Evidence map›Paper›PMID 30386376›Full record

ArticleFrontiers in genetics2018

Genetic Parameters for Resistance to Non-specific Diseases and Production Traits Measured in Challenging and Selection Environments; Application to a Rabbit Case.

Mélanie Gunia, Ingrid David, Jacques Hurtaud, Mickaël Maupin, Hélène Gilbert, Hervé Garreau

Abstract read
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review: Livestock disease resilience: from individual to herd level.Animal : an international journal of animal bioscience · 2021
    Review
  9. Why breed disease-resilient livestock, and how?Genetics, selection, evolution : GSE · 2020
    Review
  10. Article
  11. Health and welfare of rabbits farmed in different production systems.EFSA journal. European Food Safety Authority · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mélanie GuniaGenPhySE, INRA, ENVT, Université de Toulouse, Castanet Tolosan, France.
Ingrid DavidGenPhySE, INRA, ENVT, Université de Toulouse, Castanet Tolosan, France.
Jacques HurtaudHYPHARM SAS, La Corbière, Roussay, Sèvremoine, France.
Mickaël MaupinHYPHARM SAS, La Corbière, Roussay, Sèvremoine, France.
Hélène GilbertGenPhySE, INRA, ENVT, Université de Toulouse, Castanet Tolosan, France.
Hervé GarreauGenPhySE, INRA, ENVT, Université de Toulouse, Castanet Tolosan, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breeding for disease resistance is a challenging but increasingly necessary objective to overcome the issues with the reduced use of antibiotics and growing concern for animal welfare while limiting economic losses. However, implementing such strategies is a complex process because animals face numerous diseases, and the environments on selection farms differ from those on commercial farms. We evaluated whether selection for resistance to non-specific diseases based on a single visual record in selection (S) and challenging (Ch) environments is possible. Records from 23,773 purebred rabbits born between 2012 and 2016 were used in this study. After weaning (at 32 days of age), 17,712 rabbits were raised in the S environment and 6,061 sibs were raised in the Ch environment. Clinical signs of disease were recorded for all animals at the end of the test, at a single time point, at 70 or 80 days of age. The causes of mortality occurring before the end of the test were also recorded. Three disease traits were analyzed: signs of respiratory disease, signs of digestive disease, and a composite trait (Resist) taking into account signs of digestive, respiratory and various infectious diseases. This latter composite trait is proposed to capture the global resistance to disease. All disease traits were binary, with 0 being the absence of symptoms. Two production traits were also recorded: the number of kits born alive (4,121 litters) and the weaning weight (13,090 rabbits). Disease traits were analyzed with animal threshold models, assuming that traits are different in the two environments. Bivariate analyses were carried out using linear animal models. The heritabilities of the disease traits ranged from 0.04 ± 0.01 to 0.11 ± 0.03. The genetic correlations between disease traits in both environments were below unity (≤ 0.84), indicating genotype by environment interactions. Most of the genetic correlations between disease and production traits were not significantly different from zero, except between the weaning weight and Resist_S, with a favorable correlation of -0.34 ± 0.12. Given these genetic parameters, for the same level of exposure of rabbits to pathogens, the expected response to selection is a reduction of disease incidence of 4-6% per generation.

Indexed as

farminggenetic parametersgeneticsgenotype-environment interactionheritabilityrabbitresistance to disease

Identifiers

PMID30386376
PMCPMC6198044

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.