Evolution of gene regulatory networks in primates inferred by perturbations

点击翻译按钮获取中文摘要

Understanding how gene regulation evolves is crucial to understand biological diversity and human biology. Comparisons across primates are of particular relevance not only because they inform human-specific evolution but also because they bridge the gap between human and mouse, our most important model organism. While cross-species comparisons of expression levels have been amply conducted, broadening the scope to study gene regulation in genetically accessible and comparable primate cell systems is necessary to fully leverage the unique information encoded in the molecular evolution of primates. With the combination of CRISPR-based perturbations and single-cell transcriptomic read-outs, a game-changing technology to study gene regulation has recently emerged. One prominent strategy for such single-cell CRISPR screens is to target a fusion protein of catalytically inactive Cas9 (dCas9) and a repressor domain such as KRAB to a promoter using a single guide RNA (sgRNA). This significantly reduces the expression of the targeted gene and single-cell RNA-seq informs on the corresponding effect on the transcriptome. Such screens are likely to contribute substantially to our understanding of gene regulatory networks (GRNs). However, it is currently unknown how such perturbation-inferred GRNs evolve.Here, we propose to start closing this knowledge gap by comparing perturbation-inferred GRNs in neural progenitor cells (NPCs) of primates. We aim to achieve this by using our established induced pluripotent stem cells (iPSCs) from human, gorilla, orangutan and cynomolgus macaque to generate iPSCs from two individuals per species containing an inducible dCas9-KRAB at a defined genomic location. These lines will be differentiated to neural progenitor cells (NPCs) and transduced with sgRNAs targeting 100 transcription factors expressed in NPCs. After nine days of dCas9-KRAB induction, pooled cells will be harvested for scRNA-seq library generation. We aim to generate CRISPRi-scRNA-seq data for 500 cells per species and targeted TF, which is expected to provide sufficient statistical power to analyse the conservation of these TF networks. Correlating this conservation with the properties of the perturbed TFs and the properties of their targets will enable us to gather unique insights into the evolution of primate GRNs. Finally, using a novel combined epigenetic and expression read-out, we will follow up on a subset of 18 evolutionarily interesting TFs. This will reveal detailed information about the interplay of trans-effects, i.e. the downregulation of a TF, and the target gene's cis-regulatory landscape providing truly comparable functional data to corroborate inferences about regulatory evolution.