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全基因组选择(Genomic selection,GS),即全基因组范围内的标记辅助选择(marker-assisted selection,MAS)。因其具有可缩短世代间隔,提高年遗传进展;早期选择准确率高;同时还能提高低遗传力、难以测量性状选择效率等诸多优点,目前已成为动物遗传育种领域的研究热点。文内围绕"什么是GS"、"为什么选用GS"以及"影响GS的因素"这3个方面全方位诠释了GS。重点阐述了GS在猪育种中的应用现状,并结合GS在奶牛上的成功应用,简述了GS在猪育种上的展望。 相似文献
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畜禽基因组选择的研究进展 总被引：2，自引：0，他引：2
基因组选择（genomic selection,GS）是继标记辅助选择（marker-assisted selection,MAS）之后发展起来的新一代畜禽遗传评估的新方法。近年来,不少学者从各方面对GS在畜禽育种中的运用进行了研究,结果发现,与其他方法相比,GS优势明显,是当前畜禽遗传育种领域的研究热点。作者系统地阐述了GS估计染色体片段效应的方法及其准确性比较,详细介绍了影响GS准确性的因素、GS的经济效益,以及世界各国学者研究GS在实际育种中的应用情况,最后简述了中国畜禽育种开展GS策略所面临的挑战及其展望。 相似文献
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基因组选择(genomic setection,GS)是继标记辅助选择(marker-assisted selection,MAS)之后发展起来的新一代畜禽遗传评估的新方法.近年来,不少学者从各方面对GS在畜禽育种中的运用进行了研究,结果发现,与其他方法相比,GS优势明显,是当前畜禽遗传育种领域的研究热点.作者系统地阐述了GS估计染色体片段效应的方法及其准确性比较,详细介绍了影响GS准确性的因素、GS的经济效益,以及世界各国学者研究GS在实际育种中的应用情况,最后简述了中国畜禽育种开展GS策略所面临的挑战及其展望. 相似文献
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基于表型信息和谱系信息估计基因加性效应值的种畜遗传评定方法在家畜遗传改良中发挥了很大作用,但因其无法真正了解控制经济性状的遗传本质,影响了家畜遗传改良的进一步进展。分子标记辅助选择可在一定程度上提高种畜遗传评定准确性,但在目前不能精确定位QTL或基因时,其效率受到很大影响。提高种畜遗传评定准确性的最有效途径应是直接利用控制经济性状的基因,后基因组时代的功能基因组研究的快速发展为实现这一目标提供了契机。同时,多个家畜品种基因组测序完成和大量SNP多态性的发现,使得利用覆盖全基因组多态性标记信息的基因组选择方法为家畜遗传评定开拓了又一条途径。 相似文献
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《中国畜牧杂志》2017,(11)
基因组选择(Genomic Selection,GS)技术是利用覆盖全基因组与性状相连锁的标记信息,通过标记效应的求解和加和,得到个体基因组估计育种值(GEBV),从而达到对畜禽个体进行准确选择的目的。该技术率先在奶牛育种中得到广泛应用。在猪育种中,以杜洛克猪为代表,基因组选择技术的应用可以达到早期选择和提高选择准确性的效果,然而对于母系猪(以繁殖性状选择为主),并没有经济有效的利用方案。本文首先对基因组选择应用过程中关键问题进行讨论;其次简要介绍了基因组选择技术在父系猪中的应用情况;最后围绕我国母系猪育种的现状,探讨基因组选择技术在母系猪中如何应用。 相似文献
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整合生物学先验信息的全基因组选择方法及其在家畜育种中的应用进展 总被引：2，自引：2，他引：0
相较于传统的育种方法,全基因组选择（genomic selection,GS）通过对拟留种的个体进行早期选择和增加选择的准确性进而加快育种的遗传进展。通过改进GS方法无法再缩短育种的世代间隔,因而如何提高GS的准确性以获得额外的遗传进展一直是GS研究的核心问题。当前,各种组学技术不断成熟,从公开的资料或前期的研究积累获取生物学先验信息已比较容易。因而,如何在GS模型中整合已知的先验信息进而提高GS的准确性以获得额外的遗传进展成为当前育种研究的热点问题。本文对生物学先验信息的类型以及整合先验信息的GS方法进行综述,探讨了这些方法在家畜育种中的应用和前景,以期为家畜育种中开展整合生物学先验信息的GS研究提供借鉴与参考。 相似文献
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《上海畜牧兽医通讯》2019,(6)
利用全基因组的遗传标记是家畜遗传育种领域的新趋势,文章阐述了全基因组遗传标记在国内外绵羊品种中的研究进展,重点对我国地方品种滩羊重要经济性状的遗传标记研究取得的进展进行了详细介绍,并讨论了全基因组遗传标记的应用前景及研究方法。 相似文献
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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。 相似文献
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Selection and breeding are very important in production of livestock and poultry,and breeding value estimation is the core of selection and breeding.Genomic selection (GS) is a novel molecular breeding method to estimate genomic breeding value using high-density markers across the whole genome.At present,GS has been successfully applied in cattle,pig,chicken and so on,and made significant progress.This method can achieve early selection,decrease the testing costs,shorten generation interval,improve the accuracy of breeding value estimation and accelerate genomic progress.GS estimates the effect of SNP by phenotype information and SNP genotype of each individual in the reference population,and measures the SNP genotype to calculate the genomic estimated breeding value in the candidate population,then selects the best individuals according to the genomic estimated breeding value.With the rapid development of genotyping technology and the decrease of detection cost,and the continuous optimization and high efficiency of genomic selection methods,genomic selection has become an important research method in the selection and breeding of livestock and poultry.The authors reviewed some of the widely used genomic selection methods,compared the differences between different methods,analyzed the problems and challenges of genomic selection,and looked forward to its application prospects in breeding. 相似文献
