Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations.
Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations.
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DOI：
10.1038/s41598-018-29506-3
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发表时间：
2018-07-25
影响因子：
4.6
通讯作者：
Al-Khalili Szigyarto C
中科院分区：
文献类型：
--
作者：
Fasterius E;Al-Khalili Szigyarto C
对公共存储库中可用数据集的荟萃分析用于收集和总结跨实验室进行的实验，并探索科学发现的一致性。由于样本之间的数据质量和生物等效性可能会掩盖此类分析及其结论，因此我们研究了 85 个公共 RNA-seq 细胞系数据集的可比性。对 139 个样本中的单核苷酸变异进行数千次配对比较，揭示了所分析的 8 个细胞系群体的可变遗传异质性以及可变的数据质量。研究发现，H9 和 HCT116 细胞系在各个实验室中都非常稳定（中位一致性分别为 99.2% 和 98.5%），与高度可变的 HeLa 细胞 (89.3%) 形成鲜明对比。我们表明，遇到的遗传异质性极大地影响了同细胞比较之间的基因表达，强调了在比较实验数据集时询问样本的生物等效性的重要性。差异表达基因的数量和表达水平均与遗传异质性负相关。最后，我们展示了比较遗传异质数据集如何影响基因表达分析，以及同细胞数据集之间的高度差异改变了 300 多个癌症相关基因的表达，这通常是使用细胞系的研究的焦点。
Meta-analysis of datasets available in public repositories are used to gather and summarise experiments performed across laboratories, as well as to explore consistency of scientific findings. As data quality and biological equivalency across samples may obscure such analyses and consequently their conclusions, we investigated the comparability of 85 public RNA-seq cell line datasets. Thousands of pairwise comparisons of single nucleotide variants in 139 samples revealed variable genetic heterogeneity of the eight cell line populations analysed as well as variable data quality. The H9 and HCT116 cell lines were found to be remarkably stable across laboratories (with median concordances of 99.2% and 98.5%, respectively), in contrast to the highly variable HeLa cells (89.3%). We show that the genetic heterogeneity encountered greatly affects gene expression between same-cell comparisons, highlighting the importance of interrogating the biological equivalency of samples when comparing experimental datasets. Both the number of differentially expressed genes and the expression levels negatively correlate with the genetic heterogeneity. Finally, we demonstrate how comparing genetically heterogeneous datasets affect gene expression analyses and that high dissimilarity between same-cell datasets alters the expression of more than 300 cancer-related genes, which are often the focus of studies using cell lines.
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影响因子：
14.9
作者：
NCBI Resource Coordinators
通讯作者：
NCBI Resource Coordinators
影响因子：
3.3
作者：
Dolinski K;Troyanskaya OG
通讯作者：
Troyanskaya OG
影响因子：
12.3
作者：
Cirulli ET;Singh A;Shianna KV;Ge D;Smith JP;Maia JM;Heinzen EL;Goedert JJ;Goldstein DB;Center for HIV/AIDS Vaccine Immunology (CHAVI)
通讯作者：
Center for HIV/AIDS Vaccine Immunology (CHAVI)
278 种广泛使用的肿瘤细胞系交叉污染和误识别的调查
影响因子：
3.7
作者：
Huang Y;Liu Y;Zheng C;Shen C
通讯作者：
Shen C
物种鉴定和Str分析的组合可以鉴定出482个人类肿瘤细胞系的交叉污染细胞。
影响因子：
4.6
作者：
Bian X;Yang Z;Feng H;Sun H;Liu Y
通讯作者：
Liu Y