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Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish

Infectious diseases represent a major threat for the sustainable development of fish farming. Efficient vaccines are not available against all diseases, and growing antibiotics resistance limits the use of antimicrobial drugs in aquaculture. It is therefore important to understand the basis of fish...

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Autores principales: Fraslin, Clémence, Quillet, Edwige, Rochat, Tatiana, Dechamp, Nicolas, Bernardet, Jean-Francois, Collet, Bertrand, Lallias, Delphine, Boudinot, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365936/
https://www.ncbi.nlm.nih.gov/pubmed/32754193
http://dx.doi.org/10.3389/fgene.2020.00677
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author Fraslin, Clémence
Quillet, Edwige
Rochat, Tatiana
Dechamp, Nicolas
Bernardet, Jean-Francois
Collet, Bertrand
Lallias, Delphine
Boudinot, Pierre
author_facet Fraslin, Clémence
Quillet, Edwige
Rochat, Tatiana
Dechamp, Nicolas
Bernardet, Jean-Francois
Collet, Bertrand
Lallias, Delphine
Boudinot, Pierre
author_sort Fraslin, Clémence
collection PubMed
description Infectious diseases represent a major threat for the sustainable development of fish farming. Efficient vaccines are not available against all diseases, and growing antibiotics resistance limits the use of antimicrobial drugs in aquaculture. It is therefore important to understand the basis of fish natural resistance to infections to help genetic selection and to develop new approaches against infectious diseases. However, the identification of the main mechanisms determining the resistance or susceptibility of a host to a pathogenic microbe is challenging, integrating the complexity of the variation of host genetics, the variability of pathogens, and their capacity of fast evolution and adaptation. Multiple approaches have been used for this purpose: (i) genetic approaches, QTL (quantitative trait loci) mapping or GWAS (genome-wide association study) analysis, to dissect the genetic architecture of disease resistance, and (ii) transcriptomics and functional assays to link the genetic constitution of a fish to the molecular mechanisms involved in its interactions with pathogens. To date, many studies in a wide range of fish species have investigated the genetic determinism of resistance to many diseases using QTL mapping or GWAS analyses. A few of these studies pointed mainly toward adaptive mechanisms of resistance/susceptibility to infections; others pointed toward innate or intrinsic mechanisms. However, in the majority of studies, underlying mechanisms remain unknown. By comparing gene expression profiles between resistant and susceptible genetic backgrounds, transcriptomics studies have contributed to build a framework of gene pathways determining fish responsiveness to a number of pathogens. Adding functional assays to expression and genetic approaches has led to a better understanding of resistance mechanisms in some cases. The development of knock-out approaches will complement these analyses and help to validate putative candidate genes critical for resistance to infections. In this review, we highlight fish isogenic lines as a unique biological material to unravel the complexity of host response to different pathogens. In the future, combining multiple approaches will lead to a better understanding of the dynamics of interaction between the pathogen and the host immune response, and contribute to the identification of potential targets of selection for improved resistance.
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spelling pubmed-73659362020-08-03 Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish Fraslin, Clémence Quillet, Edwige Rochat, Tatiana Dechamp, Nicolas Bernardet, Jean-Francois Collet, Bertrand Lallias, Delphine Boudinot, Pierre Front Genet Genetics Infectious diseases represent a major threat for the sustainable development of fish farming. Efficient vaccines are not available against all diseases, and growing antibiotics resistance limits the use of antimicrobial drugs in aquaculture. It is therefore important to understand the basis of fish natural resistance to infections to help genetic selection and to develop new approaches against infectious diseases. However, the identification of the main mechanisms determining the resistance or susceptibility of a host to a pathogenic microbe is challenging, integrating the complexity of the variation of host genetics, the variability of pathogens, and their capacity of fast evolution and adaptation. Multiple approaches have been used for this purpose: (i) genetic approaches, QTL (quantitative trait loci) mapping or GWAS (genome-wide association study) analysis, to dissect the genetic architecture of disease resistance, and (ii) transcriptomics and functional assays to link the genetic constitution of a fish to the molecular mechanisms involved in its interactions with pathogens. To date, many studies in a wide range of fish species have investigated the genetic determinism of resistance to many diseases using QTL mapping or GWAS analyses. A few of these studies pointed mainly toward adaptive mechanisms of resistance/susceptibility to infections; others pointed toward innate or intrinsic mechanisms. However, in the majority of studies, underlying mechanisms remain unknown. By comparing gene expression profiles between resistant and susceptible genetic backgrounds, transcriptomics studies have contributed to build a framework of gene pathways determining fish responsiveness to a number of pathogens. Adding functional assays to expression and genetic approaches has led to a better understanding of resistance mechanisms in some cases. The development of knock-out approaches will complement these analyses and help to validate putative candidate genes critical for resistance to infections. In this review, we highlight fish isogenic lines as a unique biological material to unravel the complexity of host response to different pathogens. In the future, combining multiple approaches will lead to a better understanding of the dynamics of interaction between the pathogen and the host immune response, and contribute to the identification of potential targets of selection for improved resistance. Frontiers Media S.A. 2020-07-10 /pmc/articles/PMC7365936/ /pubmed/32754193 http://dx.doi.org/10.3389/fgene.2020.00677 Text en Copyright © 2020 Fraslin, Quillet, Rochat, Dechamp, Bernardet, Collet, Lallias and Boudinot. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Fraslin, Clémence
Quillet, Edwige
Rochat, Tatiana
Dechamp, Nicolas
Bernardet, Jean-Francois
Collet, Bertrand
Lallias, Delphine
Boudinot, Pierre
Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title_full Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title_fullStr Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title_full_unstemmed Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title_short Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish
title_sort combining multiple approaches and models to dissect the genetic architecture of resistance to infections in fish
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365936/
https://www.ncbi.nlm.nih.gov/pubmed/32754193
http://dx.doi.org/10.3389/fgene.2020.00677
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