Literature DB >> 26400285

Identification and evaluation of endogenous control genes for use in quantitative RT-PCR during wheat (Triticum aestivum L.) grain filling.

D Wu1, J Dong1, Y J Yao1, W C Zhao1, X Gao2.   

Abstract

The use of appropriate reference genes is essential for the generation of accurate and biologically meaningful results from quantitative real-time PCR (qRT-PCR) analysis. However, studies have found that the expression of most commonly used reference genes is not always independent of the tissues, treatments, or developmental stages studied. geNormPlus, NormFinder, and BestKeeper, were applied and the expression stability of nine candidate genes was evaluated in different data sets during wheat grain development. Varying degrees of diversity in either single or multiple reference genes were observed among the results generated from the different computer programs, parameters, and data sets. Therefore, the reliability of identified reference genes in the flag leaf and the complete set of samples was estimated by monitoring the expression dynamics of three NAM genes (TaNAM-A1, TaNAM-B1, and TaNAM-B2). The results suggest that a single control gene identified by geNormPlus for use with the complete set of samples, and multiple reference genes selected by geNormPlus and NormFinder exclusively for the flag leaf outperformed others owing to the consistent results with previous analyses of these genes, which were normalized against a verified single control gene. Given the limit of NormFinder in gene numbers of multiple reference genes, robust quantification can be achieved by normalizing against Ta27922 or multiple reference genes chosen by geNormPlus for individual tissues.

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Year:  2015        PMID: 26400285     DOI: 10.4238/2015.September.8.15

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  1 in total

1.  Genome-wide identification of internal reference genes for normalization of gene expression values during endosperm development in wheat.

Authors:  Junyi Mu; Lin Chen; Yunsong Gu; Luning Duan; Shichen Han; Yaxuan Li; Yueming Yan; Xiaohui Li
Journal:  J Appl Genet       Date:  2019-07-11       Impact factor: 3.240

  1 in total

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