Non-coding RNAs (ncRNAs) are involved in an increasing number of cellular events1. Some ncRNAs are processed by DICER and DROSHA ribonucleases to give rise to small double-stranded RNAs involved in RNA interference (RNAi)2. The DNA-damage response (DDR) is a signaling pathway that originates from the DNA lesion and arrests cell proliferation3. So far, DICER or DROSHA RNA products have not been reported to control DDR activation. Here we show that DICER and DROSHA, but not downstream elements of the RNAi pathway, are necessary to activate DDR upon oncogene-induced genotoxic stress and exogenous DNA damage, as studied also by DDR foci formation in mammalian cells and zebrafish and by checkpoint assays. DDR foci are sensitive to RNase A treatment, and DICER- and DROSHA-dependent RNA products are required to restore DDR foci in treated cells. Through RNA deep sequencing and studies of DDR activation at an inducible unique DNA double-strand break (DSB), we demonstrate that DDR foci formation requires site-specific DICER- and DROSHA-dependent small RNAs, named DDRNAs, which act in a MRE11-RAD50-NBS1 (MRN) complex-dependent manner. Chemically synthesized or in vitro-generated by DICER cleavage, DDRNAs are sufficient to restore DDR in RNase A-treated cells, also in the absence of other cellular RNAs. Our results describe an unanticipated direct role of a novel class of ncRNAs in the control of DDR activation at sites of DNA damage.

Template switching (TS) has been an inherent mechanism of reverse transcriptase, which has been exploited in several transcriptome analysis methods, such as CAGE, RNA-Seq and short RNA sequencing. TS is an attractive option, given the simplicity of the protocol, which does not require an adaptor mediated step and thus minimizes sample loss. As such, it has been used in several studies that deal with limited amounts of RNA, such as in single cell studies. Additionally, TS has also been used to introduce DNA barcodes or indexes into different samples, cells or molecules. This labeling allows one to pool several samples into one sequencing flow cell, increasing the data throughput of sequencing and takes advantage of the increasing throughput of current sequences. Here, we report TS artifacts that form owing to a process called strand invasion. Due to the way in which barcodes/indexes are introduced by TS, strand invasion becomes more problematic by introducing unsystematic biases. We describe a strategy that eliminates these artifacts in silico and propose an experimental solution that suppresses biases from TS.

Retrotransposons are mobile genetic elements that employ a germ line “copy-and-paste” mechanism to spread throughout metazoan genomes1. At least 50% of the human genome is derived from retrotransposons, with three active families (L1, Alu and SVA) associated with insertional mutagenesis and disease2-3. Epigenetic and post-transcriptional suppression block retrotransposition in somatic cells4-5, excluding early embryo development and some malignancies6-7. Recent reports of L1 expression8-9 and copy number variation10-11 (CNV) in the human brain suggest L1 mobilization may also occur during later development. However, the corresponding integration sites have not been mapped. Here we apply a high-throughput method to identify numerous L1, Alu and SVA germ line mutations, as well as 7,743 putative somatic L1 insertions in the hippocampus and caudate nucleus of three individuals. Surprisingly, we also found 13,692 and 1,350 somatic Alu and SVA insertions, respectively. Our results demonstrate that retrotransposons mobilize to protein-coding genes differentially expressed and active in the brain. Thus, somatic genome mosaicism driven by retrotransposition may reshape the genetic circuitry that underpins normal and abnormal neurobiological processes.

Background

Cap analysis of gene expression (CAGE) is a 5′ sequence tag technology to globally determine transcriptional starting sites in the genome and their expression levels and has most recently been adapted to the HeliScope single molecule sequencer. Despite significant simplifications in the CAGE protocol, it has until now been a labour intensive protocol.

Methodology

In this study we set out to adapt the protocol to a robotic workflow, which would increase throughput and reduce handling. The automated CAGE cDNA preparation system we present here can prepare 96 ‘HeliScope ready’ CAGE cDNA libraries in 8 days, as opposed to 6 weeks by a manual operator.We compare the results obtained using the same RNA in manual libraries and across multiple automation batches to assess reproducibility.

Conclusions

We show that the sequencing was highly reproducible and comparable to manual libraries with an 8 fold increase in productivity. The automated CAGE cDNA preparation system can prepare 96 CAGE sequencing samples simultaneously. Finally we discuss how the system could be used for CAGE on Illumina/SOLiD platforms, RNA-seq and full-length cDNA generation.

