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males and 10000 females. In each generation, 10 bulls and 50 cows were chosen as parents of the male progeny, and 20 bulls and 10000 cows were chosen as parents |
of the female progeny (with no selection on the dam to dam path). Mating was random resulting in random variation of progeny size among parents, i.e. the sire and dam |
of a given newborn were randomly chosen in the corresponding lists of parents. Simulation of genetic values and EBV We considered two traits A and B. Trait A corresponded to |
a production trait which had been recently and intensively selected and improved (such as milk production in dairy cattle). Trait B corresponded to a functional trait which had deteriorated because |
of a negative correlation with trait A (e.g. fertility or longevity). The genetic standard deviation of each trait (σA and σB, respectively) was set to 1 and the correlation between |
traits (ρ) was set to -0.3. For each trait, an additive polygenic model was assumed and the simulation of correlated genetic values was based on the bivariate normal distribution (see, |
e.g. ). At generation 0 (base population), genetic values for trait A were randomly and independently drawn from a N (0, 1) distribution. For a given individual (i), the genetic |
value for trait B (Bi) was generated from its value for trait A (Ai): where βi is a N (0, 1) random number independent of Ai. In the following generations, |
genetic values of individual i were simulated from the genetic values of its sire (Ap and Bp) and its dam (Am and Bm), taking into account the parent's coefficients of |
inbreeding (Fp and Fm, resp.) [12,13]: In these equations, γi and δi are two numbers randomly drawn from a N (0, 1) bivariate normal distribution with a correlation equal to |
ρ. EBV were directly simulated from genetic values, assuming an evaluation procedure leading to an accuracy (CD = square of the correlation between the EBV and the true genetic value) |
equal to 0.6 for bulls and 0.4 for cows, whatever the trait and the generation considered. Therefore, the EBV of a given individual for trait A (EBVAi) and for trait |
B (EBVBi) were computed as follows: where εi and ϕi are two independent numbers drawn from a N(0, 1) distribution. Finally, a Total Merit Index (TMIi) was computed, weighting the |
two EBV by wA and wB = 1 - wA, respectively: Sampling and use of cryopreserved semen Simulations comprised two stages. During stage 1 (generations 0 to 8), the lists |
of parents were selected based on their EBV for trait A only, without considering the evolution of the genetic mean for trait B or the average coefficient of inbreeding. During |
stage 2 (generations 9 to 12), the bulls were also used to improve trait B or to introduce genetic diversity in the breed. During stage 1, the semen of some |
bulls was sampled and cryopreserved if the animals fulfilled one of the three following conditions, which correspond to the current sampling rules of the French National Cryobank for type "II" |
(original bulls) : - (i) EBVA is three standard deviations above or below the mean of the generation, - (ii) EBVB is two standard deviations above the mean of the |
generation (trait B is considered as a functional trait and for functional traits, only animals above the average are considered), - (iii) the bull is a sire of sires with |
no male offspring selected after the evaluation process (these bulls were actually selected with one generation lag). To check the validity of this elaborate sampling method, we tested a simpler |
sampling method (similar to the one used in the Netherlands), where the semen of all young bulls is stored in the cryobank. In the simulations performed here, we investigated the |
impact of a one-time use (i.e. during a single generation) of cryopreserved semen. At generation 9, four bulls with cryopreserved semen were selected (hereafter referred to as 'cryobank bulls'), these |
bulls fulfilling one of the following conditions either (i) they are the best cryobank bulls for the TMIi or (ii) they have the lowest average kinship with the existing population |
(males and females taken together). We studied the impact of various selection orientations (use of cryopreserved semen, conservation of male lines, etc.) only on the male path, because applying the |
above conditions on the female path would be much more restrictive, less effective, and would require a larger amount of semen, all the more since the number of doses is |
generally limited in cryobanks (200, in France) . For these reasons, we considered that cryobank bulls were used only to procreate young bulls for progeny testing. The 9th generation of |
young bulls was then generated using either the bulls from the cryobank or the group of 10 sires selected as described in previous sections. Depending on the scenario (see following |
section), 0, 40 or 80 individuals (among the 100 newborn bull calves) were sired randomly by one of the four selected cryobank bulls. Simulation scenarios and results Six simulation scenarios |
were completed with two main options (Table 1). Table 1. Description of simulation scenarios Firstly, in scenario "b", emphasis was put on the selection of both traits B and A. |
To achieve this goal, three methods were compared: - b1: at generation 9, the four bulls with the highest TMI (wB = 0.5) were used to sire 40% of the |
young bulls, while the selection criterion during stage 2 remained unchanged (improving EBVA). The other young bulls were sired by bulls randomly sampled within the group of 10 sires; - |
b2: at generation 9, no cryobank bull was used, and during stage 2, TMI (wB = 0.5) was used as the selection criterion instead of EBVA; - b3: at generation |
9, the four cryobank bulls with the highest TMI were used to sire 40% of the young bulls, and during stage 2, TMI was used as the selection criterion instead |
