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Enhancing host resistance to infectious disease has received increasing attention in recent years as a major goal of farm animal breeding programs. Combining field data with genomic tools can provide opportunities to understand the genetic architecture of disease resistance, leading to new opportunities for disease control. In the current study, a genome-wide association study was performed to assess resistance to the Tilapia lake virus (TiLV), one of the biggest threats affecting Nile tilapia (Oreochromis niloticus); a key aquaculture species globally. A pond outbreak of TiLV in a pedigreed population of the GIFT strain was observed, with 950 fish classified as either survivor or mortality, and genotyped using a 65 K SNP array. A significant QTL of large effect was identified on chromosome Oni22. The average mortality rate of tilapia homozygous for the resistance allele at the most significant SNP (P value = 4.51E−10) was 11%, compared to 43% for tilapia homozygous for the susceptibility allele. Several candidate genes related to host response to viral infection were identified within this QTL, including lgals17, vps52, and trim29. These results provide a rare example of a major QTL affecting a trait of major importance to a farmed animal. Genetic markers from the QTL region have potential in marker-assisted selection to improve host resistance, providing a genetic solution to an infectious disease where few other control or mitigation options currently exist.

Background Tilapia tilapinevirus, also known as tilapia lake virus (TiLV), is a significant virus that is responsible for the die-off of farmed tilapia across the globe. The detection and quantification of the virus using environmental RNA (eRNA) from pond water samples represents a potentially non-invasive and routine strategy for monitoring pathogens and early disease forecasting in aquaculture systems. Methods Here, we report a simple iron flocculation method for concentrating viruses in water, together with a newly-developed hydrolysis probe quantitative RT-qPCR method for the detection and quantification of TiLV. Results The RT-qPCR method designed to target a conserved region of the TiLV genome segment 9 has a detection limit of 10 viral copies per µL of template. The method had a 100% analytical specificity and sensitivity for TiLV. The optimized iron flocculation method was able to recover 16.11 ± 3.3% of the virus from water samples spiked with viral cultures. Tilapia and water samples were collected for use in the detection and quantification of TiLV disease during outbreaks in an open-caged river farming system and two earthen fish farms. TiLV was detected from both clinically sick and asymptomatic fish. Most importantly, the virus was successfully detected from water samples collected from different locations in the affected farms (i.e., river water samples from affected cages (8.50 × 103 to 2.79 × 105 copies/L) and fish-rearing water samples, sewage, and reservoir (4.29 × 103 to 3.53 × 104 copies/L)). By contrast, TiLV was not detected in fish or water samples collected from two farms that had previously experienced TiLV outbreaks and from one farm that had never experienced a TiLV outbreak. In summary, this study suggests that the eRNA detection system using iron flocculation, coupled with probe based-RT-qPCR, is feasible for use in the concentration and quantification of TiLV from water. This approach may be useful for the non-invasive monitoring of TiLV in tilapia aquaculture systems and may support evidence-based decisions on biosecurity interventions needed.

Tilapia is an affordable protein source farmed in over 140 countries with the majority of production in low‐ and middle‐income countries. Intensification of tilapia farming has exacerbated losses caused by emerging and re‐emerging infectious diseases. Disease diagnostics play a crucial role in biosecurity and health management to mitigate disease loss and improve animal welfare in aquaculture. Three continuous levels of diagnostics (I, II and III) for aquatic species have been proposed by Food and Agriculture Organization of the United Nations (FAO) and the Network of Aquaculture Centers in Asia and the Pacific (NACA) to promote the integration of basic and advanced methods to achieve accurate and meaningful interpretation of diagnostic results. However, the recent proliferation of cutting‐edge molecular methods applied in the diagnosis of diseases of aquacultured animals has shifted the focus of researchers and users away from basic approaches and toward molecular diagnostics, despite the fact that many diseases can be rapidly diagnosed using inexpensive, simple microscopic examination and that most emerging diseases in aquaculture were discovered by histopathology. This review, therefore, revisits and highlights the importance of the three levels of diagnostics for diseases of tilapia, particularly the frequently overlooked basic procedures (e.g., case history records, gross pathology, presumptive diagnostic methods and histopathology). The review also covers current and emerging molecular diagnostic technologies for tilapia pathogens including polymerase chain reaction methods (conventional, quantitative, digital), isothermal amplification methods Loop‐mediated Isothermal Amplification (LAMP), recombinase polymerase amplification (RPA), clustered regularly interspaced short palindromic repeats (CRISPR)‐based detection, lateral flow immunoassays, as well as discussing what is on the horizon for tilapia disease diagnostics (next generation sequencing, artificial intelligence, environmental Deoxyribonucleic Acid (DNA) and Ribonucleic Acid (RNA) and point‐of‐care testing) providing a future vision for transferring these technologies to farmers and stakeholders for a sustainable aquatic food system transformation.

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