全基因组选择模型研究进展及展望

全基因组选择是一种利用覆盖全基因组的高密度标记进行选择育种的新方法,可通过早期选择缩短世代间隔,提高育种值估计准确性等加快遗传进展,尤其对低遗传力、难测定的复杂性状具有较好的预测效果,真正实现了基因组技术指导育种实践。随着芯片和测序技术日趋成熟,高密度标记芯片检测成本不断降低,全基因组选择模型的不断升级和优化,预测准确性不断提高,全基因组选择已成为动物遗传改良的重要手段和研究热点。目前,全基因组选择已经成为奶牛遗传评估的标准方法,并取得重要进展,在其它物种中的应用正在逐步开展。本文主要对全基因组选择的统计模型发展进行综述,总结全基因组选择在动物遗传育种中的应用现状,讨论当前存在的问题,并对全基因组选择模型的发展方向和应用前景进行展望。     

Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain

We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔG(AG) ), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii) a positive interaction exists between the use of genotypic information and a short generation interval on ΔG(AG) and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔG(AG) if genotypic information about the breeding goal trait is known. We examined four breeding schemes with or without genomic selection and with or without intensive use of young bulls using pseudo-genomic stochastic simulations. The breeding goal consisted of a milk production trait and a functional trait. The two breeding schemes with genomic selection resulted in higher ΔG(AG) , greater contributions of the functional trait to ΔG(AG) and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information on ΔG(AG) . Hence, a breeding scheme with genomic selection and with intensive use of young bulls (a turbo scheme) seems to offer the greatest potential. The third hypothesis was disproved as inclusion of genomically enhanced breeding values (GEBV) for an indicator trait in the selection index increased ΔG(AG) in the turbo scheme. Moreover, it increased the contribution of the functional trait to ΔG(AG) , and it decreased ΔF. Thus, indicator traits may still be profitable to use even when GEBV for the breeding goal traits are available.     

基因组选择及其在羊育种中的应用研究进展

数量性状是羊育种中的重要性状,受微效多基因控制、遗传力低,而传统育种方法难以提高羊的育种效率。提高动物育种效率对于选种选配工作和经济生产效益至关重要。随着育种新技术的不断革新与发展,基因组选择(genomic selection, GS)方法已成为育种技术中强大的工具,且已成功运用于个体经济价值较大的物种中,其具有缩短世代间隔、提高育种准确性、减少生产成本、提高畜禽经济效益等优势。近年来,由于基因组技术的不断成熟和各个统计模型的升级优化,以及高密度SNP芯片价格的下调,报告有关于基因组选择育种的实证和模拟研究层出不穷,且基因组选择技术已在羊育种中逐步开展,特别是在羊的重要性状中已有不少报道。由于羊的品种较多,地方性状差异化较大,个体经济价值略低,尽管基因组育种的新技术已经非常成熟,但目前仍没有在羊育种中大范围普及。为了更全面地了解该技术在羊育种中的研究现状,且基于选种选配的重要地位,作者就基因组选择在羊育种中的研究进展展开综述,主要从表型测定、基因分型、不同模型方面介绍了基因组选择在羊的重要性状中的应用和现状,讨论了其优势与挑战,并展望了基因组选择的未来发展方向。     

Genomic selection strategies in dairy cattle breeding programmes: Sexed semen cannot replace multiple ovulation and embryo transfer as superior reproductive technology

The aim of this study was to test whether the use of X-semen in a dairy cattle population using genomic selection (GS) and multiple ovulation and embryo transfer (MOET) increases the selection intensity on cow dams and thereby the genetic gain in the entire population. Also, the dynamics of using different types of sexed semen (X, Y or conventional) in the nucleus were investigated. The stochastic simulation study partly supported the hypothesis as the genetic gain in the entire population was elevated when X-semen was used in the production population as GS exploited the higher selection intensity among heifers with great accuracy. However, when MOET was applied, the effect was considerably diminished as was the exchange of females between the nucleus and the production population, thus causing modest genetic profit from using X-sorted semen in the production population. In addition, the effect of using sexed semen on the genetic gain was very small compared with the effect of MOET and highly dependent on whether cow dams or bull dams were inseminated with sexed semen and on what type of semen that was used for the bull dams. The rate of inbreeding was seldom affected by the use of sexed semen. However, when all young bull candidates were born following MOET, the results showed that the use of Y-semen in the breeding nucleus tended to decrease the rate of inbreeding as it enabled GS to increase within-family selection. This implies that the benefit from using sexed semen in a modern dairy cattle breeding scheme applying both GS and MOET may be found in its beneficial effect on the rate of inbreeding.     

