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Markers for selection of disease resistance in fish: a review

Author:
Das, Sweta   Sahoo, P. K.   


Journal:
Aquaculture International


Issue Date:
2014


Abstract(summary):

Aquaculture is the fastest growing food producing sector in the world. However, diseases result in a major loss in production. Among the several management techniques, selective breeding for resistant trait is one of the most reliable methods and provides long-term control over disease problems. Field survival or challenge survival records provide initial information of resistant stocks. However, selection programmes demand a proper marker which can identify the resistant stock easily with much accuracy. Several immunological indicators associated with resistance to a particular disease have been reported. These include positively correlated markers such as level of natural and specific antibody, respiratory burst activity of phagocytes and level of acute-phase ceruloplasmin protein and negatively correlated markers such as serum lysozyme, haemolytic and haemagglutination activities. However, for few fish species and pathogen-specific markers viz., myeloperoxidase activity, cortisol and glucose levels, macrophage aggregation and the level of plasma proteins, a confined conclusion of association has not been established. Besides immunological markers, molecular markers are in use because of their reliable screening methods. Genome can be scanned for molecular markers which provide the full linkage map of a species or stock. Association of these molecular markers with resistant traits gives rise to quantitative trait loci (QTL) for resistance to a particular pathogen. Screening of resistant stock can be carried out using these markers. Among the several marker systems, amplified fragment length polymorphism, microsatellites and single-nucleotide polymorphism play a major role in the process of selection for disease resistance. With the use of these marker techniques, we can avoid challenge testing where a huge number of animals were being killed. Multiple trait selection can also be possible with multiple QTL identification for resistance to two or more diseases simultaneously.


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