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A multi-locus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. (Carlborg)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. (Carlborg)ORCID iD: 0000-0002-2722-5264
2018 (English)In: Molecular Ecology Resources, ISSN 1755-098X, E-ISSN 1755-0998Article in journal (Refereed) Epub ahead of print
Abstract [en]

The adaptation to a new habitat often results in a confounding between genome-wide genotype and beneficial alleles. When the confounding is strong, or the allelic effects weak, it is a major statistical challenge to detect the adaptive polymorphisms. We describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci directly associated with the adaptive trait or the expression of genes known to affect it. Then, a multi-locus genetic architecture is inferred using a backward elimination association analysis across all candidate loci with an adaptive false discovery rate based threshold. Effects of population stratification are controlled by accounting for genomic kinship in both steps of the analysis and also by simultaneously testing all candidate loci in the multi locus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. We revealed associations between 33 (29) loci and flowering time at 10 (16)°C in this collection of natural accessions, where standard genome wide association analysis methods detected 5 (3) loci. The 33 (29) loci explained approximately 55.1 (48.7)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail by using new multi-locus mapping approaches taking advantage of prior biological information, genome and transcriptome data. This article is protected by copyright. All rights reserved.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Arabidopsis thaliana, Expression QTL, Flowering, Genome wide association analysis, Polygenic
National Category
Natural Sciences
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-340301DOI: 10.1111/1755-0998.12757PubMedID: 29356396OAI: oai:DiVA.org:uu-340301DiVA, id: diva2:1178252
Funder
Swedish Research Council Formas, 2013-450Available from: 2018-01-29 Created: 2018-01-29 Last updated: 2018-02-26
In thesis
1. Understanding the genetic basis of complex traits
Open this publication in new window or tab >>Understanding the genetic basis of complex traits
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Recent advances in genetics and genomics have provided numerous opportunities to study the genetic basis of complex traits. Nevertheless, dissecting the genetic basis of complex traits is still challenged by the complex genetic architecture, in which many genes are involved, and many have small contributions to phenotypic variation, interactions with other genes or environmental factors. The aim of this thesis is to evaluate the genetic basis of the complex traits by exploring available genomic resources and analytical approaches. Four studies included in this thesis explore: the genetic basis of global transcriptome variation in natural population (Study I); the genetic basis of 8-week body weight in artificial selected chicken lines (Study II); the genetic basis of flowering time variation for Arabidopsis thaliana sampled from a wide range of ecological conditions (Study III and Study IV). Findings from this thesis show that the genetic architecture of complex traits involves many polymorphisms with variable effect sizes. Some of those polymorphisms are multi-allelic and have interactions with each other and environmental factors at the same time. The presence of many alleles with minor contributions to phenotypic variation in natural and artificially selected population demonstrates that response to natural and artificial selection has been achieved by polygenic adaptation. Furthermore, population-specific large-effect loci with long-range LD to QTL in functionally related pathways indicate that emergence and fixation of loci with large effects and co-evolution of loci in the related pathway is contributing to the local adaptation of Arabidopsis thaliana. Overall, this thesis shows the complexity of complex trait genetics and provides a few insights into study designs and analysis approaches for understanding the genetic basis of complex traits.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 49
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1438
Keywords
genetic architecture, complex traits, epistasis, multi-allelic, genotype by environment interaction, polygenic adaptation
National Category
Medical and Health Sciences
Research subject
Biology with specialization in Evolutionary Genetics
Identifiers
urn:nbn:se:uu:diva-343174 (URN)978-91-513-0260-7 (ISBN)
Public defence
2018-04-27, C8:301, BMC, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2018-04-04 Created: 2018-02-26 Last updated: 2018-04-24

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Zan, Yanjun

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