pseudoMap: an innovative and comprehensive resource for identification of siRNA-mediated mechanisms in human transcribed pseudogenes

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Database tool

pseudoMap: an innovative and

comprehensive resource for identification of

siRNA-mediated mechanisms in human

transcribed pseudogenes

Wen-Ling Chan

1,2

, Wen-Kuang Yang

3,4

, Hsien-Da Huang

1,2,

* and Jan-Gowth Chang

5,6,7,

*

1

Institute of Bioinformatics and Systems Biology,2Department of Biological Science and Technology, National Chiao Tung University, Hsin-Chu, 3_{Cell/Gene Therapy Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung,}4_{Departments of} Biochemistry and Medicine, China Medical University, Taichung,5_{Center of RNA Biology and Clinical Application,}6_{Department of Laboratory} Medicine, China Medical University Hospital, Taichung, and7_{School of Medicine, China Medical University, Taichung, Taiwan}

*Corresponding author: Tel: +886 4 22052121 ext. 2008; Email: d6781@mail.cmuh.org.tw; Fax: +886 4 22031029

Correspondence may also be addressed to Hsien-Da Huang, Tel: +886 3 5712121 ext. 56957; Email: bryan@mail.nctu.edu.tw; Fax: +886 3 5739320

Submitted 31 October 2012; Revised 1 January 2013; Accepted 3 January 2013

Citation details: Chan,W.-L., Yang,W.-K., Huang,H.-D. et al. pseudoMap: an innovative and comprehensive resource for identification of siRNA-mediated mechanisms in human transcribed pseudogenes. Database (2013) Vol. 2013: article ID bat001; doi:10.1093/database/bat001.

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RNA interference (RNAi) is a gene silencing process within living cells, which is controlled by the RNA-induced silencing complex with a sequence-specific manner. In flies and mice, the pseudogene transcripts can be processed into short interfering RNAs (siRNAs) that regulate protein-coding genes through the RNAi pathway. Following these findings, we construct an innovative and comprehensive database to elucidate siRNA-mediated mechanism in human transcribed pseudogenes (TPGs). To investigate TPG producing siRNAs that regulate protein-coding genes, we mapped the TPGs to small RNAs (sRNAs) that were supported by publicly deep sequencing data from various sRNA libraries and constructed the TPG-derived siRNA-target interactions. In addition, we also presented that TPGs can act as a target for miRNAs that actually regulate the parental gene. To enable the systematic compilation and updating of these results and additional informa-tion, we have developed a database, pseudoMap, capturing various types of informainforma-tion, including sequence data, TPG and cognate annotation, deep sequencing data, RNA-folding structure, gene expression profiles, miRNA annotation and target prediction. As our knowledge, pseudoMap is the first database to demonstrate two mechanisms of human TPGs: encoding siRNAs and decoying miRNAs that target the parental gene. pseudoMap is freely accessible at http://pseudomap. mbc.nctu.edu.tw/.

Database URL: http://pseudomap.mbc.nctu.edu.tw/

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Introduction

Pseudogenes are genomic DNA sequences homologous to functional genes yet are not translated into proteins (1). Although pseudogenes are often considered the structur-ally defective non-functional copies of protein-coding genes, the human genome comprises more numbers of pseudogenes than corresponding functional genes (2). Despite the previous assumption of pseudogenes as

genomic fossils, the genome-wide investigations have demonstrated actively transcribed pseudogenes (TPGs) with functional potential (3–12). For instant, TPG of nitric oxide synthase ( NOS) acts as an antisense regulator of neuronal NOS protein synthesis in snails (13,14). Another study has established that binding of transcriptional repres-sor to receptor of makorin1-p1 could activate the hom-ologous parental gene Mkrn1 (15), despite contradictory

...

ßThe Author(s) 2013. Published by Oxford University Press.

at National Chiao Tung University Library on April 26, 2014

http://database.oxfordjournals.org/

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result was also reported (16). In addition, the TPG of PTENP1 ( PTEN), a highly conserved processed pseudogene of tumour suppressor PTEN, acts as a miRNA-decoy by bind-ing to PTEN-targetbind-ing miRNAs (17). Moreover, human pseudogene myosin light chain kinase pseudogene 1 is par-tially duplicated from the original MYLK gene and pro-motes cancer cell proliferation (18). Above findings clearly suggest that the non-coding RNA products of TPGs may play an important role in biogenesis pathway and func-tional processes.

