Identification and analysis of short open reading frames (sORFs) in the initially annotated noncoding RNA LINC00493 from human cells.

Whole transcriptome analyses have revealed that mammalian genomes are massively transcribed, resulting in the production of huge numbers of transcripts with unknown functions (TUFs). Previous research has categorized most TUFs as noncoding RNAs (ncRNAs) because most previously studied TUFs do not encode open reading frames (ORFs) with biologically significant lengths [>100 amino acids (AAs)]. Recent studies, however, have reported that several transcripts harbouring small ORFs that encode peptides shorter than 100 AAs are translated and play important biological functions. Here, we examined the translational capacity of transcripts annotated as ncRNAs in human cells, and identified several hundreds of ribosome-associated transcripts previously annotated as ncRNAs. Ribosome footprinting and polysome profiling analyses revealed that 61 of them are potentially translatable. Among them, 45 were nonnonsense-mediated mRNA decay targets, suggesting that they are productive mRNAs. We confirmed the translation of one ncRNA, LINC00493, by luciferase reporter assaying and western blotting of a FLAG-tagged LINC00493 peptide. While proteomic analysis revealed that the LINC00493 peptide interacts with many mitochondrial proteins, immunofluorescence assays showed that its peptide is mitochondrially localized. Our findings indicate that some transcripts annotated as ncRNAs encode peptides and that unannotated peptides may perform important roles in cells.

A new computational method to predict transcriptional activity of a DNA sequence from diverse datasets of massively parallel reporter assays.

In recent years, the dramatic increase in the number of applications for massively parallel reporter assay (MPRA) technology has produced a large body of data for various purposes. However, a computational model that can be applied to decipher regulatory codes for diverse MPRAs does not exist yet. Here, we propose a new computational method to predict the transcriptional activity of MPRAs, as well as luciferase reporter assays, based on the TRANScription FACtor database. We employed regression trees and multivariate adaptive regression splines to obtain these predictions and considered a feature redundancy-dependent formula for conventional regression trees to enable adaptation to diverse data. The developed method was applicable to various MPRAs despite the use of different types of transfected cells, sequence lengths, construct numbers and sequence types. We demonstrate that this method can predict the transcriptional activity of promoters in HEK293 cells through predictive functions that were estimated by independent assays in eight tumor cell lines. The prediction was generally good (Pearson's r = 0.68) which suggested that common active transcription factor binding sites across different cell types make greater contributions to transcriptional activity and that known promoter activity could confer transcriptional activity of unknown promoters in some instances, regardless of cell type.

Identification of Minimal p53 Promoter Region Regulated by MALAT1 in Human Lung Adenocarcinoma Cells.

The MALAT1 long noncoding RNA is strongly linked to cancer progression. Here we report a MALAT1 function in repressing the promoter of p53 (TP53) tumor suppressor gene. p21 and FAS, well-known p53 targets, were upregulated by MALAT1 knockdown in A549 human lung adenocarcinoma cells. We found that these upregulations were mediated by transcriptional activation of p53 through MALAT1 depletion. In addition, we identified a minimal MALAT1-responsive region in the P1 promoter of p53 gene. Flow cytometry analysis revealed that MALAT1-depleted cells exhibited G1 cell cycle arrest. These results suggest that MALAT1 affects the expression of p53 target genes through repressing p53 promoter activity, leading to influence the cell cycle progression.

Analysis of RNA decay factor mediated RNA stability contributions on RNA abundance.

BACKGROUND: Histone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels. However, this estimation does not always correlate with eventual RNA expression levels measured by RNA sequencing (RNA-seq). Part of the inconsistency may arise from the variance in RNA stability, where the transcripts that are more or less abundant than predicted RNA expression from histone epigenome data are inferred to be more or less stable. However, there is little systematic analysis to validate this assumption. Here, we used stability data of whole transcriptome measured by 5'-bromouridine immunoprecipitation chase sequencing (BRIC-seq), which enabled us to determine the half-lives of whole transcripts including lincRNAs, and we integrated BRIC-seq with ChIP-seq to achieve better estimation of the eventual transcript levels and to understand the importance of post-transcriptional regulation that determine the eventual transcript levels. RESULTS: We identified discrepancies between the RNA abundance estimated by ChIP-seq and measured RNA expression from RNA-seq; for number of genes and estimated that the expression level of 865 genes was controlled at the level of RNA stability in HeLa cells. ENCODE data analysis supported the idea that RNA stability control aids to determine transcript levels in multiple cell types. We identified UPF1, EXOSC5 and STAU1, well-studied RNA degradation factors, as controlling factors for 8% of cases. Computational simulations reasonably explained the changes of eventual mRNA levels attributable to the changes in the rates of mRNA half-lives. In addition, we propose a feedback circuit that includes the regulated degradation of mRNAs encoding transcription factors to maintain the steady state level of RNA abundance. Intriguingly, these regulatory mechanisms were distinct between mRNAs and lincRNAs. CONCLUSIONS: Integrative analysis of ChIP-seq, RNA-seq and our BRIC-seq showed that transcriptional regulation and RNA degradation are independently regulated. In addition, RNA stability is an important determinant of eventual transcript levels. RNA binding proteins, such as UPF1, STAU1 and EXOSC5 may play active roles in such controls.

