Literature DB >> 33948852

Identification and validation of miRNA reference genes in poplar under pathogen stress.

Lichun Zhang1, Xiaoqian Yang1, Yiyi Yin1, Jinxing Wang2, Yanwei Wang3.   

Abstract

Quantitative real time polymerase chain reaction (qRT-PCR) is a common method to analyze gene expression. Due to differences in RNA quantity, quality, and reverse transcription efficiency between qRT-PCR samples, reference genes are used as internal standards to normalize gene expression. However, few universal genes, especially miRNAs, have been identified as reference so far. Therefore, it is essential to identify reference genes that can be used across various experimental conditions, stress treatments, or tissues. In this study, 14 microRNAs (miRNAs) and 5.8S rRNA were assessed for expression stability in poplar trees infected with canker pathogen. Using geNorm, NormFinder and Bestkeeper reference gene analysis programs, we found that miR156g and miR156a exhibited stable expression throughout the infection process. miR156g, miR156a and 5.8S rRNA were then tested as internal standards to measure the expression of miR1447 and miR171c, and the results were compared to small RNA sequencing (RNA-seq) data. We found that when miR156a and 5.8S rRNA were used as the reference gene, the expression of miR1447 and miR171c were consistent with the small RNA-seq expression profiles. Therefore, miR156a was the most stable miRNAs examined in this study, and could be used as a reference gene in poplar under canker pathogen stress, which should enable comprehensive comparisons of miRNAs expression and avoid the bias caused by different length between detected miRNAs and traditional reference genes. The present study has expanded the miRNA reference genes available for gene expression studies in trees under biotic stress.

Entities:  

Keywords:  Canker; MiRNAs; Poplar; QRT-PCR; Reference genes

Year:  2021        PMID: 33948852     DOI: 10.1007/s11033-021-06369-y

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  35 in total

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Journal:  Genes Immun       Date:  2005-06       Impact factor: 2.676

2.  Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR.

Authors:  Mukesh Jain; Aashima Nijhawan; Akhilesh K Tyagi; Jitendra P Khurana
Journal:  Biochem Biophys Res Commun       Date:  2006-05-03       Impact factor: 3.575

3.  Quantification of mRNA using real-time RT-PCR.

Authors:  Tania Nolan; Rebecca E Hands; Stephen A Bustin
Journal:  Nat Protoc       Date:  2006       Impact factor: 13.491

Review 4.  Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references.

Authors:  Stéphanie Guénin; Mélanie Mauriat; Jérôme Pelloux; Olivier Van Wuytswinkel; Catherine Bellini; Laurent Gutierrez
Journal:  J Exp Bot       Date:  2009       Impact factor: 6.992

5.  Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber.

Authors:  Hongjian Wan; Zhenguo Zhao; Chuntao Qian; Yihu Sui; Ahmed Abbas Malik; Jinfeng Chen
Journal:  Anal Biochem       Date:  2009-12-11       Impact factor: 3.365

Review 6.  Twenty-five years of quantitative PCR for gene expression analysis.

Authors:  Heather D VanGuilder; Kent E Vrana; Willard M Freeman
Journal:  Biotechniques       Date:  2008-04       Impact factor: 1.993

7.  How to do successful gene expression analysis using real-time PCR.

Authors:  Stefaan Derveaux; Jo Vandesompele; Jan Hellemans
Journal:  Methods       Date:  2009-12-05       Impact factor: 3.608

Review 8.  Regulation of low temperature stress in plants by microRNAs.

Authors:  Swati Megha; Urmila Basu; Nat N V Kav
Journal:  Plant Cell Environ       Date:  2017-05-16       Impact factor: 7.228

9.  Selection and Validation of Appropriate Reference Genes for Quantitative Real-Time PCR Analysis of Gene Expression in Lycoris aurea.

Authors:  Rui Ma; Sheng Xu; Yucheng Zhao; Bing Xia; Ren Wang
Journal:  Front Plant Sci       Date:  2016-04-25       Impact factor: 5.753

10.  High-throughput long paired-end sequencing of a Fosmid library by PacBio.

Authors:  Zhaozhao Dai; Tong Li; Jiadong Li; Zhifei Han; Yonglong Pan; Sha Tang; Xianmin Diao; Meizhong Luo
Journal:  Plant Methods       Date:  2019-11-26       Impact factor: 4.993

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