Literature DB >> 29224864

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

D P Berry1.   

Abstract

Adaption 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.
Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  dairy; evolution; genetic; genomic; selection

Mesh:

Year:  2017        PMID: 29224864     DOI: 10.3168/jds.2017-13309

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  7 in total

1.  Using the difference in actual and expected calf liveweight relative to its dam liveweight as a statistic for interherd and intraherd benchmarking and genetic evaluations1.

Authors:  Noirin McHugh; Ross D Evans; Donagh P Berry
Journal:  J Anim Sci       Date:  2019-12-17       Impact factor: 3.159

2.  Array CGH-based detection of CNV regions and their potential association with reproduction and other economic traits in Holsteins.

Authors:  Mei Liu; Lingzhao Fang; Shuli Liu; Michael G Pan; Eyal Seroussi; John B Cole; Li Ma; Hong Chen; George E Liu
Journal:  BMC Genomics       Date:  2019-03-07       Impact factor: 3.969

3.  Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle.

Authors:  Janez Jenko; Matthew C McClure; Daragh Matthews; Jennifer McClure; Martin Johnsson; Gregor Gorjanc; John M Hickey
Journal:  Genet Sel Evol       Date:  2019-03-05       Impact factor: 4.297

4.  Assessment the effect of genomic selection and detection of selective signature in broilers.

Authors:  Xiaodong Tan; Ranran Liu; Wei Li; Maiqing Zheng; Dan Zhu; Dawei Liu; Furong Feng; Qinghe Li; Li Liu; Jie Wen; Guiping Zhao
Journal:  Poult Sci       Date:  2022-03-12       Impact factor: 4.014

5.  The impact of using different ancestral reference populations in assessing crossbred population admixture and influence on performance.

Authors:  Mohd A Jaafar; Bradley J Heins; Chad Dechow; Heather J Huson
Journal:  Front Genet       Date:  2022-09-26       Impact factor: 4.772

6.  Genomic Prediction for Twin Pregnancies.

Authors:  Shaileen P McGovern; Daniel J Weigel; Brenda C Fessenden; Dianelys Gonzalez-Peña; Natascha Vukasinovic; Anthony K McNeel; Fernando A Di Croce
Journal:  Animals (Basel)       Date:  2021-03-16       Impact factor: 2.752

7.  Large-Scale Whole Genome Sequencing Study Reveals Genetic Architecture and Key Variants for Breast Muscle Weight in Native Chickens.

Authors:  Xiaodong Tan; Lu Liu; Xiaojing Liu; Huanxian Cui; Ranran Liu; Guiping Zhao; Jie Wen
Journal:  Genes (Basel)       Date:  2021-12-21       Impact factor: 4.096

  7 in total

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