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Title: Most “Dark Matter” Transcripts Are Associated With Known Genes}
Article:
Abstract:
A series of reports over the last few years have indicated that a much larger portion of the mammalian genome is transcribed than can be accounted for by currently annotated genes, but the quantity and nature of these additional transcripts remains unclear. Here, we have used data from single- and paired-end RNA-Seq and tiling arrays to assess the quantity and composition of transcripts in PolyA+ RNA from human and mouse tissues. Relative to tiling arrays, RNA-Seq identifies many fewer transcribed regions( “seqfrags”) outside known exons and ncRNAs. Most nonexonic seqfrags are in introns, raising the possibility that they are fragments of pre-mRNAs. The chromosomal locations of the majority of intergenic seqfrags in RNA-Seq data are near known genes, consistent with alternative cleavage and polyadenylation site usage, promoter- and terminator-associated transcripts, or new alternative exons; indeed, reads that bridge splice sites identified 4, 544 new exons, affecting 3, 554 genes. Most of the remaining seqfrags correspond to either single reads that display characteristics of random sampling from a low-level background or several thousand small transcripts( median length = 111 bp) present at higher levels, which also tend to display sequence conservation and originate from regions with open chromatin. We conclude that, while there are bona fide new intergenic transcripts, their number and abundance is generally low in comparison to known exons, and the genome is not as pervasively transcribed as previously reported.
Introduction:
In recent years established views of transcription have been challenged by the observation that a much larger portion of the human and mouse genomes is transcribed than can be accounted for by currently annotated coding and noncoding genes. The bulk of these findings have come from experiments using “tiling” microarrays with probes that cover the non-repetitive genome at regular intervals[1]–[9], or from sequencing efforts of full-length cDNA libraries enriched for rare transcripts[10],[11]. Additionally, capped analysis of gene expression( CAGE) in human and mouse show that a significant number of sequenced 5′ tags map to intergenic regions[12]. Estimates of the proportion of transcripts that map to locations separate from known exons range from 47% to 80% and are distributed approximately equally between introns and intergenic regions. Dubbed transcriptional “dark matter”[13], the “hidden” transcriptome[1], or transcripts of unknown function( TUFs)[4],[14], the exact nature of much of this additional transcription is unclear, but it has been presumed to comprise a combination of novel protein coding transcripts, extensions of existing transcripts, noncoding RNAs( ncRNAs), antisense transcripts, and biological or experimental background. Determining the relative contributions of each of these potential sources is important for understanding the nature and possible biological function of transcriptional dark matter. Homology searches for transcripts mapping outside known annotation boundaries[10], as well as cDNA sequencing efforts, indicate that it is still possible to find new exons of protein coding genes[10],[15],[16]. The genomic positions of TUFs are also biased towards known transcripts[8], suggesting that at least a portion may represent extensions of current gene annotations. Nevertheless, the majority of dark matter transcripts is thought to be noncoding[2],[4],[5],[10]. Previous efforts to characterize dark matter transcripts have revealed the existence of thousands of ncRNAs with evidence for tissue-specific expression[17],[18], as well as over a thousand large intervening noncoding RNAs( lincRNAs) originating from intergenic regions bearing chromatin marks associated with transcription[19]. Other studies have reported new classes of ncRNAs, such as those that cluster close to the transcription start sites( TSSs) of protein coding genes[20]–[24]. These promoter-associated RNAs( pasRNAs) typically initiate in the nucleosome free regions that mark a TSS, with transcription occurring in both directions. Finally, results from the ENCODE pilot project have suggested a highly interleaved structure of the human transcriptome, with an estimate that as much as 93% of the human genome may give rise to primary transcripts[9]. Though this estimate was based on a combination of sources that included rapid amplification of cDNA ends coupled to detection on tiling arrays( RACE-tiling), manually curated GENCODE annotations, and paired-end sequencing of long cDNAs( GIS-PET), it was dominated by the results of RACE-tiling experiments that alone found 80% genome coverage, compared to 64. 6% and 66. 