Arendonk, J.A.M., van

Blonk, R.J.W.

Bovenhuis, H.

Haley, C.S.

Komen, J.

Koning, D.J., de

Massault, C.

English

de Koning, D.J.

van Arendonk, J.A.M.

NARCIS 

Comparison of selection methods for natural mating mass-spawning species

Wageningen Yield 

Comparison of Selection Methods for Natural Mating Mass-Spawning Species 
 
Cécile Massault1,2, Robbert Blonk2, Hans, Komen2,  Dirk Jan de Koning1, Chris Haley3, van Arendonk Johan2, 
Henk Bovenhuis2 
 
Introduction 
 
For a number of mass-spawning species in aquaculture, especially those recently domesticated, natural mating is 
still used for the production of the next generation, where a number of males and females are placed together  in a 
tank and results in a large number of offspring with unknown parents. The offspring generation is a mix of full- 
sib families and half-sib families (both paternal and maternal) thus creating a complex  structure  with few large 
families and many small families. Variation in family size may increase the rate of inbreeding per generation 
(Falconer, D. and Mackay,  T. (1996)). 
 
Three  main methods  are  used  for selective breeding:   mass selection is currently the most-used method  of 
selection in mass-spawning species (Vandeputte, M., Dupont-Nivet, M., Haffray, P., et al. (2009)), where only 
records of animals’ own performance are used as criteria of selection, best unbiased linear prediction (BLUP), 
which  uses information on relatives to increase the accuracy of selection and genomic selection (Meuwisen et al. 
2001) which includes genomic information to increase further accuracy.  Optimum contribution with constrained 
rate of inbreeding is used to limit inbreeding (Sonesson, A., and Meuwissen, T.  (2000)). However, inbreeding 
has been rarely evaluated in mass-spawning and no study on restricting inbreeding for such population structure 
exists at the moment. 
 
In this study, we use simulation to determine the rate of genetic gain and rate of inbreeding in a mass spawning 
population with skewed parental distribution. We compared consequences of three breeding schemes, i.e. 
mass selection, BLUP selection and genomic selection, during 10 generations of selection. 
 
 
 
Material and methods 
 
We simulated a genome  size of 10 Morgans, divided into 10 chromosomes (1 Morgan length each) under a finite 
locus genetic  model. Mutation-drift  equilibrium  for a  given population  is  reached  when the loss  of  
genetic variance  due to drift equalled  the gain  of genetic  variance  due to mutation  (Meuwissen,  T., Hayes,  
B. And Goddard, M., (2001)). We simulated 1 700 generations with random mating, starting with 10 000 
polymorphic markers (4 400 polymorphic  markers at drift-mutation equilibrium) with an effective population 
size of 100 (50 males and 50 females) and a mutation rate of 10-5. We kept record of the pedigree  for the last 
5 generations of random mating  in order to account for existing  inbreeding  prior selection.  The base  
population  was the last generation of random mating after reaching mutation-drift equilibrium. The base 
population G1  was identical for three selection  methods:  mass selection,  BLUP selection  and  genomic  
selection  (detailed  below). The next generation was either produced from natural mating or controlled mating, 
depending on the scenario. Pedigrees were stored for each method of selection to calculate inbreeding level, 
although pedigree records were only used for BLUP  selection.  We  simulated  3 different  scenarios  with 
512 selection  candidates  (with no missing phenotypes or genotypes)  and for the three different heritabilities 
h2    (0.2, 05 and 0.8) over 10 generations of selection. Scenario 1 uses natural mating with selection of 20 
males and 20 females, scenario 2 uses controlled mating with  selection 16 males and 32 females and scenario 
3 uses natural mating  selecting 50 males and 50 females. Each scenario was simulated 50 times. 
 
After each generation of selection, selected fish reproduced in two different ways: natural mating or controlled 
mating. During controlled mating, 16 males were mated to two females (32 in total). Females were mated to only 
 
 
1    Division of Genetics and Genomics, Roslin Institute and Royal (Dick) School of Veterinary Sciences, 
University of Edinburgh, Roslin, Midlothian, EH25 9PS, United Kingdom 
 
2 Animal Breeding and Genetics Group, Wageningen University, postbox 338, NL-6700AH,  Wageningen, The 
Netherlands 
 
3  MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU 
one male. Sixteen offspring were kept per full-sib family, 8 males and 8 females and the total of offspring was 
therefore 512. Natural mating was simulated by assigning parental contribution, that were drawn from a gamma 
distribution  of parameter  α = 1 and  β = 0.75 using  20 males  and  20 females  to reproduce  the sea  bream 
population structure observed by Antonello et al. (2009) 
 
