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Within-line segregation as contributors to long-term, single-trait selection responses in the Virginia chicken lines
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.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Populations display a remarkable capability to adapt under natural or artificial selection, even far beyond the original phenotype range, given intense single trait selection. The genetic mechanisms to facilitate this however, are still unclear. Here we use an Advanced Intercross Line, generated after 40 generations of intense bi-directional selection from a common outbred founder population, in an attempt to quantify the contribution of still segregating variants to the selection response.

While the selection response of the founding lines has been extensively profiled within this population, this has been done under the assumption that the most important regions were fixed for divergent alleles between the lines. Investigating beyond this paradigm has been previously hampered due to requirements in power, marker density, and number of recombination events. Here we use a large low-coverage sequencing dataset that has been imputed to both founder-line haplotypes as well as dense marker coverage using high-quality, deep-coverage sequenced founders. Utilizing this dataset for a multi-locus GWAS approach to contrast with a more traditional cross-QTL methodology, the aim of this study is to identify novel regions that contribute to the phenotype and assess whether and how they contribute to the selection response. Out of 40 (a=890g, 23.9% of total phenotypic variance) Loci retained in the multilocus model, 24 (a=557.5g, 15% of total phenotypic variance) do not overlap known QTL. While some freely segregate between lines, 14 (a=346.6g, 9.3% of total phenotypic variance) of them are fixed in at least one founding line, and likely contribute a significant fraction of the selection response.

The variance effect prediction result provides a functional view of markers. The RNASEH2B and TBXAS1 genes were considered as candidates, with previous research supporting body weight-related functions. For GALNT7, ENSGALG00000049347, TOM1, ENSGALG00000013583, ENSGALG00000039245, CHD7, and CNTNAP5 genes, the high conservation score provides a clue of being important for biological functions. However, the mechanism by which these genes regulate body weight still remains limited.

National Category
Genetics and Breeding in Agricultural Sciences
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-527021OAI: oai:DiVA.org:uu-527021DiVA, id: diva2:1853364
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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