Literature DB >> 33736590

AlphaPart-R implementation of the method for partitioning genetic trends.

Jana Obšteter1, Justin Holl2, John M Hickey3, Gregor Gorjanc3.   

Abstract

BACKGROUND: In this paper, we present the AlphaPart R package, an open-source implementation of a method for partitioning breeding values and genetic trends to identify the contribution of selection pathways to genetic gain. Breeding programmes improve populations for a set of traits, which can be measured with a genetic trend calculated from estimated breeding values averaged by year of birth. While sources of the overall genetic gain are generally known, their realised contributions are hard to quantify in complex breeding programmes. The aim of this paper is to present the AlphaPart R package and demonstrate it with a simulated stylized multi-tier breeding programme mimicking a pig or poultry breeding programme.
RESULTS: The package includes the main partitioning function AlphaPart, that partitions the breeding values and genetic trends by pre-defined selection paths, and a set of functions for handling data and results. The package is freely available from the CRAN repository at http://CRAN.R-project.org/package=AlphaPart . We demonstrate the use of the package by partitioning the nucleus and multiplier genetic gain of the stylized breeding programme by tier-gender paths. For traits measured and selected in the multiplier, the multiplier selection generated additional genetic gain. By using AlphaPart, we show that the additional genetic gain depends on accuracy and intensity of selection in the multiplier and the extent of gene flow from the nucleus. We have proven that AlphaPart is a valuable tool for understanding the sources of genetic gain in the nucleus and especially the multiplier, and the relationship between the sources and parameters that affect them.
CONCLUSIONS: AlphaPart implements the method for partitioning breeding values and genetic trends and provides a useful tool for quantifying the sources of genetic gain in breeding programmes. The use of AlphaPart will help breeders to improve genetic gain through a better understanding of the key selection points that are driving gains in each trait.

Entities:  

Mesh:

Year:  2021        PMID: 33736590      PMCID: PMC7977322          DOI: 10.1186/s12711-021-00600-x

Source DB:  PubMed          Journal:  Genet Sel Evol        ISSN: 0999-193X            Impact factor:   4.297


  6 in total

1.  Expected genetic contributions and their impact on gene flow and genetic gain.

Authors:  J A Woolliams; P Bijma; B Villanueva
Journal:  Genetics       Date:  1999-10       Impact factor: 4.562

2.  Partition of the genetic trend to validate multiple selection decisions.

Authors:  L A García-Cortés; J C Martínez-Ávila; M A Toro
Journal:  Animal       Date:  2008-06       Impact factor: 3.240

3.  Estimation of genetic trend in a selected population with and without the use of a control population.

Authors:  H T Blair; E J Pollak
Journal:  J Anim Sci       Date:  1984-04       Impact factor: 3.159

4.  Partition of genetic trends by origin in Landrace and Large-White pigs.

Authors:  D Škorput; G Gorjanc; A Kasap; Z Luković
Journal:  Animal       Date:  2015-07-08       Impact factor: 3.240

5.  AlphaSimR: an R package for breeding program simulations.

Authors:  R Chris Gaynor; Gregor Gorjanc; John M Hickey
Journal:  G3 (Bethesda)       Date:  2021-02-09       Impact factor: 3.154

6.  Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions.

Authors:  David M Howard; Ricardo Pong-Wong; Pieter W Knap; Valentin D Kremer; John A Woolliams
Journal:  Genet Sel Evol       Date:  2018-05-10       Impact factor: 4.297

  6 in total

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