of EBVA. To test more or less drastic selection changes, scenario b3 was tested with an increasing weight given to trait B (wB increasing from 0.5 to 1). Secondly, in |
scenarios "d", emphasis was put on genetic variability while trait A remained the breeding goal. Three methods were also compared: - d1: at generation 9, the four cryobank bulls having |
the lowest kinship with the existing population (scenario b1) were used to sire 40% of the young bulls; - d2: at generation 9, no cryobank bull was used, while during |
stage 2, the progenies on the sire to sire path were given the same size i.e. for each sire of sires, 10 male offspring were created among which those with |
the two best EBVA became the sires of dams and that with the best EBVA became a sire of sires; - d3: at generation 9, the four cryobank bulls having |
the lowest kinship with the existing population (scenario b1) were used to sire 40% of the young bulls, while during stage 2, selection was used to equalise progeny sizes on |
the sire to sire path. Simulations were performed with 1000 runs for each scenario. For each generation, individual inbreeding coefficients and genetic values were computed and averaged for the entire |
male and female populations. The individual coefficients of kinship were also computed and averaged over males only and over the entire populations. The proportion of genes originating from cryobank bulls |
was computed on the basis of the gene dropping procedure (one locus averaged over the 1000 runs). Stage 1: evolution of selected traits, diversity loss, and sampling of cryobank bulls |
As expected, the results of the different scenarios did not differ significantly for generations 0 to 8 given that in stage 1, the conditions were the same whatever the option |
chosen, (here we present results averaged over the 1000 runs of one scenario only). With the parameters chosen for the simulation, each sire of sires had on average 10 male |
offspring (across sires standard deviation s.d. = 2.9) and each sire of dams had on average 500 female offspring (across sires s.d. = 21.6). As expected (see Figure 1), selection |
on trait A during stage 1 led to a major increase in the mean of this trait (+ 6.7 initial genetic standard deviation) from generation 0 to 8, while at |
the same time, the mean of B decreased to a lesser extent (-2 initial genetic standard deviation). The average coefficient of inbreeding increased simultaneously. Young bulls were slightly more inbred |
than cows, as they originated from a smaller number of sires and dams. In parallel (generation 0 to 8), the average coefficient of kinship among the young bulls and among |
the entire population increased to 8.1% and 6.9%, respectively. Figure 1. Changes in genetic values (a) and in genetic diversity (b) (scenario b1). Dotted lines: young bulls; solid lines: whole |
population; red: trait A, blue: trait B; green: average between A and B; purple: inbreeding F; pink: kinship Φ. An average of 31 cryobank bulls was sampled per replicate, 58% |
being sampled because of outstanding EBVB (see Table 2). Table 2 shows that cryobank bulls chosen for their genetic diversity were generally born earlier than others, which can be explained |
by the fact that they were chosen with one generation lag compared to other sampling procedures. Table 2. Average number and birth generation of bulls selected for conservation Stage 2 |
in scenarios b: change in breeding goals As shown in Figure 1, introducing cryobank bulls with exceptional TMI without changing the selection criterion during stage 2 (scenario b1) had a |
temporary impact on traits A and B as well as on the diversity indicators of the young bulls. At the whole population level, the impact was negligible, since young bulls |
sired by cryobank bulls were rarely subsequently selected as sires: three generations after introduction (generation 12), the cryobank contribution to genetic diversity was less than 3% (Table 3). Table 3. |
Origin and impact of cryobank bulls used in the different scenarios When TMI was used as a selection criterion (considering wB = 0.5), without using cryobank bulls (scenario b2), there |
was a per generation increase in the mean of trait B from generation 9 on (b1: -0.3 vs b2: +0.4), while the genetic gain for trait A decreased (b1: +1.0 |
vs b2: +0.4, see additional file 1). The change in breeding goals had no impact on diversity indicators. Additional file 1. Changes in genetic values (a) and in genetic diversity |
(b) (scenario b2). The data represent the simulation results for scenario b2. Dotted lines: young bulls; solid lines: whole population; red: trait A; blue: trait B; green: average between A |
and B; purple: inbreeding F; pink: kinship Φ. Format: PDF Size: 58KB Download file This file can be viewed with: Adobe Acrobat Reader Combining the use of cryobank bulls and |
TMI as a selection criterion (scenario b3 for wB = 0.5) resulted in a slight but significant (P < 0.001) reduction in average kinship (-0.3% between scenario b2 and b3, |
with 40% of the males from generation 9 sired by cryobank bulls, see additional file 2). Concerning the selected traits, the genetic gain for trait A decreased slightly when cryobank |
bulls were used (-0.12 between scenarios b2 and b3, P < 0.001), while the genetic gain for trait B increased slightly (+0.06 between scenarios b2 and b3, P = 0.02). |
These tendencies increased slightly when 80% of the males from generation 9 were sired by cryobank bulls (see additional file 2). According to the results from Table 3, cryobank bulls |
contributed to 6.5% of the diversity three generations after their introduction. It should be noted that the cryobank bulls used were generally sampled in recent generations, their average birth generation |
being 6.6 (Table 3). Additional file 2. Changes in genetic values (a) and in average kinship (b) when trait B was added to selection goals. The data represent the simulation |
results when selection is redirected with a new trait accounting for 50% of the total merit index and when the use of semen from cryobank bulls is increased. Scenario b3 |
and whole population are considered with the weight wB given to trait B accounting for 50% of the total merit index and an increased use of the semen from cryobank |
bulls. Brown: no cryobank bull is used (scenario b2); red: cryobank bulls are used to produce 40% of sons (scenario b3); yellow: cryobank bulls are used to produce 80% of |
sons; o: genetic value for trait A; ♦: genetic value for trait B; dotted line: average genetic value between A and B; x: kinship Φ. Format: PDF Size: 57KB Download |
file This file can be viewed with: Adobe Acrobat Reader As a result of the increased weight of trait B within TMI (see Figure 2), there was a per generation |
increase in genetic gain for trait B, while there was a slightly lower increase or even a decrease in genetic gain for trait A, as well as in average kinship, |
when trait B accounted for more than 80% of EBV. When only trait B was taken into account for TMI, the genetic value of traits A and B reached 4.7 |
and 1.37, respectively at generation 12 (versus 8.4 and -0.41 respectively when wB = 0.5), while average kinship reached 8.9% at generation 12 (versus 11.9% when wB = 0.5). Figure |
2. Changes in genetic values (a) and in average kinship (b), when trait B was added to selection goals. Scenario b3 and whole population are considered with the weight wB |
of trait B increasing for computation of the total merit index. Black: wB = 0 (scenario b1); brown: wB = 0.5; red: wB = 0.6; orange: wB = 0.7; green: |
wB = 0.8; light blue: wB = 0.9; dark blue: wB = 1; o: genetic value for trait A; ♦: genetic value for trait B; x: kinship Φ. Stage 2 |
in scenarios d: improvement in genetic diversity As shown in Figure 3, the use of cryobank bulls with a minimised kinship with the current generation (scenario d1), had no impact |
if the selection policy was not modified, since none of the offspring of the cryobank bulls were selected as sires. Equalising progeny sizes on the sire to sire path alone |
(scenario d2) decreased diversity a little less (in generation 12, Φ = 12% for scenario d1 and Φ = 11% for scenario d2), with an almost negligible impact on genetic |
progress. Combining this option with the introgression of cryobank bulls (scenario d3) resulted in a significant reduction in average kinship (-2% in comparison to d1). Under such a scenario, the |
genetic mean of trait B also increased slightly (+0.3 between scenario d1 and d3, P < 0.001), while that of trait A and the average of both traits decreased slightly |
(-0.08 and -0.02 respectively, between scenarios d1 and d3, P < 0.001). It should be noted that most of the cryobank bulls used originated from the founder population, their average |
birth generation being 0.3 (Table 3). Figure 3. Changes in genetic values (a) and in average kinship (b), when the aim was to manage genetic diversity. The whole population is |
considered Brown: no change in selection; cryobank bulls used to produce 40% of male offspring (scenario d1); red: conservation of male lines (scenario d2) (curve overlapping the preceding one); yellow: |
conservation of male lines and cryobank bulls used to produce 40% of male offspring (scenario d3); o: genetic value for trait A; ♦: genetic value for trait B; dotted line: |
average genetic value between A and B; x: kinship Φ. Modifying which bulls entered the cryobank by preserving semen for all the young bulls did not significantly alter the results |
of scenarios b3 and d3, either for the selected traits or for kinship evolution (data not shown). It should be noted that in this case, the average birth generation of |
the cryobank bulls used was 7, in scenario b3 (instead of 6.6, in the first cryobank sampling method), and 0, in scenario d3 (instead of 0.3, in the first cryobank |
sampling method). In this study, we assessed the impacts of using cryopreserved bull semen either to redirect selection or to improve the genetic variability of a selected cattle breed. Simulation |
parameters were chosen as a compromise between realism in the scenarios, their applicability, and the simplicity of the model. For instance, with respect to the choice of population size, a |
breed with 20 breeding males and 10000 potential dams could be considered quite small, especially with reference to the FAO endangerment status . In our simulation, sires and dams were |
randomly chosen from lists of reproducers. This differs significantly from what occurs in real breeds, in which an unbalanced use of reproducers is frequently the case, leading to a reduced |
size of the effective population. In terms of effective size, our breed would correspond to a much larger population with a similar inbreeding rate per generation (1.07%) to that found |
in real dairy cattle breeds e.g. . Concerning sampling conditions in the simulations, as mentioned above, the procedure chosen to select bulls for cryopreservation is similar to that currently applied |
in France. This choice was made to test if bulls selected this way could be effectively used in a selected breed. Compared to the case in which all young bulls |
are sampled for cryopreservation (which corresponds more or less to the current procedure in the Netherlands), the results were basically the same. This shows that the French sampling procedure is |
reasonably efficient to select useful bulls, and could be applied in situations when only a limited number of semen samples can be stored in a cryobank (for financial reasons, for |
instance). One of the main conclusions of this study is that using cryopreserved semen is relevant for a breed for which major changes in selection objectives or practices are considered. |
Since genetic progress is rapid in dairy cattle breeds (e.g. ), a bull for which semen has been stored for a few generations, is likely to have a lower genetic |
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