Stable reference genes selected from RNAseq data do not offer any significant advantage over conventional reference genes for normalizing qPCR assays
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PROVIDER: PRJNA741505 | ENA |
REPOSITORIES: ENA
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Project description:Using robust reference genes which are stably expressed across the samples to normalized qPCR data in a study is crucial. The choice of such reference genes are made based on different approaches. Additionally, a growing body of literature suggests the use of RNA-seq as a prerequisite for choosing optimal reference genes. In this study, we raised two major questions. Firstly, is RNA-seq necessary to find stably expressing genes that could be used as reference genes to normalize qPCR data? In order to address this question we have devised a previously described statistical pipeline of ours to best select the reference genes. Interestingly, we found that RNA-seq is not necessarily needed to find optimal reference genes. Addressing this question raised the second question, is this pipeline is effective for cross-sectional studies and longitudinal studies and in different models of various species. We report that our statistical pipeline that combines two different approaches works robustly in both of the setups we have tried.
2021-12-01 | GSE178924 | GEO
Project description:In this study, we investigated the transcriptome of Bifidobacterium bifidum PRL2010 during in vitro growth by micro array technology. When B. bifidum PRL2010 was grown in liquid broth, 425 of the 1644 PRL2010 genes represented on the array were expressed in at least one of the three investigated growth phases, i.e., lag-, exponential and stationary phase. These transcriptional analyses identified a core in vitro transcriptome encompassing 150 genes, which resulted expressed in all phases. A proportion of the latter genes were further investigated as potential reference genes by Quantitative Real Time PCR (qRT-PCR) assays. Their expression stability was evaluated under different growth conditions, encompassing cultivation on different carbon sources, exposure to environmental stresses (thermal, acidic and osmotic) and growth phases. Our analyses validated six reference genes suitable for normalizing mRNA expression levels in qRT-PCR experiments applied to bifidobacteria.
2012-01-05 | GSE30832 | GEO
Project description:The present work aimed to identify reference genes for RT-qPCR studies of hypoxia in cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia treatment in eight cervical cancer cell lines or correlated with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter ABrix in 42 patients. Among these genes, we selected nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the most suitable set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (ABrix) and clinical parameters. The suitability of the three candidates as reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalizing with CHCHD1, SRSF9 and TMBIM6, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n=74) and ABrix (P<0.05, n=32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in cervical cancer samples by RT-qPCR. STC2 might be a useful prognostic hypoxia biomarker in cervical cancer that warrants further investigation.
2016-03-29 | GSE75034 | GEO
Project description: Not available
| S-EPMC6848520 | biostudies-literature
Project description:We developed a R-based script to select internal control genes based solely on read counts and gene sizes. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the custom selected genes were more stable. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. were more stable) than commonly used reference genes.
2019-08-21 | GSE136038 | GEO
Project description:In this study, we investigated the transcriptome of Bifidobacterium bifidum PRL2010 during in vitro growth by micro array technology. When B. bifidum PRL2010 was grown in liquid broth, 425 of the 1644 PRL2010 genes represented on the array were expressed in at least one of the three investigated growth phases, i.e., lag-, exponential and stationary phase. These transcriptional analyses identified a core in vitro transcriptome encompassing 150 genes, which resulted expressed in all phases. A proportion of the latter genes were further investigated as potential reference genes by Quantitative Real Time PCR (qRT-PCR) assays. Their expression stability was evaluated under different growth conditions, encompassing cultivation on different carbon sources, exposure to environmental stresses (thermal, acidic and osmotic) and growth phases. Our analyses validated six reference genes suitable for normalizing mRNA expression levels in qRT-PCR experiments applied to bifidobacteria. Transcriptional profiling of B.bifidum PRL2010 at different growth phases (lag phase, early exponential phase, late exponential phase, early stationary phase).
2012-01-05 | E-GEOD-30832 | biostudies-arrayexpress
Project description:Background/Objective: Quantitative real-time PCR (RT-qPCR) is widely used in miRNA expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. A literature search in PubMed revealed that no study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference genes for miRNA expression studies by RT-qPCR in urothelial carcinoma. Methods: Candidate reference miRNAs were selected from 24 papillary urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. Principal Findings: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-3p, miR-151-5p, miR-181a, miR-181b miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. Conclusions: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-125a-5p, miR-148b, miR-151-3p, and miR-151-5p) or three (miR-148b, miR-874, miR-181b) miRNA reference genes is recommended for normalization.
2013-02-26 | GSE36121 | GEO
Project description:The present work aimed to identify reference genes for RT-qPCR studies of hypoxia in cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia treatment in eight cervical cancer cell lines or correlated with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter ABrix in 42 patients. Among these genes, we selected nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the most suitable set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (ABrix) and clinical parameters. The suitability of the three candidates as reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalizing with CHCHD1, SRSF9 and TMBIM6, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n=74) and ABrix (P<0.05, n=32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in cervical cancer samples by RT-qPCR. STC2 might be a useful prognostic hypoxia biomarker in cervical cancer that warrants further investigation. Totally 150 tumor samples and 12 cell line samples were analysed with Illumina WG-6 and 4 cell line samples were analysed with Illumina HT-12
2016-03-29 | E-GEOD-75034 | biostudies-arrayexpress
Project description:Arabidopsis thaliana has been used regularly as a model plant in gene expression studies on transcriptional reprogramming upon pathogen infection, such as that by Pseudomonas syringae pv. tomato DC3000 (Pst DC3000), or when subjected to stress hormone treatments including jasmonic acid (JA), salicylic acid (SA), and abscisic acid (ABA). RT-qPCR has been extensively employed to quantitate these gene expression changes. However, the accuracy of the quantitation is largely dependent on the stability of the expressions of reference genes used for normalization. Recently, RNA-seq has been widely used to mine stably expressed genes for use as references in RT-qPCR. However, the amplification step in RNA-seq creates an intrinsic bias against those genes with relatively low expression levels, and therefore does not provide an accurate quantification of all expressed genes. In this study, we employed mass spectrometry-based label-free quantification (LFQ) in proteomic analyses to identify those proteins with abundances unaffected by Pst DC3000 infection. We verified, using RT-qPCR, that the levels of their corresponding mRNAs were also unaffected by Pst DC3000 infection. In addition, using RT-qPCR, we verified that the mRNAs were stably expressed upon stress hormone treatments including JA, SA, and ABA. Results indicated that the candidate genes identified here had stable expressions upon these stresses and are suitable to be used as reference genes for RT-qPCR. Among the 18 candidate reference genes reported in this study, many of them had greater expression stability than the commonly used reference genes, such as ACT7, in previous studies. Here, besides proposing more appropriate reference genes for Arabidopsis expression studies, we also demonstrated the capacity of mass spectrometry-based LFQ to quantify protein abundance and the possibility to extend protein expression studies to the transcript level.
2022-09-05 | PXD035677 | Pride
Project description:We compared standard human reference genome GRCh38 and de novo assembled reference genome HX1 in precision medicine applications for specific ethnics. In order to quantify the HX1 misassembled genes and HX1-specific contigs, we performed RNA-seq and RNC-seq on hepatocellular carcinoma cell lines (MHCC97H, MHCCLM3 and MHCCLM6) which were derived from Chinese Han individuals. In which, RNC-seq datasets of MHCC97H and MHCCLM3 had been published. We found that a considerable fraction of HX1 misassembled genes was expressed in the Chinese Han samples. Furthermore, we found no HX1-specific contigs yielded more than 2.27 FPKM (minimun FPKM of 1 copy/cell transcript) in the Chinese Han sampels.
2019-06-01 | GSE121013 | GEO