Do natural antisense transcripts make sense in eukaryotes?

Vanhée-Brossollet, Christine; Vaquero, Catherine

doi:10.1016/s0378-1119(98)00093-6

Cited by 252 publications

(210 citation statements)

References 58 publications

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“…Sense͞antisense transcript pairs were suggested to be frequent in mammalian genomes and to provide regulatory function (3). In S. cerevisiae, major components of the RNA interference machinery have not been identified (36); however, in other species, alternative mechanisms for regulation by noncoding RNAs exist (2,37). In Drosophila, it has been shown that microRNA predominantly target 3Ј UTRs (38) and these UTRs also tend to be longer than UTRs of genes not targeted (39).…”

Section: Resultsmentioning

confidence: 99%

A high-resolution map of transcription in the yeast genome

David

Huber²,

Granovskaia³

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

612

654

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There is abundant transcription from eukaryotic genomes unaccounted for by protein coding genes. A high-resolution genomewide survey of transcription in a well annotated genome will help relate transcriptional complexity to function. By quantifying RNA expression on both strands of the complete genome of Saccharomyces cerevisiae using a high-density oligonucleotide tiling array, this study identifies the boundary, structure, and level of coding and noncoding transcripts. A total of 85% of the genome is expressed in rich media. Apart from expected transcripts, we found operon-like transcripts, transcripts from neighboring genes not separated by intergenic regions, and genes with complex transcriptional architecture where different parts of the same gene are expressed at different levels. We mapped the positions of 3 and 5 UTRs of coding genes and identified hundreds of RNA transcripts distinct from annotated genes. These nonannotated transcripts, on average, have lower sequence conservation and lower rates of deletion phenotype than protein coding genes. Many other transcripts overlap known genes in antisense orientation, and for these pairs global correlations were discovered: UTR lengths correlated with gene function, localization, and requirements for regulation; antisense transcripts overlapped 3' UTRs more than 5' UTRs; UTRs with overlapping antisense tended to be longer; and the presence of antisense associated with gene function. These findings may suggest a regulatory role of antisense transcription in S. cerevisiae. Moreover, the data show that even this well studied genome has transcriptional complexity far beyond current annotation.tiling array ͉ transcriptone survey ͉ gene architecture ͉ segmentation ͉ antisense regulation P roteins constitute most structural and functional components of cells. The assumption has been that protein-encoding genes are also the main controllers of cellular processes. Recent evidence challenges this assumption, suggesting a wide-spread involvement of noncoding RNA in regulation, including through the activity of untranslated regions of mRNAs (1), antisense transcripts (2, 3), and isolated noncoding RNAs such as microRNA that control transcript levels or their translation (4).High-resolution transcriptome analysis in higher eukaryotes using tiling arrays has improved ORF annotations and exonintron predictions and discovered many new transcripts of currently unknown function (5-7). However, these studies have encountered challenges, due to noise, limited resolution, lack of strand-specific signal, and drawbacks in the analysis methods (8). Sequencing of cloned cDNAs has also revealed a high level of transcriptional complexity, including the presence of many new transcripts, alternative promoter usage, splicing, and polyadenylation, as well as the presence of many sense-antisense transcript pairs (3, 9). However, because of the cost and labor of large-scale sequencing, this approach has been limited. Therefore, there is a need to develop high-throughput, precise, and high-re...

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Section: Resultsmentioning

confidence: 99%

A high-resolution map of transcription in the yeast genome

David

Huber²,

Granovskaia³

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

612

654

View full text Add to dashboard Cite

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“…Sense and antisense genes are encoded on the opposite strands of the same genomic locus and yield transcripts that have sequence complementarity. Their genomic arrangement and sequence complementarity increase the likelihood that their regulation is affected by common factors (such as chromatin state) and their relative expression (such as transcriptional interference), at both the transcriptional and post-transcriptional level (Vanhee-Brossollet and Vaquero 1998;Dahary et al 2005). To date, antisense transcripts have been observed for up to 75% of the mammalian transcriptome in data sets generated by both sequence-based and hybridization-based methods (Katayama et al 2005).…”

Section: Discussionmentioning

confidence: 99%

Next-generation tag sequencing for cancer gene expression profiling

Morrissy¹,

Morin²,

Delaney³

et al. 2009

Genome Res.

