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Retinitis pigmentosa (RP) is the leading cause of blindness with nearly two million people affected worldwide. Many genes have been implicated in RP, yet in 30-80% of the RP patients the genetic cause remains unknown. A similar phenotype, progressive retinal atrophy (PRA), affects many dog breeds including the Miniature Schnauzer. We performed clinical, genetic and functional experiments to identify the genetic cause of PRA in the breed. The age of onset and pattern of disease progression suggested that at least two forms of PRA, types 1 and 2 respectively, affect the breed, which was confirmed by genome-wide association study that implicated two distinct genomic loci in chromosomes 15 and X, respectively. Whole-genome sequencing revealed a fully segregating recessive regulatory variant in type 1 PRA. The associated variant has a very recent origin based on haplotype analysis and lies within a regulatory site with the predicted binding site of HAND1::TCF3 transcription factor complex. Luciferase assays suggested that mutated regulatory sequence increases expression. Case-control retinal expression comparison of six best HAND1::TCF3 target genes were analyzed with quantitative reverse-transcriptase PCR assay and indicated overexpression of EDN2 and COL9A2 in the affected retina. Defects in both EDN2 and COL9A2 have been previously associated with retinal degeneration. In summary, our study describes two genetically different forms of PRA and identifies a fully penetrant variant in type 1 form with a possible regulatory effect. This would be among the first reports of a regulatory variant in retinal degeneration in any species, and establishes a new spontaneous dog model to improve our understanding of retinal biology and gene regulation while the affected breed will benefit from a reliable genetic testing.

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Background: Dilated cardiomyopathy (DCM) is a life-threatening heart disease and a common cause of heart failure due to systolic dysfunction and subsequent left or biventricular dilatation. A significant number of cases have a genetic etiology; however, as a complex disease, the exact genetic risk factors are largely unknown, and many patients remain without a molecular diagnosis. Methods: We performed GWAS followed by whole-genome, transcriptome, and immunohistochemical analyses in a spontaneously occurring canine model of DCM. Canine gene discovery was followed up in three human DCM cohorts. Results: Our results revealed two independent additive loci associated with the typical DCM phenotype comprising left ventricular systolic dysfunction and dilatation. We highlight two novel candidate genes, RNF207 and PRKAA2, known for their involvement in cardiac action potentials, energy homeostasis, and morphology. We further illustrate the distinct genetic etiologies underlying the typical DCM phenotype and ventricular premature contractions. Finally, we followed up on the canine discoveries in human DCM patients and discovered candidate variants in our two novel genes. Conclusions: Collectively, our study yields insight into the molecular pathophysiology of DCM and provides a large animal model for preclinical studies. [ABSTRACT FROM AUTHOR]

Abstract Background Histone modifications play an important role in gene regulation. Acetylation of histone 3 lysine 9 (H3K9ac) is generally associated with transcription initiation and unfolded chromatin, thereby positively influencing gene expression. Deep sequencing of the 5' ends of gene transcripts using DeepCAGE delivers detailed information about the architecture and expression level of gene promoters. The combination of H3K9ac ChIP-chip and DeepCAGE in a myeloid leukemia cell line (THP-1) allowed us to study the spatial distribution of H3K9ac around promoters using a novel clustering approach. The promoter classes were analyzed for association with relevant genomic sequence features. Results We performed a clustering of 4,481 promoters according to their surrounding H3K9ac signal and analyzed the clustered promoters for association with different sequence features. The clustering revealed three groups with major H3K9ac signal upstream, centered and downstream of the promoter. Narrow single peak promoters tend to have a concentrated activity of H3K9ac in the upstream region, while broad promoters tend to have a concentrated activity of H3K9ac and RNA polymerase II binding in the centered and downstream regions. A subset of promoters with high gene expression level, compared to subsets with low and medium gene expression, shows dramatic increase in H3K9ac activity in the upstream cluster only; this may indicate that promoters in the centered and downstream clusters are predominantly regulated at post-initiation steps. Furthermore, the upstream cluster is depleted in CpG islands and more likely to regulate un-annotated genes. Conclusions Clustering core promoters according to their surrounding acetylation signal is a promising approach for the study of histone modifications. When examining promoters clustered into groups according to their surrounding H3K9 acetylation signal, we find that the relative localization and intensity of H3K9ac is very specific depending on characteristic sequence features of the promoter. Experimental data from DeepCAGE and ChIP-chip experiments using undifferentiated (monocyte) and differentiated (macrophage) THP-1 cells leads us to the same conclusions.

Abstract Background Small RNA attracts increasing interest based on the discovery of RNA silencing and the rapid progress of our understanding of these phenomena. Although recent studies suggest the possible existence of yet undiscovered types of small RNAs in higher organisms, many studies to profile small RNA have focused on miRNA and/or siRNA rather than on the exploration of additional classes of RNAs. Results Here, we explored human small RNAs by unbiased sequencing of RNAs with sizes of 19–40 nt. We provide substantial evidences for the existence of independent classes of small RNAs. Our data shows that well-characterized non-coding RNA, such as tRNA, snoRNA, and snRNA are cleaved at sites specific to the class of ncRNA. In particular, tRNA cleavage is regulated depending on tRNA type and tissue expression. We also found small RNAs mapped to genomic regions that are transcribed in both directions by bidirectional promoters, indicating that the small RNAs are a product of dsRNA formation and their subsequent cleavage. Their partial similarity with ribosomal RNAs (rRNAs) suggests unrevealed functions of ribosomal DNA or interstitial rRNA. Further examination revealed six novel miRNAs. Conclusion Our results underscore the complexity of the small RNA world and the biogenesis of small RNAs.

