Deep sequencing of short capped RNAs reveals novel families of noncoding RNAs.

In eukaryotes, capped RNAs include long transcripts such as messenger RNAs and long noncoding RNAs, as well as shorter transcripts such as spliceosomal RNAs, small nucleolar RNAs, and enhancer RNAs. Long capped transcripts can be profiled using cap analysis gene expression (CAGE) sequencing and other methods. Here, we describe a sequencing library preparation protocol for short capped RNAs, apply it to a differentiation time course of the human cell line THP-1, and systematically compare the landscape of short capped RNAs to that of long capped RNAs. Transcription initiation peaks associated with genes in the sense direction have a strong preference to produce either long or short capped RNAs, with one out of six peaks detected in the short capped RNA libraries only. Gene-associated short capped RNAs have highly specific 3' ends, typically overlapping splice sites. Enhancers also preferentially generate either short or long capped RNAs, with 10% of enhancers observed in the short capped RNA libraries only. Enhancers producing either short or long capped RNAs show enrichment for GWAS-associated disease SNPs. We conclude that deep sequencing of short capped RNAs reveals new families of noncoding RNAs and elucidates the diversity of transcripts generated at known and novel promoters and enhancers.

Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.

CAGE (cap analysis gene expression) and RNA-seq are two major technologies used to identify transcript abundances as well as structures. They measure expression by sequencing from either the 5' end of capped molecules (CAGE) or tags randomly distributed along the length of a transcript (RNA-seq). Library protocols for clonally amplified (Illumina, SOLiD, 454 Life Sciences [Roche], Ion Torrent), second-generation sequencing platforms typically employ PCR preamplification prior to clonal amplification, while third-generation, single-molecule sequencers can sequence unamplified libraries. Although these transcriptome profiling platforms have been demonstrated to be individually reproducible, no systematic comparison has been carried out between them. Here we compare CAGE, using both second- and third-generation sequencers, and RNA-seq, using a second-generation sequencer based on a panel of RNA mixtures from two human cell lines to examine power in the discrimination of biological states, detection of differentially expressed genes, linearity of measurements, and quantification reproducibility. We found that the quantified levels of gene expression are largely comparable across platforms and conclude that CAGE and RNA-seq are complementary technologies that can be used to improve incomplete gene models. We also found systematic bias in the second- and third-generation platforms, which is likely due to steps such as linker ligation, cleavage by restriction enzymes, and PCR amplification. This study provides a perspective on the performance of these platforms, which will be a baseline in the design of further experiments to tackle complex transcriptomes uncovered in a wide range of cell types.

High quality genome assembly of the anhydrobiotic midge provides insights on a single chromosome-based emergence of extreme desiccation tolerance.

Non-biting midges (Chironomidae) are known to inhabit a wide range of environments, and certain species can tolerate extreme conditions, where the rest of insects cannot survive. In particular, the sleeping chironomid Polypedilum vanderplanki is known for the remarkable ability of its larvae to withstand almost complete desiccation by entering a state called anhydrobiosis. Chromosome numbers in chironomids are higher than in other dipterans and this extra genomic resource might facilitate rapid adaptation to novel environments. We used improved sequencing strategies to assemble a chromosome-level genome sequence for P. vanderplanki for deep comparative analysis of genomic location of genes associated with desiccation tolerance. Using whole genome-based cross-species and intra-species analysis, we provide evidence for the unique functional specialization of Chromosome 4 through extensive acquisition of novel genes. In contrast to other insect genomes, in the sleeping chironomid a uniquely high degree of subfunctionalization in paralogous anhydrobiosis genes occurs in this chromosome, as well as pseudogenization in a highly duplicated gene family. Our findings suggest that the Chromosome 4 in Polypedilum is a site of high genetic turnover, allowing it to act as a 'sandbox' for evolutionary experiments, thus facilitating the rapid adaptation of midges to harsh environments.

Antisense-oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types.

Within the scope of the FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem cells (iPSCs) and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition. From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell-type enrichment analysis identifies lncRNAs associated with pluripotency, while the knockdown of LINC02595, CATG00000090305.1, and RP11-148B6.2 modulates colony formation of iPSCs. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit a consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights that molecular phenotyping is more comprehensive in revealing affected pathways.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

Cap Analysis of Gene Expression (CAGE): A Quantitative and Genome-Wide Assay of Transcription Start Sites.

Cap analysis of gene expression (CAGE) is an approach to identify and monitor the activity (transcription initiation frequency) of transcription start sites (TSSs) at single base-pair resolution across the genome. It has been effectively used to identify active promoter and enhancer regions in cancer cells, with potential utility to identify key factors to immunotherapy. Here, we overview a series of CAGE protocols and describe detailed experimental steps of the latest protocol based on the Illumina sequencing platform; both experimental steps (see Subheadings 3.1-3.11) and computational processing steps (see Subheadings 3.12-3.20) are described.

Development of a DNA barcode tagging method for monitoring dynamic changes in gene expression by using an ultra high-throughput sequencer.