295

259

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We describe a new method, Tag-seq, which employs ultra high-throughput sequencing of 21 base pair cDNA tags for sensitive and cost-effective gene expression profiling. We compared Tag-seq data to LongSAGE data and observed improved representation of several classes of rare transcripts, including transcription factors, antisense transcripts, and intronic sequences, the latter possibly representing novel exons or genes. We observed increases in the diversity, abundance, and dynamic range of such rare transcripts and took advantage of the greater dynamic range of expression to identify, in cancers and normal libraries, altered expression ratios of alternative transcript isoforms. The strand-specific information of Tag-seq reads further allowed us to detect altered expression ratios of sense and antisense (S-AS) transcripts between cancer and normal libraries. S-AS transcripts were enriched in known cancer genes, while transcript isoforms were enriched in miRNA targeting sites. We found that transcript abundance had a stronger GC-bias in LongSAGE than Tagseq, such that AT-rich tags were less abundant than GC-rich tags in LongSAGE. Tag-seq also performed better in gene discovery, identifying >98% of genes detected by LongSAGE and profiling a distinct subset of the transcriptome characterized by AT-rich genes, which was expressed at levels below those detectable by LongSAGE. Overall, Tag-seq is sensitive to rare transcripts, has less sequence composition bias relative to LongSAGE, and allows differential expression analysis for a greater range of transcripts, including transcripts encoding important regulatory molecules.

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“…9 Many eukaryotic genes are known to have associated NATs; these include genes involved in regulation of development, cell-cycle, apoptosis and translation. 240 NATs are believed to function as negative regulators of their protein-coding counterparts. There are a variety of ways in which NATs could regulate sense mRNA expression.…”

Section: Disrupted-in-schizophrenia-2 (Disc2)mentioning

confidence: 99%

The DISC locus in psychiatric illness

et al. 2007

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The DISC locus is located at the breakpoint of a balanced t(1;11) chromosomal translocation in a large and unique Scottish family. This translocation segregates in a highly statistically significant manner with a broad diagnosis of psychiatric illness, including schizophrenia, bipolar disorder and major depression, as well as with a narrow diagnosis of schizophrenia alone. Two novel genes were identified at this locus and due to the high prevalence of schizophrenia in this family, they were named Disrupted-in-Schizophrenia-1 (DISC1) and Disrupted-in-Schizophrenia-2 (DISC2). DISC1 encodes a novel multifunctional scaffold protein, whereas DISC2 is a putative noncoding RNA gene antisense to DISC1. A number of independent genetic linkage and association studies in diverse populations support the original linkage findings in the Scottish family and genetic evidence now implicates the DISC locus in susceptibility to schizophrenia, schizoaffective disorder, bipolar disorder and major depression as well as various cognitive traits. Despite this, with the exception of the t(1;11) translocation, robust evidence for a functional variant(s) is still lacking and genetic heterogeneity is likely. Of the two genes identified at this locus, DISC1 has been prioritized as the most probable candidate susceptibility gene for psychiatric illness, as its protein sequence is directly disrupted by the translocation. Much research has been undertaken in recent years to elucidate the biological functions of the DISC1 protein and to further our understanding of how it contributes to the pathogenesis of schizophrenia. These data are the main subject of this review; however, the potential involvement of DISC2 in the pathogenesis of psychiatric illness is also discussed. A detailed picture of DISC1 function is now emerging, which encompasses roles in neurodevelopment, cytoskeletal function and cAMP signalling, and several DISC1 interactors have also been defined as independent genetic susceptibility factors for psychiatric illness. DISC1 is a hub protein in a multidimensional risk pathway for major mental illness, and studies of this pathway are opening up opportunities for a better understanding of causality and possible mechanisms of intervention. Molecular Psychiatry (2008) 13, 36-64; doi:10.1038/sj.mp.4002106; published online 2 October 2007 Keywords: schizophrenia; bipolar disorder; depression; DISC1; DISC2; mouse models Genetics of DISC1 discoverySt Clair et al. 1 first reported a Scottish family with a high loading of major mental illness, which cosegregates with a t(1;11) translocation. Long-term follow-up of this family over a period of 30 years has reported 87 family members, of whom 37 carry the translocation. 2 Of 29 individuals carrying the translocation, for whom psychiatric assessment was possible, 7 have a diagnosis of schizophrenia, 1 has a diagnosis of bipolar disorder and 10 cases of recurrent major depression were also reported. 2 Thus, 18 of 29 translocation carriers are diagnosed with major mental illness whereas none of...

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Do natural antisense transcripts make sense in eukaryotes?

Cited by 252 publications

References 58 publications

A high-resolution map of transcription in the yeast genome

A high-resolution map of transcription in the yeast genome

Next-generation tag sequencing for cancer gene expression profiling

The DISC locus in psychiatric illness

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