Literature DB >> 35801647

Genetic and phenotypic parameters for feed efficiency and component traits in American mink.

Pourya Davoudi1, Duy Do1, Stefanie M Colombo1, Bruce Rathgeber1, Guoyu Hu1, Mehdi Sargolzaei2,3, Zhiquan Wang4, Graham Plastow4, Younes Miar1.   

Abstract

Feed cost is the largest expense of mink production systems, and, therefore, improvement of feed efficiency (FE) through selection for high feed-efficient mink is a practical way to increase the mink industry's sustainability. In this study, we estimated the heritability, phenotypic, and genetic correlations for different FE measures and component traits, including harvest weight (HW), harvest length (HL), final body length (FBL), final body weight (FBW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR), using data from 2,288 American mink (for HW and HL), and 1,038 to 1,906 American mink (for other traits). Significance (P < 0.05) of fixed effects (farm, sex, and color type), a covariate (age of animal), and random effects (additive genetic, maternal, and common litter) were evaluated through univariate models implemented in ASReml-R version 4. Genetic parameters were estimated via fitting a set of bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.28 ± 0.06, 0.23 ± 0.06, 0.28 ± 0.10, 0.27 ± 0.11, 0.25 ± 0.09, 0.26 ± 0.09, 0.20 ± 0.09, 0.23 ± 0.09, 0.21 ± 0.10, 0.25 ± 0.10, and 0.26 ± 0.10 for HW, HL, FBL, FBW, ADG, DFI, FCR, RFI, RG, RIG, and KR, respectively. RIG had favorable genetic correlations with DFI (-0.62 ± 0.24) and ADG (0.58 ± 0.21), and nonsignificant (P > 0.05) genetic correlations with FBW (0.14 ± 0.31) and FBL (-0.15 ± 0.31). These results revealed that RIG might be a superior trait as it guarantees reduced feed intake with faster-growing mink yet with no negative impacts on body weight and length. In addition, the strong positive genetic correlations (±SE) between KR with component traits (0.88 ± 0.11 with FBW, 0.68 ± 0.17 with FBL, and 0.97 ± 0.02 with ADG) suggested KR as an applicable indirect measure of FE for improvement of component traits as it did not require the individual feed intake to be measured. Overall, our results confirmed the possibility of including FE traits in mink breeding programs to effectively select feed-efficient animals.
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  American mink; Kleiber ratio; genetic correlation; heritability; residual feed intake

Mesh:

Year:  2022        PMID: 35801647      PMCID: PMC9412173          DOI: 10.1093/jas/skac216

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.338


  42 in total

1.  Genetic parameters for two selection criteria for feed efficiency in rabbits.

Authors:  L Drouilhet; H Gilbert; E Balmisse; J Ruesche; A Tircazes; C Larzul; H Garreau
Journal:  J Anim Sci       Date:  2013-05-08       Impact factor: 3.159

2.  Longitudinal analysis of residual feed intake and BW in mink using random regression with heterogeneous residual variance.

Authors:  M Shirali; V H Nielsen; S H Møller; J Jensen
Journal:  Animal       Date:  2015-06-08       Impact factor: 3.240

3.  The relationship between different measures of feed efficiency and feeding behavior traits in Duroc pigs.

Authors:  D Lu; S Jiao; F Tiezzi; M Knauer; Y Huang; K A Gray; C Maltecca
Journal:  J Anim Sci       Date:  2017-08       Impact factor: 3.159

4.  Combined analysis of group recorded feed intake and individually recorded body weight and litter size in mink.

Authors:  M D Madsen; T M Villumsen; B K Hansen; S H Møller; J Jensen; M Shirali
Journal:  Animal       Date:  2020-04-23       Impact factor: 3.240

5.  Efficiency of utilisations of food energy by female growing minks.

Authors:  G Burlacu; V Rus; C Aldea; M Nicolae; L Cosmescu
Journal:  Arch Tierernahr       Date:  1984-10

6.  Genetic and phenotypic parameters for litter size, survival rate, gestation length, and litter weight traits in American mink.

Authors:  Karim Karimi; Mehdi Sargolzaei; Graham Stuart Plastow; Zhiquan Wang; Younes Miar
Journal:  J Anim Sci       Date:  2018-06-29       Impact factor: 3.159

7.  An extended anchored linkage map and virtual mapping for the American mink genome based on homology to human and dog.

Authors:  R Anistoroaei; S Ansari; A Farid; B Benkel; P Karlskov-Mortensen; K Christensen
Journal:  Genomics       Date:  2009-06-09       Impact factor: 5.736

8.  Genome analysis identifies the mutant genes for common industrial Silverblue and Hedlund white coat colours in American mink.

Authors:  Andrey D Manakhov; Tatiana V Andreeva; Oleg V Trapezov; Nikolay A Kolchanov; Evgeny I Rogaev
Journal:  Sci Rep       Date:  2019-03-14       Impact factor: 4.379

9.  Evaluation of Growth Curve Models for Body Weight in American Mink.

Authors:  Duy Ngoc Do; Younes Miar
Journal:  Animals (Basel)       Date:  2019-12-20       Impact factor: 2.752

10.  First Description of SARS-CoV-2 Infection in Two Feral American Mink (Neovison vison) Caught in the Wild.

Authors:  Jordi Aguiló-Gisbert; Miguel Padilla-Blanco; Victor Lizana; Elisa Maiques; Marta Muñoz-Baquero; Eva Chillida-Martínez; Jesús Cardells; Consuelo Rubio-Guerri
Journal:  Animals (Basel)       Date:  2021-05-16       Impact factor: 2.752

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