The RNA interference (RNAi) is an important component of the RNA modulation pathway and is incorporated into the RNA-induced silencing complex (RISC) with a sequence-specific manner (19). In mice and fruit flies, double-stranded RNAs arising from the antisense/sense transcripts of processed pseudogene, and its cognate gene, or hairpin structures from inversion and duplication, are cut by Dicer into 21 nt endogenous short interfering RNAs (esiRNAs) with the ability to bind RISC and regulate the expression of parental gene (20–25). Such regulatory mechanism in human remains unclear.

To demonstrate that in human, as in animal models, TPGs may generate naturally occurring siRNAs and Piwi interact-ing RNAs (piRNAs) to regulate the expression of protein-coding genes, we have developed a computational pipeline and constructed a database-pseudoMap, the map for studying pseudogenes. pseudoMap pre-processes the raw data of public microarray and deep sequencing data into gene expression profiles for both TPG and its cognate gene and small RNA (sRNA) profiles for TPG-derived esiRNAs. pseudoMap further combined the gene expression profiles to construct the TPG-derived esiRNA-target interactions (eSTIs). In addition, according to the previous study of pseudogene, PTENP1 exerts a miRNA decoy by binding to

cognate-targeting miRNAs (17), and pseudoMap also pro-vided the ‘miRNA regulator’ to elucidate the relationship of TPG and its cognate gene with miRNA target regulation.

Data generation

In total, more than 20 000 human pseudogenes and their cognate genes were obtained from the Ensembl Genome Browser (Ensembl 63, GRCH37) (26) using BioMart (http:// www.ensembl.org/index.html). Affymetrix GeneChipÕ

Human Genome U133A/U133Plus2 is a microarray com-posed of oligonucleotide probes to measure the level of transcription of each sequence represented, which included transcribed pseudogenes. 1404 pseudogenes have been de-tectable by this chip, thus considered being transcribed and referred as TPGs. Functional sRNAs (fsRNAs) with sequence length between 18 to 40 nt were collected from the Functional RNA Database (27), which hosts a large collec-tion of known/predicted non-coding RNA sequences from public databases: H-invDB v5.0 (6), FANTOM3 (28), miRBase 17.0 (29, 30), NONCODE v1.0 (31), Rfam v8.1 (32), RNAdb v2.0 (33) and snoRNA-LBME-db rel. 3 (34). The public deep sequencing data from sRNA libraries (35–38) were experi-mented with on human embryo stem cells, liver tissues or hepatocellular carcinoma (HCC) tissues. Supplementary Table 1summarizes the statistics of the deep sequencing data from various sRNA libraries. The genomic sequences were obtained from UCSC hg19 (39).Table 1lists the inte-grated databases and tools for mining potential regulators and functions of human TPGs.

System flow of pseudoMap

The system flow of pseudoMap is shown inFigure 1, mainly including the collection of datasets such as TPGs, parental

Table 1. Supported databases and tools in pseudoMap

Integrated database or tools Dataset Description

miRBase (29,30) miRNA annotation This database not only provides published miRNA sequences and annotations but also supplies known/predict targets

Functional RNA Database (27) sRNA annotation A database to support mining and annotation of functional RNAs Ensembl Genome Browser (26) Pseudogene, protein-coding gene It produces genome databases for vertebrates and other

eukary-otic species UCSC Genome Browser (39) Conserved region and

Genomic view of genes

This browser provides a rapid and reliable display of any re-quested portion of genomes at any scale, together with dozens of aligned annotation tracks

GeneCards (52) Gene annotation GeneCards is a searchable, integrated, database of human genes that provides concise genomic-related information of all known and predicted human genes

Mfold (40) RNA folding tool Folding RNA structure

GEO (47) Gene expression profiles and deep sequencing data

A public functional genomics data

BLAST (51) Sequence alignment tool BLAST finds regions of similarity between biological sequences

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genes, fsRNAs, sRNA deep sequencing data, expression pro-files, integration of various tools and identification of func-tions and regulafunc-tions of TPGs. Based on a genome-wide computational pipeline of sequence-alignment approaches, this work constructed pseudoMap database for elucidation of two major discoveries: TPG-derived eSTI and miRNA-decoy mechanism of TPGs. The detailed analyses are described below.

Identification of TPG-derived

esiRNAs by public next-generation

sequencing data

A computational pipeline was developed to verify the hypotheses that human TPGs may generate esiRNAs to regu-late protein-coding genes (Figure 2). An attempt was made to identify the candidates of TPG-derived esiRNAs, by align-ing the sequences of TPGs and fsRNAs. These candidates were verified using the deep sequencing data from various

sRNA libraries (35–38) experimented with on human embryo stem cells, liver tissues or HCC tissues. The hairpin structure by Mfold (40) was then determined by using the extended sequences of these candidates of esiRNAs. In pseudoMap, a total of 1232 TPGs may produce esiRNAs, which were profil-ing by deep sequencprofil-ing data, within 1404 human TPGs were characterized. The information of these TPGs is shown in

Supplementary File 1. The results showed that 4 miRNAs and 326 piRNAs may derive from TPGs. We also found that miRNA has-miR-622 was identified, which was derived from keratin 18 pseudogene 27, located on nt 858–879, as similar as miRBase database. Table 2summarizes the entire statis-tical analysis of pseudoMap.

