However precise role of individual lincRNA in disease biology remains unclear. Here, we have evaluated the lincRNA expression and their potential biological functions in MM. We performed RNA-seq on CD138+ MM cells from 296 newly diagnosed patients and 16 normal bone marrow plasma cells (NBM) and analyzed for lincRNA expression. Data from paired-end RNAseq reads were mapped to the latest human genome, differentially expressed lincRNAs were identified and for each expressed lincRNA event free survival was examined with univariate cox regression model and support vector machine. Finally, we identified protein coding genes that are strongly correlated (cor > 0.5) with lincRNAs with significant altered expression in MM and impact on EFS to identify their biological role. lincRNA and protein coding genes that have more than 10 reads/million reads for at least 15 normal samples or 62 MM samples (20% all MM samples) were included in the analysis. We identified 60 differentially expressed lincRNA (adj p value <0.05), 51 of those had at least 1.5 fold change difference. The differentially expressed lncRNAs were in close proximity of Ig-related genes, genome stability related genes, hosting miRNAs such as mir222 and mir22 and previously reported for other cancers (PVT and TTY15). We evaluated relation of these lincRNAs with event free survival (EFS) and observed 6 lincRNAs associated with shorter EFS. We have developed multivariate signature model to predict EFS by using these 6 lincRNAs. We divided our dataset into training (n=99) and test (n=156) dataset and we utilized support vector machine classification to divide samples into 2 groups using six lincRNAs. This model was able to predict good and poor survival groups in training dataset (p val < 0.001) as well as test dataset (p val = 0.002) (Figure). We examined genome wide correlation between these six differentially expressed and prognostically significant lincRNAs to expressed protein coding genes to identify their biological functions in MM. Four of these lincRNAs strongly correlated with 47 to 504 genes (abs(cor) > 0.5), affecting immune system pathways and pathways in cancer including Jak-STAT signaling pathway. We also found that these lincRNAs are also highly correlated with tumor development genes such as TNFRSF1B,FGR,TP53BP2,TNF and T or B cells related genes PIK3CD, BCL6. In addition, two of these lincRNAs (LINC00936 and CTB-61M7.2) were found highly correlated with their protein coding neighbor genes ATP2B1(cor = 0.45) and FCAR (cor = 0.95) respectively and MIR22HG was host gene for mir22 which may indicate lincRNAs are using different machinery in MM to regulate protein coding genes. In summary, we report that lincRNA is differentially expressed and prognostically significant in myeloma and may function through their impact on immune system and tumor progression. Our ongoing integrative approach will provide further evidence of their regulatory role in MM with potential therapeutic application. Figure 1. Figure 1. Disclosures Anderson: acetylon pharmaceuticals: Equity Ownership; Celgene Corporation: Consultancy; Gilead: Consultancy; Oncocorp: Equity Ownership; Millennium: Consultancy; BMS: Consultancy. Munshi:onyx: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; novartis: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees.

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Comprehensive analysis of differential expression profiles via transcriptome sequencing in SH-SY5Y cells infected with CV-A16

PLoS ONE ◽

10.1371/journal.pone.0241174 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0241174

Author(s):

Yajie Hu ◽

Zhen Yang ◽

Shenglan Wang ◽

Danxiong Sun ◽

Mingmei Zhong ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Transcriptome Sequencing ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Transcriptome Profiling ◽

Differentially Expressed ◽

Control Group ◽

Protein Coding ◽

Qrt Pcr ◽

Protein Coding Genes

Coxsackievirus A16 (CV-A16) is one of the viruses that is most frequently associated with hand-foot-and-mouth disease (HFMD). Previous studies have shown that CV-A16 infections are mostly self-limiting, but in recent years, it has been gradually found that CV-A16 infections can also induce neurological complications and eventually cause death in children with HFMD. Moreover, no curative drugs or preventative vaccines have been developed for CV-A16 infection. Therefore, it is particularly important to investigate the mechanism of CV-A16 infection-induced neuropathy. In the current study, transcriptome sequencing technology was used to identify changes in the transcriptome of SH-SY5Y cells infected with CV-A16, which might hide the mechanism of CV-A16-induced neuropathology. The transcriptome profiling showed that 82,406,974, 108,652,260 and 97,753,565 clean reads were obtained in the Control, CV-A16-12 h and CV-A16-24 h groups, respectively. And it was further detected that a total of 136 and 161 differentially expressed genes in CV-A16-12 h and CV-A16-24 h groups, respectively, when compared with Control group. Then, to explore the mechanism of CV-A16 infection, we focused on the common differentially expressed genes at different time points of CV-A16 infection and found that there were 34 differentially expressed genes based on which clustering analysis and functional category enrichment analysis were performed. The results indicated that changes in oxidation levels were particularly evident in the GO term analysis, while only the “Gonadotropin-releasing hormone receptor pathway” was enriched in the KEGG pathway analysis, which might be closely related to the neurotoxicity caused by CV-A16 infection. Meanwhile, the ID2 closely related to nervous system has been demonstrated to be increased during CV-A16 infection. Additionally, the data on differentially expressed non-protein-coding genes of different types within the transcriptome sequencing results were analyzed, and it was speculated that these dysregulated non-protein-coding genes played a pivotal role in CV-A16 infection. Ultimately, qRT-PCR was utilized to validate the transcriptome sequencing findings, and the results of qRT-PCR were in agreement with the transcriptome sequencing data. In conclusion, transcriptome profiling was carried out to analyze response of SH-SY5Y cells to CV-A16 infection. And our findings provide important information to elucidate the possible molecular mechanisms which were linked to the neuropathogenesis of CV-A16 infection.

