Literature DB >> 31701578

Selecting the hologenome to breed for an improved feed efficiency in pigs-A novel selection index.

Ramona Weishaar1, Robin Wellmann1, Amelia Camarinha-Silva1, Markus Rodehutscord1, Jörn Bennewitz1.   

Abstract

Most traits in animal breeding, including feed efficiency traits in pigs, are affected by many genes with small effect and have a moderately high heritability between 0.1 and 0.5, which enables efficient selection. Since the microbiota composition in the gastrointestinal tract is also partly heritable and was shown to have a substantial effect on feed efficiency, the host genes affect the phenotype not only directly by altering metabolic pathways, but also indirectly by changing the microbiota composition. The effect m i of the microbiota composition on the breeding value g i of an animal i is the conditional expectation of its breeding value, given the vector φ i with microbiota frequencies, that is m i = E g i | φ i . The breeding value g i of an animal can therefore be decomposed into a heritable contribution m i that arises from an altered microbiota composition and a heritable contribution p i that arises from altered metabolic pathways within the animal, so g i = m i + p i . Instead of selecting for breeding value g ^ i , an index comprising the two components m ^ i and p ^ i with appropriate weights, that is I i = λ 1 m ^ i + λ 2 p ^ i , can be used. The present study shows how this breeding strategy can be applied in pig genomic selection breeding scheme for two feed efficiency traits and daily gain.
© 2019 Blackwell Verlag GmbH.

Entities:  

Keywords:  feed efficiency; genomic selection; hologenome; microbiota; pig

Mesh:

Year:  2019        PMID: 31701578     DOI: 10.1111/jbg.12447

Source DB:  PubMed          Journal:  J Anim Breed Genet        ISSN: 0931-2668            Impact factor:   2.380


  14 in total

1.  Extend mixed models to multilayer neural networks for genomic prediction including intermediate omics data.

Authors:  Tianjing Zhao; Jian Zeng; Hao Cheng
Journal:  Genetics       Date:  2022-05-05       Impact factor: 4.402

2.  Genetic evaluation including intermediate omics features.

Authors:  Ole F Christensen; Vinzent Börner; Luis Varona; Andres Legarra
Journal:  Genetics       Date:  2021-10-02       Impact factor: 4.402

3.  Validation of a beef cattle maternal breeding objective based on a cross-sectional analysis of a large national cattle database.

Authors:  Alan J Twomey; Andrew R Cromie; Noirin McHugh; Donagh P Berry
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

4.  Microbiability and microbiome-wide association analyses of feed efficiency and performance traits in pigs.

Authors:  Amir Aliakbari; Olivier Zemb; Laurent Cauquil; Céline Barilly; Yvon Billon; Hélène Gilbert
Journal:  Genet Sel Evol       Date:  2022-04-25       Impact factor: 5.100

5.  Modeling host-microbiome interactions for the prediction of meat quality and carcass composition traits in swine.

Authors:  Piush Khanal; Christian Maltecca; Clint Schwab; Justin Fix; Matteo Bergamaschi; Francesco Tiezzi
Journal:  Genet Sel Evol       Date:  2020-07-29       Impact factor: 4.297

6.  The Gut Microbial Architecture of Efficiency Traits in the Domestic Poultry Model Species Japanese Quail (Coturnix japonica) Assessed by Mixed Linear Models.

Authors:  Solveig Vollmar; Robin Wellmann; Daniel Borda-Molina; Markus Rodehutscord; Amélia Camarinha-Silva; Jörn Bennewitz
Journal:  G3 (Bethesda)       Date:  2020-07-07       Impact factor: 3.154

7.  Heritability and genome-wide association of swine gut microbiome features with growth and fatness parameters.

Authors:  Matteo Bergamaschi; Christian Maltecca; Constantino Schillebeeckx; Nathan P McNulty; Clint Schwab; Caleb Shull; Justin Fix; Francesco Tiezzi
Journal:  Sci Rep       Date:  2020-06-23       Impact factor: 4.379

8.  Composition of the ileum microbiota is a mediator between the host genome and phosphorus utilization and other efficiency traits in Japanese quail (Coturnix japonica).

Authors:  Valentin Haas; Solveig Vollmar; Siegfried Preuß; Markus Rodehutscord; Amélia Camarinha-Silva; Jörn Bennewitz
Journal:  Genet Sel Evol       Date:  2022-03-08       Impact factor: 4.297

9.  Gut Microbial Composition and Predicted Functions Are Not Associated with Feather Pecking and Antagonistic Behavior in Laying Hens.

Authors:  Daniel Borda-Molina; Hanna Iffland; Markus Schmid; Regina Müller; Svenja Schad; Jana Seifert; Jens Tetens; Werner Bessei; Jörn Bennewitz; Amélia Camarinha-Silva
Journal:  Life (Basel)       Date:  2021-03-12

10.  Opportunities and limits of combining microbiome and genome data for complex trait prediction.

Authors:  Miguel Pérez-Enciso; Laura M Zingaretti; Yuliaxis Ramayo-Caldas; Gustavo de Los Campos
Journal:  Genet Sel Evol       Date:  2021-08-06       Impact factor: 4.297

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