We decided to include 100 known QTLs  in the genome (10 QTLs  per chromosome)  at generation  G1   (base 
population). The QTL effects were sample from a gamma  distribution of shape parameter 0.4 (Meuwissen, T., 
Hayes, B. And Goddard, M., (2001))  and scale parameter 0.12 in order to obtain a genetic variance Ϭ 2A  of 15. 
QTL effects had a probability 0.5 to be either positive or negative. The genetic value is the sum of QTL values 
per locus: 
 
 
 
where  is the genetic value of animal i,  n the total number of QTLs,  the paternal QTL allele value of 
animal i and at locus j and    the maternal QTL allele value of animal i and at locus j (Hayes and Goddard 
2009). With a heritability h2, the environmental values  were drawn from a normal distribution N(0,( Ϭ2A/h2   - 
Ϭ2A)). The phenotypic value for animal i was the sum of genetic value  and environmental value . 
 
Parents for the next generation are selected using three different method of selection: mass selection, GBLUP 
and BLUP.  No restriction on inbreeding was applied for any of the methods. Among the selection candidates, 
sex ratio was equal. We will refer the number of selected males as nselmales and the number of selected females 
as nselfemales. For all three methods, all animals were phenotyped and for genomic selection, all animals were 
genotyped with certainty. No constrain on inbreeding was applied. 
 
For mass selection,  the parents for the future  generations  were selected  according to their own performance. 
Selection candidates were ranked from the highest phenotypes to the lowest. nselmales and nselfemales with the 
highest phenotypes were therefore kept for reproduction. 
 
Estimated  breeding values  for the selection  candidates  using genomic  selection  (GBLUP)  and BLUP  were 
calculated using the following model: 
 
 
 
where y was the vector of phenotypes, µ the mean phenotype, Z the incidence matrix relating phenotypes  
to breeding values, u vector of estimated breeding values, and e vector  of environmental effects, with var(e) = I 
Ϭ2e. with I the identity matrix. In our case, no fixed effects other than the mean were added to the model. The 
new brood stock was therefore composed of the nselmales males and nselfemales females with the highest 
EBVs. In BLUP selection, var(u) equals A Ϭ
2
A ,, with A the genetic relationship matrix, while var(u) equals G 
Ϭ2A, with G the genomic relationship matrix, calculated as described by Hayes & Goddard (2008), by calculated 
a similarity value between two individuals  at each  locus, which can be either  0 (no common  alleles),  0.5 
(one common allele)  or 1 (2 common  alleles).  The genomic  relationship  value between  2  individuals  is  
the sum  of loci similarity values.  The new brood stock was therefore  composed of nselmales  males  and 
nselfemales females with the highest GEBVs. 
 
 
 
Results and discussion 
 
Figure 1 a) shows the genetic level with natural mating, 40 animals selected and low heritability (0.2). After 10 
generations of selection, GBLUP method performs the best in term of genetic level, while we obtained the worst 
results with mass selection. Genetic level obtained using BLUP method falls in between  the one from GBLUP  
and the one from mass selection. The difference of genetic level between GBLUP and BLUP is more important 
in the long term (G6    to G11). Rate of inbreeding  (∆F) are very high in general  (up to 14%  increase  for 
one generation with BLUP). For the three methods of selection, inbreeding rate increases a lot between G2   
and G3 (first selection). On average over 10 generations, ∆F was 3.7%, 6.7% and 9.4 % for mass, GBLUP  and 
BLUP selection respectively.  Average of accuracy (rgg) of selection over 10 generations was 0.34, 0.43 and 
0.54 for 
mass, BLUP  and GBLUP  selection respectively. Therefore, GBLUP selection performs better with the highest 
accuracy, but inbreeding rate remains large compared to mass selection. Genetic level is similar for GBLUP,  
BLUP  and mass selection in the long term (Figure 1 b) with high heritability. Inbreeding rate decreases  as the 
heritability increases for BLUP and GBLUP  and remains the same for mass selection (∆F of 7.2%, 5% and 3.8% 
respectively). Accuracy increases as heritability increases for the three methods (rgg of 0.64, 0.69 and 0.77 for 
mass, BLUP  and GBLUP  respectively for h2  =0.8). 
 
Figure 1 c) represents genetic level of GBLUP selection respectively, between  a natural mating population with 
40 selected animals, a controlled mating population with 48 selected animals and a natural mating population 
with 100 animals selected. No major difference are observed between  genetic level when selecting 40 animals 
with natural mating and 48 animals with controlled mating are very similar, while genetic level obtained with 
100 animals selected using natural mating is not as high as the two other scenarios. In the specific conditions of 
this  simulation,  controlled  mating  is  not an advantage  over natural  mating.  rgg     is  similar  for the three  cases 
(between  0.52 and 0.54). ∆F is the highest when using natural mating with 40 selected animals (6.7%) and 
the lowest when using natural mating with 100 selected animals (3%). ∆F of the controlled mating schemes 
(4.7%) is  lower  than natural  mating  with 40 animals  selected,  due to the population  structure  and the slight  
higher number of selected animals. While the use of genomic relationship matrix provides more accurate 
information to select  the best animals,  it acts  as  well  as  a  natural  constrain  against  inbreeding,  when  
compared  to BLUP selection. Genomic relationship matrix based on markers is more accurate than genetic 
relationship matrix based on pedigree and become more accurate by increasing the number of markers 
(VanRaden,  P. (2007)). 
 
