Encoding Method of Single-cell Spatial Transcriptomics Sequencing

Abstract

Despite significant advances in parallel single-cell RNA sequencing revealing astonishing cellular heterogeneity in many tissue types, the spatial information in the tissue context remains missing. Spatial transcriptome sequencing technology is designed to distinguish the gene expression of individual cells in their original location. The technology is important for the identification of tissue function, tracking developmental processes, and pathological and molecular detection. Encoding the position information is the key to spatial transcriptomics because different methods have different encoding efficiencies and application scenarios. In this review, we focus on the latest technologies of single-cell spatial transcriptomics, including technologies based on microwell plates, barcoded bead arrays, microdissection, in situ hybridization, and barcode in situ targeting, as well as mixed separation-based technologies. Moreover, we compare these encoding methods for use as a reference when choosing the appropriate technology.

Seq-Scope: Submicrometer-resolution spatial transcriptomics for single cell and subcellular studies

“…Prior to Seq-Scope, HDST, which has a single barcode area of 9.3 μm 2 (Vickovic et al, 2019), had been the technology that provided the highest resolution spatial transcriptomics (Asp et al, 2020; Liao et al, 2020; Zhou et al, 2020). However, HDST is seriously limited by its low transcriptome capture rate; a single barcoded area can catch only around 7 unique transcripts, even though the library was fully examined at around 90% saturation (Vickovic et al, 2019).…”

Deubiquitinating Enzymes Orchestrate the Cancer Stem Cell-Immunosuppressive Niche Dialogue: New Perspectives and Therapeutic Potential

“…In recent years, with the development of technology, single-cell sequencing ( Wen and Tang, 2016 ; Xu et al, 2020 ), spatial transcriptomics sequencing ( Zhou Y. et al, 2020 ) and ubiquitin mass spectrometry technologies ( Ohtake, 2020 ) have matured. Accurate verification can be performed at the single-cell level, RNA level, and protein level.…”

Single-cell Transcriptome Analysis Uncovers Heterogeneity and Key Regulators in Ibrutinib-resistant Chronic Lymphocytic Leukemia

“…Though next-generation sequencing [17, 18] has helped to clarify the key gene mutations, an understanding of the precise molecular mechanisms of ibrutinib resistance from a single cell perspective is needed, of which little information exists for CLL. Single-cell RNA sequencing (scRNA-seq) can assess gene expression in individual cells and systematically characterize heterogeneity at a higher resolution [19,20]. Moreover, this technology can be used to identify different cell subtypes based on relevant transcriptional modules [21,22], and thus could be used to discover reliable biomarkers for clinical e cacy and drug-resistance.…”

“…Mutations in BTK and PLCG2 are recognized as central factors for ibrutinib resistance, yet a low frequency of these mutations has been observed in our center [14][15][16].Consequently, a comprehensive understanding of CLL clonal evolution driven by the selective pressure of drug therapy is vital for precise, individualized treatment.Though next-generation sequencing [17, 18] has helped to clarify the key gene mutations, an understanding of the precise molecular mechanisms of ibrutinib resistance from a single cell perspective is needed, of which little information exists for CLL. Single-cell RNA sequencing (scRNA-seq) can assess gene expression in individual cells and systematically characterize heterogeneity at a higher resolution [19,20]. Moreover, this technology can be used to identify different cell subtypes based on relevant transcriptional modules [21,22], and thus could be used to discover reliable biomarkers for clinical e cacy and drug-resistance.Here, we characterized and analyzed the difference between CLL patients with ibrutinib-sensitive (IBS) and -resistant (IBR) by bulk and scRNA sequencing.…”