Perspectives on single-nucleus RNA sequencing in different cell types and tissues

Single-cell RNA sequencing has become a powerful and essential tool for delineating cellular diversity in normal tissues and alterations in disease states. For certain cell types and conditions, there are difficulties in isolating intact cells for transcriptome profiling due to their fragility, large size, tight interconnections, and other factors. Single-nucleus RNA sequencing (snRNA-seq) is an alternative or complementary approach for cells that are difficult to isolate. In this review, we will provide an overview of the experimental and analysis steps of snRNA-seq to understand the methods and characteristics of general and tissue-specific snRNA-seq data. Knowing the advantages and limitations of snRNA-seq will increase its use and improve the biological interpretation of the data generated using this technique

P-Selectin and P-Selectin Glycoprotein Ligand 1 Are Major Determinants for Th1 Cell Recruitment to Nonlymphoid Effector Sites in the Intestinal Lamina Propria

The recruitment of activated T cell subsets to sites of effector immune responses is mediated by homing receptors induced upon activation in secondary lymphoid tissue. Using an adoptive transfer model, the intestinal recruitment of CD4+ T cells activated with intraperitoneal antigen in complete Freund's adjuvant was examined. The data demonstrate that activated CD4+ T cells recruited to intestinal Peyer's patches (PP) and lamina propria (LP) up-regulate functional P-selectin glycoprotein ligand 1 (PSGL-1). Blockade of IL-12 inhibited functional PSGL-1 expression and reduced PP and LP CD4+ T cell recruitment by >40%. P-Selectin blockade reduced LP recruitment of activated cells by 56% without affecting PP recruitment. Studies of mice examined 3 d after adoptive transfer of differentiated T cell subsets revealed that Th1 but not Th2 cells were recruited to small intestine PP and LP. Mucosal addressin cell adhesion molecule blockade reduced Th1 recruitment to PP by 90% and to LP by >72%, whereas P-selectin blockade reduced Th1 recruitment to PP by 18% and Th1 recruitment to LP by 84%. These data suggest that IL-12–induced functional PSGL-1 expression is a major determinant for the recruitment of Th1 effector cells to noninflamed as well as inflamed intestine

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data

Characterization of intratumoral heterogeneity is critical to cancer therapy, as the presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss of heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct the underlying subclonal architecture. By examining several tumor types, we show that HoneyBADGER is effective at identifying deletions, amplifications, and copy-neutral loss-of-heterozygosity events and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure and were likely driven by alternative, nonclonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer

The diagnostic application of targeted re-sequencing in Korean patients with retinitis pigmentosa

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Abstract Background Identification of the causative genes of retinitis pigmentosa (RP) is important for the clinical care of patients with RP. However, a comprehensive genetic study has not been performed in Korean RP patients. Moreover, the genetic heterogeneity found in sensorineural genetic disorders makes identification of pathogenic mutations challenging. Therefore, high throughput genetic testing using massively parallel sequencing is needed. Results Sixty-two Korean patients with nonsyndromic RP (46 patients from 18 families and 16 simplex cases) who consented to molecular genetic testing were recruited in this study and targeted exome sequencing was applied on 53 RP-related genes. Causal variants were characterised by selecting exonic and splicing variants, selecting variants with low allele frequency (below 1 %), and discarding the remaining variants with quality below 20. The variants were additionally confirmed by an inheritance pattern and cosegregation test of the families, and the rest of the variants were prioritised using in-silico prediction tools. Finally, causal variants were detected from 10 of 18 familial cases (55.5 %) and 7 of 16 simplex cases (43.7 %) in total. Novel variants were detected in 13 of 20 (65 %) candidate variants. Compound heterozygous variants were found in four of 7 simplex cases. Conclusion Panel-based targeted re-sequencing can be used as an effective molecular diagnostic tool for RP

Clinical Perspectives of Single-Cell RNA Sequencing

The ability of single-cell genomics to resolve cellular heterogeneity is highly appreciated in cancer and is being exploited for precision medicine. In the recent decade, we have witnessed the incorporation of cancer genomics into the clinical decision-making process for molecular-targeted therapies. Compared with conventional genomics, which primarily focuses on the specific and sensitive detection of the molecular targets, single-cell genomics addresses intratumoral heterogeneity and the microenvironmental components impacting the treatment response and resistance. As an exploratory tool, single-cell genomics provides an unprecedented opportunity to improve the diagnosis, monitoring, and treatment of cancer. The results obtained upon employing bulk cancer genomics indicate that single-cell genomics is at an early stage with respect to exploration of clinical relevance and requires further innovations to become a widely utilized technology in the clinic