A Novel Strategy Facilitates Reference Gene Selection by RT-qPCR Analysis in Kidney Yang Deficiency Syndrome Mice Infected with the Influenza A (H1N1) Virus

Abstract

In reverse transcription-quantitative polymerase chain reaction (RT-qPCR) studies, endogenous reference genes are routinely used to normalize the expression of target gene studies. In order to precisely evaluate the relative expression of genes in the cells of mice suffering from Kidney Yang Deficiency Syndrome (KYDS) in response to influenza A virus (IAV) H1N1 using RT-qPCR, it is crucial to identify reliable reference genes. In the present study, 15 candidate reference genes (Actb, β2m, Gapdh, Gusb, Tuba, Grcc10, Eif4h, Rnf187, Nedd8, Ywhae, 18S rRNA, Rpl13, Ubc, Rpl32, and Ppia) were investigated in lung cells from KYDS mice infected with IAV H1N1. NormFinder, BestKeeper, and GeNorm were used to assess the stability of reference genes. The results were authenticated over extended experimental settings by a group of 10 samples. In the present study, we explored a novel method using dual-gene combinations; the difference in gene expression between the model and normal control groups was statistically analyzed by an independent-samples t-test, and the difference in the mean value between the two groups was compared. A P value > 0.05 and the lowest absolute value of the difference indicated the optimal reference two-gene combination. Four additional host innate immune system-related genes (TLR3, TLR4, TLR7, and RIG-I) were analyzed together with the two treatment datasets to confirm the selected reference genes. Our results indicated that none of these 15 candidate reference genes can be used as reference gene individually for relative quantitative fluorescence PCR analysis; however, the combination of Grcc10 and Ppia, based on the process of calculating the higher P value and lower difference values between groups, was the best choice as a reference gene for the lung tissue samples in KYDS mice infected with IAV. This technique may be applied to promote the selection process of the optimal reference gene in other experiments.

Investigation of chicken housekeeping genes using next-generation sequencing data

“…Being excluded from the analyses in the filtration steps, Rpl32 was not identified as a suitable HKG in the current work for neither lung tissue nor other tissues. The results of Fu et al (2020) indicated that none of the 15 WU-HKGs that they studied were sufficiently good as reference genes. However, they suggested the combination of Grcc10 and Ppia genes as a proper choice for the lung tissue of mouse infected with IAV.…”

“…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.…”

Immune-related lncRNA pairs as novel signature to predict prognosis and immune landscape in melanoma patients

“…All possible pairs of DEirlncRNAs (denoted lncRNA-A and lncRNA-B, respectively) were identified and assessed based on the following definitions: (I) if the ratio of lncRNA-A expression to lncRNA-B expression was greater than 1, the pair was defined as lncRNA-A|lncRNA-B = 1; (II) if the ratio of lncRNA-A expression to lncRNA-B expression was less than 1, the pair was defined as lncRNA-A|lncRNA-B = 0; (III) for a given pair, if lncRNA-A|lncRNA-B = 1 in more than 80% of all patients, the pair was considered invalid; and (IV) if lncRNA-A|lncRNA-B = 0 in more than 80% of all patients, the pair was also considered invalid. [ 21 ] Valid DEirlncRNA pairs were identified by applying these definitions and used to construct a matrix with each entry corresponding to the value of the respective lncRNA-A|lncRNA-B. Combining clinical survival status and survival time data from TCGA, prognostic DEirlncRNA pairs were obtained by univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis.…”

“…[ 11 , 20 ] Compared to multiple gene combinations, two-gene combination strategy can provide relative expression within a sample, leading to more robust and accurate speculation. [ 11 , 21 , 22 ] At the same time, the relative expression of gene pairs takes into account all possible combinations. [ 23 ] Therefore, developing new irlncRNAs to treat melanoma is of great significance and could improve the quality of life of patients.…”

“…Such irlncRNAs are of great value in evaluating tumor characteristics, prognosis, and treatment [11,20] . Compared to multiple gene combinations, two-gene combination strategy can provide relative expression within a sample, leading to more robust and accurate speculation [11,21,22] . At the same time, the relative expression of gene pairs takes into account all possible combinations [23] .…”