Ppia is the most stable housekeeping gene for qRT-PCR normalization in kidneys of three Pkd1-deficient mouse models

Anauate, Ana Carolina; Amaral, Andressa Godoy; Ferreira, Frederico Moraes; Watanabe, Elieser Hitoshi; Meca, Renata; Ormanji, Milene Subtil; Boim, Mirian Aparecida; Onuchic, Luiz Fernando; Heilberg, Ita Pfeferman

doi:10.1038/s41598-021-99366-x

Cited by 12 publications

(6 citation statements)

References 65 publications

(76 reference statements)

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“…Previous studies have reported relatively high variability for the expression of WU-HKGs in a varied range of tissues and organs in livestock animals ( Gromboni et al, 2020 ; Lozano-Villegas et al, 2021 ) as well as in humans ( Mahoney et al, 2004 ; Caracausi et al, 2017 ; Cadenas et al, 2022 ), mice ( Fu et al, 2020 ; Muñoz et al, 2021 ), and insects ( Shi et al, 2016 ), among others.…”

Section: Resultsmentioning

confidence: 99%

Investigation of chicken housekeeping genes using next-generation sequencing data

et al. 2022

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Accurate normalization of the gene expression assays, using housekeeping genes (HKGs), is critically necessary. To do so, selection of a proper set of HKGs for a specific experiment is of great importance. Despite many studies, there is no consensus about the suitable set of HKGs for implementing in the quantitative real-time PCR analyses of chicken tissues. A limited number of HKGs have been widely used. However, wide utilization of a little number of HKGs for all tissues is challenging. The emergence of high-throughput gene expression RNA-seq data has enabled the simultaneous comparison of the stability of multiple HKGs. Therefore, employing the average coefficient of variations of at least three datasets per tissue, we sorted all reliably expressed genes (REGs; with FPKM ≥ 1 in at least one sample) and introduced the top 10 most suitable and stable reference genes for each of the 16 chicken tissues. We evaluated the consistency of the results of five tissues using the same methodology on other datasets. Furthermore, we assessed 96 previously widely used HKGs (WU-HKGs) in order to challenge the accuracy of the previous studies. The New Tuxedo software suite was used for the main analyses. The results revealed novel, different sets of reference genes for each of the tissues with 17 common genes among the top 10 genes lists of 16 tissues. The results did disprove the suitability of WU-HKGs such as Actb, Ldha, Scd, B2m, and Hprt1 for any of the tissues examined. On the contrary, a total of 6, 13, 14, 23, and 32 validated housekeeping genes (V-HKGs) were discovered as the most stable and suitable reference genes for muscle, spleen, liver, heart, and kidney tissues, respectively. Although we identified a few new HKGs usable for multiple tissues, the selection of suitable HKGs is required to be tissue specific. The newly introduced reference genes from the present study, despite lacking experimental validation, will be able to contribute to the more accurate normalization for future expression analysis of chicken genes.

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Section: Resultsmentioning

confidence: 99%

Investigation of chicken housekeeping genes using next-generation sequencing data

et al. 2022

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“…It is well demonstrated that TGF-β stimulates production of fibronectin , vimentin, and α-SMA in cultured MCs 2 , 42 ; thus, the best HKG combinations herein determined were used to normalize these target genes. Several studies have reported that Ppia 14 , 17 , 43 – 48 , Gapdh 44 , 49 , 50 , and 18S 45 , 51 – 53 are suitable reference genes and could be used as normalizers of target genes in different models. In the present study, the top three candidate reference genes, whether used alone or in combination, showed the expected increase in the expression of the target genes in the TGF-β-treated group.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the growing number of studies investigating the reference genes for renal disease models 10 , 16 , 17 , to our knowledge there are no detailed reports selecting the most stable gene recommended for the frequently used in vitro model of TGF-β-induced fibrogenesis in MCs. This limitation may lead to non-reproducible data.…”

