Abstract
BackgroundOne objective of this study was to identify putative quantitative trait loci (QTL) that affect indicator phenotypes for growth, nitrogen, and carbon metabolism in muscle, liver, and adipose tissue, and for feed efficiency. Another objective was to perform an RNAseq analysis (184 fish from all families), to identify genes that are associated with carbon and nitrogen metabolism in the liver. The material consisted of a family experiment that was performed in freshwater and included 2281 individuals from 23 full-sib families. During the 12-day feed conversion test, families were randomly allocated to family tanks (50 fish per tank and 2 tanks per family) and fed a fishmeal-based diet labeled with the stable isotopes 15N and 13C at inclusion levels of 2 and 1%, respectively.ResultsUsing a linear mixed-model algorithm, a QTL for pre-smolt growth was identified on chromosome 9 and a QTL for carbon metabolism in the liver was identified on chromosome 12 that was closely related to feed conversion ratio on a tank level. For the indicators of feed efficiency traits that were derived from the stable isotope ratios (15N and 13C) of muscle tissue and growth, no convincing QTL was detected, which suggests that these traits are polygenic. The transcriptomic analysis showed that high carbon and nitrogen metabolism was associated with individuals that convert protein from the feed more efficiently, primarily due to higher expression of the proteasome, lipid, and carbon metabolic pathways in liver. In addition, we identified seven transcription factors that were associated with carbon and nitrogen metabolism and located in the identified QTL regions.ConclusionsAnalyses revealed one QTL associated with pre-smolt growth and one QTL for carbon metabolism in the liver. Both of these traits are associated with feed efficiency. However, more accurate mapping of the putative QTL will require a more diverse family material. In this experiment, fish that have a high carbon and nitrogen metabolism in the liver converted protein from the feed more efficiently, potentially because of a higher expression of the proteasome, lipid, and carbon metabolic pathways in liver. Within the QTL regions, we detected seven transcription factors that were associated with carbon and nitrogen metabolism.
Highlights
One objective of this study was to identify putative quantitative trait loci (QTL) that affect indicator phenotypes for growth, nitrogen, and carbon metabolism in muscle, liver, and adipose tissue, and for feed efficiency
Genetic and phenotypic correlations among the studied traits and feed conversion ratio (FCR) were previously reported by Dvergedal et al [4] and showed that the indicator feed efficiency traits IFCR/ IFER in muscle had estimates of the genetic correlation with FCR on a tank level that were at the boundary of the parameter space
Association analysis To test whether phenotypes for feed efficiency such as ALC and IFCR/IFER variables are associated with SNPs, we performed a genome-wide association study (GWAS) with a linear mixed-model algorithm, using indicator traits related to nitrogen and carbon metabolism, growth, and indicator traits for feed efficiency as phenotypes
Summary
One objective of this study was to identify putative quantitative trait loci (QTL) that affect indicator phenotypes for growth, nitrogen, and carbon metabolism in muscle, liver, and adipose tissue, and for feed efficiency. The isotope profiles were used to calculate indicators of FER/FCR (isotope-based FER (IFER)/ FCR (IFCR)) They (rg) of tank-FCR with indicator traits based on nitrogen and carbon metabolism in muscle tissue measured by using stable isotopes (15N and 13C) (rg ~ 1.0), and with carbon metabolism in liver (ALC) (rg ~ 0.9). These results are in accordance with those reported by Hawkins et al [9], who proposed that differences in protein metabolism between individuals are genotype-dependent. Genetic improvement of feed efficiency, by selection for growth or by other means, will decrease production costs and the environmental footprint per unit produced [11, 12]
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