4% for GENCODE annotations and GIS-PET, respectively. The fact that most TUFs do not appear to be under evolutionary selective pressure[25] has prompted suggestions that at least some of the transcriptional dark matter may constitute “leaky” background transcription[9],[26]. Consistent with this notion, many of the intergenic and intronic transcripts are detected at low levels, close to the detection limit of qPCR or Northern blots[13]. Presumably as a consequence, validation rates for unannotated transcribed regions detected in tiling array experiments have varied between 25% and 70%[1],[5],[27], and a comparison[13] of human chromosome 22 data from three major tiling array studies done on different platforms[1],[3],[27] also revealed little overlap of expressed probes, with 89% of overlapping positive probes mapping to exons or introns of known transcripts. While this low overlap may be due to differences in the samples analyzed[4], there is also evidence that some dark matter transcripts may be due to experimental artifacts. For example, a reassessment of the analysis parameters used in the tiling array study by Kampa et al.[2] revealed a similar number of transcribed fragments in real and randomized microarray data[28]. These issues make it difficult to assess the level of false positives in tiling array experiments. Transcriptome sequencing( RNA-Seq) has emerged as a new technology that does not suffer from many of the limitations of array platforms such as cross-hybridization[29]. The technique has a wide dynamic range spanning at least four to five orders of magnitude[30],[31] and allows accurate quantitation of expression levels, as determined by experiments using externally spiked-in RNA controls and quantitative PCR[30]. These characteristics make RNA-Seq suitable to accurately assess the relative proportion of sequence from the known versus the dark matter transcriptome. Comparisons between studies of eukaryotic transcriptomes have shown that the estimated proportion of transcriptional dark matter reported in RNA-Seq studies is consistently lower than estimates from tiling arrays[32]. Although most RNA-Seq studies to date have focused on polyadenylated( PolyA+) RNA, which would be enriched for coding transcripts, this cannot fully account for the differences, as most tiling array studies show nearly the same degree of nonexonic transcription for PolyA+ as for total RNA sources[1]–[9]. Indeed, it was reported that even in the most mature form of PolyA+ RNA isolated from the cytosol, approximately half of the transcribed sequence does not correspond to known exons[5]. Moreover, RNA-Seq data from Arabidobsis rRNA-depleted total RNA samples contained a relatively small proportion( 3. 5%) of intergenic reads[33]. These results may not be characteristic of the larger and more complex human and mouse transcriptomes, but they do present an example in which the proportion of dark matter transcripts is relatively low in a more heterogeneous RNA pool. Other studies, in contrast, reported a higher proportion of nonexonic reads in yeast[34] and for total RNA in human[35], leaving unresolved the question of the quantity and character of dark matter transcripts. To investigate the extent and nature of transcriptional dark matter, we have analyzed a diverse set of human and mouse tissues and cell lines using tiling microarrays and RNA-Seq. A meta-analysis of single- and paired-end read RNA-Seq data reveals that the proportion of transcripts originating from intergenic and intronic regions is much lower than identified by whole-genome tiling arrays, which appear to suffer from high false-positive rates for transcripts expressed at low levels. The majority of RNA-Seq reads that map to intergenic regions either display a high degree of correlation with neighboring genes or are associated with more than 10, 000 potential novel exonic fragments we identified in human and mouse. A genome-wide analysis of “de novo” splice junctions in human samples further revealed 2, 789 previously uncharacterized transcript fragments that have no overlap with exons of known gene annotations, 1, 259 of which map to intergenic regions. We also find 4, 544 additional exons for annotated transcripts, 723 of which extend transcripts at the 5′ end and include likely alternative promoters. The novel exons from spliced transcripts are supported by EST data, are generally more conserved, and derive from coding as well as noncoding transcripts. We conclude that analysis of data from tiling arrays leads to vast overestimates of the proportion of transcriptional dark matter. However, the mammalian transcriptome does contain thousands of unannotated transcripts, exons, promoters, and termination sites. Intriguingly, there is a strong overlap of short intergenic transcripts with DNase I hypersensitive sites, suggesting that they may be the equivalent of pasRNAs for distant enhancers.