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为了满足人们对畜产品需求的快速增长，必须在加快畜禽产业发展的同时把对环境的影响降到最低，提高畜禽遗传特性有望促进这一问题的解决。进入21世纪以来，以基因组选择为核心的分子育种技术迎来了发展机遇，利用该技术可实现早期准确选择，从而大幅度缩短世代间隔，加快群体遗传进展，并显著降低育种成本。虽然在某些畜种中（如奶牛），基因组选择取得了成功，群体也获得较大遗传进展，但仍无法满足快速增长的需求。因此，亟需寻找能够进一步加快遗传进展的方法。研究表明，在SNP标记数据中加入目标性状的已知功能基因信息，可以提高基因组育种值预测的准确性，进而加快遗传进展。而挖掘更多基因组信息的同时，开发更优化的分析方法可以更有助于目标的实现。文章总结了主要畜禽物种的可用基因组数据，包括牛、绵羊、山羊、猪和鸡以及这些数据是如何有助于鉴定影响重要性状的遗传标记和基因，从而进一步提高基因组选择的准确性。 相似文献
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E.C. Akanno F.S. Schenkel M. Sargolzaei R.M. Friendship J.A.B. Robinson 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2014,131(5):367-378
Genetic improvement of pigs in tropical developing countries has focused on imported exotic populations which have been subjected to intensive selection with attendant high population‐wide linkage disequilibrium (LD). Presently, indigenous pig population with limited selection and low LD are being considered for improvement. Given that the infrastructure for genetic improvement using the conventional BLUP selection methods are lacking, a genome‐wide selection (GS) program was proposed for developing countries. A simulation study was conducted to evaluate the option of using 60 K SNP panel and observed amount of LD in the exotic and indigenous pig populations. Several scenarios were evaluated including different size and structure of training and validation populations, different selection methods and long‐term accuracy of GS in different population/breeding structures and traits. The training set included previously selected exotic population, unselected indigenous population and their crossbreds. Traits studied included number born alive (NBA), average daily gain (ADG) and back fat thickness (BFT). The ridge regression method was used to train the prediction model. The results showed that accuracies of genomic breeding values (GBVs) in the range of 0.30 (NBA) to 0.86 (BFT) in the validation population are expected if high density marker panels are utilized. The GS method improved accuracy of breeding values better than pedigree‐based approach for traits with low heritability and in young animals with no performance data. Crossbred training population performed better than purebreds when validation was in populations with similar or a different structure as in the training set. Genome‐wide selection holds promise for genetic improvement of pigs in the tropics. 相似文献
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The economic traits of livestock has been significantly improved due to long-term under natural and artificial selection,and the specific variation characterizations emerged from the selected genome regions.As time goes on,the some polymorphism frequency of gene has dropped or disappeared,and keep in a group contains a single haploid type of multiple genes.This frequency variation of gene in specific region on the genomes is called the signatures of selection.Identifying signatures of selection can provide a straightforward insight into the mechaism of domestication and further uncover the casual genes related to the phenotypic variation.The high density SNP chips and large scale resequencing technology have been successfully applied to genomic selection signature in livestock breeds.The methods to detect selection signatures can be classed into three categories:Site frequency spectrum based methods,haplotyped based methods and population differentiation based methods.In the present article,we summarized the methods of selection signature detection and development and application of genomic selection signature methods in livestock.It will provide useful information for researchers working with breeding and evolutionary biology. 相似文献
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长期的自然和人为选择使家畜品种经济性状得到了显著改善,其相关的基因组区域也发生了特定遗传变异。随着时间的推移部分基因多态性已经下降或消失,而在群体中保留包含单一单倍型的多个基因。这种基因组上特定区域基因多态性频率的变异被称为选择信号。识别选择信号可以提供家畜驯化机制并进一步揭示表型相关的基因变异。目前,高密度SNP芯片及大规模重测序技术已成功应用于家畜选择信号鉴定研究。全基因组选择信号检测方法有等位基因频率检测法、连锁不平衡检测法和群体分化分析法。作者综述了全基因组范围内选择信号检测方法及其在家畜研究中的应用进展,为从事家畜育种及生物进化研究人员提供参考。 相似文献
