Abstract
Reliability of genomic selection (GS) models was tested in an admixed population of Atlantic salmon, originating from crossing of several wild subpopulations. The models included ordinary genomic BLUP models (GBLUP), using genome-wide SNP markers of varying densities (1–220 k), a genomic identity-by-descent model (IBD-GS), using linkage analysis of sparse genome-wide markers, as well as a classical pedigree-based model. Reliabilities of the models were compared through 5-fold cross-validation. The traits studied were salmon lice (Lepeophtheirus salmonis) resistance (LR), measured as (log) density on the skin and fillet color (FC), with respective estimated heritabilities of 0.14 and 0.43. All genomic models outperformed the classical pedigree-based model, for both traits and at all marker densities. However, the relative improvement differed considerably between traits, models and marker densities. For the highly heritable FC, the IBD-GS had similar reliability as GBLUP at high marker densities (>22 k). In contrast, for the lowly heritable LR, IBD-GS was clearly inferior to GBLUP, irrespective of marker density. Hence, GBLUP was robust to marker density for the lowly heritable LR, but sensitive to marker density for the highly heritable FC. We hypothesize that this phenomenon may be explained by historical admixture of different founder populations, expected to reduce short-range lice density (LD) and induce long-range LD. The relative importance of LD/relationship information is expected to decrease/increase with increasing heritability of the trait. Still, using the ordinary GBLUP, the typical long-range LD of an admixed population may be effectively captured by sparse markers, while efficient utilization of relationship information may require denser markers (e.g., 22 k or more).
Highlights
Aquaculture populations are characterized by high male and female fecundity, typically resulting in large full-sib families
RELIABILITY OF DIFFERENT MODELS AND MARKER DENSITIES Based on the five-fold cross validation, the reliability of the PED model was slightly higher for fillet color (FC) (0.36) than for lice resistance (0.34), the relative increases in reliabilities for the different genomic selection (GS) models are presented in Figures 4, 5 for lice resistance and FC, respectively
The relative increase in reliability using GS was substantial, but moderate for FC (21% for IBD genomic relationship matrix (IBD-GS) and 22% for genomic BLUP models (GBLUP) with 220 k)
Summary
Aquaculture populations are characterized by high male and female fecundity, typically resulting in large full-sib families. Traditional aquaculture selection programs involve sib-testing, which has limited reliability under classical selection schemes, as selection candidates are evaluated based on mid-parent means. This leads to increased co-selection among close relatives, and enforcing restrictions on inbreeding will hamper selection on such traits more than selection for individually evaluated traits. In situations where several QTL underlie the trait, MAS will be more complex, and power of QTL detection lower as each QTL explains a smaller fraction of the total genetic variance For such traits genomic selection (GS) is a viable alternative, utilizing information from numerous genome-wide marker loci jointly in the genetic analysis (Meuwissen et al, 2001). Superior performance of GS models compared with classical models has been documented in several publications (e.g., Nielsen et al, 2009; Ødegård et al, 2009; Ødegård and Meuwissen, 2014), while documentation from real aquaculture data has been largely absent so far
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