Single-cell RNA-sequencing (scRNA-seq) offers a powerful approach for studying genome-wide mRNA levels within single cells at high-throughput. Using this tool, researchers can characterize how phenotypic differences between cells may be explained by differences in their underlying mRNA composition. In Chapter 1, we introduce the reader to scRNA-seq, focusing on how the technology works, key considerations for its use, and basic data preprocessing and analysis steps for the data generated by these experiments. In Chapter 2, we combine scRNA-seq with lineage tracing to study smooth muscle cell (SMC) fates in atherosclerosis. We identify a population SMC-derived cells with stem cell, endothelial, and monocyte-like characteristics marked by Ly6a, Vcam1, and Ly6c1, which we refer to as SEM cells. Through ex vivo cell culture experiments, we demonstrate SEM cells are multipotent, and harbor the capacity to differentiate into SMCs, macrophage-like cells, and fibroblast-like cells. We further demonstrate that retinoic acid signaling regulates the SMC to SEM transition. In Chapter 3, we develop a novel statistical tool, Tempo, to infer circadian timing of cells from scRNA-seq experiments. Tempo incorporates prior knowledge of core circadian clock gene expression peak times and prior knowledge of cell circadian phases. Using this prior knowledge and the observed data, Tempo estimates an approximate posterior distribution of cell phases. Through both evaluations on simulated and real scRNA-seq data, we demonstrate that Tempo offers a substantial improvement in circadian phase point estimates over existing tools. Moreover, demonstrate that Tempo’s uncertainty quantifications are well-calibrated. In Chapter 4, we use scRNA-seq to study the sex-dependent circadian transcriptome of aortic cell types, and their response to either genetic deletion of the clock gene Bmal1 or acute misalignment with the light-dark cycle. We identified several novel sex and time dependent effects, such as decreased heat shock protein expression in female SMCs at ZT12 and sex-dependent alterations of gene sets involved in SMC phenotypic switching. In mice acute misaligned with the light-dark cycle, we identified several changes in SMCs suggesting an accumulation of unfolded proteins and cell stress. Additionally, acute misalignment may induce changes in the relative timing among aortic cell types and macrophages, which may be deleterious.