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Background  In quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression results are dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat ( Capra hircus ) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for skin research have not been identified in goat. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of  C. hircus  using high-throughput sequencing technology.    Results  Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes ( SRP68 ,  NCBP3 ,  RRAGA ,  EIF4H ,  CTBP2 ,  PTPRA ,  CNBP , and  EEF2 ) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including  SDHA  and  YWHAZ  from a previous study, and 2 conventional genes ( ACTB  and  GAPDH ) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds, and (4) sampling sites were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that  NCBP3 + SDHA + PTPRA  were more stably expressed than previously used genes in all conditions analysis, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released.    Conclusion  This study presents the first list of candidate HKGs for  C. hircus  skin tissues based on an RNA-seq dataset. We propose that the  NCBP3 + SDHA + PTPRA  combination could be regarded as a triplet set of HKGs in skin molecular biology experiments in  C. hircus  and other closely related species. In addition, we also encourage researchers who perform candidate HKG evaluations and who require comprehensive analysis to adopt our new algorithm, ComprFinder.

Transcriptome-based selection and validation of optimal house-keeping genes for skin research in goats (Capra hircus)