Literature DB >> 28462770

Review: Deciphering animal robustness. A synthesis to facilitate its use in livestock breeding and management.

N C Friggens1, F Blanc2, D P Berry3, L Puillet1.   

Abstract

As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal's capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal's ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.

Keywords:  genotype-by-environment; reproduction; resilience; sustainability; trade-offs

Mesh:

Year:  2017        PMID: 28462770     DOI: 10.1017/S175173111700088X

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  25 in total

1.  Genetic analysis of robustness in meat sheep through body weight and body condition score changes over time.

Authors:  Tiphaine Macé; Eliel González-García; Julien Pradel; Sara Parisot; Fabien Carrière; Sebastien Douls; Didier Foulquié; Dominique Hazard
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

2.  A dynamic model as a tool to describe the variability of lifetime body weight trajectories in livestock females.

Authors:  L Puillet; O Martin
Journal:  J Anim Sci       Date:  2017-11       Impact factor: 3.159

3.  Feeding restriction in the pre and postpartum period of hair ewes raised in the semi-arid region: implications on performance and carcass traits of the progeny.

Authors:  Aline Vieira Landim; Maria Claudete Rodrigues Peres; Hélio Henrique Araújo Costa; Robson Mateus Freitas Silveira; Adailton Camêlo Costa; Michelle de Oliveira Maia Parente; Gerson Barreto Mourão; Concepta Margaret McManus
Journal:  Trop Anim Health Prod       Date:  2022-09-15       Impact factor: 1.893

4.  Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens.

Authors:  Nicolas Bedere; Tom V L Berghof; Katrijn Peeters; Marie-Hélène Pinard-van der Laan; Jeroen Visscher; Ingrid David; Han A Mulder
Journal:  Genet Sel Evol       Date:  2022-04-20       Impact factor: 5.100

5.  Characterizing the acute heat stress response in gilts: I. Thermoregulatory and production variables.

Authors:  J T Seibert; K L Graves; B J Hale; A F Keating; L H Baumgard; J W Ross
Journal:  J Anim Sci       Date:  2018-04-03       Impact factor: 3.159

6.  Little genetic variability in resilience among cattle exists for a range of performance traits across herds in Ireland differing in Fasciola hepatica prevalence.

Authors:  Alan J Twomey; David A Graham; Michael L Doherty; Astrid Blom; Donagh P Berry
Journal:  J Anim Sci       Date:  2018-06-04       Impact factor: 3.159

7.  Robustness scores in fattening pigs based on routinely collected phenotypes: determination and genetic parameters.

Authors:  Guillaume Lenoir; Loïc Flatres-Grall; Nicolas C Friggens; Ingrid David
Journal:  J Anim Sci       Date:  2022-05-01       Impact factor: 3.338

8.  Opinion paper: Measuring livestock robustness and resilience: are we on the right track?

Authors:  P Llonch; G Hoffmann; R Bodas; D Mirbach; C Verwer; M J Haskell
Journal:  Animal       Date:  2020-01-09       Impact factor: 3.240

9.  Investigating the genetic architecture of disease resilience in pigs by genome-wide association studies of complete blood count traits collected from a natural disease challenge model.

Authors:  Xuechun Bai; Tianfu Yang; Austin M Putz; Zhiquan Wang; Changxi Li; Frédéric Fortin; John C S Harding; Michael K Dyck; Jack C M Dekkers; Catherine J Field; Graham S Plastow
Journal:  BMC Genomics       Date:  2021-07-13       Impact factor: 3.969

Review 10.  Omics Application in Animal Science-A Special Emphasis on Stress Response and Damaging Behaviour in Pigs.

Authors:  Claudia Kasper; David Ribeiro; André M de Almeida; Catherine Larzul; Laurence Liaubet; Eduard Murani
Journal:  Genes (Basel)       Date:  2020-08-11       Impact factor: 4.096

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