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Symposium review: Breeding a better cow-Will she be adaptable?

机译:专题讨论会回顾:繁殖出更好的母牛-她会适应吗?

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ABSTRACTAdaption is a process that makes an individual or population more suited to their environment. Long-term adaptation is predicated on ample usable genetic variation. Evolutionary forces influencing the extent and dynamics of genetic variation in a population include random drift, mutation, recombination, selection, and migration; the relative importance of each differs by population (i.e., drift is likely to be more influential in smaller populations) and number of generations exposed to selection (i.e., mutation is expected to contribute substantially to genetic variability following many generations of selection). The infinitesimal model, which underpins most genetic and genomic evaluations, assumes that each quantitative trait is controlled by an infinitely large number of unlinked and non-epistatic loci, each with an infinitely small effect. Under the infinitesimal model, selection is not expected to noticeably alter the allele frequencies, despite a potential substantial change in the population mean; the exception is in the first few generations of selection when genetic variance is expected to decline, after which it stabilizes. Despite the common use of the heritability statistic in quantitative genetics as a descriptor of adaption or response to selection, it is arguably the coefficient of genetic variation that is more informative to gauge adaptation potential and should, therefore, always be cited in such studies; for example, the heritability of fertility traits in dairy cows is generally low, yet the coefficient of genetic variation for most traits is comparable to many other performance traits, thus supporting the observed rapid genetic gain in fertility performance in dairy populations. Empirical evidence from long-term selection studies, across a range of animal and plant species, fails to support the premise that selection will deplete genetic variability. Even after 100 yr (synonymous with 100 generations) of selection in corn for high protein or oil content, there appears to be no obvious plateauing in the response to selection. Although populations in several selection experiments did reach a selection limit after multiple generations of directional selection, this does not equate to an exhaustion of genetic variance; such a declaration is supported by the observed rapid responses to reverse selection once implemented in long-term selection studies. New technologies such as genome-wide enabled selection and genome editing, as well as having the potential to accelerate genetic gain, could also increase the genetic variation, or at least reduce the erosion of genetic variance over time. In conclusion, there is no evidence, either theoretical or empirical, to indicate that dairy cow breeding programs will be unable to adapt to evolving challenges and opportunities, at least not because of an absence of ample genetic variability.
机译:ABSTRACTAdaption是使个人或人群更适应其环境的过程。长期适应取决于充足的可用遗传变异。影响种群遗传变异程度和动力学的进化力包括随机漂移,突变,重组,选择和迁移。每种方法的相对重要性因人群而异(即,漂移可能在较小的人群中更具影响力)以及暴露于选择的世代数(即,预期突变会导致许多代选择后的遗传变异)。支持大多数遗传和基因组评估的无穷小模型假设,每个定量性状都由无数个无关联和非上位性基因座控制,每个基因座的作用都无限小。在无穷小模型下,尽管总体均值可能发生实质性变化,但选择不会显着改变等位基因频率。唯一的例外是在选择的前几代中,遗传变异有望下降,然后稳定下来。尽管在定量遗传学中普遍使用遗传力统计作为对选择的适应性或反应的描述,但可以说遗传变异系数更有助于衡量适应性潜力,因此,在此类研究中应始终引用它;例如,奶牛育性性状的遗传性通常较低,但是大多数性状的遗传变异系数可与许多其他性能性状媲美,从而支持观察到的奶牛育性性能的快速遗传增益。长期选择研究涉及许多动植物物种的经验证据未能支持选择会耗尽遗传变异性的前提。即使在玉米中因蛋白质或油含量高而选择了100年(相当于100代)后,对选择的反应似乎也没有明显的平稳期。尽管在多次选择实验中的种群在经过多代定向选择后的确达到了选择极限,但这并不等于用尽了遗传变异。一旦在长期选择研究中实施,观察到的对逆向选择的快速反应便支持了这种声明。诸如全基因组选择和基因组编辑等新技术,以及具有加速遗传增益的潜力,也可以增加遗传变异,或至少减少随着时间的推移遗传变异的侵蚀。总之,无论是理论上还是经验上都没有证据表明,奶牛育种计划将无法适应不断变化的挑战和机遇,至少由于缺乏足够的遗传变异性,这是不可行的。

著录项

  • 来源
    《Journal of dairy science》 |2018年第4期|3665-3685|共21页
  • 作者

    D.P. Berry;

  • 作者单位

    Teagasc, Animal & Grassland Research and Innovation Centre, Moorepark, Fermoy, Co;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    evolution; dairy; genetic; selection; genomic;

    机译:进化;乳制品;遗传;选择;基因组;
  • 入库时间 2022-08-17 23:22:37

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