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Dodds K.G.,Agresearch Ltd. | McEwan J.C.,Agresearch Ltd. | Brauning R.,Agresearch Ltd. | Anderson R.M.,Agresearch Ltd. | And 3 more authors.
BMC Genomics | Year: 2015

Background: Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set. Results: We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a 'fin plot') is given to illustrate this issue and to guide filtering parameters. Conclusion: We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method. © 2015 Dodds et al. Source


Kristjansson T.,Stofnfiskur | Arnason T.,Agricultural University of Iceland
Aquaculture Research | Year: 2016

During the development of breeding programme for Atlantic cod Gadus morhua L., in Iceland, genetic parameters were estimated for 1402 individuals, which were assigned with DNA profiling to 140 dams and 70 sires. The cod was reared in cages on the eastern and western coasts of Iceland from 2004 to 2005. At the average body weight of 1.8 kg, the estimated heritability (h2 ± SE) for body weight, gutted weight and the condition factor (CF) were 0.31 ± 0.06, 0.34 ± 0.04 and 0.24 ± 0.06 respectively. Genetic correlation (rG) in body weight between the two rearing locations was estimated as 0.95, which reflects a low G × E interaction. The estimated heritability for hepatosomatic index (HSI) and fillet yields was 0.061 ± 0.04 and 0.04 ± 0.04 respectively. The HSI and fillet yields were highly genetically correlated with body weight or 0.67 and 0.82 respectively. The genetic correlation between the CF and body weight was estimated as 0.31. There appears to be substantial amount of additive genetic variation for body weight suggesting that selection is likely to be successful. Low heritability for fillet yields and the HSI indicates less promise of genetic improvement. Assigning of parentage to individuals with DNA profiling was 80% successful. © 2016 John Wiley & Sons Ltd. Source


Kristjansson T.,Stofnfiskur | Arnason T.,Agricultural University of Iceland
Aquaculture Research | Year: 2015

Three-year classes of Atlantic cod Gadus morhua were studied throughout their rearing in the eastern coast of Iceland from 2004 to 2011. The growth and status of maturity were recorded during the rearing. For one of the year classes, genetic parameters for body weight and maturity status were estimated from 757 individuals, which were the offspring of 40 dams and 20 sires. The estimate for heritability of body weight was h2 = 0.34 at the average weight of 630 g, and heritability for proportion of maturity was h2 = 0.17 given the same weight. The relationship between body weight and the proportion of mature individuals at first winter revealed a strong genetic correlation of rG = 0.90. The phenotypic relationship between body weight and proportion of maturity was estimated with a Bayesian logistic regression as P(yi = 1(mature)) = Φ(β0 + β1weight + β2sex). The best fit yielded β0 = -2.9320 with a 95% interval between -3.2807 and -2.5394, β1weight = 0.0041 with a 95% interval ranging from 0.0035 to 0.0046 and β1sex = -0.0201 with a 95% interval from -0.2003 to 0.1445. The gender had no notable effect. This strong phenotypic and genetic correlation in body weight and maturation suggests that an increased growth rate will consequently lead to a higher proportion of mature individuals in the population. As a consequence, genetic manipulations to simultaneously increase growth and delay maturation may present a challenge. © 2015 John Wiley & Sons Ltd . Source

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