The FANTOM5 consortium utilised cap analysis of gene expression (CAGE) to provide an unprecedented insight into transcriptional regulation in human cells and tissues. In the current study, we have used CAGE-based transcriptional profiling on an extended dense time course of the response of human monocyte-derived macrophages grown in macrophage colony-stimulating factor (CSF1) to bacterial lipopolysaccharide (LPS). We propose that this system provides a model for the differentiation and adaptation of monocytes entering the intestinal lamina propria. The response to LPS is shown to be a cascade of successive waves of transient gene expression extending over at least 48 hours, with hundreds of positive and negative regulatory loops. Promoter analysis using motif activity response analysis (MARA) identified some of the transcription factors likely to be responsible for the temporal profile of transcriptional activation. Each LPS-inducible locus was associated with multiple inducible enhancers, and in each case, transient eRNA transcription at multiple sites detected by CAGE preceded the appearance of promoter-associated transcripts. LPS-inducible long non-coding RNAs were commonly associated with clusters of inducible enhancers. We used these data to re-examine the hundreds of loci associated with susceptibility to inflammatory bowel disease (IBD) in genome-wide association studies. Loci associated with IBD were strongly and specifically (relative to rheumatoid arthritis and unrelated traits) enriched for promoters that were regulated in monocyte differentiation or activation. Amongst previously-identified IBD susceptibility loci, the vast majority contained at least one promoter that was regulated in CSF1-dependent monocyte-macrophage transitions and/or in response to LPS. On this basis, we concluded that IBD loci are strongly-enriched for monocyte-specific genes, and identified at least 134 additional candidate genes associated with IBD susceptibility from reanalysis of published GWA studies. We propose that dysregulation of monocyte adaptation to the environment of the gastrointestinal mucosa is the key process leading to inflammatory bowel disease. [ABSTRACT FROM AUTHOR]

Background: As larger datasets are produced with the development of genome-scale experimental techniques, it has become essential to explicitly describe the meta-data (information describing the data) generated by an experiment. The experimental process is a part of the metadata required to interpret the produced data, and SDRF (Sample and Data Relationship Format) supports its description in a spreadsheet or tab-delimited file. This format was primarily developed to describe microarray studies in MAGE-tab, and it is being applied in a broader context in ISA-tab. While the format provides an explicit framework to describe experiments, increase of experimental steps makes it less obvious to understand the content of the SDRF files. Results: Here, we describe a new tool, SDRF2GRAPH, for displaying experimental steps described in an SDRF file as an investigation design graph, a directed acyclic graph representing experimental steps. A spreadsheet, in Microsoft Excel for example, which is used to edit and inspect the descriptions, can be directly input via a web-based interface without converting to tab-delimited text. This makes it much easier to organize large contents of SDRF described in multiple spreadsheets. Conclusion: SDRF2GRAPH is applicable for a wide range of SDRF files for not only microarray-based analysis but also other genome-scale technologies, such as next generation sequencers. Visualization of the Investigation Design Graph (IDG) structure leads to an easy understanding of the experimental process described in the SDRF files even if the experiment is complicated, and such visualization also encourages the creation of SDRF files by providing prompt visual feedback. [ABSTRACT FROM AUTHOR]

Background: Evolutionarily conserved RFX transcription factors (TFs) regulate their target genes through a DNA sequence motif called the X-box. Thereby they regulate cellular specialization and terminal differentiation. Here, we provide a comprehensive analysis of all the eight human RFX genes (RFX1–8), their spatial and temporal expression profiles, potential upstream regulators and target genes. Results: We extracted all known human RFX1–8 gene expression profiles from the FANTOM5 database derived from transcription start site (TSS) activity as captured by Cap Analysis of Gene Expression (CAGE) technology. RFX genes are broadly (RFX1–3, RFX5, RFX7) and specifically (RFX4, RFX6) expressed in different cell types, with high expression in four organ systems: immune system, gastrointestinal tract, reproductive system and nervous system. Tissue type specific expression profiles link defined RFX family members with the target gene batteries they regulate. We experimentally confirmed novel TSS locations and characterized the previously undescribed RFX8 to be lowly expressed. RFX tissue and cell type specificity arises mainly from differences in TSS architecture. RFX transcript isoforms lacking a DNA binding domain (DBD) open up new possibilities for combinatorial target gene regulation. Our results favor a new grouping of the RFX family based on protein domain composition. We uncovered and experimentally confirmed the TFs SP2 and ESR1 as upstream regulators of specific RFX genes. Using TF binding profiles from the JASPAR database, we determined relevant patterns of X-box motif positioning with respect to gene TSS locations of human RFX target genes. Conclusions: The wealth of data we provide will serve as the basis for precisely determining the roles RFX TFs play in human development and disease. [ABSTRACT FROM AUTHOR]