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Farber, E. A.

Publications and source records attributed to Farber, E. A..

3 recordsLinked to original sources

Evaluation of a scalable approach to generate cell-type specific transcriptomic profiles of mesenchymal lineage cells

Genome-wide association studies (GWASs) have revolutionized our understanding of the genetics of complex diseases, such as osteoporosis; however, the challenge has been converting associations to causal genes. Studies have demonstrated the utility of transcriptomics data in linking disease-associated variants to genes; though for osteoporosis, few population transcriptomics datasets have been generated on bone or bone cells, and an even smaller number have profiled individual cell-types. To begin to evaluate approaches to address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions, a popular model of osteoblast differentiation and activity, 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 for the generation of cell-type specific transcriptomic profiles of mesenchymal lineage cells derived from large populations of mice to inform genetic 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 nearly identical from a transcriptomic perspective to cells isolated directly from bone. We also demonstrated the ability to multiplex single cells and subsequently assign cells to their "mouse-of-origin" using demultiplexing approaches based on genotypes inferred from coding SNPs. 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 showed that identified 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 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 mouse, and potentially human, populations.

bioinformatics↗

Cell-specific chromatin landscape of human coronary artery resolves regulatory mechanisms of disease risk

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

genomics↗

Systems genetics analyses in Diversity Outbred mice inform human bone mineral density GWAS and identify Qsox1 as a novel determinant of bone strength

Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we used Diversity Outbred (DO) mice to directly address these limitations by performing the first systems genetics analysis of 55 complex skeletal phenotypes. We applied a network approach to cortical bone RNA-seq data to discover 72 genes likely to be causal for human BMD GWAS associations, including the novel genes SERTAD4 and GLT8D2. We also performed GWAS in the DO for a wide-range of bone traits and identified Qsox1 as a novel gene influencing cortical bone accrual and bone strength. Our results provide a new perspective on the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

genetics↗