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This study tested and compared different implementation strategies for genomic selection for Norwegian White Sheep, aiming to increase genetic gain for maternal traits. These strategies were evaluated for their genetic gain ingrowth, carcass and maternal traits, total genetic gain, a weighted sum of the gain in each trait and rates of inbreeding through a full-scale stochastic simulation. Results showed genomic selection schemes to increase genetic gain for maternal traits but reduced genetic gain for other traits. This could also be obtained by selecting rams for artificial selection at a higher age. Implementation of genomic selection in the current breeding structure increased genetic gain for maternal traits up to 57%, outcompeted by reducing the generation interval for artificial insemination rams from current 3 to 2 years. Then, total genetic gain for maternal traits increased by 65%-77% and total genetic gain by18%-20%, but at increased rates of inbreeding., (© 2020 The Authors. Journal of Animal Breeding and Genetics published by Blackwell Verlag GmbH.)

Background: In traditional family-based aquaculture breeding, each sire is mated to two dams in order to separate the sire's genetic effect from other family effects. Factorial mating involves more mates per sire and/or dam and result in more but smaller full- and/or half-sib families. For traits measured on sibs of selection candidates, factorial mating increases intensity of selection between families when selection is on traditional best linear unbiased prediction (BLUP) estimated breeding values (TRAD-EBV). However, selection on genome-wide estimated breeding values (GW-EBV), uses both within- and between-family effects and the advantage of factorial mating is less obvious. Our aim was to compare by computer simulation the impact of various factorial mating strategies for truncation selection on TRAD-EBV versus GW-EBV on rates of inbreeding, accuracy of selection and genetic gain for two traits, i.e. one measured on selection candidates (CAND-TRAIT) and one on their sibs (SIB-TRAIT)., Results: Sire:dam mating ratios of 1:1, 2:2 or 10:10 were tested with 100, 200 or 1000 families produced from a constant number of parents (100 sires and 100 dams), and a mating ratio of 1:2 with 200 families produced from 100 sires and 200 dams. With GW-EBV, changing the mating ratio from 1:1 to 10:10 had a limited effect on genetic gain (less than 5 %) for both CAND-TRAIT and SIB-TRAIT, whereas with TRAD-EBV, selection intensity increased for SIB-TRAIT and genetic gain increased by 41 and 77 % for schemes with 3000 and 12,000 selection candidates, respectively. For both GW-EBV and TRAD-EBV, rates of inbreeding decreased by up to ~30 % when the mating ratio was changed from 1:1 to 10:10 for schemes with 3000 to 12,000 selection candidates. Similar results were found for alternative heritabilities of SIB-TRAIT and total number of tested sibs., Conclusions: Changing the sire:dam mating ratio from 1:1 to 10:10 increased genetic gain substantially with TRAD-EBV, mainly through increased selection intensity for the SIB-TRAIT, whereas with GW-EBV, it had a limited effect on genetic gain for both traits. Rates of inbreeding decreased for both selection methods.

Background: Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs., Methods: Six alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat), paternal (Pat) or a mixture of maternal and paternal (MatPat) double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC), minimum coancestry mating (MinC), or random (RAND) mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes., Results: Results showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed., Conclusions: In conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the selection candidates and require the use of sib tests, such as disease resistance and meat quality.

Background: Traditional family-based aquaculture breeding programs, in which families are kept separately until individual tagging and most traits are measured on the sibs of the candidates, are costly and require a high level of reproductive control. The most widely used alternative is a selection scheme, where families are reared communally and the candidates are selected based on their own individual measurements of the traits under selection. However, in the latter selection schemes, inclusion of new traits depends on the availability of non-invasive techniques to measure the traits on selection candidates. This is a severe limitation of these schemes, especially for disease resistance and fillet quality traits., Methods: Here, we present a new selection scheme, which was validated using computer simulations comprising 100 families, among which 1, 10 or 100 were reared communally in groups. Pooling of the DNA from 2000, 20000 or 50000 test individuals with the highest and lowest phenotypes was used to estimate 500, 5000 or 10000 marker effects. One thousand or 2000 out of 20000 candidates were preselected for a growth-like trait. These pre-selected candidates were genotyped, and they were selected on their genome-wide breeding values for a trait that could not be measured on the candidates., Results: A high accuracy of selection, i.e. 0.60-0.88 was obtained with 20000-50000 test individuals but it was reduced when only 2000 test individuals were used. This shows the importance of having large numbers of phenotypic records to accurately estimate marker effects. The accuracy of selection decreased with increasing numbers of families per group., Conclusions: This new selection scheme combines communal rearing of families, pre-selection of candidates, DNA pooling and genomic selection and makes multi-trait selection possible in aquaculture selection schemes without keeping families separately until individual tagging is possible. The new scheme can also be used for other farmed species, for which the cost of genotyping test individuals may be high, e.g. if trait heritability is low.

