A method for partitioning trends in genetic mean and variance

Thiago De Paula Oliveira; Jana Obsteter; Ivan Pocrnic; Gregor Gorjanc

A method for partitioning trends in genetic mean and variance

Thiago De Paula Oliveira, Jana Obsteter, Ivan Pocrnic, Gregor Gorjanc

Research output: Contribution to conference › Poster › peer-review

Abstract

Quantifying sources of genetic change is essential for identifying key breeding actions and optimising breeding programmes. However, the observed genetic change is a sum of contributions from different groups of individuals (often referred to as selection pathways), which are difficult to disentangle and quantify due to the complexity of breeding programmes. Here we extended a simple method to analyse the contributions of groups to the genetic variance. Our approach showed the importance of analysing the partition of the genetic mean and variance rather than just the genetic mean and demonstrated that the contributions are not necessarily independent.

Original language	English
Number of pages	6
Publication status	Published - 18 Jul 2022
Event	International Workshop on Statistical Modelling - Trieste, Italy Duration: 18 Jul 2022 → 22 Jul 2022 Conference number: 36 https://www.iwsm2022.com/

Conference

Conference	International Workshop on Statistical Modelling
Country/Territory	Italy
City	Trieste
Period	18/07/22 → 22/07/22
Internet address	https://www.iwsm2022.com/

Quantifying the Drivers of Genetic Change in Plant Breeding
De Paula Oliveira, T. (Researcher) & Gorjanc, G. (Principal Investigator)
1/10/20 → 30/09/23
Project: Research

Cite this

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title = "A method for partitioning trends in genetic mean and variance",

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AU - De Paula Oliveira, Thiago

AU - Obsteter, Jana

AU - Pocrnic, Ivan

AU - Gorjanc, Gregor

N1 - Conference code: 36

PY - 2022/7/18

Y1 - 2022/7/18

N2 - Quantifying sources of genetic change is essential for identifying key breeding actions and optimising breeding programmes. However, the observed genetic change is a sum of contributions from different groups of individuals (often referred to as selection pathways), which are difficult to disentangle and quantify due to the complexity of breeding programmes. Here we extended a simple method to analyse the contributions of groups to the genetic variance. Our approach showed the importance of analysing the partition of the genetic mean and variance rather than just the genetic mean and demonstrated that the contributions are not necessarily independent.

AB - Quantifying sources of genetic change is essential for identifying key breeding actions and optimising breeding programmes. However, the observed genetic change is a sum of contributions from different groups of individuals (often referred to as selection pathways), which are difficult to disentangle and quantify due to the complexity of breeding programmes. Here we extended a simple method to analyse the contributions of groups to the genetic variance. Our approach showed the importance of analysing the partition of the genetic mean and variance rather than just the genetic mean and demonstrated that the contributions are not necessarily independent.

M3 - Poster

T2 - International Workshop on Statistical Modelling

Y2 - 18 July 2022 through 22 July 2022

ER -

A method for partitioning trends in genetic mean and variance

Abstract

Conference

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Projects

Quantifying the Drivers of Genetic Change in Plant Breeding

Cite this