Morana Vitezic

Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan

Large-scale sequencing projects have revealed an unexpected complexity in the origins, structures and functions of mammalian transcripts. Many loci are known to produce overlapping coding and noncoding RNAs with capped 5′ ends that vary in size. Methods to identify the 5′ ends of transcripts will facilitate the discovery of new promoters and 5′ ends derived from secondary capping events. Such methods often require high input amounts of RNA not obtainable from highly refined samples such as tissue microdissections and subcellular fractions. Therefore, we developed nano–cap analysis of gene expression (nanoCAGE), a method that captures the 5′ ends of transcripts from as little as 10 ng of total RNA, and CAGEscan, a mate-pair adaptation of nanoCAGE that captures the transcript 5′ ends linked to a downstream region. Both of these methods allow further annotation-agnostic studies of the complex human transcriptome.

Molecular Networks of DYX1C1 Gene Show Connection to Neuronal Migration Genes and Cytoskeletal Proteins

BACKGROUND The dyslexia susceptibility 1 candidate 1 (DYX1C1) gene has recently been associated with dyslexia and reading scores in several population samples. The DYX1C1 has also been shown to affect neuronal migration and modulate estrogen receptor signaling. METHODS We have analyzed the molecular networks of DYX1C1 by gene expression and protein interaction profiling in a human neuroblastoma cell line. RESULTS We find that DYX1C1 can modulate the expression of nervous system development and neuronal migration genes such as RELN and associate with a number of cytoskeletal proteins. We also show by live cell imaging that DYX1C1 regulates cell migration of the human neuroblastoma cell line dependent on its tetratricopeptide repeat and DYX1 protein domains. The DYX1 domain is a novel highly conserved domain identified in this study by multiple sequence alignment of DYX1C1 proteins recovered from a wide range of eukaryotic species. CONCLUSIONS Our results contribute to the hypothesis that dyslexia has a developmental neurobiological basis by linking DYX1C1 with many genes involved in neuronal migration disorders.

Regional differences in gene expression and promoter usage in aged human brains

To characterize the promoterome of caudate and putamen regions (striatum), frontal and temporal cortices, and hippocampi from aged human brains, we used high-throughput cap analysis of gene expression to profile the transcription start sites and to quantify the differences in gene expression across the 5 brain regions. We also analyzed the extent to which methylation influenced the observed expression profiles. We sequenced more than 71 million cap analysis of gene expression tags corresponding to 70,202 promoter regions and 16,888 genes. More than 7000 transcripts were differentially expressed, mainly because of differential alternative promoter usage. Unexpectedly, 7% of differentially expressed genes were neurodevelopmental transcription factors. Functional pathway analysis on the differentially expressed genes revealed an overrepresentation of several signaling pathways (e.g., fibroblast growth factor and wnt signaling) in hippocampus and striatum. We also found that although 73% of methylation signals mapped within genes, the influence of methylation on the expression profile was small. Our study underscores alternative promoter usage as an important mechanism for determining the regional differences in gene expression at old age.

RECLU: A pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE)

BackgroundNext generation sequencing based technologies are being extensively used to study transcriptomes. Among these, cap analysis of gene expression (CAGE) is specialized in detecting the most 5’ ends of RNA molecules. After mapping the sequenced reads back to a reference genome CAGE data highlights the transcriptional start sites (TSSs) and their usage at a single nucleotide resolution.ResultsWe propose a pipeline to group the single nucleotide TSS into larger reproducible peaks and compare their usage across biological states. Importantly, our pipeline discovers broad peaks as well as the fine structure of individual transcriptional start sites embedded within them. We assess the performance of our approach on a large CAGE datasets including 156 primary cell types and two cell lines with biological replicas. We demonstrate that genes have complicated structures of transcription initiation events. In particular, we discover that narrow peaks embedded in broader regions of transcriptional activity can be differentially used even if the larger region is not.ConclusionsBy examining the reproducible fine scaled organization of TSS we can detect many differentially regulated peaks undetected by previous approaches.

Brain-specific noncoding RNAs are likely to originate in repeats and may play a role in up-regulating genes in cis

The mouse and human brain express a large number of noncoding RNAs (ncRNAs). Some of these are known to participate in neural progenitor cell fate determination, cell differentiation, neuronal and synaptic plasticity and transposable elements derived ncRNAs contribute to somatic variation. Dysregulation of specific long ncRNAs (lncRNAs) has been shown in neuro-developmental and neuro-degenerative diseases thus highlighting the importance of lncRNAs in brain function. Even though it is known that lncRNAs are expressed in cells at low levels in a tissue-specific manner, bioinformatics analyses of brain-specific ncRNAs has not been performed. We analyzed previously published custom microarray ncRNA expression data generated from twelve human tissues to identify tissue-specific ncRNAs. We find that among the 12 tissues studied, brain has the largest number of ncRNAs. Our analyses show that genes in the vicinity of brain-specific ncRNAs are significantly up regulated in the brain. Investigations of repeat representation show that brain-specific ncRNAs are significantly more likely to originate in repeat regions especially DNA/TcMar-Tigger compared with non-tissue-specific ncRNAs. We find SINE/Alus depleted from brain-specific dataset when compared with non-tissue-specific ncRNAs. Our data provide a bioinformatics comparison between brain-specific and non tissue-specific ncRNAs. This article is part of a Directed Issue entitled: The Non-coding RNA Revolution.

