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Brown adipose tissues have unique non-shivering thermogenesis functions, can be found in newborn ruminate animals, and then are gradually replaced by white adipose tissues in adulthood. For the purpose of exploring the intrinsic mechanism underlying the conversion process from brown (BAT) to white adipose tissue (WAT), it is necessary to utilize Quantitative PCR (qPCR) to study gene expression profiling. In this study, we identified reference genes that were consistently expressed during the transformation from goat BAT to WAT using RNA-seq data. Then, twelve genes were evaluated as candidate reference genes for qPCR in goat perirenal adipose tissue using three tools (geNorm, Normfinder, and BestKeeper). In addition, the selected reference genes were used to normalize the gene expression of PGC-1α and GPAT4. It was found that traditional reference genes, such as GAPDH, RPLP0, HPRT1, and PPIA were not suitable for target gene normalization. In contrast, CTNNB, PFDN5, and EIF3M, selected from RNA sequencing data, showed the least variation and were recommended as the best reference genes during the transformation from BAT to WAT.
Pubmed ID: 32927876
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Excel-based tool using pair-wise correlations for determination of stable housekeeping genes, differentially regulated target genes and sample integrity. It determines the best suited standards, out of ten candidates, and combines them into an index. The index can be compared with further ten target genes to decide, whether they are differentially expressed under an applied treatment. All data processing is based on crossing points.
View all literature mentionsSoftware for identifying the optimal normalization gene among a set of candidates. It ranks the set of candidate normalization genes according to their expression stability in a given sample set and given experimental design. It can analyze expression data obtained through any quantitative method e.g. real time RT-PCR and microarray based expression analysis. NormFinder.xla adds the NormFinder functionality directly to Excel. A version for R is also available.
View all literature mentionsSoftware to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.
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