The pathway for RNA interference is widespread in metazoans and participates in numerous cellular tasks, from gene silencing to chromatin remodeling and protection against retrotransposition. The unicellular eukaryote Trypanosoma cruzi is missing the canonical RNAi pathway and is unable to induce RNAi-related processes. To further understand alternative RNA pathways operating in this organism, we have performed deep sequencing and genome-wide analyses of a size-fractioned cDNA library (16–61 nt) from the epimastigote life stage. Deep sequencing generated 582,243 short sequences of which 91% could be aligned with the genome sequence. About 95–98% of the aligned data (depending on the haplotype) corresponded to small RNAs derived from tRNAs, rRNAs, snRNAs and snoRNAs. The largest class consisted of tRNA-derived small RNAs which primarily originated from the 3′ end of tRNAs, followed by small RNAs derived from rRNA. The remaining sequences revealed the presence of 92 novel transcribed loci, of which 79 did not show homology to known RNA classes.

Author Summary

Chagas' disease is a major health problem in Latin America and is caused by the protozoan parasite Trypanosoma cruzi. T. cruzi lacks the pathway for RNA interference, which is widespread among eukaryotes, and is therefore unable to induce RNAi-related processes. In many organisms, small RNAs play an important role in regulating gene expression and other cellular processes. In order to understand if other small RNA pathways are operating in this organism, we performed high throughput sequencing and genome-wide analyses of the short transcriptome. We identified an abundance of small RNAs derived from non-coding RNA genes, including transfer RNAs, ribosomal RNAs as well as small nucleolar RNAs and small nuclear RNAs. Certain tRNA types were overrepresented as precursors for small RNAs. Further, we identified 79 novel small non-coding RNAs, not previously reported. We did not identify canonical small RNAs, like microRNAs and small interfering RNAs, and concluded that these do not exist in T. cruzi. This study has provided insights into the short transcriptome of a major human pathogen and provided starting points for further functional investigation of small RNAs and their biological roles.

Human DICER1 protein cleaves double-stranded RNA into small sizes, a crucial step in production of single-stranded RNAs which are mediating factors of cytoplasmic RNA interference. Here, we clearly demonstrate that human DICER1 protein localizes not only to the cytoplasm but also to the nucleoplasm. We also find that human DICER1 protein associates with the NUP153 protein, one component of the nuclear pore complex. This association is detected predominantly in the cytoplasm but is also clearly distinguishable at the nuclear periphery. Additional characterization of the NUP153-DICER1 association suggests NUP153 plays a crucial role in the nuclear localization of the DICER1 protein.

Genetic cases of congenital pituitary hormone deficiency are common and many are caused by transcription factor defects. Mouse models with orthologous mutations are invaluable for uncovering the molecular mechanisms that lead to problems in organ development and typical patient characteristics. We are using mutant mice defective in the transcription factors PROP1 and POU1F1 for gene expression profiling to identify target genes for these critical transcription factors and candidates for cases of pituitary hormone deficiency of unknown etiology. These studies reveal critical roles for Wnt signalling pathways including the TCF/LEF transcription factors and interacting proteins of the groucho family, bone morphogenetic proteins antagonists, and targets of notch signalling. Current studies are investigating roles of novel homeobox genes and pathways that regulate the transition from proliferation to differentiation, cell adhesion and cell migration.

Pituitary adenomas are a common human health problem, yet most cases are sporadic, necessitating alternative approaches to traditional Mendelian genetic studies. Mouse models of adenoma formation offer the opportunity for gene expression profiling during progressive stages of hyperplasia, adenoma and tumorigenesis. This approach holds promise for identification of relevant pathways and candidate genes as risk factors for adenoma formation, understanding mechanisms of progression, and identifying drug targets and clinically relevant biomarkers.

Despite recent controversies, the evidence that the majority of the human genome is transcribed into RNA remains strong.

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 non-coding RNAs with capped 5′ ends that vary in size. Methods that identify the 5′ ends of transcripts will facilitate the discovery of novel 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 have developed nanoCAGE (Cap Analysis of Gene Expression), a method that captures the 5′ ends of transcripts from as little as 10 nanograms 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.

Background

Although transcription in mammalian genomes can initiate from various genomic positions (e.g., 3′UTR, coding exons, etc.), most locations on genomes are not prone to transcription initiation. It is of practical and theoretical interest to be able to estimate such collections of non-TSS locations (NTLs). The identification of large portions of NTLs can contribute to better focusing the search for TSS locations and thus contribute to promoter and gene finding. It can help in the assessment of 5′ completeness of expressed sequences, contribute to more successful experimental designs, as well as more accurate gene annotation.

