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Complex genetic architecture of the chicken Growth1 QTL region
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
School of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg VA, USA.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The genetic complexity of polygenic traits represents a captivating and intricate facet of biological inheritance. Unlike Mendelian traits controlled by a single gene, polygenic traits are influenced by multiple genetic loci, each exerting a modest effect on the trait. This cumulative impact of numerous genes, interactions among them, environmental factors, and epigenetic modifications results in a multifaceted architecture of genetic contributions to complex traits.

Given the well-characterized genome, diverse traits, and range of genetic resources, chicken (Gallus gallus) was employed as a model organism to dissect the intricate genetic makeup of a previously identified major Quantitative Trait Loci (QTL) for body weight on chromosome 1.

A multigenerational advanced intercross line (AIL) of 3215 chickens whose genomes had been sequenced to an average of 0.4x was analyzed using genome-wide association study (GWAS) and variance-heterogeneity GWAS (vGWAS) to identify markers associated with 8-week body weight. Additionally, epistatic interactions were studied using the natural and orthogonal interaction (NOIA) model.

Six genetic modules, two from GWAS and four from vGWAS, were strongly associated with the studied trait. We found evidence of both additive- and non-additive interactions between these modules and constructed a putative local epistasis network for the region. Our screens for functional alleles revealed a missense variant in the gene ribonuclease H2 subunit B (RNASEH2B), which has previously been associated with growth-related traits in chickens and Darwin’s finches. In addition, one of the most strongly associated SNPs identified is located in a non-coding region upstream of the long non-coding RNA, ENSGALG00000053256, previously suggested as a candidate gene for regulating chicken body weight. By studying large numbers of individuals from a family material using approaches to capture both additive and non-additive effects, this study advances our understanding of genetic complexities in a highly polygenic trait and has practical implications for poultry breeding and agriculture.

National Category
Genetics and Breeding in Agricultural Sciences
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-527020OAI: oai:DiVA.org:uu-527020DiVA, id: diva2:1853357
Available from: 2024-04-22 Created: 2024-04-22 Last updated: 2024-04-22
In thesis
1. Exploring the Genetic Landscape of Chicken Populations: Admixture, Growth QTLs, and Long-Term Selection Dynamics
Open this publication in new window or tab >>Exploring the Genetic Landscape of Chicken Populations: Admixture, Growth QTLs, and Long-Term Selection Dynamics
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis analyzes the genetic structure of chicken populations across different breeding histories and environments. Genomic methodologies were used to uncover complex traits and domestication history over time. The work consists of three studies contributing to a broader understanding of chicken genetic diversity and the impact of selective breeding practices.

The first study delves into the global chicken population, using genome-wide analysis to uncover the intricate fine structure and historical admixture events that have shaped these populations. The research has unveiled significant connections between populations and pivotal breeding events, highlighting the complex relationships within chicken populations. This study offers intriguing insights into the genetic continuity and admixture patterns across diverse chicken breeds, from junglefowl to commercial lines.

The second study focuses on the genetic complexity within a specific quantitative trait locus (QTL) region known as Growth1, which is influential in chicken growth. This study, conducted using an advanced intercross line from the Virginia body weight line, identifies significant additive, haplotype, and epistasis effects within the Growth1 QTL region. The findings challenge simplistic genetic models by demonstrating the involvement of multiple loci in regulating body weight and contribute to understanding complex trait architecture.

The third study extends the investigation to the long-term effects of selection on chicken lines, providing a deeper understanding of the genetic mechanisms underlying selection responses. By mapping multiple additive QTLs associated with body weight compared with the GWA study results, several novel regions were determined and are still contributing to the selection response even after 40 generations of intense selection.

These different views provide practical insights into chickens' intricate genetic makeup. By analyzing their domestication history, genetic variation effects, and the population's response to selective breeding, we better understand one of the most important economic organisms for humans — the chicken. This understanding can potentially inform and improve selective breeding practices, leading to more efficient and sustainable poultry production.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2024. p. 36
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 2053
Keywords
Virginia Chicken Lines, population genetics, QTL, admixture, selective breeding, bioinformatics
National Category
Genetics and Breeding in Agricultural Sciences
Research subject
Bioinformatics
Identifiers
urn:nbn:se:uu:diva-527022 (URN)978-91-513-2137-0 (ISBN)
Public defence
2024-06-13, room A1:111a, BMC, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2024-05-17 Created: 2024-04-22 Last updated: 2024-05-17

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