Identification of TPG-derived

esiRNA-target interactions

Our previous approach (41) was modified to identify TPG-derived esiRNA targets. Briefly, the esiRNA target

Figure 1. System flow of pseudoMap. The system flow of pseudoMap mainly includes the collection of datasets such as TPGs, parental genes, miRNAs, piRNAs, sRNA deep sequencing data and expression profiles; integration of various tools and identifi-cation of functions and regulations of TPGs. Based on a genome-wide computational pipeline of sequence-alignment approaches and gene expression profiles, this work constructed pseudoMap database for elucidation of two major discoveries: TPG-derived esiRNA-target interaction and miRNA-decoy mechanism of TPGs.

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sites within the conserved regions of coding, 5’-UTR and 3’-UTR of genes were identified in 12 metazoan genomes by using three computational approaches, TargetScan (42– 44), miRanda (45) and RNAhybrid (46). The minima free energy (MFE) threshold was 20 kcal/mol with a score more than or equal to 150 for miRanda and default param-eters for TargetScan and RNAhybrid. The targets were iden-tified using the following criteria: (i) the potential target sites were determined by at least two approaches; (ii) mul-tiple target sites were prioritized and (iii) target sites must be located in accessible regions. Finally, we provided the gene expression profiles of TPG and its cognate gene to construct the eSTIs.

Gene expression analysis

The mRNA abundances of TPGs and protein-coding genes were obtained from Gene Expression Omnibus (47), such as GDS596 examined from 79 human physiologically normal tissues (48), GSE2109 examined from 2158 samples with 61 tumour tissues, GSE3526 examined from 353 samples with 65 normal tissues (49) and GSE5364 examined from primary human tumours and adjacent non-tumour tissues, which include 270 tumours and 71 normal-cancer pairs from pa-tients with breast, colon, liver, lung, oesophagal and thy-roid cancers (50). Moreover, the Pearson correlation coefficient was computed from TPGs and protein-coding genes.

Determination of miRNA-target

interactions

According to the study by Poliseno et al. (17), pseudogenes PTENP1 and KRAS1P act as a ‘miRNA decoy’, binding to and thereby reducing the effective cellular concentration of

Figure 2. Computational pipeline for identification of TPG-derived esiRNA-target interactions.

Table 2. Summarizes the entire statistical analysis of pseudoMap

Dataset Counts

No. of miRNA regulators 5771/1014a No. of TPG-derived miRNAs 4 No. of TPG-derived piRNAs 326 Deep sequencing data for profiling TPG-derived esiRNAs

Human embryo stem cell—hB 247 Human embryo stem cell—hESC 553 Human embryo stem cell—hues6 190 Human embryo stem cell—hues6NP 81 Human embryo stem cell—hues6Neuron 16 HBV(+) adjacent tissue sample 1 917 HBV(+) adjacent tissue sample 2 4377 HBV(+) distal tissue sample 1 1011 HBV(+) HCC tissue sample 1 1281 HBV(+) HCC tissue sample 2 2649 HBV-infected liver tissue 3056 HBV(+) side tissue sample 1 1087 HCV(+) adjacent tissue sample 14 297 HCV(+) HCC tissue sample 9277 HBV( ) HCV( ) adjacent tissue sample 2324 HBV( ) HCV( ) HCC tissue sample 6579 Human normal liver tissue sample 1 1220 Human normal liver tissue sample 2 1290 Human normal liver tissue sample 3 1209 Severe chronic hepatitis B liver tissue 1247

a

1014 distinct miRNAs involved in 5771 miRNA regulators.

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miRNAs, therefore resulting their cognate genes to escape miRNA-mediated repression. In this study, we analyse the relationships between TPG and its cognate gene with miRNA decoys mechanism to examine miRNA-target inter-actions (MTIs) by performing a pipeline. First, the parental genes were obtained by mapping the TPGs and genomic sequences with the BLAST (51) program. The MTIs with TPGs and parental genes were then investigated using our previous approach (41). The MFE threshold was 20 kcal/mol with a score more than or equal to 150 for miRanda and default parameters for TargetScan and RNAhybrid. Finally, the TPGs and their cognates co-regulated by miRNAs were obtained. The miRNA and 3’UTR sequences were obtained from miRBase R18

(29,30) and Ensembl Genome Browser release 63 (26), re-spectively. Analysis results indicated that 874 miRNAs with MFE 20 and Score 150 interact with many possible target sites in 248 TPGs and their cognate genes and might potentially co-regulate this pair of TPG and parental gene (Supplementary File 2).

