Abstract

Genetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is therefore of high interest. Here, we extend a previously proposed framework for temporal analysis of genetic variance using the pedigree-based model, to a new framework for temporal and genomic analysis of genetic variance using marker-based models. To this end, we describe the theory of partitioning genetic variance into genic variance and within-chromosome and between-chromosome linkage-disequilibrium, and how to estimate these variance components from a marker-based model fitted to observed phenotype and marker data. The new framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values and (iii) calculating the variance of sampled genetic values by time and genome partitions. Analysing time partitions indicates breeding programme sustainability, while analysing genome partitions indicates contributions from chromosomes and chromosome pairs and linkage-disequilibrium. We demonstrate the framework with a simulated breeding programme involving a complex trait. Results show good concordance between simulated and estimated variances, provided that the fitted model is capturing genetic complexity of a trait. We observe a reduction of genetic variance due to selection and drift changing allele frequencies, and due to selection inducing negative linkage-disequilibrium.

Highlights

  • This study analyses temporal and genomic trends of additive genetic variance in different stages of a breeding programme

  • MATERIALS AND METHODS we present study material and methods in seven parts: (1) simulation of a breeding programme where we generate true genetic values and corresponding variances, and simulated phenotype and marker genotype data, (2) theory for the temporal and genomic analysis of genetic variance assuming we know quantitative trait loci (QTL) genotypes and their effects, (3) statistical analysis where we describe marker-based model fitted to the simulated phenotype and marker genotype data, (4) statistical and computational approaches to estimate marker effects, genetic values and variances, (5) validation of the framework with different genetic architectures of a simulated trait, (6) summarising the results and (7) software implementation

  • Overall, the results show that estimates from the data following the framework were in concordance with the true values for temporal and genomic analysis, provided that the fitted model is capturing the genetic complexity of a trait

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Summary

Introduction

This study analyses temporal and genomic trends of additive genetic variance in different stages of a breeding programme. Genetic variance is one of the critical parameters in a breeding programme because it determines the potential for selection (Lush 1937; Falconer and Mackay 1996; Lynch and Walsh 1998; Walsh and Lynch 2018). Estimation of genetic variance has received considerable attention in the literature (Lynch and Walsh 1998; Walsh and Lynch 2018), where most of the attention is on statistical models and approaches for estimation. Recent ability to genotype individuals at scale has renewed interest in analysing genetic variance. This study extends previously proposed framework for temporal analysis of genetic variance using the pedigreebased model of Sorensen et al (2001), to a new framework for temporal and genomic analysis of genetic variance using markerbased models

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