Partial least square regression (PLSR) and principal component regression (PCR) are methods designed for situations where the number of predictors is larger than the number of records. The aim was to compare the accuracy of genome-wide breeding values (EBV) produced using PLSR and PCR with a Bayesian method, 'BayesB'. Marker densities of 1, 2, 4 and 8 Ne markers/Morgan were evaluated when the effective population size (Ne) was 100. The correlation between true breeding value and estimated breeding value increased with density from 0.611 to 0.681 and 0.604 to 0.658 using PLSR and PCR respectively, with an overall advantage to PLSR of 0.016 (s.e = 0.008). Both methods gave a lower accuracy compared to the 'BayesB', for which accuracy increased from 0.690 to 0.860. PLSR and PCR appeared less responsive to increased marker density with the advantage of 'BayesB' increasing by 17% from a marker density of 1 to 8Ne/M. PCR and PLSR showed greater bias than 'BayesB' in predicting breeding values at all densities. Although, the PLSR and PCR were computationally faster and simpler, these advantages do not outweigh the reduction in accuracy, and there is a benefit in obtaining relevant prior information from the distribution of gene effects.

Minimum coancestry mating with a maximum of one offspring per mating pair (MC1) is compared with random mating schemes for populations with overlapping generations. Optimum contribution selection is used, whereby DeltaF is restricted. For schemes with DeltaF restricted to 0.25% per year, 256 animals born per year and heritability of 0.25, genetic gain increased with 18% compared with random mating. The effect of MC1 on genetic gain decreased for larger schemes and schemes with a less stringent restriction on inbreeding. Breeding schemes hardly changed when omitting the iteration on the generation interval to find an optimum distribution of parents over age-classes, which saves computer time, but inbreeding and genetic merit fluctuated more before the schemes had reached a steady-state. When bulls were progeny tested, these progeny tested bulls were selected instead of the young bulls, which led to increased generation intervals, increased selection intensity of bulls and increased genetic gain (35% compared to a scheme without progeny testing for random mating). The effect of MC1 decreased for schemes with progeny testing. MC1 mating increased genetic gain from 11-18% for overlapping and 1-4% for discrete generations, when comparing schemes with similar genetic gain and size.

Abstract A within-family marker-assisted selection scheme was designed for typical aquaculture breeding schemes, where most traits are recorded on sibs of the candidates. Here, sibs of candidates were tested for the trait and genotyped to establish genetic marker effects on the trait. BLUP breeding values were calculated, including information of the markers (MAS) or not (NONMAS). These breeding values were identical for all family members in the NONMAS schemes, but differed between family members in the MAS schemes, making within-family selection possible. MAS had up to twice the total genetic gain of the corresponding NONMAS scheme. MAS was somewhat less effective when heritability increased from 0.06 to 0.12 or when the frequency of the positive allele was < 0.5. The relative efficiency of MAS was higher for schemes with more candidates, because of larger fullsib family sizes. MAS was also more efficient when male:female mating ratio changed from 1:1 to 1:5 or when the QTL explained more of the total genetic variation. Four instead of two markers linked to the QTL increased genetic gain somewhat. There was no significant difference in polygenic genetic gain between MAS and NONMAS for most schemes. The rates of inbreeding were lower for MAS than NON-MAS schemes, because fewer full-sibs were selected by MAS.

