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Genetic Kidney Diseases (GKDs) Modeling Using Genome Editing Technologies

Authors :
Fernando Gómez-García
Raquel Martínez-Pulleiro
Noa Carrera
Catarina Allegue
Miguel A. Garcia-Gonzalez
Source :
Cells, Vol 11, Iss 9, p 1571 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Genetic kidney diseases (GKDs) are a group of rare diseases, affecting approximately about 60 to 80 per 100,000 individuals, for which there is currently no treatment that can cure them (in many cases). GKDs usually leads to early-onset chronic kidney disease, which results in patients having to undergo dialysis or kidney transplant. Here, we briefly describe genetic causes and phenotypic effects of six GKDs representative of different ranges of prevalence and renal involvement (ciliopathy, glomerulopathy, and tubulopathy). One of the shared characteristics of GKDs is that most of them are monogenic. This characteristic makes it possible to use site-specific nuclease systems to edit the genes that cause GKDs and generate in vitro and in vivo models that reflect the genetic abnormalities of GKDs. We describe and compare these site-specific nuclease systems (zinc finger nucleases (ZFNs), transcription activator-like effect nucleases (TALENs) and regularly clustered short palindromic repeat-associated protein (CRISPR-Cas9)) and review how these systems have allowed the generation of cellular and animal GKDs models and how they have contributed to shed light on many still unknown fields in GKDs. We also indicate the main obstacles limiting the application of these systems in a more efficient way. The information provided here will be useful to gain an accurate understanding of the technological advances in the field of genome editing for GKDs, as well as to serve as a guide for the selection of both the genome editing tool and the gene delivery method most suitable for the successful development of GKDs models.

Details

Language :
English
ISSN :
20734409
Volume :
11
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Cells
Publication Type :
Academic Journal
Accession number :
edsdoj.6ec7f02fd304e35ba1b39ad82335590
Document Type :
article
Full Text :
https://doi.org/10.3390/cells11091571