Using Single-Cell RNA-Seq Data to Trace Tissue Cells Responsive to Thyroid Hormones

Abstract

Thyroid hormones mediate a remarkable range of functions in many tissues and organ systems through the thyroid hormone receptors—THRA and THRB. Tissues and organs are composed of heterogeneous cells of different cell types. These different cell types have varying receptor expression abilities, which lead to variable responses in thyroid hormone regulation. The tissue-specific Thra and Thrb gene expression patterns help us understand the action of thyroid hormones at the tissue level. However, the situation becomes complicated if we wish to focus on tissues more closely to trace the responsive cells, which is a vital step in the process of understanding the molecular mechanism of diseases related to thyroid hormone regulation. Single-cell RNA sequencing technology is a powerful tool used to profile gene expression programs in individual cells. The Tabula Muris Consortium generates a single-cell transcriptomic atlas across the life span of Mus musculus that includes data from 23 tissues and organs. It provides an unprecedented opportunity to understand thyroid hormone regulation at the cell type resolution. We demonstrated the approaches that allow application of the single-cell RNA-Seq data generated by the Tabula Muris Consortium to trace responsive cells in tissues. First, employing the single-cell RNA-Seq data, we calculated the ability of different cell types to express Thra and Thrb, which direct us to the cell types sensitive to thyroid hormone regulation in tissues and organs. Next, using a cell clustering algorithm, we explored the subtypes with low Thra or Thrb expression within the different cell types and identified the potentially responsive cell subtypes. Finally, in the liver tissue treated with thyroid hormones, using the single-cell RNA-Seq data, we successfully traced the responsive cell types. We acknowledge that the computational predictions reported here need to be further validated using wet-lab experiments. However, we believe our results provide powerful information and will be beneficial for wet lab researchers.