Methodology

Using comprehensive collections of Cap Analysis of Gene Expression (CAGE) and other transcript data from mouse and human genomes, we developed a methodology that allows us, by performing computational TSS prediction with very high sensitivity, to annotate, with a high accuracy in a strand specific manner, locations of mammalian genomes that are highly unlikely to harbor transcription start sites (TSSs). The properties of the immediate genomic neighborhood of 98,682 accurately determined mouse and 113,814 human TSSs are used to determine features that distinguish genomic transcription initiation locations from those that are not likely to initiate transcription. In our algorithm we utilize various constraining properties of features identified in the upstream and downstream regions around TSSs, as well as statistical analyses of these surrounding regions.

Conclusions

Our analysis of human chromosomes 4, 21 and 22 estimates ∼46%, ∼41% and ∼27% of these chromosomes, respectively, as being NTLs. This suggests that on average more than 40% of the human genome can be expected to be highly unlikely to initiate transcription. Our method represents the first one that utilizes high-sensitivity TSS prediction to identify, with high accuracy, large portions of mammalian genomes as NTLs. The server with our algorithm implemented is available at http://cbrc.kaust.edu.sa/ddm/.

The international Functional Annotation Of the Mammalian Genomes 4 (FANTOM4) research collaboration set out to better understand the transcriptional network that regulates macrophage differentiation and to uncover novel components of the transcriptome employing a series of high-throughput experiments. The primary and unique technique is cap analysis of gene expression (CAGE), sequencing mRNA 5′-ends with a second-generation sequencer to quantify promoter activities even in the absence of gene annotation. Additional genome-wide experiments complement the setup including short RNA sequencing, microarray gene expression profiling on large-scale perturbation experiments and ChIP–chip for epigenetic marks and transcription factors. All the experiments are performed in a differentiation time course of the THP-1 human leukemic cell line. Furthermore, we performed a large-scale mammalian two-hybrid (M2H) assay between transcription factors and monitored their expression profile across human and mouse tissues with qRT-PCR to address combinatorial effects of regulation by transcription factors. These interdependent data have been analyzed individually and in combination with each other and are published in related but distinct papers. We provide all data together with systematic annotation in an integrated view as resource for the scientific community (http://fantom.gsc.riken.jp/4/). Additionally, we assembled a rich set of derived analysis results including published predicted and validated regulatory interactions. Here we introduce the resource and its update after the initial release.

Non-coding RNA (ncRNA) transcripts are RNA molecules that do not code for proteins, but elicit function by other mechanisms. The vast majority of RNA produced in a cell is non-coding ribosomal RNA, produced from relatively few loci, however more recently complementary DNA (cDNA) cloning, tag sequencing, and genome tiling array studies suggest that ncRNAs also account for the majority of RNA species produced by a cell. ncRNA based regulation has been referred to as a ‘hidden layer’ of signals or ‘dark matter’ that control gene expression in cellular processes by poorly described mechanisms. These terms have appeared as ncRNAs until recently have been ignored by expression profiling and cDNA annotation projects and their mode of action is diverse (e.g. influencing chromatin structure and epigenetics, translational silencing, transcriptional silencing). Here, we highlight recent functional genomics strategies toward identifying and assigning function to ncRNA transcription.

We report a catalog of the mouse embryonic pituitary gland transcriptome consisting of five cDNA libraries including wild type tissue from E12.5 and E14.5, Prop1df/df mutant at E14.5, and two cDNA subtractions: E14.5 WT-E14.5 Prop1df/df and E14.5 WT-E12.5 WT. DNA sequence information is assembled into a searchable database with gene ontology terms representing 12,009 expressed genes. We validated coverage of the libraries by detecting most known homeobox gene transcription factor cDNAs. A total of 45 homeobox genes were detected as part of the pituitary transcriptome, representing most expected ones, which validated library coverage, and many novel ones, underscoring the utility of this resource as a discovery tool. We took a similar approach for signaling-pathway members with novel pituitary expression and found 157 genes related to the BMP, FGF, WNT, SHH and NOTCH pathways. These genes are exciting candidates for regulators of pituitary development and function.

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.

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.

Initial gene discovery efforts through analysis of genome sequences and identification and characterization of expressed RNAs have revealed that only a relatively small portion of the genome is transcribed into protein coding mRNAs in vertebrates. However, in contrast with this paucity of protein coding ‘genes’, there is an enormous complexity in transcription and the protein coding mRNAs contribute to a very small fraction of transcripts in comparison with the different varieties of non-coding RNAs (ncRNAs). This transcriptome complexity may be hypothesized to have a regulatory role that is required for the development and function of organisms as complex as vertebrates. At the same time, it raises the fundamental question of the unequivocal definition of a gene. It is intriguing to postulate that many ncRNAs might finely modulate gene activity by acting as regulatory elements. The emerging hypotheses suggest that the gene regulatory machinery may be deeply interconnected with the world of short RNAs. These RNAs may generally act for fine-tuning of the protein-coding transcriptome.

