Abstract High-throughput transcriptomic technologies have advanced rapidly, enabling genome-wide gene expression profiling. Microarrays, introduced in 1995, laid the foundation for large-scale analysis but were later surpassed in 2008 by RNA sequencing (RNA-seq), which offers single-nucleotide resolution, detects low-abundance transcripts, and does not require prior sequence knowledge. Bulk RNA-seq provides robust insights into global transcriptomic changes but lacks single-cell resolution. Single-cell RNA sequencing (scRNA-seq), introduced in 2009, addressed this limitation by revealing cellular heterogeneity and dynamic gene expression. However, its application in bone research is constrained due to difficulties in releasing bone cells called osteocytes from the mineralized matrix, often resulting in low yield and dissociation-induced artifacts. In order to address these challenges, single-nucleus RNA sequencing (snRNA-seq), first introduced in 2016 to enable transcriptomic profiling from isolated nuclei, was used in this study. We developed a protocol for snRNA-seq on bone tissue, achieving high-yield recovery of osteocyte nuclei from snap-frozen, marrow-flushed long bones. This approach minimized dissociation bias and enhanced osteocyte representation. We applied this robust method to long bones from young adult male and female mice, generating a high-resolution map of osteocyte gene expression under physiological conditions. Compared to scRNA-seq datasets, where osteocytes represent only 0.18–6.64% of cells, our snRNA-seq approach increased osteocyte capture and transcriptomic fidelity to 18.5%. We identified an osteocyte transcriptomic signature highlighting the top 30 genes, including Sost, which is typically undetected or lowly-expressed in scRNA-seq. Notably, 23 of these genes have not been well-characterized in osteocytes, including Tg, Kcnq5, Rapgef4os1, Cacna1a, Egr3, Dok5, and Lgr6, which may represent novel regulators of osteocyte biology. This study represents the first application of snRNA-seq specifically for osteocyte analysis in bone tissue, providing a valuable resource for investigating osteocyte biology and skeletal disorders.
Kitase et al. (Thu,) studied this question.