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如何培育一个健壮的猪种--加裕分享

作者:Pius B. Mwansa博士来源:家育种猪公司时间:2017-08-09 15:45点击:

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生猪育种的发展导致了生产性状的显著正基因变化,这是由于对生长速度和饲料效率等性状的直接选择性压力造成的。然而,这些在效率和生产力上的基因改良,却看到了随之而来的高生理需求的增加,而这可能对农场动物的生产寿命带来不利影响(Knap和Rauw,2009)。

Developments in pig breeding have led to considerable positive genetic changes in production traits due to direct selective pressure on traits such as growth rate and feed efficiency. These genetic improvements in efficiency and productivity, however, have seen attendant increases in high physiological demands, which may have unfavorable consequences on productive longevity of farm animals (Knap and Rauw, 2009).

如今,在商业生产中的猪被预计会适应遇到的各种各样的环境条件和挑战。Knap(2005)定义了农场动物的这种多样性,即“将高产量潜力与抗压能力结合在一起的能力,允许在各种环境条件下的高产潜力的无问题表达”。这种适应性的定义冗长但确实包含了组成要素。基因公司经常会关注他们的育种计划中的功能性状,尽管主要是考虑表型选择(例如健康、繁殖力、运动能力、乳头数量、体格的健全程度以及不同生命阶段的死亡率)。

Today, pigsare expected to perform in a variety of environmental conditions/challenges encountered in commercial operations.This versatility in farm animals was defined by Knap (2005) as ‘the ability to combine a high production potential with resilience to stressors, allowing for unproblematic expression of a high production potential in a wide variety of environmental conditions’. This definition of adaptability is verbose but does capture the component elements more inclusively. Genetic companies regularly pay some attention to functional traits in their breeding programs, albeit, mostlyin phenotypic selection consideration(for example health, fertility, locomotion, teat number, structural soundness, and mortality at various stages of life).

此外,育种计划期望对核心群体进行的基因改良,可以转化为在商业管理/环境条件下可实现的令人满意的改良。一个由环境交互作用的基因型(GxE)会出现其在核心群体水平的遗传进展不会引起在商业水平上有非常相似的进展水平。通过直接比较两种环境中给定性状的基因表达,可以衡量不同环境中相同性状的遗传表现的相似性,这通常被用来衡量遗传相关性。当遗传相关从1.0(两个环境中完美的关联)变动时,在每个环境中性状的遗传表达是不同的。下图1是Li和Hermesch(2013)文章中的一个图示,展示了两种不同环境下生长速率的遗传相关性随生长速度增加的平均变化而变化。平均日增重的差异在40g/天或以下的环境有非常相似的遗传相关性(> 0.90)。然而,平均日增重在两种环境中记录的差异在60克/天或以上时,更多结果显示遗传相关性较低,而且遗传相关值变化更大。因此,在这个例子中,当平均日增重的差异大于60g/天时,在两个环境中遗传对性状表达的影响是不同的,显然发生了基因x环境交互作用。因此,两个环境中的平均日增重在遗传评估系统中可以被认为是不同性状,以解释基因x环境相互作用效应。

Furthermore, breeding programs expect genetic improvements made in nucleus unitsto translate into desirableimprovement realized under commercial management/environment conditions.A genotype by environment (GxE) interaction occurs whengenetic improvement at the nucleus level does not result in a very similar level of improvement at the commercial level. Similarity in genetic performance of the same trait in different environments can be measured by directly comparing the genetic expression of a given trait in both environments, this is commonly measured as the genetic correlation. As the genetic correlation moves away from 1.0 (perfect association in both environments) then the genetic expression of the trait is different in each environment.   Figure 1 below is a graphical example from Li and Hermesch (2013), showing how the genetic correlation between growth rate in two different environments changed as the average difference in growth rate increased. Environments where the difference in average ADG was 40 grams/day or less had very similar genetic correlations (>0.90). However, asADGrecorded in two environments differedby 60 g/day or more resulted in lower genetic correlations and more variability in the genetic correlation values. Thus, in this example when the difference in average ADG was greater than 60g/day the genetic impact on expression of the trait was different in the two environments and clearly a GxE interaction occurred. Thus, the ADG in the two environments may be regarded as different traits in genetic evaluation systems in order to account for GxE interaction effect.

图1. 随着两个环境中平均生长速度的差异增加时,每个环境中定义生长速度的遗传相关系数都有所下降(Li and Hermesch 2013)。

Figure, 1. Genetic correlations for growth rate defined as a separate trait in each environment declined as the difference in mean growth rate between two environments increased

(Li and Hermesch 2013).

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育种的目的是在广泛的环境条件和管理系统中生产具有高水平性能的动物。毫无疑问,育种目标应该为商品猪生长环境(不是核心群)而定义,而最优选择指标(工具)应该考虑到可能存在于经济特性的基因x环境交互效应。实现这一目标的一个非常有效的方法是将商品猪数据和核心群数据一起纳入核心种猪的遗传评估。这种方法虽然在过去很难有效实施,但基因组工具的使用为这种方法的实施创造了新的机会。加裕公司最近发起了一项大型研究项目,通过将商品猪群体数据纳入其基因组评估系统,专注于利用基因组学来提高核心群体的选择。

Breeding objectives aim to produce animals with a high-level of performance in a wide range of environmental conditions and management systems. Undoubtedly, breeding objectives should be defined for commercial environments (not nucleus) and optimal selection indexes (tools) should account for GxE interactions that may exist for economic traits of interest. A very effective way to accomplish this is to incorporate commercial data along with nucleus data in the genetic evaluation of nucleus pigs.  While this approach has been difficult to implement effectively in the past, the use of genomic tools has created new opportunities in this approach. Genesus has recently initiated a large research project focused on the use of genomics to enhance nucleus level selection by incorporating commercial herd data into its genomic evaluation system.

选择拥有在不同环境中获得高水平生产力的内在能力的种猪,对于加裕公司来说,是一个高级目标,因为它是提高猪基因改良价值链中客户利润最大化的关键。

Selection of pigs with the inherent ability to achieve high level productivity in diverse environments is, for Genesus Inc.,a high-ranking objectivebecause it is a key to maximizing profitability for our customers in the pig genetic improvement value-chain.

参考文献

References

Knap PW .2005. 培育健壮的猪。澳大利亚实验农业杂志。45, 763–773.

Knap, P.W and W. M. Rauw .2009.选育高生产力的猪。在“资源分配理论应用于农场动物生产” (Ed. WM Rauw.) pp. 210-229. (CABI: Wallingford, UK)

Li, L, and S, Hermesch. 2013. 在澳大利亚猪身上利用多性状分析方法,对日增重进行环境相互作用的基因型分析。 Proc. Assoc. Advmt. Anim. Breed. Genet. 20, 323-326.

Knap PW .2005. Breeding robust pigs. Australian Journal of Experimental Agriculture 45, 763–773.

 

Knap, P.W and W. M. Rauw .2009. Selection for high production in pigs. In 'Resource allocation theory applied to farm animal production.' (Ed. WM Rauw.) pp. 210-229. (CABI: Wallingford, UK)

 

Li, L, and S, Hermesch. 2013. Genotype by environment interactions for average daily gain using multiple-trait analyses in Australian pigs. Proc. Assoc. Advmt. Anim. Breed. Genet. 20, 323-326.

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