A novel experimental approach for systematic identification of box H/ACA snoRNAs from eukaryotes

Gu, Ai Di; Zhou, Hui; Yu, Chun Hong; Qu, Liang‐Hu

doi:10.1093/nar/gni185

Cited by 23 publications

(20 citation statements)

References 33 publications

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“…These box H/ACA RNAs were cloned from a HeLa cell extract immunoprecipitated with an anti-GAR1 antibody (18) or their expression were verified by Northern blot and primer extension (8,13,15). Clearly, these snoRNAs were formed by retrotransposition in the course of primate evolution, for example, the data obtained in this study suggest that the ACA63 gene originated as the result of retroposition of the ACA63b copy.…”

Section: Resultsmentioning

confidence: 99%

Genome-wide analyses of retrogenes derived from the human box H/ACA snoRNAs

Luo

Li²

2006

Nucleic Acids Research

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The family of box H/ACA snoRNA is an abundant class of non-protein-coding RNAs, which play important roles in the post-transcriptional modification of rRNAs and snRNAs. Here we report the characterization in the human genome of 202 sequences derived from box H/ACA snoRNAs. Most of them were retrogenes formed using the L1 integration machinery. About 96% of the box H/ACA RNA-related sequences are found in corresponding locations on the chimpanzee and human chromosomes, while the mouse shares ∼50% of these human sequences, suggesting that some of the H/ACA RNA-related sequences in primate occurred after the rodent/primate divergence. Of the H/ACA RNA-related sequences, 49% are found in intronic regions of protein-coding genes and 64 H/ACA-related sequences can be folded to the typical secondary structure of the box H/ACA snoRNA family, while 30 of them were recognized as functional homologs of their corresponding box H/ACA snoRNAs previously reported. Of the 64 sequences with the typical secondary structure of the box H/ACA RNA family, 11 were found in EST databases and 5 among which were shown to be expressed in more than one human tissue. Notably, U107f is nested in an intron of a protein gene coding for nudix-type motif 13, but expressed from the opposite strand, and the searching of EST databases revealed it can be expressed in liver and spleen, even in melanotic melanoma.

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Section: Resultsmentioning

confidence: 99%

Genome-wide analyses of retrogenes derived from the human box H/ACA snoRNAs

Luo

Li²

2006

Nucleic Acids Research

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“…In addition to rRNA modification, snoR11 is predicted to modify the U at position 5 near the 59 end of U1 snRNA. In human, the homologous residue (U6) interacts with the 59 splice site during pre-mRNA splicing, and is pseudouridylated (Reddy et al 1981b), possibly by an H/ACA scaRNA, U109 (Gu et al 2005;Lestrade and Weber 2006).…”

Section: Pseudouridylation Guide (H/aca Box) Rnasmentioning

confidence: 99%

Structural RNAs of known and unknown function identified in malaria parasites by comparative genomics and RNA analysis

Chakrabarti¹,

Pearson²,

Grate³

et al. 2007

RNA

115

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As the genomes of more eukaryotic pathogens are sequenced, understanding how molecular differences between parasite and host might be exploited to provide new therapies has become a major focus. Central to cell function are RNA-containing complexes involved in gene expression, such as the ribosome, the spliceosome, snoRNAs, RNase P, and telomerase, among others. In this article we identify by comparative genomics and validate by RNA analysis numerous previously unknown structural RNAs encoded by the Plasmodium falciparum genome, including the telomerase RNA, U3, 31 snoRNAs, as well as previously predicted spliceosomal snRNAs, SRP RNA, MRP RNA, and RNAse P RNA. Furthermore, we identify six new RNA coding genes of unknown function. To investigate the relationships of the RNA coding genes to other genomic features in related parasites, we developed a genome browser for P. falciparum (http://areslab.ucsc.edu/cgi-bin/hgGateway). Additional experiments provide evidence supporting the prediction that snoRNAs guide methylation of a specific position on U4 snRNA, as well as predicting an snRNA promoter element particular to Plasmodium sp. These findings should allow detailed structural comparisons between the RNA components of the gene expression machinery of the parasite and its vertebrate hosts.

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“…Early screens for snoRNAs used experimental methods and yielded relatively few genes (Ni et al 1997;Liang-Hu et al 2001;Higa et al 2002;Wachi et al 2004;Yang et al 2005) because experimental methods tend to be biased in favor of highly expressed sequences (Hüttenhofer et al 2001;Gu et al 2005). More recent efforts combined bioinformatics methods with sequencing of cDNA libraries or microarray data to carry out genome-wide scans-Caenorhabditis elegans Zemann et al 2006;Huang et al 2007); other genomes: mouse (Hüttenhofer et al 2001), Arabidopsis thaliana (Marker et al 2002), and Drosophila melanogaster (Yuan et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Computational prediction of Caenorhabditis box H/ACA snoRNAs using genomic properties of their host genes

Wang

Ruvinsky

2009

RNA

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Identification of small nucleolar RNAs (snoRNAs) in genomic sequences has been challenging due to the relative paucity of sequence features. Many current prediction algorithms rely on detection of snoRNA motifs complementary to target sites in snRNAs and rRNAs. However, recent discovery of snoRNAs without apparent targets requires development of alternative prediction methods. We present an approach that combines rule-based filters and a Bayesian Classifier to identify a class of snoRNAs (H/ACA) without requiring target sequence information. It takes advantage of unique attributes of their genomic organization and improved species-specific motif characterization to predict snoRNAs that may otherwise be difficult to discover. Searches in the genomes of Caenorhabditis elegans and the closely related Caenorhabditis briggsae suggest that our method performs well compared to recent benchmark algorithms. Our results illustrate the benefits of training gene discovery engines on features restricted to particular phylogenetic groups and the utility of incorporating diverse data types in gene prediction.

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A novel experimental approach for systematic identification of box H/ACA snoRNAs from eukaryotes

Cited by 23 publications

References 33 publications

Genome-wide analyses of retrogenes derived from the human box H/ACA snoRNAs

Genome-wide analyses of retrogenes derived from the human box H/ACA snoRNAs

Structural RNAs of known and unknown function identified in malaria parasites by comparative genomics and RNA analysis

Computational prediction of Caenorhabditis box H/ACA snoRNAs using genomic properties of their host genes

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