Section: Introductionmentioning

confidence: 99%

Determination of reference genes as a quantitative standard for gene expression analysis in mouse mesangial cells stimulated with TGF-β

Bronel

Anauate

Maquigussa

et al. 2022

Sci Rep

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Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard technique for gene expression analysis, but the choice of quantitative reference genes (housekeeping genes, HKG) remains challenging. Identify the best HKG is essential for estimating the expression level of target genes. Therefore, the aim of this study was to determine the best HKG for an in vitro model with mouse mesangial cells (MMCs) stimulated with 5 ng/mL of TGF-β. Five candidates HKG were selected: Actb, Hprt, Gapdh, 18S and Ppia. After quantitative expression, the best combination of these genes was analyzed in silico using six software programs. To validate the results, the best genes were used to normalize the expression levels of fibronectin, vimentin and α-SMA. In silico analysis revealed that Ppia, Gapdh and 18S were the most stable genes between the groups. GenEX software and Spearman's correlation determined Ppia and Gapdh as the best HKG pair, and validation of the HKG by normalizing fibronectin, vimentin and α-SMA were consistent with results from the literature. Our results established the combination of Ppia and Gapdh as the best HKG pair for gene expression analysis by RT-PCR in this in vitro model using MMCs treated with TGF-β.

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“…MiR-16-5p was found to show the most stable expression levels across the samples with a p -value of 0.452 in comparison to RNU6B which had a p -value of 0.001. In the case of RNA reference genes, PPIA [ 53 ] and GAPDH [ 54 ] were compared. Here, PPIA was found to show the most stable expression levels across the samples with a p -value of 0.019 in comparison to GAPDH which had a p -value of 0.003.…”

Section: Methodsmentioning

confidence: 99%

Characterization of Adrenal miRNA-Based Dysregulations in Cushing’s Syndrome

Vetrivel

Zhang

Engel

et al. 2022

IJMS

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MiRNAs are important epigenetic players with tissue- and disease-specific effects. In this study, our aim was to investigate the putative differential expression of miRNAs in adrenal tissues from different forms of Cushing’s syndrome (CS). For this, miRNA-based next-generation sequencing was performed in adrenal tissues taken from patients with ACTH-independent cortisol-producing adrenocortical adenomas (CPA), from patients with ACTH-dependent pituitary Cushing’s disease (CD) after bilateral adrenalectomy, and from control subjects. A confirmatory QPCR was also performed in adrenals from patients with other CS subtypes, such as primary bilateral macronodular hyperplasia and ectopic CS. Sequencing revealed significant differences in the miRNA profiles of CD and CPA. QPCR revealed the upregulated expression of miR-1247-5p in CPA and PBMAH (log2 fold change > 2.5, p < 0.05). MiR-379-5p was found to be upregulated in PBMAH and CD (log2 fold change > 1.8, p < 0.05). Analyses of miR-1247-5p and miR-379-5p expression in the adrenals of mice which had been exposed to short-term ACTH stimulation showed no influence on the adrenal miRNA expression profiles. For miRNA-specific target prediction, RNA-seq data from the adrenals of CPA, PBMAH, and control samples were analyzed with different bioinformatic platforms. The analyses revealed that both miR-1247-5p and miR-379-5p target specific genes in the WNT signaling pathway. In conclusion, this study identified distinct adrenal miRNAs as being associated with CS subtypes.

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Ppia is the most stable housekeeping gene for qRT-PCR normalization in kidneys of three Pkd1-deficient mouse models

Cited by 12 publications

References 65 publications

Investigation of chicken housekeeping genes using next-generation sequencing data

Investigation of chicken housekeeping genes using next-generation sequencing data

Determination of reference genes as a quantitative standard for gene expression analysis in mouse mesangial cells stimulated with TGF-β

Characterization of Adrenal miRNA-Based Dysregulations in Cushing’s Syndrome

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