Web interface

As a web-based system, pseudoMap can thoroughly iden-tify TPGs, including TPGs act as a miRNA regulators and TPGs-derived eSTIs in humans. There are two ways to access pseudoMap: by browsing the database content or by searching for a particular TPG. Figure 3A displays the

Figure 3. Web interface of pseudoMap. (A) Browse interface of pseudoMap illustrates general information of TPGs, miRNA regulators, esiRNAs and gene expression profiles. (B) The miRNA regulator indicates the miRNA decoys mechanisms between TPG and its cognate. (C) Gene expression profiles of TPG and its cognate gene in various experimental conditions. (D) The diagram of esiRNA represents TPG-derived siRNAs as profiled by deep sequencing data. It displays the more fine-grained information of (E) esiRNA-target interaction and (F) RNA folding structure of TPG-derived esiRNA. In addition, pseudoMap also incorporates the external sources, such as (G) UCSC genome browser for a genomic view, GeneCards for gene annotation and miRBase for miRNA annotation.

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interface of output results of the browse gateway. The interface contains general information of TPGs, the rela-tionships of TPG and its cognate gene with miRNA-mediated repression termed as ‘miRNA Regulator’, TPG-derived eSTIs named as ‘esiRNA’, and ‘Expression’ showed the gene expression profiles.Figure 3B provides a detailed view of miRNA regulator, which displays more fine-grained information. Above results indicated the rela-tionships between TPGs and cognate genes by a miRNA decoy mechanism such as that observed by Poliseno et al. (17). The ‘Expression’ presents the gene expression profiles of not only distinct TPG and corresponding parental gene but also TPG referenced by cognate in various experimental conditions (Figure 3C). Moreover, the view of esiRNA indi-cates the TPG-derived esiRNAs and graphical display of deep sequencing data (Figure 3D). The red line represents

the TPG and the blue line refers to esiRNAs. We also esti-mate the eSTIs (Figure 3E) and the RNA folding structure of TPG-derived esiRNA (Figure 3F). All the results and se-quences can be downloaded for further experimental tests. In pseudoMap, we also incorporate the external sources, such as UCSC genome browser (39) for a genomic view, GeneCards (52) for gene annotation and miRBase (29) for miRNA annotation (Figure 3G). In addition, pseudoMap also consists of a tutorial and knowledge of pseudogenes.

In the search gateway, the TPG ID, Ensembl ID, TPG symbol and parental gene symbol are allowed for further analysis. Figure 4displays the interface of output results with the search a particular TPG ID/Ensembl ID/TPG symbol/parental gene symbol. The interface contains the general information of TPG, miRNA regulators, gene ex-pression profiles and TPG-derived esiRNAs.

Figure 4. Search interface of pseudoMap.

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Construction and content

In pseudoMap, various databases are integrated and main-tained with MySQL (http://www.mysql.com/) relational database management system. While operating on an Apache HTTP server (http://www.apache.org/) and PHP (http://www.php.net/) on a Linux operation system (http:// www.linux.com), pseudoMap was constructed using the Smarty template engine (http://www.smarty.net). Based on PHP, JavaScript (http://www.javascriptsource.com/), CSS (http://www.w3schools.com/css/) and HTML (http://www. w3schools.com/html/) languages, the web interface enables dynamic MySQL queries with user-friendly graphics. Above software are open source technologies.

Discussion and conclusions

Comparison with other previous databases related to pseudogenes

A few databases have been constructed to explore pseudo-genes. In particular, PseudoGene database (53) identifies pseudogenes using various computational methods in genomes; HOPPSIGEN (54) represents the homologous pro-cessed pseudogenes shared between the mouse and human genomes that contains location information and potential function; as a web-based system, PseudoGeneQuest (55) identifies novel human pseudogenes based on a user-provided protein sequence; in addition, the University of Iowa’s UI Pseudogenes website contains human pseudo-genes and the candidates for gene conversion (56). However, these databases focus on automatic detection of pseudogenes by using a variety of homology-based approaches. Our database, pseudoMap, aims at providing comprehensive resource for genome-wide identifying the functions and regulators of human TPGs. In briefly, there are three major differentiating features from currently public databases of pseudogenes. First, pseudoMap eluci-dates the relationships of TPG and its cognate gene with miRNA decoys mechanism. Second, to explore the inter-action of TPG and its parental gene, pseudoMap provides the gene expression profiles of TPG and its cognate gene in various experimental conditions. Third, pseudoMap curates the TPG-derived esiRNAs, which supported by deep sequen-cing data, as well as their interacting gene targets in the human genome.Table 3lists the detailed comparisons of pseudoMap with other previous databases related to pseudogenes.