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Transcriptomic and Proteomic Profiling of Human Stable and Unstable Carotid Atherosclerotic Plaques

Frontiers in Genetics ◽

10.3389/fgene.2021.755507 ◽

2021 ◽

Vol 12 ◽

Author(s):

Mei-hua Bao ◽

Ruo-qi Zhang ◽

Xiao-shan Huang ◽

Ji Zhou ◽

Zhen Guo ◽

...

Keyword(s):

Cellular Response ◽

Target Gene ◽

Clinical Manifestations ◽

Differentially Expressed ◽

Atherosclerotic Plaques ◽

Proteomic Profiling ◽

Illumina Hiseq ◽

Protein Coding ◽

Protein Coding Genes ◽

The Stability

Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis-acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques.

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Transcriptome-wide map of m6A circRNAs identified in a rat model of hypoxia mediated pulmonary hypertension

10.21203/rs.2.15953/v4 ◽

2020 ◽

Author(s):

Hua Su ◽

Guowen Wang ◽

Lingfang Wu ◽

Xiuqing Ma ◽

Kejing Ying ◽

...

Keyword(s):

Pulmonary Hypertension ◽

Key Words ◽

Clinical Significance ◽

Rat Model ◽

Physiological Process ◽

Effective Therapy ◽

Differentially Expressed ◽

Protein Coding ◽

Protein Coding Genes

Abstract Background: Hypoxia mediated pulmonary hypertension (HPH) is a lethal disease and lacks effective therapy. CircRNAs play significant roles in physiological process. Recently, circRNAs are found to be m 6 A-modified. The abundance of circRNAs was influenced by m 6 A. Furthermore, the significance of m 6 A circRNAs has not been elucidated in HPH yet. Here we aim to investigate the transcriptome-wide map of m 6 A circRNAs in HPH. Results: Differentially expressed m 6 A abundance was detected in lungs of HPH rats. M 6 A abundance in circRNAs was significantly reduced in hypoxia in vitro . M 6 A circRNAs were mainly from protein-coding genes spanned single exons in control and HPH groups. Moreover, m 6 A influenced the circRNA–miRNA–mRNA co-expression network in hypoxia. M 6 A circXpo6 and m 6 A circTmtc3 were firstly identified to be downregulated in HPH. Conclusion: Our study firstly identified the transcriptome-wide map of m 6 A circRNAs in HPH. M 6 A can influence circRNA–miRNA–mRNA network. Furthermore, we firstly identified two HPH-associated m 6 A circRNAs: circXpo6 and circTmtc3. However, the clinical significance of m 6 A circRNAs for HPH should be further validated. Key words: m 6 A circRNAs; hypoxia mediated pulmonary hypertension; m 6 A circXpo6; m 6 A circTmtc3

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Genome-wide transcriptome study using deep RNA sequencing for myocardial infarction and coronary artery calcification

BMC Medical Genomics ◽

10.1186/s12920-020-00838-2 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Xiaoling Zhang ◽

◽

Jeroen G. J. van Rooij ◽

Yoshiyuki Wakabayashi ◽

Shih-Jen Hwang ◽

...

Keyword(s):

Myocardial Infarction ◽

Coronary Artery ◽

Rna Sequencing ◽

Coronary Artery Calcification ◽

Subclinical Atherosclerosis ◽

Density Lipoprotein ◽

Differentially Expressed ◽

Protein Coding ◽

Protein Coding Genes ◽

History Of

Abstract Background Coronary artery calcification (CAC) is a noninvasive measure of coronary atherosclerosis, the proximal pathophysiology underlying most cases of myocardial infarction (MI). We sought to identify expression signatures of early MI and subclinical atherosclerosis in the Framingham Heart Study (FHS). In this study, we conducted paired-end RNA sequencing on whole blood collected from 198 FHS participants (55 with a history of early MI, 72 with high CAC without prior MI, and 71 controls free of elevated CAC levels or history of MI). We applied DESeq2 to identify coding-genes and long intergenic noncoding RNAs (lincRNAs) differentially expressed in MI and high CAC, respectively, compared with the control. Results On average, 150 million paired-end reads were obtained for each sample. At the false discovery rate (FDR) < 0.1, we found 68 coding genes and 2 lincRNAs that were differentially expressed in early MI versus controls. Among them, 60 coding genes were detectable and thus tested in an independent RNA-Seq data of 807 individuals from the Rotterdam Study, and 8 genes were supported by p value and direction of the effect. Immune response, lipid metabolic process, and interferon regulatory factor were enriched in these 68 genes. By contrast, only 3 coding genes and 1 lincRNA were differentially expressed in high CAC versus controls. APOD, encoding a component of high-density lipoprotein, was significantly downregulated in both early MI (FDR = 0.007) and high CAC (FDR = 0.01) compared with controls. Conclusions We identified transcriptomic signatures of early MI that include differentially expressed protein-coding genes and lincRNAs, suggesting important roles for protein-coding genes and lincRNAs in the pathogenesis of MI.

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