Literature DB >> 31404229

Selection and validation of reference genes of Paeonia lactiflora in growth development and light stress.

Yingling Wan1, Aiying Hong2, Yixuan Zhang1, Yan Liu1.   

Abstract

The stem of Paeonia lactiflora will bend when it grows in greenhouse at a low light intensity. It is important to explore causes of morphological changes of peony to improve its quality. Gene expression can be evaluated by quantitative real-time PCR, based on reference gene. However, systematic selection of reference genes under weak lighting for herbaceous peony is lacking. To address this problem, we first selected 10 candidate reference genes based on a coefficient of variation of gene expression from peony stem transcriptome data. Then, geNorm, NormFinder and BestKeeper were applied to assess the stability of the genes, and RankAggreg was used to give a comprehensive ranking. The results show that there are some differences in optimal reference genes among samples from different organs and under the two lighting conditions, and the optimal number of suitable reference genes is distinct. Two selected suitable reference genes were then used to normalize target genes, and the results were compared with transcriptome data. Consistent gene expression trends were obtained, indicating the reliability of the method. To the best of our knowledge, this is the first time reference genes for herbaceous peony were selected in different organs, developmental stages and under two kinds of lighting conditions. The findings can provide a practical method for selecting reference genes for peony under these conditions and demonstrate a useful combination of reference genes.

Entities:  

Keywords:  F-box; GAPDH; Herbaceous peony; Light stress; Reference gene

Year:  2019        PMID: 31404229      PMCID: PMC6656899          DOI: 10.1007/s12298-019-00684-2

Source DB:  PubMed          Journal:  Physiol Mol Biol Plants        ISSN: 0974-0430


  28 in total

1.  Guideline to reference gene selection for quantitative real-time PCR.

Authors:  Aleksandar Radonić; Stefanie Thulke; Ian M Mackay; Olfert Landt; Wolfgang Siegert; Andreas Nitsche
Journal:  Biochem Biophys Res Commun       Date:  2004-01-23       Impact factor: 3.575

2.  Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations.

Authors:  Michael W Pfaffl; Ales Tichopad; Christian Prgomet; Tanja P Neuvians
Journal:  Biotechnol Lett       Date:  2004-03       Impact factor: 2.461

3.  Real-time RT-PCR profiling of over 1400 Arabidopsis transcription factors: unprecedented sensitivity reveals novel root- and shoot-specific genes.

Authors:  Tomasz Czechowski; Rajendra P Bari; Mark Stitt; Wolf-Rüdiger Scheible; Michael K Udvardi
Journal:  Plant J       Date:  2004-04       Impact factor: 6.417

4.  The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization.

Authors:  K Dheda; J F Huggett; J S Chang; L U Kim; S A Bustin; M A Johnson; G A W Rook; A Zumla
Journal:  Anal Biochem       Date:  2005-09-01       Impact factor: 3.365

5.  Mapping and quantifying mammalian transcriptomes by RNA-Seq.

Authors:  Ali Mortazavi; Brian A Williams; Kenneth McCue; Lorian Schaeffer; Barbara Wold
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

6.  Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress.

Authors:  Nathalie Nicot; Jean-François Hausman; Lucien Hoffmann; Danièle Evers
Journal:  J Exp Bot       Date:  2005-09-27       Impact factor: 6.992

7.  Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis.

Authors:  Tomasz Czechowski; Mark Stitt; Thomas Altmann; Michael K Udvardi; Wolf-Rüdiger Scheible
Journal:  Plant Physiol       Date:  2005-09       Impact factor: 8.340

8.  Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

Authors:  Claus Lindbjerg Andersen; Jens Ledet Jensen; Torben Falck Ørntoft
Journal:  Cancer Res       Date:  2004-08-01       Impact factor: 12.701

9.  RankAggreg, an R package for weighted rank aggregation.

Authors:  Vasyl Pihur; Susmita Datta; Somnath Datta
Journal:  BMC Bioinformatics       Date:  2009-02-19       Impact factor: 3.169

10.  Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

Authors:  Jo Vandesompele; Katleen De Preter; Filip Pattyn; Bruce Poppe; Nadine Van Roy; Anne De Paepe; Frank Speleman
Journal:  Genome Biol       Date:  2002-06-18       Impact factor: 13.583

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  4 in total

1.  Candidate reference genes for quantitative gene expression analysis in Lagerstroemia indica.

Authors:  Manli Chen; Qing Wang; Ya Li; Lulu Gao; Fenni Lv; Rutong Yang; Peng Wang
Journal:  Mol Biol Rep       Date:  2021-02-11       Impact factor: 2.316

2.  Ca2+ participates in programmed cell death by modulating ROS during pollen cryopreservation.

Authors:  Ruifen Ren; Hao Zhou; Lingling Zhang; Xueru Jiang; Yan Liu
Journal:  Plant Cell Rep       Date:  2022-02-21       Impact factor: 4.570

3.  Transcriptome and weighted correlation network analyses provide insights into inflorescence stem straightness in Paeonia lactiflora.

Authors:  Yingling Wan; Min Zhang; Aiying Hong; Xinyu Lan; Huiyan Yang; Yan Liu
Journal:  Plant Mol Biol       Date:  2019-12-12       Impact factor: 4.076

4.  Characteristics of Microsatellites Mined from Transcriptome Data and the Development of Novel Markers in Paeonia lactiflora.

Authors:  Yingling Wan; Min Zhang; Aiying Hong; Yixuan Zhang; Yan Liu
Journal:  Genes (Basel)       Date:  2020-02-19       Impact factor: 4.096

  4 in total

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