Data and Materials Availability: data for the human-cow transcriptome comparison with and without co-culture with trophoblast cells is available under GSE136299 in the Gene Expression Omnibus (GEO) database of NCBI, https://www.ncbi.nlm.nih.gov/geo/. The comparative fibroblast gene expression data is available under PRJNA564062 under SUB6229748 and SUB6264591 on the Sequence Read Archive (SRA) of NCBI, https://www.ncbi.nlm.nih.gov/sra.

Among animal species, cell types vary greatly in terms of number and kind. The number of cell types found within an organism differs considerably between species, and cell type diversity is a significant contributor to differences in organismal structure and function. These observations suggest that cell type origination is a significant source of evolutionary novelty. The molecular mechanisms that result in the evolution of novel cell types, however, are poorly understood. Here, we show that a novel cell type of eutherians mammals, the decidual stromal cell (DSC), evolved by rewiring an ancestral cellular stress response. We isolated the precursor cell type of DSCs, endometrial stromal fibroblasts (ESFs), from the opossum Monodelphis domestica. We show that, in opossum ESFs, the majority of decidual core regulatory genes respond to decidualizing signals but do not regulate decidual effector genes. Rather, in opossum ESFs, decidual transcription factors function in apoptotic and oxidative stress response. We propose that rewiring of cellular stress responses was an important mechanism for the evolution of the eutherian decidual cell type.

The evolution and diversification of cell types is a key means by which animal complexity evolves. Recently, hierarchical clustering and phylogenetic methods have been applied to RNA-seq data to infer cell type evolutionary history and homology. A major challenge for interpreting this data is that cell type transcriptomes may not evolve independently due to correlated changes in gene expression. This nonindependence can arise for several reasons, such as common regulatory sequences for genes expressed in multiple tissues, that is, pleiotropic effects of mutations. We develop a model to estimate the level of correlated transcriptome evolution (LCE) and apply it to different data sets. The results reveal pervasive correlated transcriptome evolution among different cell and tissue types. In general, tissues related by morphology or developmental lineage exhibit higher LCE than more distantly related tissues. Analyzing new data collected from bird skin appendages suggests that LCE decreases with the phylogenetic age of tissues compared, with recently evolved tissues exhibiting the highest LCE. Furthermore, we show correlated evolution can alter patterns of hierarchical clustering, causing different tissue types from the same species to cluster together. To identify genes that most strongly contribute to the correlated evolution signal, we performed a gene-wise estimation of LCE on a data set with ten species. Removing genes with high LCE allows for accurate reconstruction of evolutionary relationships among tissue types. Our study provides a statistical method to measure and account for correlated gene expression evolution when interpreting comparative transcriptome data.

In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

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