Family growth response to fishmeal and plant-based diets shows genotype×diet interaction in rainbow trout (Oncorhynchus mykiss)

Abstract

Family growth response to fishmeal and plant-based diets shows genotype x diet interaction in rainbow trout (Oncorhynchus mykiss)Lindsey R. Pierce (Abstract)The ability of rainbow trout to efficiently utilize plant-based diets for growth and the genetic variation for that trait have not been thoroughly examined. In this study, growth of a pedigreed population from the commercial Kamloop strain was assessed while feeding plant-based or traditional fishmeal-based diets. Both fish oil (5.00%) and soybean oil (8.43%) were included in the plant-based diet, and only fish oil was used in the fishmeal diet (10.10%). Ninety-five full-sib families nested within 47 half-sib families were reared in a common environment. Parentage assignment was performed on approximately 1,000 fish fed each diet using eight microsatellite markers chosen for nonduplication, a minimum of five alleles with no known null alleles, at least 50% heterozygosity, and unambiguous scoring. Progeny were assigned to parental pairs using two allocation programs, PAPA and FAP, to increase accuracy and to test assignment efficiency. The fish fed the fish meal/oil diet were approximately 8% larger than the fish fed the plant-based diet (P < 0.05). A significant genotype x diet effect accounted for 5% of the random variation. The genetic correlation for growth on the two diets was 73%, with a heritability of 30% across the diets. With this, I conclude that substantial genetic variation for utilizing plant-based diets containing soybean meal and oil exists in this widely used commercial rainbow trout strain. The genetic variation can be explored to detect and select for genes involved in improved utilization of plant-based diets containing soybean meal and oil if growth on plant-based meals becomes a long-term breeding goal in rainbow trout production.iii Acknowledgements My ability to relocate, complete research, perform class assignments, work as a teaching assistant, and study would have been impossible without the support and encouragement of close family, faculty, and friends. I have made several lasting connections throughout my master's studies and will continue collaborating with these individuals.

Estimating Breeding Values With Molecular Relatedness and Reconstructed Pedigrees in Natural Mating Populations of Common Sole, Solea Solea

“…Loss of selection candidates due to ambiguous parental allocation was 33%. Comparable results (10-30%) were found by several authors in other species (Herlin et al 2007(Herlin et al , 2008Pierce et al 2008). Loss of selection candidates has major effects on costs of selection procedures in breeding programs and may lead to lower realized selection responses and increased rates of inbreeding.…”

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

“…Dupont-Nivet et al (2009) went to the extent of creating maternal clones for genetic variance component assessment to minimise maternal effects. Other strategies include reducing the age span of experimental fish (Pierce et al, 2008) or by minimising the size range of eggs between spawns (Dupont-Nivet et al, 2009). The potential source of bias caused by differences in maternal effects is simply eliminated in our design because c 2 is equal zero as only one dam is used.…”

“…There is also an emerging need for GxE assessment of growth rate in newly formulated diets with significant re-ranking of family performances between diets observed by Pierce et al (2008), Dupont-Nivet et al…”

“…Designs using synchronous spawning are difficult to achieved in practice (Dupont-Nivet et al, 2008;Quinton et al, 2007;Boucher et al, 2011) making it necessary to pool spawns over a period of more than one day (Pierce et al, 2008). Mixing fish born more than one day apart is undesirable as older fish may maintain a size advantage they never relinquished (Tave, 1995) causing biased estimates of genetic parameters.…”

“…Oreochromis niloticus (Ponzoni et al, 2005), 0.70+0.10 for D. labrax (Dupont-Nivet et al, 2008), 0.73+0.13 for Oncorhynchus mykiss (Pierce et al, 2008), 0.75+0.09 for Oncorhynchus mykiss (Dupont-Nivet et al, 2010), 0.82+0.21 for Coregonus lavaretus L. (Quinton et al, 2007), 0.67+0.12 Oncorhynchus mykiss Walbaum (Boucher et al, 2011) and 0.74+0.21 to 0.84+0.15 for Oreochromis niloticus (Khaw et al, 2009). …”