ゲノム配列からのマイクロRNA遺伝子と偽遺伝子の発見

学位の種別: 論文博士審査委員会委員 : (主査)東京大学教授 浅井 潔, 東京大学准教授 程 久美子, 北海道大学教授 廣瀬 哲郎, 早稲田大学准教授 浜田 道昭University of Tokyo(東京大学

fRNAdb: a platform for mining/annotating functional RNA candidates from non-coding RNA sequences

There are abundance of transcripts that code for no particular protein and that remain functionally uncharacterized. Some of these transcripts may have novel functions while others might be junk transcripts. Unfortunately, the experimental validation of such transcripts to find functional non-coding RNA candidates is very costly. Therefore, our primary interest is to computationally mine candidate functional transcripts from a pool of uncharacterized transcripts. We introduce fRNAdb: a novel database service that hosts a large collection of non-coding transcripts including annotated/non-annotated sequences from the H-inv database, NONCODE and RNAdb. A set of computational analyses have been performed on the included sequences. These analyses include RNA secondary structure motif discovery, EST support evaluation, cis-regulatory element search, protein homology search, etc. fRNAdb provides an efficient interface to help users filter out particular transcripts under their own criteria to sort out functional RNA candidates. fRNAdb is available a

Discovery of short pseudogenes derived from messenger RNAs

More than 40% of the human genome is generated by retrotransposition, a series of in vivo processes involving reverse transcription of RNA molecules and integration of the transcripts into the genomic sequence. The mechanism of retrotransposition, however, is not fully understood, and additional genomic elements generated by retrotransposition may remain to be discovered. Here, we report that the human genome contains many previously unidentified short pseudogenes generated by retrotransposition of mRNAs. Genomic elements generated by non-long terminal repeat retrotransposition have specific sequence signatures: a poly-A tract that is immediately downstream and a pair of duplicated sequences, called target site duplications (TSDs), at either end. Using a new computer program, TSDscan, that can accurately detect pseudogenes based on the presence of the poly-A tract and TSDs, we found 654 short (≤300 bp), previously unknown pseudogenes derived from mRNAs. Comprehensive analyses of the pseudogenes that we identified and their parent mRNAs revealed that the pseudogene length depends on the parent mRNA length: long mRNAs generate more short pseudogenes than do short mRNAs. To explain this phenomenon, we hypothesize that most long mRNAs are truncated before they are reverse transcribed. Truncated mRNAs would be rapidly degraded during reverse transcription, resulting in the generation of short pseudogenes

Prediction of conserved precursors of miRNAs and their mature forms by integrating position-specific structural features.

MicroRNA (miRNA) precursor hairpins have a unique secondary structure, nucleotide length, and nucleotide content that are in most cases evolutionarily conserved. The aim of this study was to utilize position-specific features of miRNA hairpins to improve their identification. To this end, we defined the evolutionary and structurally conserved features in each position of miRNA hairpins with heuristically derived values, which were successfully integrated using a probabilistic framework. Our method, miRRim2, can not only accurately detect miRNA hairpins, but infer the location of a mature miRNA sequence. To evaluate the accuracy of miRRim2, we designed a cross validation test in which the whole human genome was used for evaluation. miRRim2 could more accurately detect miRNA hairpins than the other computational predictions that had been performed on the human genome, and detect the position of the 5'-end of mature miRNAs with sensitivity and positive predictive value (PPV) above 0.4. To further evaluate miRRim2 on independent data, we applied it to the Ciona intestinalis genome. Our method detected 47 known miRNA hairpins among top 115 candidates, and pinpointed the 5'-end of mature miRNAs with sensitivity and PPV about 0.4. When our results were compared with deep-sequencing reads of small RNA libraries from Ciona intestinalis cells, we found several candidates in which the predicted mature miRNAs were in good accordance with deep-sequencing results

LncRNA-dependent nuclear stress bodies promote intron retention through SR protein phosphorylation

A number of long noncoding RNAs (lncRNAs) are induced in response to specific stresses to construct membrane-less nuclear bodies; however, their function remains poorly understood. Here, we report the role of nuclear stress bodies (nSBs) formed on highly repetitive satellite III (HSATIII) lncRNAs derived from primate-specific satellite III repeats upon thermal stress exposure. A transcriptomic analysis revealed that depletion of HSATIII lncRNAs, resulting in elimination of nSBs, promoted splicing of 533 retained introns during thermal stress recovery. A HSATIII-Comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) analysis identified multiple splicing factors in nSBs, including serine and arginine-rich pre-mRNA splicing factors (SRSFs), the phosphorylation states of which affect splicing patterns. SRSFs are rapidly de-phosphorylated upon thermal stress exposure. During stress recovery, CDC like kinase 1 (CLK1) was recruited to nSBs and accelerated the re-phosphorylation of SRSF9, thereby promoting target intron retention. Our findings suggest that HSATIII-dependent nSBs serve as a conditional platform for phosphorylation of SRSFs by CLK1 to promote the rapid adaptation of gene expression through intron retention following thermal stress exposure

miRRim: A novel system to find conserved miRNAs with high sensitivity and specificity

The identification of novel miRNAs has significant biological and clinical importance. However, none of the known miRNA features alone is sufficient for accurately detecting novel miRNAs. The aim of this paper is to integrate these features in a straightforward manner for detecting miRNAs with better accuracy. Since most miRNA regions are highly conserved among vertebrates for the ability to form stable hairpin structures, we implemented a hidden Markov model that outputs multidimensional feature vectors composed of both evolutionary features and secondary structural ones. The proposed method, called miRRim, outperformed existing ones in terms of detection/prediction performance: The total number of predictions was smaller than with existing methods when the number of miRNAs detected was adjusted to be the same. Moreover, there were several candidates predicted only by our method that are clustered with the known miRNAs, suggesting that our method is able to detect novel miRNAs. Genomic coordinates of predicted miRNA can be obtained from http://mirrim.ncrna.org/