Discussion:
In contrast to earlier studies based on oligonucleotide tiling array analysis of RNA[1]–[9], GIS-PET[9], and RACE-tiling arrays[9], but consistent with other RNA-Seq studies[16],[33],[36]–[38], we find that the proportion of dark matter transcripts among polyadenylated RNA from a large variety of different tissue types is small. Our comparison between tiling arrays and RNA-Seq data from the same tissues indicates that tiling arrays are ill-suited to accurately detect transcripts expressed at low levels. The major fraction of nonexonic transcripts in RNA-Seq data is associated with known genes and includes thousands of new alternative exons and hundreds of alternative promoters. However, we do not find evidence for widespread interleaved transcripts as previously described[9]; virtually all exon-exon junctions detected correspond to junctions within the same gene. Aside from new exons, most of the transcripts that are within or proximal to known genes can be explained as pasRNAs or terminator-associated RNAs, pre-mRNA fragments, or by alternative cleavage and polyadenylation site usage. The relatively small fraction of seqfrags that are not associated with known genes corresponds strongly to DNase I-hypersensitive regions. Altogether, we propose that most of the dark matter transcriptome may result from the process of transcribing known genes. Pervasive transcription of intergenic regions as described in previous studies occurs at a significantly reduced level and is of a random character. The intergenic regions that are transcribed above background consist of a mix of both coding and noncoding transcripts. In contrast to the extensive intergenic transcription reported in tiling array studies, we found relatively few transcripts in these regions( 16, 268 seqfrags expressed above background levels in human and 11, 533 in mouse). These numbers may be smaller, as some adjacent seqfrags may be parts of a single transcript that contain regions with sequence mapping ambiguities, or they may be larger as more tissues and cell types are surveyed. The fact that non-exonic transcripts do not overlap with Evofold or RNAz regions argues against widespread roles as structural RNA. The most compelling support that these transcripts may have an independent function comes from the fact that they overlap with DNase I hypersensitive regions and that, unlike the many transcripts found by tiling array studies and from deep sequencing of subtracted cDNA libraries[11], the transcripts found by RNA-Seq show a significantly higher degree of conservation between species. We note, however, that these same two properties are consistent with low-level transcription from enhancers. Indeed, in yeast, it is known that placement of a strong activating transcription factor binding site in random regions of the genome results in the formation of a promoter[56]. Thus, single-exon intergenic seqfrags may represent the analog of pasRNAs for enhancers. Our findings are based primarily on analysis of PolyA+ enriched RNA; however, our conclusions are corroborated by CAGE tags, GIS-PET, and RNA-Seq analysis of rRNA-depleted total RNA. Similar conclusions to ours were also reached in an independent RNA-Seq analysis of rRNA-depleted human total RNA( G. Schroth, pers. communication). It does not appear as if additional sequencing would substantially alter our conclusions, since coverage bias towards known exons increases with the number of reads. Moreover, while RNA-Seq analysis of PolyA+ RNA biases against very long and very short RNAs, this would not be expected to affect our ability to detect the widespread and pervasive transcription reported previously. Nonetheless, analysis of further tissues and cell types would be expected to identify additional intergenic ncRNA seqfrags that are more abundant but expressed in rare or specialized cell types. It is also likely that total RNA harbors additional transcripts not seen in PolyA+ enriched RNA and that are not evident in current total RNA-Seq analyses due to limitations in read counts. A major remaining question is the possible function of the novel intergenic transcripts, if any. Undoubtedly, there are many functional ncRNAs remaining to be characterized[57]. However, we and others have emphasized that expression, conservation, and even localization and physical interactions of these RNAs do not constitute direct evidence for function[32]. Promoters and terminators are known to produce transcripts that appear to be associated primarily with the mechanics of gene expression and do not have known independent functions. To be conservative, a null hypothesis should perhaps be that novel transcripts—particularly those that are small and low-abundance—are a by-product rather than an independent functional unit[58]. Searching for phenotypes caused by genetic perturbation may be the most useful approach to disproving the null hypothesis.
The human genome was sequenced a decade ago , but its exact gene composition remains a subject of debate . The number of protein-coding genes is much lower than initially expected , and the number of distinct transcripts is much larger than the number of protein-coding genes . Moreover , the proportion of the genome that is transcribed in any given cell type remains an open question: results from “tiling” microarray analyses suggest that transcription is pervasive and that most of the genome is transcribed , whereas new deep sequencing-based methods suggest that most transcripts originate from known genes . We have addressed this discrepancy by comparing samples from the same tissues using both technologies . Our analyses indicate that RNA sequencing appears more reliable for transcripts with low expression levels , that most transcripts correspond to known genes or are near known genes , and that many transcripts may represent new exons or aberrant products of the transcription process . We also identify several thousand small transcripts that map outside known genes; their sequences are often conserved and are often encoded in regions of open chromatin . We propose that most of these transcripts may be by-products of the activity of enhancers , which associate with promoters as part of their role as long-range gene regulatory sites . Overall , however , we find that most of the genome is not appreciably transcribed .