School of Chemistry, 131, Princess Street, Manchester M1 7DN, UK; The Manchester Institute of Biotechnology, 131, Princess Street, Manchester M1 7DN, UK.
The Manchester Institute of Biotechnology, 131, Princess Street, Manchester M1 7DN, UK; Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester M13 9PL, UK.
Cell Syst. 2018 Feb 28;6(2):230-244.e1. doi: 10.1016/j.cels.2018.01.003. Epub 2018 Feb 7.
The expression levels of SLC or ABC membrane transporter transcripts typically differ 100- to 10,000-fold between different tissues. The Gini coefficient characterizes such inequalities and here is used to describe the distribution of the expression of each transporter among different human tissues and cell lines. Many transporters exhibit extremely high Gini coefficients even for common substrates, indicating considerable specialization consistent with divergent evolution. The expression profiles of SLC transporters in different cell lines behave similarly, although Gini coefficients for ABC transporters tend to be larger in cell lines than in tissues, implying selection. Transporter genes are significantly more heterogeneously expressed than the members of most non-transporter gene classes. Transcripts with the stablest expression have a low Gini index and often differ significantly from the "housekeeping" genes commonly used for normalization in transcriptomics/qPCR studies. PCBP1 has a low Gini coefficient, is reasonably expressed, and is an excellent novel reference gene. The approach, referred to as GeneGini, provides rapid and simple characterization of expression-profile distributions and improved normalization of genome-wide expression-profiling data.
SLC 或 ABC 膜转运蛋白转录本的表达水平在不同组织之间通常相差 100-10000 倍。基尼系数描述了这种不平等，这里用于描述每个转运蛋白在不同人类组织和细胞系中的表达分布。许多转运蛋白即使对常见的底物也表现出极高的基尼系数，表明存在与分歧进化相一致的高度专业化。不同细胞系中 SLC 转运蛋白的表达谱表现相似，尽管 ABC 转运蛋白的基尼系数在细胞系中通常大于组织，暗示选择。转运蛋白基因的表达比大多数非转运蛋白基因类别的成员明显更加异质。表达最稳定的转录本具有较低的基尼指数，并且通常与转录组学/qPCR 研究中常用的“管家”基因有显著差异。PCBP1 具有较低的基尼系数，表达合理，是一种极好的新型参考基因。该方法称为 GeneGini，可快速简单地描述表达谱分布，并改善全基因组表达谱数据的归一化。
