Stock K F, Reents R
Vereinigte Informationssysteme Tierhaltung w.V. (vit), Verden, Germany.
Reprod Domest Anim. 2013 Sep;48 Suppl 1:2-10. doi: 10.1111/rda.12201.
Technical advances and development in the market for genomic tools have facilitated access to whole-genome data across species. Building-up on the acquired knowledge of the genome sequences, large-scale genotyping has been optimized for broad use, so genotype information can be routinely used to predict genetic merit. Genomic selection (GS) refers to the use of aggregates of estimated marker effects as predictors which allow improved individual differentiation at young age. Realizable benefits of GS are influenced by several factors and vary in quantity and quality between species. General characteristics and challenges of GS in implementation and routine application are described, followed by an overview over the current status of its use, prospects and challenges in important animal species. Genetic gain for a particular trait can be enhanced by shortening of the generation interval, increased selection accuracy and increased selection intensity, with species- and breed-specific relevance of the determinants. Reliable predictions based on genetic marker effects require assembly of a reference for linking of phenotype and genotype data to allow estimation and regular re-estimation. Experiences from dairy breeding have shown that international collaboration can set the course for fast and successful implementation of innovative selection tools, so genomics may significantly impact the structures of future breeding and breeding programmes. Traits of great and increasing importance, which were difficult to improve in the conventional systems, could be emphasized, if continuous availability of high-quality phenotype data can be assured. Equally elaborate strategies for genotyping and phenotyping will allow tailored approaches to balance efficient animal production, sustainability, animal health and welfare in future.
基因组工具市场的技术进步与发展促进了跨物种全基因组数据的获取。基于所获得的基因组序列知识,大规模基因分型已得到优化以供广泛使用,因此基因型信息可常规用于预测遗传价值。基因组选择(GS)是指使用估计的标记效应汇总作为预测指标,从而在幼年时就能更好地区分个体。GS的可实现效益受多种因素影响,不同物种在数量和质量上存在差异。本文描述了GS在实施和常规应用中的一般特征及挑战,随后概述了其在重要动物物种中的使用现状、前景和挑战。通过缩短世代间隔、提高选择准确性和增加选择强度,可以提高特定性状的遗传进展,这些因素因物种和品种而异。基于遗传标记效应的可靠预测需要建立一个参考,将表型和基因型数据联系起来,以便进行估计和定期重新估计。奶牛育种的经验表明,国际合作可为快速成功实施创新选择工具指明方向,因此基因组学可能会对未来育种和育种计划的结构产生重大影响。如果能够确保持续提供高质量的表型数据,就可以强调那些在传统系统中难以改良但重要性日益增加的性状。同样,精心制定的基因分型和表型分型策略将有助于在未来采用量身定制的方法,以平衡高效动物生产、可持续性、动物健康和福利。