{"title":"Stability of the sdha, hprt, prl3d1 and hes1 Gene Expression in a Rat Liver Fibrosis Model","authors":"E. I. Lebedeva, A. S. Babenko, A. Shchastniy","doi":"10.33647/2074-5982-18-2-17-30","DOIUrl":null,"url":null,"abstract":"So far, no versatile set of reference genes for normalizing real-time polymerase chain reaction data has been identified. Numerous studies focusing the selection of reference genes for specific purposes frequently fail to elaborate a suitable selection strategy. In a number of such studies, the stage of selecting reference genes is ignored due to either its high cost or other reasons. As a result, the normalization of data is carried out using genes, which have previously shown their effectiveness under other, sometimes completely different, experimental conditions. In this work, we aim to study variations in the level of mRNA expression of several genes, some of which are commonly used to normalize RT-PCR data. As special conditions, modeling of rat liver fibrosis with thioacetamide was used.In our experiment, when considering the process of fibrogenesis as a whole, the optimal reference genes were found to be hes1 and sdha. However, when focusing on specific stages of fibrosis, a pair of genes should be selected depending on the stability indicators. At the initial fibrogenesis stages, sdha and hprt can be used. The hes1 gene is suitable as a reference gene, when the average Cq value of the target genes is approximately 29 cycles (as in hes1). Hes1 should be used with care when working in the Cq ranges of target genes of 26–29 and above 30, since the error is likely to increase. Following the same principle, the optimum Cq value for the sdha gene was observed to be 27, although the Cq range of 24–27 is also acceptable. At the same time, when working in the Cq range of above 28, the use of sdha may be associated with an increase in calculation errors.","PeriodicalId":14837,"journal":{"name":"Journal Biomed","volume":"68 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal Biomed","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33647/2074-5982-18-2-17-30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
So far, no versatile set of reference genes for normalizing real-time polymerase chain reaction data has been identified. Numerous studies focusing the selection of reference genes for specific purposes frequently fail to elaborate a suitable selection strategy. In a number of such studies, the stage of selecting reference genes is ignored due to either its high cost or other reasons. As a result, the normalization of data is carried out using genes, which have previously shown their effectiveness under other, sometimes completely different, experimental conditions. In this work, we aim to study variations in the level of mRNA expression of several genes, some of which are commonly used to normalize RT-PCR data. As special conditions, modeling of rat liver fibrosis with thioacetamide was used.In our experiment, when considering the process of fibrogenesis as a whole, the optimal reference genes were found to be hes1 and sdha. However, when focusing on specific stages of fibrosis, a pair of genes should be selected depending on the stability indicators. At the initial fibrogenesis stages, sdha and hprt can be used. The hes1 gene is suitable as a reference gene, when the average Cq value of the target genes is approximately 29 cycles (as in hes1). Hes1 should be used with care when working in the Cq ranges of target genes of 26–29 and above 30, since the error is likely to increase. Following the same principle, the optimum Cq value for the sdha gene was observed to be 27, although the Cq range of 24–27 is also acceptable. At the same time, when working in the Cq range of above 28, the use of sdha may be associated with an increase in calculation errors.