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program. [ABSTRACT FROM AUTHOR]

Abstract: A simulation study was conducted to investigate the potential advantage of two-step selection for dissemination of genetic gains in salmon production through a system with a nucleus breeding population, a multiplier tier and a grow-out tier. Results demonstrated that profit (measured in the grow-out tier in generation 8) can be substantially increased through production and dissemination of specialised stocks suited for e.g. specific production environments or markets. Truncation selection alternatives in two steps with varying selection proportions were compared to random sampling of parents in both dissemination steps: from the nucleus to the multiplier and from the multiplier to the grow-out tier. Strategies where truncation selection was used in one step and random sampling of parents in the other step were also tested. The selection alternatives with truncation selection in both steps gave on average between 31% and 26% higher profit than random selection. The selection alternative with an extremely low truncation selection proportion in two steps would on average give 2% higher profit than the selection alternative with extremely low truncation selection proportion from the nucleus to the multiplier (1st step), and a normally low truncation selection proportion from the multiplier to the grow-out (2nd step). However, the former alternative yielded five times fewer eggs. The study also showed that one step of truncation selection and one of random sampling of parents, irrespective of the order, would give on average about 19% higher profit compared to random selection in two steps. The effect of the correlation between the nucleus/multiplier breeding goal and the breeding objective of the grow-out was that profit was highest when the correlation was high. With a negative genetic correlation between the traits, profit was still high if the trait with the highest heritability (i.e. the trait measured on candidate itself) had the highest economic value. It was concluded that selection of specialised stocks for specific breeding objectives in two steps from the nucleus via the multiplier and to the grow-out could increase profit by 24%. Specific breeding objectives would also give more flexibility for a final product when the grow-out producers could ask for unique trait-combinations for their fish. [Copyright &y& Elsevier]

Background: In the past, pedigree relationships were used to control and monitor inbreeding because genomic relationships among selection candidates were not available until recently. The aim of this study was to understand the consequences for genetic variability across the genome when genomic information is used to estimate breeding values and in managing the inbreeding generated in the course of selection on genome-enhanced estimated breeding values. Methods: These consequences were measured by genetic gain, pedigree- and genome-based rates of inbreeding, and local inbreeding across the genome. Breeding schemes were compared by simulating truncation selection or optimum contribution selection with a restriction on pedigree- or genome-based inbreeding, and with selection using estimated breeding values based on genome- or pedigree-based BLUP. Trait information was recorded on full-sibs of the candidates. Results: When the information used to estimate breeding values and to constrain rates of inbreeding were either both pedigree-based or both genome-based, rates of genomic inbreeding were close to the desired values and the identical-by-descent profiles were reasonably uniform across the genome. However, with a pedigree-based inbreeding constraint and genome-based estimated breeding values, genomic rates of inbreeding were much higher than expected. With pedigree-instead of genome-based estimated breeding values, the impact of the largest QTL on the breeding values was much smaller, resulting in a more uniform genome-wide identical-by-descent profile but genomic rates of inbreeding were still higher than expected based on pedigree relationships, because they measure the inbreeding at a neutral locus not linked to any QTL. Neutral loci did not exist here, where there were 100 QTL on each chromosome. With a pedigree-based inbreeding constraint and genome-based estimated breeding values, genomic rates of inbreeding substantially exceeded the value of its constraint. In contrast, with a genome-based inbreeding constraint and genome-based estimated breeding values, marker frequencies changed, but this change was limited by the inbreeding constraint at the marker position. Conclusions: To control inbreeding, it is necessary to account for it on the same basis as what is used to estimate breeding values, i.e. pedigree-based inbreeding control with traditional pedigree-based BLUP estimated breeding values and genome-based inbreeding control with genome-based estimated breeding values. [ABSTRACT FROM AUTHOR]

Background: Selection schemes aiming at introgressing genetic material from a donor into a recipient line may be performed by backcross-breeding programs combined with selection to preserve the favourable characteristics of the donor population. This stochastic simulation study investigated whether genomic selection can be effective in preserving a major quantitative trait locus (QTL) allele from a donor line during the backcrossing phase. Methods: In a simulation study, two fish populations were generated: a recipient line selected for a production trait and a donor line characterized by an enhanced level of disease resistance. Both traits were polygenic, but one major QTL affecting disease resistance was segregating only within the donor line. Backcrossing was combined with three types of selection (for total merit index) among the crossbred individuals: classical selection, genomic selection using genome-wide dense marker maps, and gene-assisted genomic selection. It was assumed that production could be observed directly on the selection candidates, while disease resistance had to be inferred from tested sibs of the selection candidates. Results: Classical selection was inefficient in preserving the target QTL through the backcrossing phase. In contrast, genomic selection (without specific knowledge of the target QTL) was usually effective in preserving the target QTL, and had higher genetic response to selection, especially for disease resistance. Compared with pure genomic selection, gene-assisted selection had an advantage with respect to disease resistance (28-40% increase in genetic gain) and acted as an extra precaution against loss of the target QTL. However, for total merit index the advantage of geneassisted genomic selection over genomic selection was lower (4-5% increase in genetic gain). Conclusion: Substantial differences between introgression programs using classical and genomic selection were observed, and the former was generally inferior with respect to both genetic gain and the ability to preserve the target QTL. Combining genomic selection with gene-assisted selection for the target QTL acted as an extra precaution against loss of the target QTL and gave additional genetic gain for disease resistance. However, the effect on total merit index was limited. [ABSTRACT FROM AUTHOR]

Abstract: The simulation study examined the effect in optimal contribution selection of specifying an additive genetic relationship matrix (A-matrix) deviating from the true A-matrix of the base population. A base population of 160 males and 160 females was sampled evenly from 4 or 8 randomly chosen, drift-differentiated, wild subpopulations. Wild fish had true inbreeding coefficient of F wild, either 0.05 or 0.20, giving additive genetic relationships of 2F wild within, and 0 between subpopulations. Selection based upon phenotypes was simulated on one continuous trait of heritability, h wild 2, either 0.1 or 0.3. Base animals were mated either within subpopulations, or at random, so that the first round of selection occurred either on purebred or crossbred fish respectively. Optimum contributions was implemented from generation 1 for a desired rate of inbreeding of 0.5% per generation, using an assumed F wild ⁎ which varied between 0.0 and 0.3. Assuming F wild ⁎ =0.0 compared to 0.3, resulted in steeper regressions of the fractional contributions of subpopulations on average breeding value, higher true inbreeding and consequently reduced additive genetic variance, albeit with larger genetic gain from the first round of selection. When the first round of selection followed random mating the regression of the fractional contributions of the subpopulations was also less steep. These effects persisted, but originated from the misspecification of F wild ⁎ and so will not accumulate further in the medium-to long-term. Consequently, assuming F wild ⁎ was less than the true value led to sub-optimal use of subpopulations with an increased risk of loss of alleles of direct and strategic relevance to the breeding program. In conclusion, assuming F wild ⁎ ≈0.0 should be avoided and F wild ⁎ should be estimated with procedures such as marker estimated kinships, Q ST estimates or empirical observations of clines. [Copyright &y& Elsevier]

Abstract: Guidelines for constructing base populations in fish were examined using a drift model. A large number of drift differentiated, wild subpopulations, with inbreeding F wild (F wild ∈[0.05–0.20]), and a trait with heritability h tot 2 (h tot 2 ∈[0.10–0.30]), were assumed. A base population was generated by sampling 2N fish from each of nsub subpopulations (nsub ∈[1–8]), and then mated to produce 160 or 240 families per generation. The matings were either at random, in a structured diallel-cross, or within subpopulations to produce generation 1. Optimal contribution selection on phenotype was applied from generation 1 to11, with a rate of inbreeding of 0.5% per generation. Genetic gain (Δg) improved with nsub, the improvement being largest when going from one to two subpopulations, with diminishing returns. Most of the potential improvement was obtained with nsub =4, and was well predicted by . Initial matings across subpopulations improved Δg from the second round of selection compared to within. Consequently the effect of the mating strategy were first observed 3 generation after decisions were made and persisted over subsequent generations, but with minimal effect on the accumulated additive genetic gain in generation 11. It was concluded that sampling from at least four subpopulations was beneficial and that mating across subpopulations should start as early as possible. [Copyright &y& Elsevier]

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]