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The main aim of the current study was to compare the accuracy of selection for muscle content of fat and the health-promoting omega-3 fatty acids EPA and DHA in Atlantic salmon, by varying the sources of genetic information used in the estimation of breeding values. The following genetic information sources were compared: pedigree, SNP-chip markers and allele-specific expression markers. The results showed that differences between information sources were in general small, and different genetic information performed best for different traits. SNP-chip performed best for DHA, and pedigree performed best for EPA. Knowledge from gene expression analysis of a few individuals can be utilized to select a small panel of markers that perform relatively well. Genetic markers of allele-specific expression were able to capture a lot of genetic variation for DHA, but did not give significantly higher accuracies when combined with SNP-chip or pedigree information. The cross-validation accuracies for selection for DHA and EPA were moderate and offer possibilities for selection for these traits, especially if one extends the reference data set to a much bigger population, with more sibs per selection candidate. • We reveal the possibilities and accuracies of selection for the health promoting fatty acids EPA and DHA in Atlantic salmon. • The following genetic information sources were compared: pedigree, SNP-chip markers, and allele-specific expression markers. • A new discovery of this paper is that that different genetic information sources performs best for different traits. • Markers of variation in gene expression explain large fractions of the total genetic variability for DHA in Atlantic salmon. • Selection accuracies for DHA and EPA were moderate and show potential for selective breeding for these traits. [ABSTRACT FROM AUTHOR]

The objective of this study was to identify genetic variants associated with long-chain omega-3 fatty acid content in Atlantic salmon muscle, in order to identify genes underlying the genetic variation in these traits, by performing a genome-wide association study. Fatty acid composition, including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) content and the ratios DHA/DPA (docosapentaenoic acid) and DHA/ALA (α-linolenic acid) of skeletal muscle was determined in 642 Atlantic salmon individuals from the Salmobreed broodstock program. Further, a 57 K single-nucleotide polymorphism (SNP) array was used to genotype the 642 individuals to search for SNPs associated with skeletal muscle content of individual omega-3 fatty acids as well as ratios between fatty acids, using a mixed model approach. We identified markers showing a significant association with the ratio of DHA to DPA located on chromosome 19, close to the candidate gene elovl2 , which is directly involved in the conversion of DPA to DHA. The results further suggested that genetic variation affecting fillet EPA and DHA content is present on Atlantic salmon chromosome 21, as the GWAS analysis of EPA, DHA and DHA/ALA ratio all pointed to this chromosome. No known genes of direct relevance to the omega-3 bioconversion pathway were found here. We discuss the relevance of other interesting genes related to lipid metabolism and health located in this region. • 642 Atlantic salmon were genotyped (57K SNP-chip) to search for SNPs associated with muscle content of omega-3 fatty acids • Muscle omega-3 traits appeared to have a polygenic architecture • A few potential QTL were identified that explained moderate levels of the genetic variation • Significantly associated markers for DHA/DPA ratio were located near elovl2, which is involved in DPA to DHA conversion • The results suggest that genetic variation affecting fillet EPA and DHA content is present on chromosome 21 [ABSTRACT FROM AUTHOR]

In analytical chemistry, multivariate calibration is applied when substituting a time-consuming reference measurement (based on e.g. chromatography) with a high-throughput measurement (based on e.g. vibrational spectroscopy). An average error term, of the response variable, is often used to evaluate the performance of a calibration model. However, indirect relationships, between the response and explanatory variables, may be used for calibration. In such cases, model validity cannot necessarily be determined solely by the average error term. One should also consider the use of the models, as well as the validity of the indirect relationships in future samples. If the analyte of interest is partly quantified from signals of interfering compounds, then these interfering compounds will play a hidden role in the calibration. This hidden role may affect future use of the calibration model as strong covariance relationships between analyte estimates and interfering compounds may be imposed. Hence, such model cannot detect changes in the relationship between the analyte and interfering compounds. The problem is called the cage of covariance. This paper discusses the concept cage of covariance and possible consequences of applying models exposed to this issue. • The concept of Cage of Covariance is explained and visualized. • Estimates of several response variables may depend on each other. • This is problematic if estimates are used in e.g. breeding programs. [ABSTRACT FROM AUTHOR]