Applications

PseudoMap provides two major applications. One is the non-coding RNA products of TPGs, as like animal models, that may generate esiRNAs to regulate protein-coding genes in humans. In this process, pseudoMap supplies next-generation sequencing data from sRNA libraries to Tab

le 3. Comp arisons of pseudoM ap with curre ntly public data bases of pseud ogene s Sup ported features pseud oMap (our data base) Pseu doGene d atabase UI pse udogene Ho ppsigen Web interfac e http: //pseudom ap.mbc.n ctu.edu.tw/ http ://www.pseudog ene.org/ https://genome.uiowa .edu /pseudoge nes/ h ttp://pbil.univ-ly on1.fr/da tabases/hop p sigen.ht ml Desc ription pseud oMap pr ovides a compreh ensive re-source fo r genome -wide identifyin g the functions and re gulators of hum an p seudogene s. Thi s site contains a comp rehensive database of iden tified pseudogen es, utilities used to find pseudo genes, various publication data sets a nd a pseudoge ne know ledgebase. This site serves as a repository for all pseu dogenes in the hu man genom e and prov ides a ranked list of human pseu dogenes that have been identified as candidate s for gene conv ersion. Ho ppsigen is a nucleic database of homolo gous pro cessed ps eudogenes. Spec ies sup ported Human Euka ryote and prokaryo te Human Hu man Sequ ence do wnload Yes Yes Yes Yes Pseu dogene informatio n Yes Yes Yes Yes Pare ntal gen e infor mation Yes Yes — — Kno wledge of pseu dogenes Yes Yes — Yes miR NA–pseudog ene inte ractions Yes — — — miR NA–parental gene interactio ns Yes — — — Gen e expressi on prof iles Yes (both pseudogen e and its par ental ge ne) — — — Pseu dogene-d erived siRN As Yes — — — Deep sequen cing d ata for profiling TPG-d erived siRN As Yes — — —

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support the candidates of TPG-derived esiRNAs and gene expression profiles to verify the target interactions, respectively. Another application is that both the gene and pseudogene contain miRNA target sites, if the pseudogene competes for the freely available repressor molecules that would be free the gene to reduce the miRNA-mediated repression. Another words, the pseudogene may act as a ‘miRNA decoy’ to release the re-pression of its cognate gene. pseudoMap provides another insight into the pathway of MTIs with TPG-mediated mechanism.

Conclusion

In this study, we performed a computational pipeline to identify TPG-derived esiRNAs-target interactions and con-structed a comprehensive database to represent the poten-tial functions and regulators of TPGs in human. To our knowledge, the pseudoMap is the first database to identify TPGs to enable biologists and bioinformaticians to eluci-date two major discoveries, the relationships between TPG and its cognate gene with miRNA decoyed mechanisms and TPG-derived eSTIs. Efforts are underway in our labora-tory to expand the methods used in pseudoMap to other species such as mice, fruit flies and plants. The pseudoMap will be updated frequently by continuingly surveying ex-perimentally validated sRNAs and will be maintained with a long-term support from National Chiao Tung University and National Science Council at Taiwan. This novel and cre-ative resource is now freely available at http://pseudomap. mbc.nctu.edu.tw/.

Supplementary data

Supplementary Dataare available at Database online.

Funding

National Science Council of the Republic of China [NSC 99-2320-B-037-006-MY3 to J.G.C., NSC 98-2314-B039-010MY3 to W.K.Y., NSC 98-2311-B-009-004-MY3 to H.D.H., NSC 99-2627-B-009-003 to H.D.H., NSC 101-2311-B-009-003-MY3 to H.D.H. and NSC 100-2627-B-009-002 to H.D.H.]; UST-UCSD International Center of Excellence in Advanced Bio-engineering sponsored by the Taiwan National Science Council I-RiCE Program [NSC 101-2911-I-009 -101 - to H.D.H., in part]; Veterans General Hospitals and University System of Taiwan (VGHUST) Joint Research Program [VGHUST101-G5-1-1 to H.D.H., in part]; MOE ATU [in part]. Funding for open access charge: National Science Council of the Republic of China.

Conflict of interest statement. None declared.

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