Using microarrays made with cDNAs from subtracted placental libraries, we show increased hemoglobin production in the preeclamptic placenta. Heme and hemoglobin may cause endothelial damage and inflammation and drive pathological changes in the placenta if they are released there.

Study Objective:

To create a library enriched in cDNAs from preeclamptic placentas to print on to microarrays for placental profiling of preeclampsia (PE) and high risk pregnancies.

Design:

Prospective study.

Setting:

University women's clinic and academic research laboratory.

Patients:

Ten patients with PE, 5 with PE and bilateral notching, 5 with bilateral notching without PE, and 15 normotensive patients were recruited.

Interventions:

Placenta and placenta bed biopsies were collected after delivery.

Main Outcome Measures:

Subtracted libraries of PE transcripts were produced, and cDNAs from these libraries were used to make PE-specific cDNA arrays. Results were verified quantitatively using real-time PCR and histologically using in situ hybridization and immunohistochemistry.

Results:

30 genes were significantly altered in at least one group comparison. Differences in two candidate genes were confirmed using quantitative rt-PCR. Hemoglobin α2 and γ transcripts were significantly over-expressed in the PE placenta. Scattered cells in the placenta and placental blood vessels were shown to express genes encoding these hemoglobin-chains.

Conclusions:

We demonstrate increased hemoglobin production in the PE placenta. The hemoglobin may be released into the placenta blood vessel lumen. Free heme and hemoglobin are potent toxins which cause endothelial damage and inflammation.

A set of methods is presented for normalization, quantification of noise and co-expression analysis for gene expression studies using deep sequencing.

With the advent of ultra high-throughput sequencing technologies, increasingly researchers are turning to deep sequencing for gene expression studies. Here we present a set of rigorous methods for normalization, quantification of noise, and co-expression analysis of deep sequencing data. Using these methods on 122 cap analysis of gene expression (CAGE) samples of transcription start sites, we construct genome-wide 'promoteromes' in human and mouse consisting of a three-tiered hierarchy of transcription start sites, transcription start clusters, and transcription start regions.

The genome-scale data collected by the FANTOM4 collaborative research project are presented as an integrated web resource.

In FANTOM4, an international collaborative research project, we collected a wide range of genome-scale data, including 24 million mRNA 5'-reads (CAGE tags) and microarray expression profiles along a differentiation time course of the human THP-1 cell line and under 52 systematic siRNA perturbations. In addition, data regarding chromatin status derived from ChIP-chip to elucidate the transcriptional regulatory interactions are included. Here we present these data to the research community as an integrated web resource.

EdgeExpressDB is a novel database and set of interfaces for interpreting biological networks and comparing large high-throughput expression datasets.

EdgeExpressDB is a novel database and set of interfaces for interpreting biological networks and comparing large high-throughput expression datasets that requires minimal development for new data types and search patterns. The FANTOM4 EdgeExpress database summarizes gene expression patterns in the context of alternative promoter structures and regulatory transcription factors and microRNAs using intuitive gene-centric and sub-network views. This is an important resource for gene regulation in acute myeloid leukemia, monocyte/macrophage differentiation and human transcriptional networks.

Background

The transcriptome of the cerebral cortex is remarkably homogeneous, with variations being stronger between individuals than between areas. It is thought that due to the presence of many distinct cell types, differences within one cell population will be averaged with the noise from others. Studies of sorted cells expressing the same transgene have shown that cell populations can be distinguished according to their transcriptional profile.

Methodology

We have prepared a low-redundancy set of 16,209 full-length cDNA clones which represents the transcriptome of the mouse visual cortex in its coding and non-coding aspects. Using an independent tag-based approach, CAGE, we confirmed the cortical expression of 72% of the clones. Clones were amplified by PCR and spotted on glass slides, and we interrogated the microarrays with RNA from flow-sorted fluorescent cells from the cerebral cortex of parvalbumin-egfp transgenic mice.

Conclusions

We provide an annotated cDNA clone collection which is particularly suitable for transcriptomic analysis in the mouse brain. Spotting it on microarrays, we compared the transcriptome of EGFP positive and negative cells in a parvalbumin-egfp transgenic background and showed that more than 30% of clones are differentially expressed. Our clone collection will be a useful resource for the study of the transcriptome of single cell types in the cerebral cortex.