^^^^^^^^^^^^ ЭКСПЕРИМЕНТАЛЬНЫЕ
СТАТЬИ
581.1
IDENTIFICATION OF CONSERVED microRNAs AND THEIR TARGETS
IN Phalaenopsis ORCHID1
© 2013 J. Wang*2, J. Wang*2, C. Zhang*2, Y. Yan**, W. Wu**, Z. Ma**
*College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, P.R. China **Zhenjiang Institute of Vegetable Science, Zhenjiang, Jiangsu, P.R. China Received September 13, 2012
The microRNAs (miRNAs) are a new type of tiny, noncoding, single-stranded endogenous RNA molecules performing their function of regulating gene expression by targeting mRNAs for degradation or restraining protein translation. Thousands of miRNAs have been identified in many plant species to date, whereas only limited number of miRNAs have been identified in Phalaenopsis orchid. By using an exact computational analysis, 30 potential miRNAs were found from all known sequences (205823 nt, 5505 GSS, and 8066 EST) in this study. These 30 miRNAs belong to 26 miRNA families and show significant variation in size. According to the previously established systemic method, 193 Phalaenopsis orchid genes were predicted as potential target genes of 20 miRNAs. The majority of these potential target genes in Phalaenopsis orchid encode hypothetical proteins, which functions are either indefinite or unknown. The rest miRNA target genes encode transcription factors that function in stress response, signal transduction, and a variety of other metabolic processes. To validate the predicted miRNAs and the mutual relationship between miRNAs and their target genes, qRT-PCR was applied to detect the tissue-specific expression levels of four putative miRNAs and their target genes in Phalaenopsis leaves, flowers, and roots. This study provided for some important information about Phalaenopsis pre-miRNAs, mature miRNAs, and miRNA target genes and will be helpful for future research of miRNA functions in Phalaenopsis.
Keywords: Phalaenopsis - miRNA - comparative analysis - targets - qRT-PCR
УДК
DOI: 10.7868/S0015330313060158
INTRODUCTION
Tiny noncoding micro RNAs (miRNAs) present in plants are about 21 nucleotides (nt) in length and perform their vital regulatory functions in plants and animals through targeting mRNAs for degradation or restraining their translation [1, 2]. An increasing number of studies have shown that miRNAs play a major role in a variety of metabolic and biological processes in plants, including leaf development, flower development, regulation of flowering time, root growth, signal transduc-tion, abiotic and biotic stresses, etc. [2-4].
The first reports about plant miRNAs were published in 2002 [5, 6]. Then plant miRNAs were studied
1 This text was submitted by the authors in English.
2 These authors contributed equally to this work.
Abbreviations'. EST - expressed sequence tag; GM - genetically modified; GSS - genome survey sequences; miRNA - microRNA; nt - nucleotide; NCBI - national center for biotechnology information.
Corresponding author. Changwei Zhang. College of Horticulture, Nanjing Agricultural University, № 1 Weigang, Nanjing, Jiangsu, 210095 P.R. China. Fax. +86-25-8439-5266; e-mail. changweizh@ njau.edu.cn
advance by leaps and bounds. The miRNAs can be identified by large-scale RNA sequencing, direct cloning, or other approaches [7]. Until now, more than 3521 plant miRNAs have been identified in 29 plant species and deposited in the public available database miRBase website (http://www.mirbase.org/, v. 17) [8]. This database offers a powerful tool to find miRNAs in other plant species via using comparative genomics approach.
Phalaenopsis orchid is one of the most popular and important epiphytic monopodial orchid around the world, which is appreciated for its beauty and a huge commercial value. Breeding Phalaenopsis orchid by traditional methods is a lengthy process. Therefore, it would be of great advantage to apply the molecular breeding technology to improve orchid important traits, such as novel flower color, fragrance, and shape, cut-flower longevity, and flowering control, abiotic stress tolerance, and resistance to pests and diseases [9]. Since miRNAs can regulate gene expression by targeting mRNAs for degradation or by inhibiting protein translation, we can use them to change or improve orchid important traits by the GM technology. To our
knowledge, although the stable genetic transformation system has been elaborated, there is little knowledge of miRNAs in Phalaenopsis orchid. The genomic sequence resources for orchids are limited [10].
The objective of this study was to find some miRNAs and predict their target genes and to learn the potential functions of predicted miRNAs.
MATERIALS AND METHODS
Sequence databases. There are 3521 known plant miRNAs in total, which were downloaded from the miRBase database (http://www.mirbase.org/, v. 17, April 27, 2011) [8]. These miRNAs were got from 29 plant species, including Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Brassica rapa, Glycine max, Zea mays, Saccharum officinarum, Sorghum bicolor, and other. All downloaded miRNAs were used as references to find the conserved miRNAs in Phalaenopsis orchid.
