Untangling the effects of cellular composition on coexpression analysis
Untangling the effects of cellular composition on coexpression analysis
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DOI：
10.1101/gr.256735.119
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发表时间：
2020-06-01
期刊：
影响因子：
7
通讯作者：
Pavlidis, Paul
中科院分区：
文献类型：
--
作者：
Farahbod, Marjan;Pavlidis, Paul
共表达分析被广泛用于推断调控网络，预测基因功能，以及基于聚类等方法的转录组分析研究的解释。大多数此类研究使用从大块组织收集的数据，其中细胞组成的影响存在潜在的混淆。然而，组合物对共表达分析的影响尚未详细研究。在这里，我们研究这个问题的情况下，人类RNA分析。聚焦于脑组织，我们发现，对于大多数基因，不同细胞类型的表达水平差异占其测量的RNA水平方差的很大一部分（中位数R-2 = 0.68）。然后，我们表明，在不同细胞类型中具有相似表达模式的基因，由于细胞组成变化的影响，在大块组织中具有相关的RNA水平。我们证明，大部分的共表达和共表达簇的形成可以归因于这种影响的大脑和血液转录组。对于大脑，我们进一步展示了这种组合物诱导的共表达如何掩盖在单细胞数据中观察到的潜在细胞内共表达。试图纠正成分产生了混合的结果。我们的结论是，在大脑，血液，并可能，其他复杂的组织中占主导地位的共表达信号可以归因于细胞成分的影响，而不是细胞内型的调控关系。这些结果对共表达分析的相关性和解释有影响。
Coexpression analysis is widely used for inferring regulatory networks, predicting gene function, and interpretation of transcriptome profiling studies, based on methods such as clustering. The majority of such studies use data collected from bulk tissue, where the effects of cellular composition present a potential confound. However, the impact of composition on coexpression analysis has not been studied in detail. Here, we examine this issue for the case of human RNA analysis. Focusing on brain tissue, we found that, for most genes, differences in expression levels across cell types account for a large fraction of the variance of their measured RNA levels (median R-2 = 0.68). We then show that genes that have similar expression patterns across cell types will have correlated RNA levels in bulk tissue, due to the effect of variation in cellular composition. We demonstrate that much of the coexpression and the formation of coexpression clusters can be attributed to this effect for both brain and blood transcriptomes. For brain, we further show how this composition-induced coexpression masks underlying intra-cell-type coexpression observed in single-cell data. An attempt to correct for composition yielded mixed results. Our conclusion is that the dominant coexpression signal in brain, blood, and, likely, other complex tissues can be attributed to cellular compositional effects, rather than intra-cell-type regulatory relationships. These results have implications for the relevance and interpretation of coexpression analysis.