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Immune cells are highly plastic in both gene expression and cell phenotype. We have established a method of gene expressional plasticity and virtual sorting to evaluate immune cell subpopulations and their characteristic genes in human CD4 + T cells. In this study, we continued to investigate the informatics mechanism on the effectiveness of virtual sorting. We found that virtual sorting had an overall positive correlation to the Pearson correlation in the identification of positively correlated genes. However, owing to nonlinear biological anticorrelation, virtual sorting showed a distinctive advantage for anticorrelated genes, suggesting an important role in the identification of negative regulators. In addition, based on virtual sorting results, we identified two basic gene sets among highly plastic genes, i.e., highly plastic cell cycle-associated molecules and highly plastic immune and defense response-associated molecules. Genes within each set tended to be positively connected, but genes between two sets were often anticorrelated. Further analysis revealed preferential transcription factor binding motifs existed between highly plastic cell cycle-associated molecules and highly plastic immune and defense response-associated molecules. Our results strongly suggested predetermined regulation, which was called an immune cell internal phenotype, should exist and could be mined by virtual sorting analysis. This provided efficient functional clues to study immune cell phenotypes and their regulation. Moreover, the current substantial virtual sorting results in both CD4 + T cells and B cells provide a useful resource for big-data-driven experimental studies and knowledge discoveries.

Virtual Sorting Has a Distinctive Advantage in Identification of Anticorrelated Genes and Further Negative Regulators of Immune Cell Subpopulations