畜禽基因组选择方法研究进展

畜禽的选种选育在生产中至关重要,育种值估计是选种选育的核心。基因组选择（genomic selection,GS）是利用全基因组范围内的高密度标记估计个体基因组育种值的一种新型分子育种方法,目前已在牛、猪、鸡等畜禽育种中得到应用并取得了良好的效果。该方法可实现畜禽育种早期选择,降低测定费用,缩短世代间隔,提高育种值估计准确性,加快遗传进展。基因组选择主要是通过参考群体中每个个体的表型性状信息和单核苷酸多态性（single nucleotide polymorphism,SNP）基因型估计出每个SNP的效应值,然后测定候选群体中每个个体的SNP基因型,计算候选个体的基因组育种值,根据基因组育种值的高低对候选群体进行合理的选择。随着基因分型技术快速发展和检测成本不断降低,以及基因组选择方法不断优化,基因组选择已成为畜禽选种选育的重要手段。作者对一些常用的基因组选择方法进行了综述,比较了不同方法之间的差异,分析了基因组选择存在的问题与挑战,并展望了其在畜禽育种中的应用前景。     

Evaluation of the efficiency of alternative two-tier nucleus breeding systems designed to improve meat sheep in Kenya

A deterministic approach was used to genetically and economically evaluate the efficiency of five two‐tier nucleus breeding systems for meat sheep in Kenya. The nucleus breeding systems differed in terms of whether the system was closed or open, in the type of animals that were involved in the movement of genetic superiority and in the number of selection pathways in each system. These systems were compared under four alternative breeding objectives based on monetary genetic gain and profit per ewe. The first objective simulated a situation where the flock size cannot be increased due to non‐feed related constraints (FLOCK). The second specifically assumed that the flock size is restricted due to limited amount of feed resources (FEED). The third and fourth objectives assumed that sheep performed only tangible roles (TR) and both tangible and intangible roles (IR) in the production system respectively. Monetary genetic gains were highest for all objectives in an open nucleus system with a certain proportion of commercial‐born ewes being introduced in the nucleus while at the same time utilizing young rams from the nucleus to breed sires and dams for the nucleus and commercial sector (ONyre). Utilizing young rams in a closed nucleus system for the dissemination of superior genes resulted in higher annual monetary genetic gain than utilization of old rams. Profit per ewe was significantly higher for FLOCK and IR in ONyre. In a closed system that allowed for downward movement of dams from the nucleus to the commercial sector to breed sires and dams, profit per ewe was highest for FEED and TR. The success of a nucleus breeding system should also focus on the profitability and logistics of establishing it. The implication of these results on the choice of two‐tier nucleus breeding systems for the improvement of meat sheep is discussed.     

国外肉羊遗传育种研究进展

绵羊群体中存在大量的品种内和品种间的遗传变异。这种变异影响羔羊肉及羊肉生产的性状 ,并提供遗传改良肉质性状的潜力。本文综述活体性状的遗传变异 ,包括生产系统和育种目标 ;品种 /基因型评价 ;遗传参数和选择所致的遗传变化评分 ;信息和改良系统的组织等     

应用BLUP法评定肉羊育种值的试验研究

本研究根据BLUP原理,利用甘肃省皇城种羊场2000-2003年共4 610只绵羊的断乳重数据资料,筛选出在西北生态条件下,估测肉用种羊育种值的单性状动物模型y=Xb+ Za+Wm+Sl+e。利用此模型评定出61只种公羊的优劣次序,选定出品系繁育继承公羊。     

