背景：在定量实时聚合酶链反应（qRT-PCR）实验中，准确可靠的靶基因表达结果取决于管家基因（HKG）的最佳扩增。RNA-seq技术提供了一种新的方法来检测具有改进的稳定性的新HKG。山羊（Caprahircus）是经济上重要的牲畜物种，在世界动物纤维和肉类产业中起着不可或缺的作用。不幸的是,尚未在山羊中确定用于皮肤研究的统一可靠的HKG。因此,本研究旨在利用高通量测序技术，为C.hircus的皮肤组织鉴定一组稳定的HKG。
结果：基于39个山羊皮肤组织样本的转录组数据集，8个基因(SRP68，NCBP3，RRAGA，EIF4H,CTBP2,PTPRA,CNBP,和EEF2）具有相对稳定的表达水平被鉴定并选择为新的候选HKG。先前研究中常用的HKG，包括SDHA和YWHAZ，还检查了2个常规基因(ACTB和GAPDH)。四个不同的实验变量：（1）不同的发展阶段，（2）毛囊周期阶段，(3)品种,(4)采样点用于测定和验证。四种算法(geNorm，NormFinder,BestKeeper,和ΔCt方法)和综合算法(ComprFinder，内部开发)用于评估每个HKG的稳定性。结果表明，在所有条件分析中，NCBP3SDHAPTPRA的表达比以前使用的基因更稳定。并且这种组合在使靶基因表达正常化方面是有效的。此外，一种用于综合分析的新算法，ComprFinder,开发和发布。
结论：本研究基于RNA-seq数据集，提出了用于C.hircus皮肤组织的候选HKG的第一个列表。我们建议NCBP3SDHAPTPRA组合可被视为在C.hircus和其他密切相关物种的皮肤分子生物学实验中HKG的三联体。此外,我们还鼓励进行HKG候选评估并需要全面分析的研究人员采用我们的新算法，ComprFinder。
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.
CONCLUSIONS: 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.
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