Building promoter aware transcriptional regulatory networks using siRNA perturbation and deepCAGE.

Perturbation and time-course data sets, in combination with computational approaches, can be used to infer transcriptional regulatory networks which ultimately govern the developmental pathways and responses of cells. Here, we individually knocked down the four transcription factors PU.1, IRF8, MYB and SP1 in the human monocyte leukemia THP-1 cell line and profiled the genome-wide transcriptional response of individual transcription starting sites using deep sequencing based Cap Analysis of Gene Expression. From the proximal promoter regions of the responding transcription starting sites, we derived de novo binding-site motifs, characterized their biological function and constructed a network. We found a previously described composite motif for PU.1 and IRF8 that explains the overlapping set of transcriptional responses upon knockdown of either factor.

Identification of TNF-α-responsive promoters and enhancers in the intestinal epithelial cell model Caco-2.

The Caco-2 cell line is one of the most important in vitro models for enterocytes, and is used to study drug absorption and disease, including inflammatory bowel disease and cancer. In order to use the model optimally, it is necessary to map its functional entities. In this study, we have generated genome-wide maps of active transcription start sites (TSSs), and active enhancers in Caco-2 cells with or without tumour necrosis factor (TNF)-α stimulation to mimic an inflammatory state. We found 520 promoters that significantly changed their usage level upon TNF-α stimulation; of these, 52% are not annotated. A subset of these has the potential to confer change in protein function due to protein domain exclusion. Moreover, we locate 890 transcribed enhancer candidates, where ∼50% are changing in usage after TNF-α stimulation. These enhancers share motif enrichments with similarly responding gene promoters. As a case example, we characterize an enhancer regulating the laminin-5 γ2-chain (LAMC2) gene by nuclear factor (NF)-κB binding. This report is the first to present comprehensive TSS and enhancer maps over Caco-2 cells, and highlights many novel inflammation-specific promoters and enhancers.

Profiling transcription initiation in human aged brain using deep-CAGE

The genome sequencing projects completed in recent years revealed that the number of protein-coding genes does not change appreciably with increasing complexity of the organisms, and it is now generally accepted that this divergence is largely due to variation at the regulatory level. Mechanisms such as alternative splicing, alternative promoters and antisense transcription allow to both obtain a high number of transcripts from a relatively small number of genes and to fine tune isoforms expression in a cell-specific or developmentally-restricted manner. It is likely that the extensive use of such mechanisms plays a pivotal role in development, adult function and ageing of complex tissues like brain. The aim of this study was to characterize transcription start sites (TSSs) in different areas of human aged brain and correlate expression with methylation and structural genomic variation. Since its ability to profile TSSs at high resolution and at a genome wide level, we used Cap Analysis of Gene Expression (CAGE) combined with high-throughput sequencing (deep-CAGE) to collect exact TSSs and their expression levels. We present here our findings on alternative promoters and antisense transcription. Post-mortem tissue from 5 different brain regions was collected from 5 human donors and used to prepare 25 libraries.

A comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells

PROM1 is the gene encoding prominin-1 or CD133, an important cell surface marker for the isolation of both normal and cancer stem cells. PROM1 transcripts initiate at a range of transcription start sites (TSS) associated with distinct tissue and cancer expression profiles. Using high resolution Cap Analysis of Gene Expression (CAGE) sequencing we characterize TSS utilization across a broad range of normal and developmental tissues. We identify a novel proximal promoter (P6) within CD133+ melanoma cell lines and stem cells. Additional exon array sampling finds P6 to be active in populations enriched for mesenchyme, neural stem cells and within CD133+ enriched Ewing sarcomas. The P6 promoter is enriched with respect to previously characterized PROM1 promoters for a HMGI/Y (HMGA1) family transcription factor binding site motif and exhibits different epigenetic modifications relative to the canonical promoter region of PROM1.

CAGE-defined promoter regions of the genes implicated in Rett Syndrome

BackgroundMutations in three functionally diverse genes cause Rett Syndrome. Although the functions of Forkhead box G1 (FOXG1), Methyl CpG binding protein 2 (MECP2) and Cyclin-dependent kinase-like 5 (CDKL5) have been studied individually, not much is known about their relation to each other with respect to expression levels and regulatory regions. Here we analyzed data from hundreds of mouse and human samples included in the FANTOM5 project, to identify transcript initiation sites, expression levels, expression correlations and regulatory regions of the three genes.ResultsOur investigations reveal the predominantly used transcription start sites (TSSs) for each gene including novel transcription start sites for FOXG1. We show that FOXG1 expression is poorly correlated with the expression of MECP2 and CDKL5. We identify promoter shapes for each TSS, the predicted location of enhancers for each gene and the common transcription factors likely to regulate the three genes. Our data imply Polycomb Repressive Complex 2 (PRC2) mediated silencing of Foxg1 in cerebellum.ConclusionsOur analyses provide a comprehensive picture of the regulatory regions of the three genes involved in Rett Syndrome.