品系育种中细毛(半细毛)羊选择指数的研制和应用探讨

品系育种是迄今畜禽纯种选育与杂交利用系统中最为安全高效的途径,综合选择指数则是多性状选择改良的理想方法。该研究试将综合选择指数与绵羊品系育种相结合,提供了一种制作\"绵羊品系选择指数\"的方法示例,以便高效可控并有预见性地推进绵羊品系育种进程。     

大白猪基因组选择在不同应用策略下的比较研究

目前,基因组选择（genomic selection,GS）技术已经在种猪育种中开展,但为获得较高的收益,还需研究一些应用策略,如确定仔猪基因分型个体比例和早期仔猪留种比例。本试验选择温氏集团出生于2011—2016年的大白种猪作为研究对象,共有超过4.5万条的生长测定记录,超过7万条繁殖记录,和2 090个个体的简化基因组测序（GBS）数据,其中,出生于2016年7~12月的440个体作为候选群体。研究性状包括两个生长性状（校正100 kg日龄和校正100 kg背膘厚）和一个繁殖性状（总产仔数）。为对比预测效果,在候选群体进行育种值预测时,按照是否利用其基因型或表型信息分为4种预测方案,比较不同方案的预测可靠性和个体选择指数的排名情况。结果显示,在预测候选群育种值时,利用其表型或基因型信息均比不利用时的预测结果更加可靠。对生长性状终测前、后进行基因组选择指数计算,发现,终测后指数排名前30%的个体都位于终测前指数排名前60%内。若仔猪出生后仅选择常规BLUP预测指数排名前60%的个体,会导致有接近15%的具有优秀潜力的个体被遗漏。本研究建议,对所有新生健康仔猪都进行基因分型并计算基因组选择指数,然后对指数排名靠前60%的个体进行性能测定。     

基因组选择技术在羊育种中的应用研究

随着分子生物技术的发展,在2001年有一种新型动物育种方法——基因组选择出现,此项技术弥补了传统育种的不足,具有缩短世代间隔、降低育种成本等优势。羊养殖作为畜牧产业中的重要组成部分,育种困难是当前亟须解决的难题。因此,本文综述了基因组选择的原理、方法及基因分型的方法,同时总结了基因组选择技术在羊育种方面的应用以及该技术在应用中面临的挑战,以期为之后羊育种研究提供理论参考。     

基于元共祖的基因组联合育种模拟研究

旨在将整合元共祖的一步法(single-step genomic best linear unbiased prediction with metafounders,MF-SSGBLUP)应用到基因组联合育种中,并与其他经典基因组选择方法进行比较分析。本研究使用QMSim软件模拟3个系谱相互独立的奶牛群体;分别使用广义最小二乘法(generalized least squares,GLS)和原始方法(naïve,NAI)估计不同群体间的祖先关系矩阵Γ;将MF-SSGBLUP、SSGBLUP和BLUP用于3个模拟群体的联合育种,评估各方法在遗传参数和育种值估计方面的差异。在不同遗传力下,GLS所得的Γ矩阵在对角线元素上略低于NAI法,在非对角线元素上没有明显差异,且基因组关系矩阵与基于元共祖构建的亲缘关系矩阵对角线元素相关系数(0.750~0.775)高于基因组关系矩阵与传统的亲缘关系矩阵相关系数(0.508~0.572)。MF-SSGBLUP遗传力估计值(0.138、0.140、0.297和0.298)与当代群体遗传力(0.107和0.296)的偏差小于其余两种方法(0.145、0.173、0.273和0.340),且MF-SSGBLUP估计育种值准确性(0.888~0.908)高于SSGBLUP法(0.863~0.876)和BLUP法(0.854~0.871)。表明,MF-SSGBLUP的遗传参数估计值无偏性更好,估计育种值准确性更高。根据上述模拟数据结果表明,在联合育种中,整合元共祖的基因组选择方法优于其他经典基因组选择方法。