Date of Award
Master of Science
Largemouth bass (Micropterus salmoides) have increasingly become more popular as a food fish within the aquaculture industry. With growing popularity comes the desire to improve growth rates for the current stocks, specifically the ability to reach market size (1.5lbs) more quickly. This research aims to establish a predictive model for largemouth bass growth to 1.5 pounds, evaluate the distribution of polymorphisms in insulin-like growth factor (IGF) genes among North Central Region (NCR) largemouth bass stocks and supply hatcheries, and correlate IGF gene polymorphisms to growth and gene expression using populations having differing genetic profiles. For objective 1 a predictive Bayesian hierchical model was established using wild populations demonstrating the ability to predict growth to 1.5 lbs. Objective 2 determined if the IGF-I and IGF-II genetic profile of populations available to North Central Region (NCR) growers differed greatly from what was previously described in identified populations of interest for a growth trial. In objective 3, it was observed that IGF I and IGF II expression in the skeletal muscle of fast growing largemouth bass was lower than slow growing bass, and there was a significant (r2=.59928, p=.0031) negative correlation between weight and IGF II expression. Overall, this research shows that, with proper data collection, a predictive model can be used to show which available populations may reach market size fastest, that the current gene pool has room for improvement through introduction of important, currently absent alleles, and that IGF-II may be an important biomarker for growth in largemouth bass. These findings are the starting point for future research and give NCR growers selection tools to begin improving growth rate and reduce time to market.
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