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A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis.

ABSTRACT: Comparative DNA microarray analyses typically yield very large gene expression data sets that reflect complex patterns of change. Despite the wealth of information that is obtained, the identification of stable reference genes is required for normalization of disease- or drug-induced changes across tested groups. This is a prerequisite in quantitative real-time reverse transcription-PCR (qRT-PCR) and relative RT-PCR but rare in gene microarray analysis. The goal of the present study was to outline a simple method for identification of reliable reference genes derived from DNA microarray data sets by comparative statistical analysis of software-generated and manually calculated candidate genes.DNA microarray data sets derived from whole-blood samples obtained from 14 Zucker diabetic fatty (ZDF) rats (7 lean and 7 diabetic obese) were used for the method development. This involved the use of software-generated filtering parameters to accomplish the desired signal-to-noise ratios, 75th percentile signal manual normalizations, and the selection of reference genes as endogenous controls for target gene expression normalization.The combination of software-generated and manual normalization methods yielded a group of 5 stably expressed, suitable endogenous control genes which can be used in further target gene expression determinations in whole blood of ZDF rats.This method can be used to correct for potentially false results and aid in the selection of suitable endogenous control genes. It is especially useful when aimed to aid the software in cases of borderline results, where the expression and/or the fold change values are just beyond the pre-established set of acceptable parameters.

SUBMITTER: Casares FM

PROVIDER: S-EPMC4868104 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis.

Casares Federico M FM

Medical science monitor basic research 20160428

<h4>Background</h4>Comparative DNA microarray analyses typically yield very large gene expression data sets that reflect complex patterns of change. Despite the wealth of information that is obtained, the identification of stable reference genes is required for normalization of disease- or drug-induced changes across tested groups. This is a prerequisite in quantitative real-time reverse transcription-PCR (qRT-PCR) and relative RT-PCR but rare in gene microarray analysis. The goal of the present ...[more]

PMID: 27122237

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Project description:Due to its high sensitivity and reproducibility, quantitative real-time PCR (qPCR) is practiced as a useful research tool for targeted gene expression analysis. For qPCR operations, the normalization with suitable reference genes (RGs) is a crucial step that eventually determines the reliability of the obtained results. Although pepper is considered an ideal model plant for the study of non-climacteric fruit development, at present no specific RG have been developed or validated for the qPCR analyses of pepper fruit. Therefore, this study aimed to identify stably expressed genes for their potential use as RGs in pepper fruit studies. Initially, a total of 35 putative RGs were selected by mining the pepper transcriptome data sets derived from the PGP (Pepper Genome Platform) and PGD (Pepper Genome Database). Their expression stabilities were further measured in a set of pepper (Capsicum annuum L. var. 007e) fruit samples, which represented four different fruit developmental stages (IM: Immature; MG: Mature green; B: Break; MR: Mature red) using the qPCR analysis. Then, based on the qPCR results, three different statistical algorithms, namely geNorm, Normfinder, and boxplot, were chosen to evaluate the expression stabilities of these putative RGs. It should be noted that nine genes were proven to be qualified as RGs during pepper fruit development, namely CaREV05 (CA00g79660); CaREV08 (CA06g02180); CaREV09 (CA06g05650); CaREV16 (Capana12g002666); CaREV21 (Capana10g001439); CaREV23 (Capana05g000680); CaREV26 (Capana01g002973); CaREV27 (Capana11g000123); CaREV31 (Capana04g002411); and CaREV33 (Capana08g001826). Further analysis based on geNorm suggested that the application of the two most stably expressed genes (CaREV05 and CaREV08) would provide optimal transcript normalization in the qPCR experiments. Therefore, a new and comprehensive strategy for the identification of optimal RGs was developed. This strategy allowed for the effective normalization of the qPCR analysis of the pepper fruit development at the whole pepper genome level. This study not only explored the optimal RGs specific for studying pepper fruit development, but also introduced a referable strategy of RG mining which could potentially be implicated in other plant species.

Dataset Information

A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis.

Publications

A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis.

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