Dissecting the human kidney allograft transcriptome: single-cell RNA sequencing

Curr Opin Organ Transplant. 2021 Feb 1;26(1):43-51. doi: 10.1097/MOT.0000000000000840.

Abstract

Purpose of review: Single-cell RNA sequencing (scRNA-seq) has provided opportunities to interrogate kidney allografts at a hitherto unavailable molecular level of resolution. Understanding of this technology is essential to better appreciate the relevant biomedical literature.

Recent findings: Sequencing is a technique to determine the order of nucleotides in a segment of RNA or DNA. RNA-seq of kidney allograft tissues has revealed novel mechanistic insights but does not provide information on individual cell types and cell states. scRNA-seq enables to study the transcriptome of individual cells and assess the transcriptional differences and similarities within a population of cells. Initial studies on rejecting kidney allograft tissues in humans have identified the transcriptional profile of the active players of the innate and adaptive immune system. Application of scRNA-seq in a preclinical model of kidney transplantation has revealed that allograft-infiltrating myeloid cells follow a trajectory of differentiation from monocytes to proinflammatory macrophages and exhibit distinct interactions with kidney allograft parenchymal cells; myeloid cell expression of Axl played a major role in promoting intragraft myeloid cell and T-cell differentiation.

Summary: The current review discusses the technical aspects of scRNA-seq and summarizes the application of this technology to dissect the human kidney allograft transcriptome.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Allografts
  • Biomarkers / metabolism
  • Graft Rejection / metabolism
  • Humans
  • Kidney / immunology
  • Kidney Transplantation
  • Macrophages / metabolism
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / methods
  • Transcriptome / immunology*
  • Transplantation, Homologous

Substances

  • Biomarkers