Academic literature on the topic 'Long intergenic non-coding RNAs (lincRNAs)'

Abstract Long intergenic non-coding RNAs (lincRNAs) are endogenous RNAs with a transcript length of more than 200nt that lack a long open reading frame. The functional impact of lincRNAs is not well known yet but lincRNAs have been associated with chromatin remodelling, histone modification and DNA methylation, and have been found to impact tumorigenesis. The expression levels of lincRNAs are often significantly altered in various malignancies and can be used as diagnostic markers and potential drug targets. Recent studies have shown that lincRNAs also contribute to the initiation and development of acute myeloid leukemia (AML)(Mer et al. 2018). Today, AML is defined by morphological, genetic, and clinical features but the underlying molecular mechanisms are still not completely understood. Hence, we analysed the transcriptome of 190 AML patients with different cytogenetic aberrations (normal karyotype, n = 50; PML-RARA, n= 49; RUNX1-RUNX1T1, n = 45; CBFB-MYH11, n = 46) to identify and quantify lincRNAs to further expand the knowledge of the contribution of different regulatory levels to the pathogenesis in AML. Total RNA was used for 150bp paired-end RNA sequencing (RNA-Seq) with a median read depth of 50 million. UClncR pipeline (Sun et al. 2017) with a gamma model for stranded RNA-Seq was used for the identification and quantification of novel and known lincRNA. The pipeline automatically performs the novel transcript assembly, predicts lncRNA candidates by filtering based on length, expression, repetitive regions, and coding potential, and quantifies both, known and novel lincRNAs. The resulting count matrix was filtered and only lincRNAs with a minimal count of 5 in at least 66% of the samples were kept. Subsequently, we performed a combined normalization and differential expression (DE) analysis of the lincRNA counts by integration of trimmed mean of M-values normalization factors into the statistical model used to test for DE. lincRNAs with an FDR < 0.05 and an absolute logFC > 1.5 were considered DE. 354 unique lincRNAs were identified to be DE between the different AML subtypes. Among those lincRNAs we found MEG3 to be specifically up-regulated in AML with PML-RARA fusion (p < 0.001), whereas the lincRNA was comparably lower expressed in all the other subtypes (Figure 1). MEG3 is a known tumor suppressor that is usually found to be down-regulated in AML. Recent studies indicated that MEG3 expression is regulated by miRNA-22. miRNA-22 is located on the short arm of chromosome 17 and carries a predicted PML-RARA binding site in its promoter region. Binding of the PML-RARA fusion protein to the miRNA-22 promoter might result in its up-regulation which subsequently modulates MEG3 expression levels. Hence, MEG3 might contribute to the pathogenesis in AML with PML-RARA fusion and can be used as a molecular marker. The lincRNA CRNDE showed an expression profile similar to MEG3 in our cohort. CRNDE has already been linked with the PML-RARA fusion in acute promyelocytic leukemia. In addition we found a significantly higher expression of CASC15 in AML RUNX1-RUNX1T1 compared to the other subtypes (p < 0.01). It has been recently reported that CASC15 regulates SOX4 expression in RUNX1-rearranged acute leukemia. As expected we found a high expression of SOX4 in AML RUNX1-RUNX1T1. Using the identified 354 DE lincRNAs a neural network was built to classify the various AML subtypes. The dataset was randomly split into training (90%) and test (10%) data which was used to train the neural network. The procedure was repeated 1000 times to ensure that every sample was seen by the classifier multiple times. The neural network was composed of 424 units, 2 hidden layers with 50 and 20 units, respectively, and the Rectified Linear Unit activation function. The trained neural network with 10-fold cross-validation was able to unambiguously classify the four AML subtypes with an accuracy of 98%. Conclusions: 1) We demonstrated that lincRNAs can be used to reliably classify AML subgroups and the identified subgroup-specific lincRNAs might play a role in therapeutic strategies for these pts. 2) MEG3 can be used as a new molecular marker for AML with PML-RARA fusion. 3) LincRNAs are an additional regulatory level that can further improve diagnosis but might also be taken into account for treatment decisions. Disclosures Walter: MLL Munich Leukemia Laboratory: Employment. Hernández:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment.

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.

Long non-coding RNAs (lncRNAs) are transcribed RNA molecules >200 nucleotides in length that do not encode proteins and serve as key regulators of diverse biological processes. Recently, thousands of long intergenic non-coding RNAs (lincRNAs), a type of lncRNAs, have been identified in mammalians using massive parallel large sequencing technologies. The availability of the genome sequence of sheep (Ovis aries) has allowed us genomic prediction of non-coding RNAs. This is the first study to identify lincRNAs using RNA-seq data of eight different tissues of sheep, including brain, heart, kidney, liver, lung, ovary, skin, and white adipose. A computational pipeline was employed to characterize 325 putative lincRNAs with high confidence from eight important tissues of sheep using different criteria such as GC content, exon number, gene length, co-expression analysis, stability, and tissue-specific scores. Sixty-four putative lincRNAs displayed tissues-specific expression. The highest number of tissues-specific lincRNAs was found in skin and brain. All novel lincRNAs that aligned to the human and mouse lincRNAs had conserved synteny. These closest protein-coding genes were enriched in 11 significant GO terms such as limb development, appendage development, striated muscle tissue development, and multicellular organismal development. The findings reported here have important implications for the study of sheep genome.

Abstract Background The aetiology of Crohn’s disease [CD] involves immune dysregulation in a genetically susceptible individual. Genome-wide association studies [GWAS] have identified 200 loci associated with CD, ulcerative colitis, or both, most of which fall within non-coding DNA regions. Long non-coding RNAs [lncRNAs] regulate gene expression by diverse mechanisms and have been associated with disease activity in inflammatory bowel disease. However, disease-associated lncRNAs have not been characterised in pathogenic immune cell populations. Methods Terminal ileal samples were obtained from 22 CD patients and 13 controls. RNA from lamina propria CD4+ T cells was sequenced and long intergenic non-coding RNAs [lincRNAs] were detected. Overall expression patterns, differential expression [DE], and pathway and gene enrichment analyses were performed. Knockdown of novel lincRNAs XLOC_000261 and XLOC_000014 was performed. Expression of Th1 or Th17-associated transcription factors, T-bet and RORγt, respectively, was assessed by flow cytometry. Results A total of 6402 lincRNAs were expressed, 960 of which were novel. Unsupervised clustering and principal component analysis showed that the lincRNA expression discriminated patients from controls. A total of 1792 lincRNAs were DE, and 295 [79 novel; 216 known] mapped to 267 of 5727 DE protein-coding genes. The novel lincRNAs were enriched in inflammatory and Notch signalling pathways [p &lt;0.05]. Furthermore, DE lincRNAs in CD patients were more frequently found in DNA regions with known inflammatory bowel disease [IBD]-associated loci. The novel lincRNA XLOC_000261 negatively regulated RORγt expression in Th17 cells. Conclusions We describe a novel set of DE lincRNAs in CD-associated CD4+ cells and demonstrate that novel lincRNA XLOC_000261 appears to negatively regulate RORγt protein expression in Th17 cells.

Abstract microRNAs (miRNAs) and long intergenic noncoding RNAs (lincRNAs) have been reported as important markers for many cancers. In search of new markers for the metastatic or aggressive phenotypes in the neuroendocrine tumor pheochromocytomas and paragangliomas (PCPG), we analyzed the non-coding transcriptome from patient gene expression data in The Cancer Genome Atlas. We used differential expression analysis and an elastic-net machine-learning model to identify miRNA and lincRNA transcriptomic signature specific to PCPG molecular subtypes. Similarly, miRNAs and lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis were performed for identifying factors associated with metastasis-free survival. Upregulation of 13 lincRNAs and 4 miRNAs was found to be associated with aggressive/metastatic PCPGs. RT-PCR validation in tumor samples from PCPG patients confirmed the overexpression of 4 miRNAs and 4 lincRNAs in metastatic compared to non-metastatic PCPGs. Kaplan-Meier analysis identified 3 miRNAs and 5 lincRNAs as prognostic markers for metastasis-free survival of patients in PCPGs. In a multivariate Cox regression analysis combining these miRNA and lincRNA expression signatures with the previously identified clinically relevant parameters like SDHB germline mutation, ATRX somatic mutation, tumor location and hormone secretion phenotypes, we identified the miRNA miR-182 and lincRNA HIF1A-AS2 as independent predictors of poor metastasis-free survival. We formulated a risk-score model using multivariate analysis of lincRNA and miRNA expression profiles, presence of SDHB and ATRX mutations, tumor location, and hormone secretion phenotypes. Stratification of PCPG patients with this risk-score showed significant differences in metastasis-free survival.

Head and neck squamous cell carcinoma is one of the most common and fatal cancers worldwide. Even a multimodal approach consisting of standard chemo- and radiotherapy along with surgical resection is only effective in approximately 50% of the cases. The rest of the patients develop a relapse of the disease and acquire resistance to treatment. Especially this group of individuals needs novel, personalized, targeted therapy. The first step to discovering such solutions is to investigate the tumor microenvironment, thus understanding the role and mechanism of the function of coding and non-coding sequences of the human genome. In recent years, RNA molecules gained great interest when the complex character of their impact on our biology allowed them to come out of the shadows of the “junk DNA” label. Furthermore, long non-coding RNAs (lncRNA), specifically the intergenic subgroup (lincRNA), are one of the most aberrantly expressed in several malignancies, which makes them particularly promising future diagnostic biomarkers and therapeutic targets. This review contains characteristics of known and validated lincRNAs in HNSCC, such as XIST, MALAT, HOTAIR, HOTTIP, lincRNA-p21, LINC02487, LINC02195, LINC00668, LINC00519, LINC00511, LINC00460, LINC00312, and LINC00052, with a description of their prognostic abilities. Even though much work remains to be done, lincRNAs are important factors in cancer biology that will become valuable biomarkers of tumor stage, outcome prognosis, and contribution to personalized medicine.

Long intergenic non-coding RNAs (lincRNAs) regulate testicular development by acting on protein-coding genes. However, little is known about whether lincRNAs and protein-coding genes exhibit the same expression pattern in the same phase of postnatal testicular development in goats. Therefore, this study aimed to demonstrate the expression patterns and roles of lincRNAs during the postnatal development of the goat testis. Herein, the testes of Yiling goats with average ages of 0, 30, 60, 90, 120, 150, and 180 days postnatal (DP) were used for RNA-seq. In total, 20,269 lincRNAs were identified, including 16,931 novel lincRNAs. We identified seven time-specifically diverse lincRNA modules and six mRNA modules by weighted gene co-expression network analysis (WGCNA). Interestingly, the down-regulation of growth-related lincRNAs was nearly one month earlier than the up-regulation of spermatogenesis-related lincRNAs, while the down-regulation of growth-related protein-coding genes and the correspondent up-regulation of spermatogenesis-related protein-coding genes occurred at the same age. Then, potential lincRNA target genes were predicted. Moreover, the co-expression network of lincRNAs demonstrated that ENSCHIT00000000777, ENSCHIT00000002069, and ENSCHIT00000005076 were the key lincRNAs in the process of testis development. Our study discovered the divergent regulation patterns of lincRNA on spermatogenesis and testis growth, providing a fresh insight into age-biased changes in lincRNA expression in the goat testis.

Background Long non-coding RNAs (lncRNAs), a class of regulatory RNAs, play a major role in various cellular processes. Long intergenic non-coding RNAs (lincRNAs), a subclass of lncRNAs, are involved in the trans- and cis-regulation of gene expression. In the case of cis-regulation, by recruiting chromatin-modifying complexes, lincRNAs influence adjacent gene expression. Methods We used quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) to evaluate the coexpression of LOC100287225, a lincRNA, and DCC, one of its adjacent genes that is often decreased in colorectal cancer, in pairs of tumor and adjacent tumor-free tissues of 30 colorectal cancer patients. Results The qRT-PCR results revealed the misregulation of these genes during tumorigenesis. Their relative expression levels were significantly lower in tumor tissues than adjacent tumor-free tissues. However, the analysis found no significant correlation between reduced expression of these genes. Conclusions Our study demonstrated the concurrent misregulation of DCC and LOC100287225 in colorectal cancer.

Long intergenic non-coding RNAs (lincRNAs) have been demonstrated to be vital regulators of diverse biological processes in both animals and plants. While many lincRNAs have been identified in cotton, we still know little about the repositories and conservativeness of lincRNAs in different cotton species or about their role in responding to biotic stresses. Here, by using publicly available RNA-seq datasets from diverse sources, including experiments of Verticillium dahliae (Vd) infection, we identified 24,425 and 17,713 lincRNAs, respectively, in Gossypium hirsutum (Ghr) and G. barbadense (Gba), the two cultivated allotetraploid cotton species, and 6933 and 5911 lincRNAs, respectively, in G. arboreum (Gar) and G. raimondii (Gra), the two extant diploid progenitors of the allotetraploid cotton. While closely related subgenomes, such as Ghr_At and Gba_At, tend to have more conserved lincRNAs, most lincRNAs are species-specific. The majority of the synthetic and transcribed lincRNAs (78.2%) have a one-to-one orthologous relationship between different (sub)genomes, although a few of them (0.7%) are retained in all (sub)genomes of the four species. The Vd responsiveness of lincRNAs seems to be positively associated with their conservation level. The major functionalities of the Vd-responsive lincRNAs seem to be largely conserved amongst Gra, Ghr, and Gba. Many Vd-responsive Ghr-lincRNAs overlap with Vd-responsive QTL, and several lincRNAs were predicted to be endogenous target mimicries of miR482/2118, with a pair being highly conserved between Ghr and Gba. On top of the confirmation of the feature characteristics of the lincRNAs previously reported in cotton and other species, our study provided new insights into the conservativeness and divergence of lincRNAs during cotton evolution and into the relationship between the conservativeness and Vd responsiveness of lincRNAs. The study also identified candidate lincRNAs with a potential role in disease response for functional characterization.

Homologous long non-coding RNAs (lncRNAs) are elusive to identify by sequence similarity due to their fast-evolutionary rate. Here we develop LincOFinder, a pipeline that finds conserved intergenic lncRNAs (lincRNAs) between distant related species by means of microsynteny analyses. Using this tool, we have identified 16 bona fide homologous lincRNAs between the amphioxus and human genomes. We characterized and compared in amphioxus and Xenopus the expression domain of one of them, Hotairm1, located in the anterior part of the Hox cluster. In addition, we analyzed the function of this lincRNA in Xenopus, showing that its disruption produces a severe headless phenotype, most probably by interfering with the regulation of the Hox cluster. Our results strongly suggest that this lincRNA has probably been regulating the Hox cluster since the early origin of chordates. Our work pioneers the use of syntenic searches to identify non-coding genes over long evolutionary distances and helps to further understand lncRNA evolution.

Long intergenic non-coding RNAs (lincRNAs) are an abundant and functionally diverse class of eukaryotic transcripts. Reported lincRNA repertoires in mammals vary, but are commonly in the thousands to tens of thousands of transcripts, covering similar to 90% of the genome. In addition to elucidating function, there is particular interest in understanding the origin and evolution of lincRNAs. Aside from mammals, lincRNA populations have been sparsely sampled, precluding evolutionary analyses focused on their emergence and persistence. Here we present Evolinc, a two-module pipeline designed to facilitate lincRNA discovery and characterize aspects of lincRNA evolution. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analysis workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species. Here we validate lincRNA catalogs generated with Evolinc-I against previously annotated Arabidopsis and human lincRNA data. Evolinc-I recapitulated earlier findings and uncovered an additional 70 Arabidopsis and 43 human lincRNAs. We demonstrate the usefulness of Evolinc-II by examining the evolutionary histories of a public dataset of 5,361 Arabidopsis lincRNAs. We used Evolinc-II to winnow this dataset to 40 lincRNAs conserved across species in Brassicaceae. Finally, we show how Evolinc-II can be used to recover the evolutionary history of a known lincRNA, the human telomerase RNA (TERC). These latter analyses revealed unexpected duplication events as well as the loss and subsequent acquisition of a novel TERC locus in the lineage leading to mice and rats. The Evolinc pipeline is currently integrated in CyVerse's Discovery Environment and is free for use by researchers.

Coronary artery disease (CAD) is the most common type of cardiovascular disease and is one of the leading causes of morbidity and mortality globally. However, the pathogenesis of atherosclerosis which leads to CAD and results in heart attacks, heart failure and death is not well understood. In this context, studies have demonstrated a positive correlation between increased hepatic free fatty acids (FFAs) in atherosclerosis and CAD. Although CAD has welldefined environmental risk factors, genome-wide association studies (GWAS) have demonstrated a genetic influence on CAD. Previous studies have shown that genetic variation within the human Y chromosome is associated with an increased risk of developing CAD independent of traditional cardiovascular risk factors; possibly through a modulating effect of an adaptive immunity and inflammatory response by macrophages in men. However, no Y chromosome-linked gene has been investigated in this disease so far. Long non-coding RNAs (lncRNAs) have recently gained focused attention as a new class of regulatory RNA molecules involved in cardiovascular function and associated disease, particularly long intergenic noncoding RNAs (lincRNAs), the largest class within the lncRNA group so far. To date, Y chromosome-linked lincRNAs are poorly characterised and the potential link between these non-coding RNA molecules and CAD in men has not been investigated. In this context, I hypothesised that Y chromosome-linked lncRNAs may regulate pathways involved in lipid metabolism and trigger an over accumulation of FFAs in coronary arteries contributing to atherosclerosis, the underlying cause of CAD. The main objective of this thesis was to therefore further investigate the relationship between the Y chromosome, lncRNAs and CAD in light of the deficiencies within the literature to better understand the causative molecular mechanisms of CAD pathophysiology in men. In my first study (Chapter 2), I identified for the first time through gene expression analysis (real-time PCR) the expression of the following (unannotated in PubMed) Y chromosomelinked lincRNA transcripts: lnc-KDM5D-4:1, lnc-ZFY-1:1, lnc-ZFY-1:3, lnc-ZFY-2:1, lnc- RBMY1B-1:1, lnc-RBMY1B-1:4, lnc-RBMY1J-1:1, lnc-RBMY1J-1:2, and lnc-RBMY1J- 1:3, across 21 different normal, human tissues such as adipose, bladder, brain, cervix, colon, esophagus, heart, kidney, liver, lung, ovary, placenta, prostate, skeletal muscle, small intestine, spleen, testes, thymus, thyroid, trachea, and white blood cells (WBCs) (leukocytes). I found that Y-linked lincRNAs were expressed at low levels (with the lowest CT number equal at 24.5) with a high tissue-specificity for some. Also, the Y-linked RNA gene lnc-KDM5D-4 was widely expressed across male tissues while the Y-linked RNA gene lnc-RBMY1J-1 was specific to the testes. Furthermore, this study presents the first evidence through gene expression analysis that the Y chromosome-linked lincRNA transcripts, lnc-KDM5D-4:1, lnc- ZFY-1:1, lnc-ZFY-1:3, lnc-ZFY-2:1, lnc-RBMY1B-1:1, lnc-RBMY1B-1:4, and lnc- RBMY1J-1:3 are expressed in male leukocytes. Hence, these lincRNAs could be potential non-protein coding gene candidates for CAD research. Knowing that the Y chromosome contributes to lipid levels in humans, to further explore the potential function of these Y-linked lincRNAs in CAD in men, I then studied their expression in a fatty liver context (steatosis-associated atherosclerosis) (Chapter 3). This was performed using the human hepatocellular liver carcinoma cell line, HepG2; the human model of liver cells in CAD research. This study showed for the first time that the Y-linked lincRNA transcripts lnc-KDM5D-4:1, lnc-ZFY-1:1, lnc-ZFY-2:1, lnc-RBMY1B-1:1, and lncxix RBMY1B-1:4 were expressed in HepG2 cells, hence in hepatocellular carcinoma (HCC). Furthermore, this study demonstrated that lnc-KDM5D-4 is a nuclear-retained lincRNA using RNA fluorescence in situ hybridisation (RNA FISH), and is upregulated in palmitate-induced steatosis within hepatocytes (Fold Change = 2.16; p-value = 0.00216). The human Atherosclerosis RT2 Profiler™ PCR Array determined that the silencing of lnc-KDM5D-4 in HepG2 cells was triggering the upregulation of the inhibitor of apoptosis (IAP) gene baculoviral IAP repeat containing 3 (BIRC3) (Fold Change = 12.45, p-value = 0.000025), a well-described protein-coding gene expressed by vascular smooth muscle cells and macrophage foam cells of the inflamed vascular wall of atherosclerotic arteries. Furthermore, perilipin 2 (PLIN2), a gene known to be implicated in lipid metabolism, was also found upregulated. Therefore, this study provides the first evidence for the involvement of a Ychromosome- linked lincRNA, lnc-KDM5D-4, in steatosis-associated atherosclerosis and its retained-nuclear cellular localisation in human hepatocytes, suggesting a function which takes place in the cell nucleus and may play a role in regulating metabolic processes in the liver that are implicated in atherosclerosis. Having shown that a Y chromosome-linked lincRNA could be involved in the determination of lipid level and hence atherosclerosis in men, and to further explore the role of lnc-KDM5D- 4, the expression of this Y-linked lincRNA was studied in human coronary artery smooth muscle cells, especially in atherosclerotic coronary artery cells (Chapter 4). The expression of other non-coding RNAs were also studied such as the protein kinase, Y-linked, pseudogene (PRKY) - previously considered as a new functional candidate for the development of CAD. By analysing the transcriptome of human atherosclerotic and non-atherosclerotic coronary artery smooth muscle cells, I established evidence for the implication of the human Y chromosome in atherosclerosis and CAD. This study exposed the general underexpression of the transcripts from the Y chromosome in atherosclerotic cells implicating a loss or a repression of this chromosome in relation to CAD. Furthermore, this research determined by RNA sequencing a significant downregulation of seven transcripts from Y chromosome genes, including RPS4Y1, USP9Y, DDX3Y, TXLNGY, NLGN4Y and PRKY. RNA FISH determined the subcellular localisation of PRKY in smooth muscle cells by showing a nuclear and a cytoplasmic expression. Furthermore, qPCR gene expression analysis demonstrated that lnc- KDM5D-4 is significantly downregulated in atherosclerotic cells in comparison to the nonatherosclerotic cells. Together, these results showed that lnc-KDM5D-4 is a potential regulator of PLIN2 and BIRC3 genes. Therefore, the downregulation of lnc-KDM5D-4 in atherosclerotic coronary artery smooth muscle cells suggests that this downregulation could be linked to the inflammation of the vascular smooth muscle cells in pathophysiology of CAD via the inhibition of apoptosis of the vascular smooth muscle cells triggered by the upregulation of BIRC3 in these cells. Overall, this study is the first to emphasise a potential involvement of a Y-specific lincRNA, called lnc-KDM5D-4, as a potential contributor to physiology in males. Lnc-KDM5D-4 knockdown resulted in an upregulation of anti-apoptosis and lipid metabolism-related genes. Collectively, our data suggest that the male–specific lnc-KDM5D-4 may regulate key processes in cellular inflammation that trigger atherosclerosis and CAD in men. Accordingly, this data suggests that lnc-KDM5D-4 may provide a novel molecular biomarker for atherosclerotic arteries, and could potentially lead to revolutionary treatment modalities on Y-linked lincRNA as therapeutic agents to manipulate CAD-causing genes in men.
Doctor of Philosophy

