Effects of nonrandom mating schemes to delay the inbreeding accumulation in cultured populations of coho salmon (Oncorhynchus kisutch)

2004 ◽  
Vol 61 (4) ◽  
pp. 547-553 ◽  
Author(s):  
José A Gallardo ◽  
Jean Paul Lhorente ◽  
Ximena García ◽  
Roberto Neira
Keyword(s):  
Coho Salmon ◽  
Random Mating ◽  
Oncorhynchus Kisutch ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Nonrandom Mating ◽  
The Family ◽  
Best Linear Unbiased ◽  
The Mean ◽  
High Degree

Chilean salmon culture is based on a high degree of artificial selection, which has had the tendency to increase the inbreeding (F). Three types of nonrandom mating were evaluated to control the inbreeding in two best linear unbiased prediction selected coho salmon (Oncorhynchus kisutch) populations (even and odd). These included compensatory mating on the basis of breeding values (C), modified compensatory mating (C1) based on the family mean of breeding values, and mating that minimized the mean co-ancestry of the group selected (MC scheme). In the odd population, the MC scheme (F = 2.0%) reduced the increase in inbreeding of the next generation by 50% and 46% when compared with random mating of selected individuals with sib mating restricted (F = 3.9%) and with C (F = 3.7%), respectively. In the even population, the MC scheme reduced the increase in inbreeding by 14% compared with C1 (9.7 versus 11.2). In both populations, the MC scheme also reduced variance in inbreeding (even, 59%; odd, 39%). Thus, the MC scheme was more efficient in reducing the increase and variance of inbreeding, thus limiting the expression of inbreeding depression. Although the MC scheme was more time consuming, we recommend this scheme to carry out crosses in each generation.

Effects of Gravel Size, Egg Depth, and Egg Density on Intragravel Movement and Emergence of Coho Salmon (Oncorhynchus kisutch) Alevins

1970 ◽  
Vol 27 (7) ◽  
pp. 1191-1199 ◽  
Author(s):  
L. M. Dill ◽  
T. G. Northcote
Keyword(s):  
Environmental Variables ◽  
Coho Salmon ◽  
Oncorhynchus Kisutch ◽  
High Density ◽  
Low Density ◽  
Gravel Size ◽  
Egg Density ◽  
The Mean

In experimental aquaria with large gravel (3.2–6.3 cm), vertical and lateral movements of coho salmon (Oncorhynchus kisutch) alevins were more extensive and area utilized per alevin was greater than in small gravel (1.9–3.2 cm). At low density (50 per aquarium) the alevins moved farther towards the inlet, but the mean area occupied per alevin was the same as that at high density (100 per aquarium). Burial depths tested (20 and 30 cm) had no significant effect on vertical or lateral movements or on area utilized per alevin. Alevin orientation in the gravel, survival to emergence, and timing of emergence were not affected by any of the environmental variables examined.

scholarly journals Prediction of Rates of Inbreeding in Populations Selected on Best Linear Unbiased Prediction of Breeding Value

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 361-373
Author(s):  
Piter Bijma ◽  
John A Woolliams
Keyword(s):  
Linear Model ◽  
Goodness Of Fit ◽  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Quadratic Model ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Wide Range ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Abstract Predictions for the rate of inbreeding (ΔF) in populations with discrete generations undergoing selection on best linear unbiased prediction (BLUP) of breeding value were developed. Predictions were based on the concept of long-term genetic contributions using a recently established relationship between expected contributions and rates of inbreeding and a known procedure for predicting expected contributions. Expected contributions of individuals were predicted using a linear model, μi(x) = α βsi, where si denotes the selective advantage as a deviation from the contemporaries, which was the sum of the breeding values of the individual and the breeding values of its mates. The accuracy of predictions was evaluated for a wide range of population and genetic parameters. Accurate predictions were obtained for populations of 5–20 sires. For 20–80 sires, systematic underprediction of on average 11% was found, which was shown to be related to the goodness of fit of the linear model. Using simulation, it was shown that a quadratic model would give accurate predictions for those schemes. Furthermore, it was shown that, contrary to random selection, ΔF less than halved when the number of parents was doubled and that in specific cases ΔF may increase with the number of dams.

scholarly journals The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Animals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 569
Author(s):  
Chen Wei ◽  
Hanpeng Luo ◽  
Bingru Zhao ◽  
Kechuan Tian ◽  
Xixia Huang ◽  
...  
Keyword(s):  
Rank Correlation ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Breeding Value ◽  
Genomic Information ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Merino Sheep ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

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