As the results showed, rate of inbreeding with GBLUP selection is very high (6.7% in scenario 1 with h2  of 0.2), 
which is similar to Sonesson, A. and Meuwissen, T. (2009). However, inbreeding rate using BLUP selection 
method without restriction  on inbreeding  was  larger  (9.4 %). The high rate  of inbreeding  observed  can be 
explained by several factors. Inbreeding was recorded and taking into account from the last 5 generations before 
base generation, therefore additional inbreeding was accounted prior selection. The second factor is the actual 
effect  of using variable family size in the population. Brood stocks were kept fairly small in our simulation, 
because in natural mating of mass-spawning, not all parents contribute to the offspring. This will not be the case 
for species, where reproduction can be controlled. The low number of candidates although can have an impact on 
inbreeding,  because  few  families  will  be represented  in the sample,  due to uneven  parental  
contributions. Finally, we did not apply any restriction on inbreeding to assess the actual increase of inbreeding 
using natural mating in mass-spawning. It confirms the reported high inbreeding rate after one generation of 3-
6% (Fesshaye, Y., El-Bialy, Z, Rezk, M. et al. (2006)). Those characteristics are specific from mass-spawning 
species, where natural mating is still used to produce the next generation. Our results show that, while the 
effect on gain of genetic  level  is  rather minor compare to breeding programs with control  over 
reproduction,  it is  essential  to restrain inbreeding and genetic gain of different breeding  schemes should be 
compared at equal inbreeding rate. 
 
We did not use  a training  data  set to perform GBLUP selection  method. With the low number of selection 
candidates  and the uneven family  size  using natural  mating,  it was  not possible  to have a  large  number  of 
families with a large number of offspring in each family. Therefore all animals were selection candidates and all 
animals were phenotyped. The uneven parental contribution to offspring is a limitation in genomic selection for 
natural mating mass-spawning species. Sonesson, A. and Meuwissen, T. (2009)  use 100 full-sib families of at 
least 60 individuals (30 as candidate  selection and 30 as test)  – i.e. controlled mating. However, with the sea 
bream reference population of 1257 individuals, only 3 families have the required amount of progeny.  A natural 
mating  population of roughly 40 000 individuals  will meet the criteria  of 100 full-sib families  of at  least 60 
offspring each, which is a very large sample size for parentage assignment. Although, genetic gain is similar in 
controlled  mating  and  natural  mating,  accuracy  of  selection  is  higher with  controlled  mating.  Effort  in 
controlling reproduction in mass-spawning species (undergoing in sea bass, Vandeputte,  M., Dupont-Nivet, M., 
Haffray, P., et al. (2009)) will increase the efficiency of genomic selection for those species. 
 
 
 
Conclusion 
 
We demonstrated that GBLUP is an efficient method of selection for natural mating mass-spawning species 
compared to BLUP and mass selection. However high inbreeding rate is a limitation and need to be constrained. 
 
References 
 
Antonello J., Massault C., Franch R. (2009) Aquaculture 298, 29-35 
 Falconer D.S., Mackay T.F.C (1996) Longman. New York. 464 
pp. Fessehaye Y., El-Bialy Z., Rezk M.A. Aquaculture 256, 148-
158 
Hayes B.J, Goddard M.E. (2008) J. Anim. Science 86, 2089–2092 
 
Meuwissen T.H.E., Hayes B.J., Goddard M.E. (2001) Genetics 157, 1819-1829 
 
Sonesson A.K., Meuwissen, T.H.E. (2000) Genet. Sel. Evol 32, 231-248 
 
Sonesson A.K., Meuwissen T.H.E (2009) Genet. Sel. Evol. 41, 37-46 
 
Vandeputte, M., Dupont-Nivet, M., Haffray, P., et al. (2009) Aquaculture 286, 20-27 
 
VanRaden, P. M. (2007) Interbull Bull  37, 33–36. 
 
 
Figure 1 - Comparison of genetic level: a) between  GBLUP, BLUP and mass with natural mating, h2 = 0.2 and 
40 selected animals, b) between three heritability (0.2, 0.5 and 0.8) of GBLUP with natural mating, 40 animals 
selected, c) between GBLUP with natural mating  (40 animals selecetd) , controlled mating (48 animals selected) 
and natural mating (100 animals selected) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 


Aquaculture 286,

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Comparison of selection methods for natural mating mass-spawning species

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