Single‐cell technologies in reproductive immunology
Year: 2019
Type: review
Abstract: The maternal-fetal interface represents a unique immune privileged site that maintains the ability to defend against pathogens while orchestrating the necessary tissue remodeling required for placentation. The recent discovery of novel cellular families (innate lymphoid cells, tissue-resident NK cells) suggests that our understanding of the decidual immunome is incomplete. To understand this complex milieu, new technological developments allow reproductive immunologists to collect increasingly complex data at a cellular resolution. Polychromatic flow cytometry allows for greater resolution in the identification of novel cell types by surface and intracellular protein. Single-cell RNA-seq coupled with microfluidics allows for efficient cellular transcriptomics. The extreme dimensionality and size of data sets generated, however, requires the application of novel computational approaches for unbiased analysis. There are now multiple dimensionality reduction (tSNE, SPADE) and visualization tools (SPICE) that allow researchers to efficiently analyze flow cytometry data. Development of computational tools has also been extended to RNA-seq data (including scRNA-seq), which requires specific analytical tools. Here, we provide an overview and a brief primer for the reproductive immunology community on data acquisition and computational tools for the analysis of complex flow cytometry and RNA-seq data.
DOI: 10.1111/aji.13157
Institution: University of Wisconsin–Madison
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: Endocrinology and Reproductive Physiology Training Grant, Characterization of Emca4, the Rat Ortholog of the 8q24 Breast Cancer Risk Locus, Effective Anti-Tumor Vaccination - Targeting Checkpoint Regulation at the Time of T-cell Activation, UW Comprehensive Cancer Center Support, Interactions Between the Microbiome, Immunity and Respiratory Health in Traditional Agrarian and Suburban children, Reproductive Scientist Development Program
OpenAlex ID: W2952108394