Long noncoding RNA NEAT1-dependent SFPQ relocation from promoter region to paraspeckle mediates IL8 expression upon immune stimuli.

Although thousands of long noncoding RNAs (lncRNAs) are localized in the nucleus, only a few dozen have been functionally characterized. Here we show that nuclear enriched abundant transcript 1 (NEAT1), an essential lncRNA for the formation of nuclear body paraspeckles, is induced by influenza virus and herpes simplex virus infection as well as by Toll-like receptor3-p38 pathway-triggered poly I:C stimulation, resulting in excess formation of paraspeckles. We found that NEAT1 facilitates the expression of antiviral genes including cytokines such as interleukin-8 (IL8). We found that splicing factor proline/glutamine-rich (SFPQ), a NEAT1-binding paraspeckle protein, is a repressor of IL8 transcription, and that NEAT1 induction relocates SFPQ from the IL8 promoter to the paraspeckles, leading to transcriptional activation of IL8. Together, our data show that NEAT1 plays an important role in the innate immune response through the transcriptional regulation of antiviral genes by the stimulus-responsive cooperative action of NEAT1 and SFPQ.

Identification of hundreds of novel UPF1 target transcripts by direct determination of whole transcriptome stability.

UPF1 eliminates aberrant mRNAs harboring premature termination codons, and regulates the steady-state levels of normal physiological mRNAs. Although genome-wide studies of UPF1 targets performed, previous studies did not distinguish indirect UPF1 targets because they could not determine UPF1-dependent altered RNA stabilities. Here, we measured the decay rates of the whole transcriptome in UPF1-depleted HeLa cells using BRIC-seq, an inhibitor-free method for directly measuring RNA stability. We determined the half-lives and expression levels of 9,229 transcripts. An amount of 785 transcripts were stabilized in UPF1-depleted cells. Among these, the expression levels of 76 transcripts were increased, but those of the other 709 transcripts were not altered. RNA immunoprecipitation showed UPF1 bound to the stabilized transcripts, suggesting that UPF1 directly degrades the 709 transcripts. Many UPF1 targets in this study were newly identified. This study clearly demonstrates that direct determination of RNA stability is a powerful approach for identifying targets of RNA degradation factors.

Linear regression models predicting strength of transcriptional activity of promoters.

We developed linear regression models which predict strength of transcriptional activity of promoters from their sequences. Intrinsic transcriptional strength data of 451 human promoter sequences in three cell lines (HEK293, MCF7 and 3T3), which were measured by systematic luciferase reporter gene assays, were used to build the models. The models sum up contributions of CG dinucleotide content and transcription factor binding sites (TFBSs) to transcriptional strength. We evaluated prediction accuracies of the models by cross validation tests and found that they have adequate ability for predicting transcriptional strength of promoters in spite of their simple formalization. We also evaluated statistical significance of the contributions and proposed a picture of regulatory code hidden in promoter sequences. That is, CG dinucleotide content and TFBSs mainly determine strength of transcriptional activity under ubiquitous and specific environments, respectively.

Analysis of the promoter of mutated human whey acidic protein (WAP) gene.

Although whey acidic protein (WAP) has been identified in the milk of a range of species, it has been predicted that WAP is not secreted into human milk as a result of critical point mutations within the coding region. In the present study, we first investigated computationally the promoter region of mutated human WAP genes by comparing with those of other known WAP genes. Computational database analyses showed that the human WAP promoter region was highly conserved, as in other species with milk WAP. Next, we evaluated the activity of the human WAP promoter (2.6 kb) using a reporter gene assay. MCF-7 cells were stably transfected with the hWAP/hGH (human growth hormone) fusion gene, cultured on Matrigel, and treated with lactogenic hormones. Radioimmunoassay detected hGH in the culture medium, indicating that the human WAP promoter was responsible for the lactogenic hormones. The human WAP promoter was significantly more active in MCF-7 cells than the mouse WAP promoter (2.4 kb). The present results provide us with important information on the molecular evolution of milk protein genes.

Chromosome-wide assessment of replication timing for human chromosomes 11q and 21q: disease-related genes in timing-switch regions.

The completion of the human genome sequence will greatly accelerate development of a new branch of bioscience and provide fundamental knowledge to biomedical research. We used the sequence information to measure replication timing of the entire lengths of human chromosomes 11q and 21q. Megabase-sized zones that replicate early or late in S phase (thus early/late transition) were defined at the sequence level. Early zones were more GC-rich and gene-rich than were late zones, and early/late transitions occurred primarily at positions identical to or near GC% transitions. We also found the single nucleotide polymorphism (SNP) frequency was high in the late-replicating and replication-transition regions. In the early/late transition regions, concentrated occurrence of cancer-related genes that include CCND1 encoding cyclin D1 (BCL1), FGF4 (KFGF), TIAM1 and FLI1, was observed. The transition regions contained other disease-related genes including APP associated with familial Alzheimer's disease (AD1), SOD1 associated with familial amyotrophic lateral sclerosis (ALS1) and PTS associated with phenylketonuria. These findings are discussed with respect to the prediction that increased DNA damage occurs in replication-transition regions. We propose that genome-wide assessment of replication timing serves as an efficient strategy for identifying disease-related genes.