Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Exploring the Genetic Landscape of Chicken Populations: Admixture, Growth QTLs, and Long-Term Selection Dynamics
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. (Carl-Johan Rubin'r group)ORCID iD: 0000-0001-9305-2931
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Description
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 [en]
Virginia Chicken Lines, population genetics, QTL, admixture, selective breeding, bioinformatics
National Category
Genetics and Breeding in Agricultural Sciences
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-527022ISBN: 978-91-513-2137-0 (print)OAI: oai:DiVA.org:uu-527022DiVA, id: diva2:1853374
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
List of papers
1. Researching on the fine structure and admixture of the worldwide chicken population reveal connections between populations and important events in breeding history
Open this publication in new window or tab >>Researching on the fine structure and admixture of the worldwide chicken population reveal connections between populations and important events in breeding history
Show others...
2021 (English)In: Evolutionary Applications, E-ISSN 1752-4571, Vol. 15, no 4, p. 553-564Article in journal (Refereed) Published
National Category
Genetics and Breeding in Agricultural Sciences
Identifiers
urn:nbn:se:uu:diva-527018 (URN)10.1111/eva.13241 (DOI)
Funder
Swedish Research Council, 2018‐05991Swedish Research Council, 2018‐05973
Available from: 2024-04-22 Created: 2024-04-22 Last updated: 2024-04-22
2. Complex genetic architecture of the chicken Growth1 QTL region
Open this publication in new window or tab >>Complex genetic architecture of the chicken Growth1 QTL region
Show others...
(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:nbn:se:uu:diva-527020 (URN)
Available from: 2024-04-22 Created: 2024-04-22 Last updated: 2024-04-22
3. Within-line segregation as contributors to long-term, single-trait selection responses in the Virginia chicken lines
Open this publication in new window or tab >>Within-line segregation as contributors to long-term, single-trait selection responses in the Virginia chicken lines
Show others...
(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:nbn:se:uu:diva-527021 (URN)
Available from: 2024-04-22 Created: 2024-04-22 Last updated: 2024-04-22

Open Access in DiVA

UUThesis_JH-Ou-2024(961 kB)59 downloads
File information
File name FULLTEXT01.pdfFile size 961 kBChecksum SHA-512
1b0961239247d40c28fba8203fe6f4c10469d19ccca99dce37509def243b12e3b049aa42dee7e582977f0e8d52f7bec9bd2cc7783fe29ae84211efd36a08fa96
Type fulltextMimetype application/pdf

Authority records

Ou, Jen-Hsiang

Search in DiVA

By author/editor
Ou, Jen-Hsiang
By organisation
Department of Medical Biochemistry and Microbiology
Genetics and Breeding in Agricultural Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 60 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 596 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf