A Global Clustering Algorithm to Identify Long Intergenic Non-Coding RNA - with Applications in Mouse Macrophages

Identification of diffuse signals from the chromatin immunoprecipitation and high-throughput massively parallel sequencing (ChIP-Seq) technology poses significant computational challenges, and there are few methods currently available. We present a novel global clustering approach to enrich diffuse CHIP-Seq signals of RNA polymerase II and histone 3 lysine 4 trimethylation (H3K4Me3) and apply it to identify putative long intergenic non-coding RNAs (lincRNAs) in macrophage cells. Our global clustering method compares favorably to the local clustering method SICER that was also designed to identify diffuse CHIP-Seq signals. The validity of the algorithm is confirmed at several levels. First, 8 out of a total of 11 selected putative lincRNA regions in primary macrophages respond to lipopolysaccharides (LPS) treatment as predicted by our computational method. Second, the genes nearest to lincRNAs are enriched with biological functions related to metabolic processes under resting conditions but with developmental and immune-related functions under LPS treatment. Third, the putative lincRNAs have conserved promoters, modestly conserved exons, and expected secondary structures by prediction. Last, they are enriched with motifs of transcription factors such as PU.1 and AP.1, previously shown to be important lineage determining factors in macrophages, and 83% of them overlap with distal enhancers markers. In summary, GCLS based on RNA polymerase II and H3K4Me3 CHIP-Seq method can effectively detect putative lincRNAs that exhibit expected characteristics, as exemplified by macrophages in the study

Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome

Additional file 3. This file contains all supplementary tables relating to lncRNA identification via the conservation of synteny. Table S3. lncRNAs inferred in one species by the genomic alignment of a transcript assembled with the RNA-seq libraries from a related spdecies. Table S12. Presence of intergenic lncRNAs both in sheep and cattle, in regions of conserved synteny. Table S13. Presence of intergenic lncRNAs both in sheep and goat, in regions of conserved synteny. Table S14. Presence of intergenic lncRNAs both in cattle and goat, in regions of conserved synteny. Table S15. Presence of intergenic lncRNAs both in sheep and humans, in regions of conserved synteny. Table S16. Presence of intergenic lncRNAs both in goat and humans, in regions of conserved synteny. Table S17. Presence of intergenic lncRNAs both in cattle and humans, in regions of conserved synteny. Table S18. High-confidence lncRNA pairs, those conserved across species both sequentially and positionally

A Large Fraction of Extragenic RNA Pol II Transcription Sites Overlap Enhancers

A substantial fraction of extragenic Pol II transcription sites coincides with transcriptional enhancers, which may be relevant for functional annotation of mammalian genomes

Bioinformatics Tools and Novel Challenges in Long Non-Coding RNAs (lncRNAs) Functional Analysis

The advent of next generation sequencing revealed that a fraction of transcribed RNAs (short and long RNAs) is non-coding. Long non-coding RNAs (lncRNAs) have a crucial role in regulating gene expression and in epigenetics (chromatin and histones remodeling). LncRNAs may have different roles: gene activators (signaling), repressors (decoy), cis and trans gene expression regulators (guides) and chromatin modificators (scaffolds) without the need to be mutually exclusive. LncRNAs are also implicated in a number of diseases. The huge amount of inhomogeneous data produced so far poses several bioinformatics challenges spanning from the simple annotation to the more complex functional annotation. In this review, we report and discuss several bioinformatics resources freely available and dealing with the study of lncRNAs. To our knowledge, this is the first review summarizing all the available bioinformatics resources on lncRNAs appeared in the literature after the completion of the human genome project. Therefore, the aim of this review is to provide a little guide for biologists and bioinformaticians looking for dedicated resources, public repositories and other tools for lncRNAs functional analysis

Genetic factors regulating lung vasculature and immune cell functions associate with resistance to pneumococcal infection

Streptococcus pneumoniae is an important human pathogen responsible for high mortality and morbidity worldwide. The susceptibility to pneumococcal infections is controlled by as yet unknown genetic factors. To elucidate these factors could help to develop new medical treatments and tools to identify those most at risk. In recent years genome wide association studies (GWAS) in mice and humans have proved successful in identification of causal genes involved in many complex diseases for example diabetes, systemic lupus or cholesterol metabolism. In this study a GWAS approach was used to map genetic loci associated with susceptibility to pneumococcal infection in 26 inbred mouse strains. As a result four candidate QTLs were identified on chromosomes 7, 13, 18 and 19. Interestingly, the QTL on chromosome 7 was located within S. pneumoniae resistance QTL (Spir1) identified previously in a linkage study of BALB/cOlaHsd and CBA/CaOlaHsd F2 intercrosses. We showed that only a limited number of genes encoded within the QTLs carried phenotype-associated polymorphisms (22 genes out of several hundred located within the QTLs). These candidate genes are known to regulate TGFb signalling, smooth muscle and immune cells functions. Interestingly, our pulmonary histopathology and gene expression data demonstrated, lung vasculature plays an important role in resistance to pneumococcal infection. Therefore we concluded that the cumulative effect of these candidate genes on vasculature and immune cells functions as contributory factors in the observed differences in susceptibility to pneumococcal infection. We also propose that TGFbmediated regulation of fibroblast differentiation plays an important role in development of invasive pneumococcal disease.This work was supported by the European Union-funded Pneumopath Project HEALTH-F3-2009-222983. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer-reviewedPublisher Versio

LncRNAs as Regulators of Atherosclerotic Plaque Stability

Current clinical data show that, despite constant efforts to develop novel therapies and clinical approaches, atherosclerotic cardiovascular diseases (ASCVD) are still one of the leading causes of death worldwide. Advanced and unstable atherosclerotic plaques most often trigger acute coronary events that can lead to fatal outcomes. However, despite the fact that different plaque phenotypes may require different treatments, current approaches to prognosis, diagnosis, and classification of acute coronary syndrome do not consider the diversity of plaque phenotypes. Long non-coding RNAs (lncRNAs) represent an important class of molecules that are implicated in epigenetic control of numerous cellular processes. Here we review the latest knowledge about lncRNAs’ influence on plaque development and stability through regulation of immune response, lipid metabolism, extracellular matrix remodelling, endothelial cell function, and vascular smooth muscle function, with special emphasis on pro-atherogenic and anti-atherogenic lncRNA functions. In addition, we present current challenges in the research of lncRNAs’ role in atherosclerosis and translation of the findings from animal models to humans. Finally, we present the directions for future lncRNA-oriented research, which may ultimately result in patient-oriented therapeutic strategies for ASCVD

Non-coding RNAs in ovine immunity: Identification of unannotated genes and functional analyses of high throughput genomic data

210 p.Non-coding RNAs (ncRNAs) are involved in several biological processes in mammals, including the immune system response to pathogens and vaccines. The annotation and functional characterization of two of the main classes of ncRNAs, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), is more advanced in humans than in livestock species, and thus, there is limited knowledge about the function of these transcripts. The main objective of this work was the identification of ovine non-coding genes, concretely miRNA and lncRNA genes, that are involved in the innate and adaptive immune responses induced by vaccines, vaccine components and pathogen infections. For this purpose, high-throughput transcriptome sequencing datasets produced for this purpose and datasets publicly available were analysed with bioinformatic tools and workflows in order to identify unannotated non-coding genes, profile their expression in different tissues and perform evolutionary conservation analyses. More than 12000 unannotated ovine lncRNAs and 1000 ovine miRNAs were identified in the different analyses, with varying levels of sequence conservation. Differential expression analyses between unstimulated samples and samples stimulated with pathogen infection or vaccination resulted in hundreds of lncRNAs and miRNAs with changed expression. Gene co-expression analyses revealed immune gene-enriched clusters associated with immune system activation. These genes make up a prioritized set of potential candidates for deeper experimental analyses. Taken together, these results should help completing the sheep non-coding gene catalogue, and most importantly, they give evidence of immune state-specific ncRNA expression patterns in a livestock species

Multi-Omic and Single-cell Characterization of a 3D Skin-Like Tissue Model of Systemic Sclerosis with a Focus on Epigenetics

Systemic sclerosis (SSc) is a rare fibrotic autoimmune disease with high mortality and limited FDA approved therapies. Clinical concordance among twins is low; however, a modest familial heritability implicates complex interactions between polygenic risk alleles and the environment as causal – interactions that are mediated by epigenetics. Although mechanisms of tissue fibrosis have been successfully identified and targeted in established in vitro models for SSc, these molecules have ultimately failed in clinical trials. This likely reflects the lack of a reliable in vitro model that faithfully recapitulates the disease. I utilized a 3D skin-like tissue model to study SSc skin fibrosis. I paired this model with epigenomic analysis of Assay for Transposase Accessible Chromatin with sequencing (ATAC-seq). The goal was two-fold: 1) to epigenetically characterize and validate this 3D model and 2) to elucidate epigenetic mechanisms of skin fibrosis at a single-cell level using our 3D tissue model. In Chapter 2, I showed that SSc 3D tissues have patterns of chromatin accessibility that are distinct from monolayer fibroblasts. I also identified a novel region of SSc dysregulation predicted to regulate expression of the gene FER1L6. In Chapter 3, I used a similar experimental strategy to determine if select variants implicated in disease susceptibility impact chromatin accessibility. I identified a region of potential chromatin dysregulation in fibroblasts from an SSc individual with African-Ancestry specific variants of interest. This study demonstrates the potential to determine causality of SSc-associated non-coding variants. In Chapter 4, I applied single-cell ATAC-seq to a 3D tissue model containing increased cellular complexity. I identified several fibroblast subpopulations that correlated with those identified in human skin. Finally, I proposed a model for epigenetic dysregulation in SSc skin fibrosis. These findings establish that 3D tissues are epigenetically distinct from monolayer cultures and closely approximate human skin fibroblast populations. Using this model, I validated previous findings in addition to generating novel insights. Collectively, I believe this body of work contributes to a more accurate understanding of SSc skin fibrosis and establishes a reliable in vitro model for identification of targeted epigenetic therapies that can more effectively translate to clinical improvement