Genome-wide computational identification and manual annotation of human long noncoding RNA genesExperimental evidence suggests that half or more of the mammalian transcriptome consists of noncoding RNA. Noncoding RNAs are divided into short noncoding RNAs (including microRNAs) and long noncoding RNAs (lncRNAs). We defined complementary DNAs (cDNAs) lacking any positive-strand open reading frames (ORFs) longer than 30 amino acids, as well as cDNAs lacking any evidence of interspecies conservation of their longer-than-30-amino acid ORFs, as noncoding. We have identified 5446 lncRNA genes in the human genome from approximately 24,000 full-length cDNAs, using our new ORF-prediction pipeline. We combined them nonredundantly with lncRNAs from four published sources to derive 6736 lncRNA genes. In an effort to distinguish standalone and antisense lncRNA genes from database artifacts, we stratified our catalog of lncRNAs according to the distance between each lncRNA gene candidate and its nearest known protein-coding gene. We concurrently examined the protein-coding capacity of known genes overlapping with lncRNAs. Remarkably, 62% of known genes with "hypothetical protein" names actually lacked protein-coding capacity. This study has greatly expanded the known human lncRNA catalog, increased its accuracy through manual annotation of cDNA-to-genome alignments, and revealed that a large set of hypothetical-protein genes in GenBank lacks protein-coding capacity. In addition, we have developed, independently of existing NCBI tools, command-line programs with high-throughput ORF-finding and BLASTP-parsing functionality, suitable for future automated assessments of protein-coding capacity of novel transcripts.
Long noncoding RNAs are rarely translated in two human cell linesData from the Encyclopedia of DNA Elements (ENCODE) project show over 9640 human genome loci classified as long noncoding RNAs (lncRNAs), yet only ~100 have been deeply characterized to determine their role in the cell. To measure the protein-coding output from these RNAs, we jointly analyzed two recent data sets produced in the ENCODE project: tandem mass spectrometry (MS/MS) data mapping expressed peptides to their encoding genomic loci, and RNA-seq data generated by ENCODE in long polyA+ and polyA- fractions in the cell lines K562 and GM12878. We used the machine-learning algorithm RuleFit3 to regress the peptide data against RNA expression data. The most important covariate for predicting translation was, surprisingly, the Cytosol polyA- fraction in both cell lines. LncRNAs are ~13-fold less likely to produce detectable peptides than similar mRNAs, indicating that ~92% of GENCODE v7 lncRNAs are not translated in these two ENCODE cell lines. Intersecting 9640 lncRNA loci with 79,333 peptides yielded 85 unique peptides matching 69 lncRNAs. Most cases were due to a coding transcript misannotated as lncRNA. Two exceptions were an unprocessed pseudogene and a bona fide lncRNA gene, both with open reading frames (ORFs) compromised by upstream stop codons. All potentially translatable lncRNA ORFs had only a single peptide match, indicating low protein abundance and/or false-positive peptide matches. We conclude that with very few exceptions, ribosomes are able to distinguish coding from noncoding transcripts and, hence, that ectopic translation and cryptic mRNAs are rare in the human lncRNAome.
Sall4 Regulates Distinct Transcription Circuitries in Different Blastocyst-Derived Stem Cell LineagesActivity-Dependent Human Brain Coding/Noncoding Gene Regulatory NetworksWhile most gene transcription yields RNA transcripts that code for proteins, a sizable proportion of the genome generates RNA transcripts that do not code for proteins, but may have important regulatory functions. The brain-derived neurotrophic factor (BDNF) gene, a key regulator of neuronal activity, is overlapped by a primate-specific, antisense long noncoding RNA (lncRNA) called BDNFOS. We demonstrate reciprocal patterns of BDNF and BDNFOS transcription in highly active regions of human neocortex removed as a treatment for intractable seizures. A genome-wide analysis of activity-dependent coding and noncoding human transcription using a custom lncRNA microarray identified 1288 differentially expressed lncRNAs, of which 26 had expression profiles that matched activity-dependent coding genes and an additional 8 were adjacent to or overlapping with differentially expressed protein-coding genes. The functions of most of these protein-coding partner genes, such as ARC, include long-term potentiation, synaptic activity, and memory. The nuclear lncRNAs NEAT1, MALAT1, and RPPH1, composing an RNAse P-dependent lncRNA-maturation pathway, were also upregulated. As a means to replicate human neuronal activity, repeated depolarization of SY5Y cells resulted in sustained CREB activation and produced an inverse pattern of BDNF-BDNFOS co-expression that was not achieved with a single depolarization. RNAi-mediated knockdown of BDNFOS in human SY5Y cells increased BDNF expression, suggesting that BDNFOS directly downregulates BDNF. Temporal expression patterns of other lncRNA-messenger RNA pairs validated the effect of chronic neuronal activity on the transcriptome and implied various lncRNA regulatory mechanisms. lncRNAs, some of which are unique to primates, thus appear to have potentially important regulatory roles in activity-dependent human brain plasticity.
Mining Affymetrix microarray data for long non-coding RNAs: altered expression in the nucleus accumbens of heroin abusersAlthough recent data suggest that some long non-coding RNAs (lncRNAs) exert widespread effects on gene expression and organelle formation, lncRNAs as a group constitute a sizable but poorly characterized fraction of the human transcriptome. We investigated whether some human lncRNA sequences were fortuitously represented on commonly used microarrays, then used this annotation to assess lncRNA expression in human brain. A computational and annotation pipeline was developed to identify lncRNA transcripts represented on Affymetrix U133 arrays. A previously published dataset derived from human nucleus accumbens was then examined for potential lncRNA expression. Twenty-three lncRNAs were determined to be represented on U133 arrays. Of these, dataset analysis revealed that five lncRNAs were consistently detected in samples of human nucleus accumbens. Strikingly, the abundance of these lncRNAs was up-regulated in human heroin abusers compared to matched drug-free control subjects, a finding confirmed by quantitative PCR. This study presents a paradigm for examining existing Affymetrix datasets for the detection and potential regulation of lncRNA expression, including changes associated with human disease. The finding that all detected lncRNAs were up-regulated in heroin abusers is consonant with the proposed role of lncRNAs as mediators of widespread changes in gene expression as occur in drug abuse.