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Prediction of response to marker-assisted and genomic selection using selection index theory 总被引：1，自引：0，他引：1
J. C. M. Dekkers 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2007,124(6):331-341
Selection index methods can be used for deterministic assessment of the potential benefit of including marker information in genetic improvement programmes using marker-assisted selection (MAS). By specifying estimates of breeding values derived from marker information (M-EBV) as a correlated trait with heritability equal to 1, it was demonstrated that marker information can be incorporated in standard software for selection index predictions of response and rates of inbreeding, which requires specifying phenotypic traits and their genetic parameters. Path coefficient methods were used to derive genetic and phenotypic correlations between M-EBV and the phenotypic data. Methods were extended to multi-trait selection and to the case when M-EBV are based on high-density marker genotype data, as in genomic selection. Methods were applied to several example scenarios, which confirmed previous results that MAS substantially increases response to selection but also demonstrated that MAS can result in substantial reductions in the rates of inbreeding. Although further validation by stochastic simulation is required, the developed methodology provides an easy means of deterministically evaluating the potential benefits of MAS and to optimize selection strategies with availability of marker data. 相似文献
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Tom Granleese Samuel A. Clark Julius H. J. van der Werf 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2019,136(2):91-101
Benefits of genomic selection (GS) in livestock breeding operations are well known particularly where traits are sex‐limited, hard to measure, have a low heritability and/or measured later in life. Sheep and beef breeders have a higher cost:benefit ratio for GS compared to dairy. Therefore, strategies for genotyping selection candidates should be explored to maximize the economic benefit of GS. The aim of the paper was to investigate, via simulation, the additional genetic gain achieved by selecting proportions of male selection candidates to be genotyped via truncation selection. A two‐trait selection index was used that contained an easy and early‐in‐life measurement (such as post‐weaning weight) as well as a hard‐to‐measure trait (such as intra‐muscular fat). We also evaluated the optimal proportion of female selection candidates to be genotyped in breeding programmes using natural mating and/or artificial insemination (NatAI), multiple ovulation and embryo transfer (MOET) or juvenile in vitro fertilization and embryo transfer (JIVET). The final aim of the project was to investigate the total dollars spent to increase the genetic merit by one genetic standard deviation (SD) using GS and/or reproductive technologies. For NatAI and MOET breeding programmes, females were selected to have progeny by 2 years of age, while 1‐month‐old females were required for JIVET. Genomic testing the top 20% of male selection candidates achieved 80% of the maximum benefit from GS when selection of male candidates prior to genomic testing had an accuracy of 0.36, while 54% needed to be tested to get the same benefit when the prior selection accuracy was 0.11. To achieve 80% of the maximum benefit in female, selection required 66%, 47% and 56% of female selection candidates to be genotyped in NatAI, MOET and JIVET breeding programmes, respectively. While JIVET and MOET breeding programmes achieved the highest annual genetic gain, genotyping male selection candidates provides the most economical way to increase rates of genetic gain facilitated by genomic testing. 相似文献