About this Research Topic
Diseases have caused significant economic losses for the aquaculture sector, approx. 35-50% of turnover especially in the (sub)-tropics. The disease challenges have become more critical due to the combined effects of aquaculture intensification and environmental changes. Climate change aggravates the impact of diseases on animal health by affecting pathogens, hosts, disease carrying vectors, transmission rate or changes in the distribution of competitors, predators or parasites in ecosystems. An example is high ambient and water temperature increases the rate of development of pathogens or parasites, e.g., prevalence of streptococcosis is strongly associated with high water temperature (≥30°C) during hot and dry seasons, which can result in disease outbreaks with severe financial, environmental and ethical implications.
In commercial settings mitigating disease risks by culturing healthy and resilient animals is crucial for profitability, sustainability and animal welfare of the aquaculture industry. Selective breeding is one of the measures that can be adopted to improve disease resistance, tolerance or resilience. The advantages of disease management through the application of genetics include low input and maintenance costs, permanence and consistency of effect as well as its environmental-sustainability. The degree of success of selective breeding depends on the availability of genetic variation for resistance to diseases. The potential for genetic improvement is promising given the accumulating evidence of genetic variation for resistance against diseases in several aquatic animal species, including carps, salmonids and shrimps. To date, genetic improvement programs for infectious diseases have relied mainly on challenge tests through immersion, injection or feeding. However, the challenge test requires expensive bio-secure facilities and extensive labour, as well a high risk of disease spread to the environment. This approach also uses only information from siblings of breeding candidates and thus, reducing accuracy of selection. In this regard, there is a growing interest in exploring alternative new phenotypes; however, quantification of viral load on a large scale routine basis readily for selection is also challenging due to high laboratory costs and difficult measurements that in some cases still require sacrifice of selection animals. Collectively, these factors may contribute to slowing down genetic progress made in future generations of selected populations.
With recent developments in high throughput next generation genome sequencing platforms coupled with advanced statistical, genetic and computational approaches, these emerging technologies have opened new possibilities for improving disease resistance traits based on DNA or genome sequence information in well-established breeding programs with the availability of accurate and consistent phenotypes. Furthermore, microbial genomics also assists infection control and outbreak response. The integration of multiple ‘omics’ platforms (e.g., transcriptomics, proteomics, metabolomics, microbiomics) provides new sources of data to understand the factors underlying biology and genetic architecture of disease resistance in pedigreed and well phenotyped populations and hence, accelerating genetic gain for disease traits in aquatic animal species. Finally, the potential opportunities gene editing technologies offer to enhance aquaculture production are emerging, but scientific applications of gene editing in aquaculture remain at an early stage.
This Research Topic and discusses innovative approaches and recent advances in genetics and genomics of disease resistance to provide solutions to the disease challenges. It focuses on four main themes:
(i) genetic enhancement of disease resistance in aquatic animal species;
(ii) optimisation of breeding programs for improved disease and environmental tolerance;
(iii) advanced genetic and statistical methods to accelerate genetic gains in disease traits, and
(iv) new technologies and ‘omics’ approaches to dissect genetic architecture of disease traits.
We welcome submissions of Original Research, Data Reports, Conceptual Analysis, Hypothesis and Theory, Perspective, and high quality Reviews that fall within (but are not restricted) to the following:
A. Genetic enhancement of disease resistance, tolerance and resilience in aquatic animals and plants:
1. Model species (e.g., zebrafish, stickleback fish and any other aquatic model organisms);
2. Marine and freshwater fishes, crustaceans and molluscs;
3. Aquatic plants in aquaculture
B. Optimization of breeding programs for improved disease resistance in aquatic animals :
1. Genetic basis of new traits that can be used as novel selection criteria to enhance resistance, tolerance, resilience and ‘robustness’ of aquatic species;
2. Multiple trait selection approaches to simultaneously improve both disease resistance and productivity of aquatic species, including selection for adaptation across culture environments;
3. Genetics of host and pathogen interactions: microbiome, mechanisms and modelling
C. Advanced statistical and genetic methods to accelerate genetic gains in disease resistance:
1. Novel genetic and epidemiological models to evaluate and select for resistance to infectious diseases;
2. New computer algorithms or bioinformatic tools to facilitate variant detection, gene mapping and genome-wide analysis for traits related to disease resistance;
3. Prediction of individual response to vaccination against infectious diseases in aquatic animals
D. New technologies and ‘omic’ approaches:
1. Microbial genomics for infection control and outbreak response;
2. Genomic selection for improved disease resistance in aquaculture breeding programs
3. Multi-omic data to identify biomarkers.
4. DNA test arrays for disease diagnostics, treatment and prevention
5. Gene and genome editing for research on disease resistance
Keywords: Aquaculture, Genetic Improvement, Disease resistance, Next Generation Sequencing, Statistical Genetics/Genomics, Genes, Gene mapping and Marker-Assisted Selection
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.