2015
DOI: 10.1371/journal.pone.0136343
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Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean

Abstract: Differential gene expression profiles often provide important clues for gene functions. While reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an important tool, the validity of the results depends heavily on the choice of proper reference genes. In this study, we employed new and published RNA-sequencing (RNA-Seq) datasets (26 sequencing libraries in total) to evaluate reference genes reported in previous soybean studies. In silico PCR showed that 13 out of 37 previously rep… Show more

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Cited by 73 publications
(70 citation statements)
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“…In this sense, several reports in different plant species like Arabidopsis 54, soybean45, rice55, cotton56 among others, have supported the importance of identifying stably expressed genes for each species, tissue, treatment or condition to be analyzed.…”
Section: Discussionmentioning
confidence: 98%
“…In this sense, several reports in different plant species like Arabidopsis 54, soybean45, rice55, cotton56 among others, have supported the importance of identifying stably expressed genes for each species, tissue, treatment or condition to be analyzed.…”
Section: Discussionmentioning
confidence: 98%
“…RNA‐seq data (see below) were exploited to select genes for normalization of the quantitative PCR data, applying the method of Yim et al . (). Briefly, genes with a coefficient of variation smaller than 20%, behaving in a normally distributed manner, and with large expression values (FPKM) were selected.…”
Section: Methodsmentioning
confidence: 97%
“…For real-time PCR experiments, RNase free DNase I treatment was carried out as previously described by Semighini, Marins, Goldman, and Goldman (2002). RNA-seq data (see below) were exploited to select genes for normalization of the quantitative PCR data, applying the method of Yim et al (2015). Briefly, genes with a coefficient of variation smaller than 20%, behaving in a normally distributed manner, and with large expression values (FPKM) were selected.…”
Section: Rna Extraction and Real-time Pcr Reactionsmentioning
confidence: 99%
“…For real‐time PCR experiments, RNase free DNase I treatment was carried out as previously described by Semighini, Marins, Goldman, and Goldman (). RNASeq data (see below) was exploited to select genes for normalisation of the qPCR data, applying the method of Yim et al (). Briefly, genes with a coefficient of variation smaller than 20%, behaving in a normally distributed manner, and with large expression values (FPKM), were selected.…”
Section: Methodsmentioning
confidence: 99%