Analysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genes

Simple item page
dc.creatorRichardson, Casey R. (TTU)
dc.creatorLuo, Qing-Jun (TTU)
dc.creatorGontcharova, Viktoria (TTU)
dc.creatorJiang, Ying-Wen (TTU)
dc.creatorSamanta, Manoj
dc.creatorYoun, Eunseog (TTU)
dc.creatorRock, Christopher D. (TTU)
dc.date.accessioned2022-05-17T19:03:55Z
dc.date.available2022-05-17T19:03:55Z
dc.date.issued2010
dc.description© 2010 Richardson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.description.abstractBackground: MicroRNAs (miRNAs) and trans-acting small-interfering RNAs (tasi-RNAs) are small (20–22 nt long) RNAs (smRNAs) generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs) are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery. Principal Findings: We explored rice (Oryza sativa) sense and antisense gene expression in publicly available whole genome tiling array transcriptome data and sequenced smRNA libraries (as well as C. elegans) and found evidence of transitivity of MIRNA genes similar to that found in Arabidopsis. Statistical analysis of antisense transcript abundances, presence of antisense ESTs, and association with smRNAs suggests several hundred Arabidopsis ‘orphan’ hypothetical genes are non-coding RNAs. Consistent with this hypothesis, we found novel Arabidopsis homologues of some MIRNA genes on the antisense strand of previously annotated protein-coding genes. A Support Vector Machine (SVM) was applied using thermodynamic energy of binding plus novel expression features of sense/antisense transcription topology and siRNA abundances to build a prediction model of miRNA targets. The SVM when trained on targets could predict the “ancient” (deeply conserved) class of validated Arabidopsis MIRNA genes with an accuracy of 84%, and 76% for “new” rapidly-evolving MIRNA genes. Conclusions: Antisense and smRNA expression features and computational methods may identify novel MIRNA genes and other non-coding RNAs in plants and potentially other kingdoms, which can provide insight into antisense transcription, miRNA evolution, and post-transcriptional gene regulation.en_US
dc.identifier.citationRichardson CR, Luo Q-J, Gontcharova V, Jiang Y-W, Samanta M, et al. (2010) Analysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genes. PLoS ONE 5(5): e10710. doi:10.1371/journal.pone.0010710en_US
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0010710
dc.identifier.urihttps://hdl.handle.net/2346/89197
dc.language.isoengen_US
dc.subjectMicroRNAsen_US
dc.subjectArabidopsis Thalianaen_US
dc.subjectSmall Interfering RNAen_US
dc.subjectPlant Genomicsen_US
dc.subjectGenomic Signal Processingen_US
dc.subjectRiceen_US
dc.subjectSupport Vector Machinesen_US
dc.subjectNon-Coding RNAen_US
dc.titleAnalysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genesen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
rock_article.pdf
Size:
471.39 KB
Format:
Adobe Portable Document Format
Description:
Main article with TTU Libraries cover page
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.57 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Faculty Research