Single-Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population-Level scRNA-Seq Studies.

Genome-wide association studies (GWASs) have advanced our understanding of the genetics of osteoporosis; however, the challenge has been converting associations to causal genes. Studies have utilized transcriptomics data to link disease-associated variants to genes, but few population transcriptomics data sets have been generated on bone at the single-cell level. To address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions from five diversity outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells from large populations of mice to inform genetic studies. By enriching for mesenchymal lineage cells in vitro, coupled with pooling of multiple samples and downstream genotype deconvolution, we demonstrate the scalability of this model for population-level studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were similar from a transcriptomic perspective to cells isolated in vivo. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell types. SCENIC was used to reconstruct gene regulatory networks (GRNs), and we observed that cell types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of bone mineral density (BMD) heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells in large populations. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Differential Transcriptome Responses in Human THP-1 Macrophages Following Exposure to T98G and LN-18 Human Glioblastoma Secretions: A Simplified Bioinformatics Approach to Understanding Patient-Glioma-Specific Effects on Tumor-Associated Macrophages.

A common theme in glioma disease progression is robust infiltration of immune cells within the tumor microenvironment, resulting in a state of chronic inflammation. This disease state is characterized by an abundance of CD68+ microglia and CD163+ bone marrow-derived macrophages with the greater the percentage of CD163+ cells, the poorer the prognosis. These macrophages are "cold," in that their phenotype is of an alternatively activated state (M0-M2-like) supporting tumor growth rather than being engaged with classically activated, pro-inflammatory, and anti-tumor activities, referred to as "hot", or M1-like. Herein, we have developed an in vitro approach that uses two human glioma cell lines, T98G and LN-18, which exhibit a variety of differing mutations and characteristics, to demonstrate their disparate effects on differentiated THP-1 macrophages. We first developed an approach to differentiating THP-1 monocytes to macrophages with mixed transcriptomic phenotypes we regard as M0-like macrophages. We then found that supernatants from the two different glioma cell lines induced different gene expression profiles in THP-1 macrophages, suggesting that from patient to patient, gliomas may be considered as different diseases. This study suggests that in addition to standard glioma treatment modalities, transcriptome profiling of the effects of cultured glioma cells on a standard THP-1 macrophage in vitro model may lead to future druggable targets that aim to reprogram tumor-associated macrophages towards an anti-tumor phenotype.

Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease.

Aberrant splicing underlies many human diseases, including cancer, cardiovascular diseases and neurological disorders. Genome-wide mapping of splicing quantitative trait loci (sQTLs) has shown that genetic regulation of alternative splicing is widespread. However, identification of the corresponding isoform or protein products associated with disease-associated sQTLs is challenging with short-read RNA-seq, which cannot precisely characterize full-length transcript isoforms. Furthermore, contemporary sQTL interpretation often relies on reference transcript annotations, which are incomplete. Solutions to these issues may be found through integration of newly emerging long-read sequencing technologies. Long-read sequencing offers the capability to sequence full-length mRNA transcripts and, in some cases, to link sQTLs to transcript isoforms containing disease-relevant protein alterations. Here, we provide an overview of sQTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions and comment on future directions in the field. Based on recent progress, long-read RNA sequencing promises to be part of the human disease genetics toolkit to discover and treat protein isoforms causing rare and complex diseases.