Literature DB >> 22878892

Identification and validation of potential conserved microRNAs and their targets in peach (Prunus persica).

Zhihong Gao1, Xiaoyan Luo, Ting Shi, Bin Cai, Zhen Zhang, Zongming Cheng, Weibing Zhuang.   

Abstract

MicroRNAs are a class of small, endogenous, non-coding RNA molecules that negatively regulate gene expression at the transcriptional or the post-transcriptional level. Although a large number of miRNAs have been identified in many plant species, especially from model plants and crops, they remain largely unknown in peach. In this study, 110 potential miRNAs belonging to 37 families were identified using computational methods. A total of 43 potential targets were found for 21 families based on near-perfect or perfect complementarity between the plant miRNA and the target sequences. A majority of the targets were transcription factors which play important roles in peach development. qRT-PCR analysis of RNA samples prepared from different peach tissues for 25 miRNA families revealed that miRNAs were differentially expressed in different tissues. Furthermore, two target genes were experimentally verified by detection of the miRNA-mediated mRNA cleavage sites in peach using RNA ligase-mediated 5' rapid amplification of cDNA ends (RLM-RACE). Finally, we studied the expression pattern of the two target genes in three different tissues of peach to further understand the mechanism of the interaction between miRNAs and their target genes.

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Year:  2012        PMID: 22878892      PMCID: PMC3887836          DOI: 10.1007/s10059-012-0004-7

Source DB:  PubMed          Journal:  Mol Cells        ISSN: 1016-8478            Impact factor:   5.034


  48 in total

1.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Authors:  K J Livak; T D Schmittgen
Journal:  Methods       Date:  2001-12       Impact factor: 3.608

2.  Mfold web server for nucleic acid folding and hybridization prediction.

Authors:  Michael Zuker
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  Prediction of plant microRNA targets.

Authors:  Matthew W Rhoades; Brenda J Reinhart; Lee P Lim; Christopher B Burge; Bonnie Bartel; David P Bartel
Journal:  Cell       Date:  2002-08-23       Impact factor: 41.582

Review 4.  MicroRNAs in trees.

Authors:  Ying-Hsuan Sun; Rui Shi; Xing-Hai Zhang; Vincent L Chiang; Ronald R Sederoff
Journal:  Plant Mol Biol       Date:  2011-12-08       Impact factor: 4.076

5.  DICER-LIKE1: blind men and elephants in Arabidopsis development.

Authors:  Stephen E Schauer; Steven E Jacobsen; David W Meinke; Animesh Ray
Journal:  Trends Plant Sci       Date:  2002-11       Impact factor: 18.313

6.  Direct isolation of high-quality low molecular weight RNA of pear peel from the extraction mixture containing nucleic acid.

Authors:  Xin-wei Wang; Ai-sheng Xiong; Quan-hong Yao; Zhen Zhang; Yu-shan Qiao
Journal:  Mol Biotechnol       Date:  2009-08-11       Impact factor: 2.695

7.  Cleavage of Scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA.

Authors:  Cesar Llave; Zhixin Xie; Kristin D Kasschau; James C Carrington
Journal:  Science       Date:  2002-09-20       Impact factor: 47.728

8.  MiR-RACE, a new efficient approach to determine the precise sequences of computationally identified trifoliate orange (Poncirus trifoliata) microRNAs.

Authors:  Changnian Song; Jinggui Fang; Chen Wang; Lei Guo; Kibet Korir Nicholas; Zhengqiang Ma
Journal:  PLoS One       Date:  2010-06-07       Impact factor: 3.240

9.  Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata).

Authors:  Changnian Song; Chen Wang; Changqing Zhang; Nicholas Kibet Korir; Huaping Yu; Zhengqiang Ma; Jinggui Fang
Journal:  BMC Genomics       Date:  2010-07-13       Impact factor: 3.969

10.  Deep sequencing identifies novel and conserved microRNAs in peanuts (Arachis hypogaea L.).

Authors:  Chuan-Zhi Zhao; Han Xia; Taylor Price Frazier; Ying-Yin Yao; Yu-Ping Bi; Ai-Qin Li; Meng-Jun Li; Chang-Sheng Li; Bao-Hong Zhang; Xing-Jun Wang
Journal:  BMC Plant Biol       Date:  2010-01-05       Impact factor: 4.215

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  7 in total

1.  Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures.

Authors:  Chandran Nithin; Nisha Patwa; Amal Thomas; Ranjit Prasad Bahadur; Jolly Basak
Journal:  BMC Plant Biol       Date:  2015-06-12       Impact factor: 4.215

Review 2.  Prunus transcription factors: breeding perspectives.

Authors:  Valmor J Bianchi; Manuel Rubio; Livio Trainotti; Ignazio Verde; Claudio Bonghi; Pedro Martínez-Gómez
Journal:  Front Plant Sci       Date:  2015-06-12       Impact factor: 5.753

3.  Integrative analysis of miRNA and mRNA profiles in response to ethylene in rose petals during flower opening.

Authors:  Haixia Pei; Nan Ma; Jiwei Chen; Yi Zheng; Ji Tian; Jing Li; Shuai Zhang; Zhangjun Fei; Junping Gao
Journal:  PLoS One       Date:  2013-05-16       Impact factor: 3.240

4.  Identification of miRNAs and their target genes in peach (Prunus persica L.) using high-throughput sequencing and degradome analysis.

Authors:  Xiaoyan Luo; Zhihong Gao; Ting Shi; Zongming Cheng; Zhen Zhang; Zhaojun Ni
Journal:  PLoS One       Date:  2013-11-13       Impact factor: 3.240

5.  Identification of Known and Novel microRNAs and Their Targets in Peach (Prunus persica) Fruit by High-Throughput Sequencing.

Authors:  Chunhua Zhang; Binbin Zhang; Ruijuan Ma; Mingliang Yu; Shaolei Guo; Lei Guo; Nicholas Kibet Korir
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

6.  Identification and characterization of Prunus persica miRNAs in response to UVB radiation in greenhouse through high-throughput sequencing.

Authors:  Shaoxuan Li; Zhanru Shao; Xiling Fu; Wei Xiao; Ling Li; Ming Chen; Mingyue Sun; Dongmei Li; Dongsheng Gao
Journal:  BMC Genomics       Date:  2017-12-02       Impact factor: 3.969

7.  Identification and characterization of microRNAs in tree peony during chilling induced dormancy release by high-throughput sequencing.

Authors:  Yuxi Zhang; Yanyan Wang; Xuekai Gao; Chunying Liu; Shupeng Gai
Journal:  Sci Rep       Date:  2018-03-14       Impact factor: 4.379

  7 in total

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