Genomweite Bemühungen haben eine große Anzahl langer nichtkodierender RNAs (lncRNAs) identifiziert, obwohl ihre möglichen Funktionen weitgehend rätselhaft bleiben. Hier verwendeten wir ein System zur synchronisierten Blüteninduktion in Arabidopsis, um 4106 blütenbezogene lange intergene RNAs (lincRNAs) zu identifizieren. Blütenbezogene lincRNAs sind typischerweise mit funktionellen Enhancern assoziiert, die bidirektional transkribiert werden und mit verschiedenen funktionellen Genmodulen assoziiert sind, die mit der Entwicklung von Blütenorganen zusammenhängen, die durch Koexpressionsnetzwerkanalyse aufgedeckt wurden. Die Master-regulatorischen Transkriptionsfaktoren (TFs) APETALA1 (AP1) und SEPALLATA3 (SEP3) binden an lincRNA-assoziierte Enhancer. Die Bindung dieser TFs korreliert mit der Zunahme der lincRNA-Transkription und fördert möglicherweise die Zugänglichkeit von Chromatin an Enhancern, gefolgt von der Aktivierung einer Untergruppe von Zielgenen. Darüber hinaus ist die Evolutionsdynamik von lincRNAs in Pflanzen, einschließlich nicht blühender Pflanzen, noch nicht bekannt, und das Expressionsmuster in verschiedenen Pflanzenarten war ziemlich unbekannt. Hier identifizierten wir Tausende von lincRNAs in 26 Pflanzenarten, einschließlich nicht blühender Pflanzen. Ein direkter Vergleich von lincRNAs zeigt, dass die meisten lincRNAs speziesspezifisch sind und das Expressionsmuster von lincRNAs einen hohen Transkriptionsumsatz nahe legt. Darüber hinaus zeigen konservierte lincRNAs eine aktive Regulation durch Transkriptionsfaktoren wie AP1 und SEP3. Konservierte lincRNAs zeigen eine konservierte blütenbezogene Funktionalität sowohl in der Brassicaceae- als auch in der Grasfamilie. Die Evolutionslandschaft von lincRNAs in Pflanzen liefert wichtige Einblicke in die Erhaltung und Funktionalität von lincRNAs.
Genome-wide efforts have identified a large number of long non-coding RNAs (lncRNAs), although their potential functions remain largely enigmatic. Here, we used a system for synchronized floral induction in Arabidopsis to identify 4106 flower-related long intergenic RNAs (lincRNAs). Flower-related lincRNAs are typically associated with functional enhancers which are bi-directionally transcribed and are associated with diverse functional gene modules related to floral organ development revealed by co-expression network analysis. The master regulatory transcription factors (TFs) APETALA1 (AP1) and SEPALLATA3 (SEP3) bind to lincRNA-associated enhancers. The binding of these TFs is correlated with the increase in lincRNA transcription and potentially promotes chromatin accessibility at enhancers, followed by activation of a subset of target genes. Furthermore, the evolutionary dynamics of lincRNAs in plants including non-flowering plants still remain to be elusive and the expression pattern in different plant species was quite unknown. Here, we identified thousands of lincRNAs in 26 plant species including non-flowering plants, and allow us to infer sequence conserved and synteny based homolog lincRNAs, and explore conserved characteristics of lincRNAs during plants evolution. Direct comparison of lincRNAs reveals most lincRNAs are species-specific and the expression pattern of lincRNAs suggests their high evolutionary gain and loss. Moreover, conserved lincRNAs show active regulation by transcriptional factors such as AP1 and SEP3. Conserved lincRNAs demonstrate conserved flower related functionality in both the Brassicaceae and grass family. The evolutionary landscape of lincRNAs in plants provide important insights into the conservation and functionality of lincRNAs.

Most of the genome is transcribed into non-coding transcripts that far exceed in number the transcripts of protein-coding genes. These RNAs are subdivided into different classes. Long non-coding RNAs (lncRNAs) are at least 200 nucleotides in length and are transcribed from promoter, coding, intergenic or enhancer regions (eRNAs). These RNAs repress or enhance the transcription of target genes by facilitating the interaction between promoters and enhancers or by interacting with transcription factors and targeting histone-modifying enzymes. Short non-coding RNAs include a diverse group of functional types: miRNAs (micro RNAs) and siRNAs (small interfering RNAs) are negative regulators of gene expression; piRNAs (Piwi-interacting RNAs) suppress the action of transposable elements in the germline; snRNAs (small nuclear RNAs) are involved in mRNA splicing and rRNA maturation; tRNA-derived non-coding RNAs are involved in the cellular reaction to stress and in the repression of gene function. Additional short RNAs are rasiRNAs (repeat-associated small interfering RNAs) that appear to be involved in centromeric heterochromatin formation.