Author: QIN AN

Publisher:

Published: 2020

Total Pages: 221

ISBN-13:

Single-cell genomics is the study of molecular modalities, or "-omes" from individual cells. Many protocols have been developed to profile genome, epigenome, transcriptome, and proteome from single cells. Among all these protocols, single-cell transcriptome profiling using single-cell RNA sequencing is the most popular and mature one. This technique has been demonstrated to be very powerful in dissecting cell types within a heterogeneous tissue, as well as revealing cell type specific responses to stimuli. It has also been used to reconstruct cell trajectory during complex biological progress, such as cell differentiation. More importantly, it can be used to reveal gene co-expression networks among cell types, and ultimately the molecular mechanism of gene regulation. In the first two projects of my thesis, I described how we use single-cell RNA sequencing to understand the molecular mechanism controlling trophoblasts proliferation and differentiation during human peri-implantation embryo development, as well as the mechanism of retinal progenitor cells commitment during early human retinogenesis. In the first project, we profiled human embryonic stem cell derived retinal organoids using single-cell RNA sequencing, to understand the molecular mechanism of early retinogenesis. The development of the mammalian retina is a complicated process involving generating distinct types of neurons from retinal progenitor cells (RPCs) in a spatiotemporal-specific manner. The progression of RPCs during retinogenesis includes RPC proliferation, cell fate commitment, and specific neuronal differentiation. In this study, by performing single-cell RNA-sequencing (scRNA-seq) on cells isolated from human embryonic stem cell (hESC)-derived 3D retinal organoids, we successfully deconstructed the temporal progression of RPCs during early human retinogenesis. We identified two distinct subtypes of RPCs with unique molecular profiles, namely multipotent RPCs and neurogenic RPCs. We found genes related to the Notch and Wnt signaling pathway, as well as chromatin remodeling, were dynamically regulated during RPC commitment. Interestingly, our analysis identified CCND1, a G1-phase cell cycle regulator, was co-expressed with ASCL1 in a cell-cycle independent manner. Temporally-controlled overexpression of CCND1 in retinal organoids demonstrated a role for CCND1 in promoting early retinal neurogenesis. Together, our results revealed critical pathways and novel genes in the early retinogenesis of humans. In the second project, we profiled transcriptome from individual trophoblast cells collected from human peri-implantation embryos, to reveal how these cells proliferate and differentiate to establish placenta. Multipotent trophoblasts undergo dynamic morphological movement and cellular differentiation after conceptus implantation to generate placenta. However, the mechanism controlling trophoblast development and differentiation during peri-implantation development in human remains elusive. In this study, we modeled human conceptus peri-implantation development from blastocyst to early post-implantation stages by using an in vitro coculture system and profiled the transcriptome of 476 individual trophoblast cells from these conceptuses. We revealed the genetic networks regulating peri-implantation trophoblast development. While determining when trophoblast differentiation happens, our bioinformatic analysis identified T-box transcription factor 3 (TBX3) as a key regulator for the differentiation of cytotrophoblast into syncytiotrophoblast. The function of TBX3 in trophoblast differentiation is then validated by a loss-of-function experiment. In conclusion, our results provided a valuable resource to study the regulation of trophoblasts development and differentiation during human peri-implantation development. In parallel with the development of single-cell RNA sequencing, many efforts have been put in profiling other molecular modalities from single cells, such as genome, epigenome, and proteome. By elaborately combining these protocols, we can profile more than one types of "omes" from individual cells simultaneously. These techniques, commonly termed as "single-cell multimodal profiling", can generate data that has certain advantages compared to single-cell "mono-omics" approaches. Specifically, since each molecular modality provides orthogonal information about cell identities and status, the joint clustering of single-cell multi-omics data can better resolve cell types within a heterogeneous cell population. Also, because more than one molecular modalities were profiled simultaneously from every single cell, we could have better inferences about the relationship between these omics. In the third project, we demonstrated how to use scMT-seq (simultaneous profiling of transcriptome and DNA methylome from a single cell), to investigate the gene regulatory role of DNA methylation in sensory neurons during peripheral nerve injury response and regeneration. DNA methylation is implicated in neuronal injury response and regeneration, but its role in regulating stable transcription changes in different types of dorsal root ganglion (DRG) neurons is unclear. In this study, we simultaneously profiled both the DNA methylome and mRNA transcriptome from single DRG neurons at different ages under either control or peripheral nerve injury condition. We found that age-related expression changes in Notch signaling genes and methylation changes at Notch receptor binding sites are associated with the age-dependent decline in peripheral nerve regeneration potential. Moreover, selective hypomethylation of AP-1 complex binding sites on regeneration-associated gene (RAG) promoters coincides with RAG transcriptional upregulation after injury. Consistent with the findings that different subtypes of DRG neurons exhibit distinct methylome changes upon injury responses, in a hybrid CAST/Ei; C57BL/6 genetic background, we further observed allele-specific gene regulation and methylation changes for many RAGs after injury. We suggest that the genetic background determines distinct allele-specific DNA methylomes, which contribute to age-dependent regulation and neuronal subtype-specific injury-responses in different mouse strains.