CAGE (cap analysis of gene expression) is a method for identifying transcription start sites by sequencing the first 20 or 21 nucleotides from the 5' end of capped transcripts, allowing genome-wide promoter analyses to be performed. The potential of the CAGE as a form of expression profiling was limited previously by sequencing technology and the labor-intensive protocol. Here we describe an improved CAGE method for use with a next generation sequencer. This modified method allows the identification of the RNA source of each CAGE tag within a pooled library by introducing DNA tags (barcodes). The method not only drastically improves the sequencing capacity, but also contributes to savings in both time and budget. Additionally, this pooled CAGE tag method enables the dynamic changes in promoter usage and gene expression to be monitored.

FANTOM5 CAGE profiles of human and mouse samples.

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

Detecting expressed genes using CAGE.

Cap analysis of gene expression (CAGE) provides accurate high-throughput measurement of RNA expression. By the large-scale analysis of 5' end of transcripts using CAGE method, it enables not only determination of the transcription start site but also prediction of promoter region. Here we provide a protocol for the construction of no-amplification non-tagging CAGE libraries for Illumina next-generation sequencers (nAnT-iCAGE). We have excluded the commonly used PCR amplification and cleavage of restriction enzyme to eliminate any potential biases. As a result, we achieved less biased simple preparation process.

CAGE (cap analysis of gene expression): a protocol for the detection of promoter and transcriptional networks.

We provide here a protocol for the preparation of cap-analysis gene expression (CAGE) libraries, which allows for measuring the expression of eukaryotic capped RNAs and simultaneously map the promoter regions. The presented protocol simplifies the previously published ones and moreover produces tags that are 27 nucleotides long, which facilitates mapping to the genome. The protocol takes less than 5 days to complete and presents a notable improvement compared to previously published versions.

5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing.

Cap-analysis gene expression (CAGE) provides accurate high-throughput measurement of RNA expression. CAGE allows mapping of all the initiation sites of both capped coding and noncoding RNAs. In addition, transcriptional start sites within promoters are characterized at single-nucleotide resolution. The latter allows the regulatory inputs driving gene expression to be studied, which in turn enables the construction of transcriptional networks. Here we provide an optimized protocol for the construction of CAGE libraries on the basis of the preparation of 27-nt-long tags corresponding to initial bases at the 5' ends of capped RNAs. We have optimized the methods using simple steps based on filtration, which altogether takes 4 d to complete. The CAGE tags can be readily sequenced with Illumina sequencers, and upon modification they are also amenable to sequencing using other platforms.

Tunable fractionation of nucleic acids.

We developed a method for selective purification of DNA using the cationic detergent, cetyltrimethylammonium bromide (CTAB), accompanied with urea and controlled high-salt (NaCl) concentration. This method is effective for rapid separation of DNA fragments from artifacts such as PCR primer dimers or ligation adapters. The CTAB-associated purification completely removed the short PCR artifacts and primers, as well as enzymes and buffer, while recovering a sufficient quantity of amplicons for subsequent experiments such as preparation of libraries. This method could also be applied to the fractionation of nucleic acids generated by other types of reactions.

Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE.

Finding and characterizing mRNAs, their transcription start sites (TSS), and their associated promoters is a major focus in post-genome biology. Mammalian cells have at least 5-10 magnitudes more TSS than previously believed, and deeper sequencing is necessary to detect all active promoters in a given tissue. Here, we present a new method for high-throughput sequencing of 5' cDNA tags-DeepCAGE: merging the Cap Analysis of Gene Expression method with ultra-high-throughput sequence technology. We apply DeepCAGE to characterize 1.4 million sequenced TSS from mouse hippocampus and reveal a wealth of novel core promoters that are preferentially used in hippocampus: This is the most comprehensive promoter data set for any tissue to date. Using these data, we present evidence indicating a key role for the Arnt2 transcription factor in hippocampus gene regulation. DeepCAGE can also detect promoters used only in a small subset of cells within the complex tissue.

Tiny RNAs associated with transcription start sites in animals.

It has been reported that relatively short RNAs of heterogeneous sizes are derived from sequences near the promoters of eukaryotic genes. In conjunction with the FANTOM4 project, we have identified tiny RNAs with a modal length of 18 nt that map within -60 to +120 nt of transcription start sites (TSSs) in human, chicken and Drosophila. These transcription initiation RNAs (tiRNAs) are derived from sequences on the same strand as the TSS and are preferentially associated with G+C-rich promoters. The 5' ends of tiRNAs show peak density 10-30 nt downstream of TSSs, indicating that they are processed. tiRNAs are generally, although not exclusively, associated with highly expressed transcripts and sites of RNA polymerase II binding. We suggest that tiRNAs may be a general feature of transcription in metazoa and possibly all eukaryotes.

Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray.

Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE) genes, 33K annotated non-expressed (ANE) genes, and 5.5K non-annotated expressed (NAE) genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria.