Rat deconvolution as knowledge miner for immune cell trafficking from toxicogenomics databases

Toxicogenomics databases are useful for understanding biological responses in individuals because they are derived from well-controlled experiments and include a diverse spectrum of biological responses. Although these databases contain no information regarding immune cells in the liver, which are important in the progression of liver injury, deconvolution that estimates cell-type proportions from bulk transcriptome could add information regarding immune cell trafficking to the database. However, deconvolution has been mainly applied to humans and mice and less often to rats, which are the main target of toxicogenomics databases. Here, we developed a deconvolution method for rats and established a methodology to obtain information regarding immune cells from toxicogenomics databases. The contributions of this work are three-fold. First, we obtained the gene expression profiles of various rat immune cells necessary for deconvolution and constructed a dataset; second, we compared the accuracy of models based on human and mouse datasets and showed the impact of species differences on deconvolution; third, we showed that rat deconvolution could retrieve information regarding immune cell trafficking from toxicogenomics databases. Correspondence: Tadahaya Mizuno毒理基因组学（Toxicogenomics）数据库有助于解析个体的生物学应答，因其源自经过严格对照设计的实验，且涵盖了多样化的生物学应答谱。 尽管此类数据库未包含与肝损伤进展密切相关的肝脏免疫细胞相关信息，但从批量转录组（bulk transcriptome）数据中估算细胞类型占比的细胞反卷积（deconvolution）技术，可为数据库补充免疫细胞迁移相关的信息。 不过，细胞反卷积技术目前主要应用于人类与小鼠，在作为毒理基因组学数据库主要研究对象的大鼠中应用较少。 本研究开发了一款适用于大鼠的细胞反卷积方法，并建立了从毒理基因组学数据库中提取免疫细胞相关信息的研究方法。 本研究的贡献主要有三点：其一，获取了细胞反卷积所需的各类大鼠免疫细胞基因表达谱，并构建了配套数据集；其二，对比了基于人类与小鼠数据集训练的模型的准确性，阐明了物种差异对细胞反卷积效果的影响；其三，验证了大鼠专属细胞反卷积方法可从毒理基因组学数据库中提取免疫细胞迁移相关的信息。 通讯作者：Tadahaya Mizuno