A sum of 205 823 nt, 5505 GSS, and 8066 EST sequences were downloaded from NCBI in May 2012 (http://www.ncbi.nlm.nih.gov/nucest); they served as source sequences of the Phalaenopsis orchid potential pre-miRNAs. Furthermore, the EST sequences were also used to predict the target genes of miRNAs. The nonredundant (NR) protein database was got from NCBI (ftp://ftp.ncbi.nih.gov/blast/db/).
Software. All primitive nucleotides, GSS, and EST sequences were assembled by using the CAP3 software (http://seq.cs.iastate.edu/cap3.html). The alignment tool named Basic Local Alignment Search Tool (BLAST) 2.2.24 (August 23, 2010) was downloaded from the NCBI website (ftp://ftp.ncbi.nlm.nih. gov/blast/executables/blast+/LATEST/) and was used to identify the potential conserved miRNAs. The potential miRNAs and their targets were identified by means of an alignment tool of WATER, which was got from the Vienna RNA Package 1.8.4 (http://www. tbi.univie.ac.at/~ivo/RNA/) [11]. The second structures of pre-miRNAs were got by using the procedure of Mfold 3.5 (http://mfold.rit.albany.edu/?q=mfold/ RNA-Folding-Form).
Identification of potential conversed miRNAs by homolog search. A total of 205 823 nt, 5505 GSS, and 8066 EST sequences were used as source sequences for the search for Phalaenopsis orchid pre-miRNAs in this study. By using computational method, we identified some potential conserved miRNAs. The concrete steps of this method were as described in [7]. Firstly, we assembled these source sequences (205 823 nt, 5505 GSS, and 8066 EST sequences) with the CAP3 in the default parameter to remove the repeated nucleotides, GSS, and EST. Next, we aligned the contigs and singletons to plant miRNAs by using the
BLASTN algorithm with an E value of 1 x 10-10, and the lengths of alignment sequences were kept between 17 and 24 nt. Then, we used the WATER algorithm to get the results with no more than 3-nt substitutions, which included insertions, deletions, mutations, and gaps, between known miRNAs and homological sequences got from the BLASTN search. The full-length sequences were obtained by extending the alignment sequences. Protein-coding sequences were then removed by using BLASTX against the NR protein databases that were downloaded from NCBI. By using the RNAfold software, we acquired the secondary structures of the full-length sequences. Lastly, the following criteria were raised to identify the potential miRNAs: (1) there were no more than 3-nt substitutions between the reference miRNA sequences and the EST, GSS, and nt sequences; (2) the minimum length of the pre-miRNA was 45 nt; (3) the potential pre-miRNA could be folded into a perfect or near-perfect stem-loop hairpin secondary structure; (4) the mismatches in the miRNA/miRNA* duplex should not be greater than 6 nt; (5) there were no loops in the miRNA/miRNA* duplex; (6) the predicted pre-miRNAs had high absolute values for MFE (minimal folding free energy), and MFEI (minimal folding free energy index) values of the predicted secondary structures should be higher than 0.85; and (7) there are only two base pairs ofmax-imum consecutive mismatches between miRNA and miRNA* [7, 12, 13]. Finally, some possible false sequences of pre-miRNAs should be checked by manual examination.
Prediction of miRNA target genes in Phalaenopsis orchid. All assembled Phalaenopsis orchid EST sequences were used to predict the miRNA target genes. Through using the BLAST-based method, we obtained the protein-coding EST dataset. The detailed methods were as follows. Firstly, we confirmed the strands of contigs and singletons by using BLASTX with an E value of1 x 10-10 against the NR protein database. Then, we selected the best alingment result to check the strand position of the EST sequences. If the best alingment result strand of the EST sequence was "+", the EST strand position was kept. If it was "-", the EST sequence was transformed to reverse complementary sequence. If there was no alingment result, the original sequence was kept. Lastly, we got the treated EST dataset and then used the WATER as a powerful tool to predict the target genes of miRNAs. The stringent criterion for the prediction of potential miRNA target genes in Phalaenopsis orchid was as following [12,13]: (a) not more than four mismatches exist between the predicted miRNAs and their corresponding potential miRNA target genes; (b) no more than two continuous mismatches exist in the miRNA/target duplex; (c) the number of mismatches in positions between nucleotide 1 and 9 of the miRNA/target duplex
Table 1. The miRNAs and their target gene primers designed for qRT-PCR
Mature miRNA Query miRNA NM Mature miRNA sequence (5'—3') Sequence Location
pap-miR5021 ath-miR5021 1 TGAGAAGAAGAAGAAGAAGA JI634134.1 5'
ath-miR5021 3 TGAGCGGAAGCAAGAAGAAAA JI734905.1 5'
pap-miR26
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