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The methylation landscape and its role in domestication and gene regulation in the chicken

Nature Ecology & Evolution volume 4, pages 1713–1724 (2020)Cite this article

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Abstract

Domestication is one of the strongest examples of artificial selection and has produced some of the most extreme within-species phenotypic variation known. In the case of the chicken, it has been hypothesized that DNA methylation may play a mechanistic role in the domestication response. By inter-crossing wild-derived red junglefowl with domestic chickens, we mapped quantitative trait loci for hypothalamic methylation (methQTL), gene expression (eQTL) and behaviour. We find large, stable methylation differences, with 6,179 cis and 2,973 trans methQTL identified. Over 46% of the trans effects were genotypically controlled by five loci, mainly associated with increased methylation in the junglefowl genotype. In a third of eQTL, we find that there is a correlation between gene expression and methylation, while statistical causality analysis reveals multiple instances where methylation is driving gene expression, as well as the reverse. We also show that methylation is correlated with some aspects of behavioural variation in the inter-cross. In conclusion, our data suggest a role for methylation in the regulation of gene expression underlying the domesticated phenotype of the chicken.

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Fig. 1: Local (cis) and trans methQTL detected in the inter-cross.
Fig. 2: Significant NEO causal methQTL/eQTL complex on chromosome 7 at 27 Mb.
Fig. 3: Median methylation for regions upstream of the TSS, in the gene body and downstream of the TTS.

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Data availability

Microarray data for the chicken hypothalamus tissue are available at E-MTAB-3154 in ArrayExpress. DNA methylation and behavioural phenotypes (https://doi.org/10.6084/m9.figshare.12803873), genotypes (https://doi.org/10.6084/m9.figshare.12803876) and a readymade QTL cross-file (https://doi.org/10.6084/m9.figshare.12803870) are available via Figshare.

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Acknowledgements

The research was carried out within the framework of the Swedish Centre of Excellence in Animal Welfare Science, and the Linköping University Neuro-network. SNP genotyping was performed by the Uppsala Sequencing Center. Bioinformatic support was provided by NBIS (National Bioinformatics Infrastructure Sweden). The project was supported by grants from the European Research Council (advanced grant GENEWELL and Consolidator grant FERALGEN 772874), the Swedish Research Council (VR), Carl Tryggers Stiftelse, and the Linköping University Neuro-network.

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Authors and Affiliations

  1. AVIAN Behavioural Genomics and Physiology Group, Linköping University, Linköping, Sweden

    Andrey Höglund, Rie Henriksen, Jesper Fogelholm, Carlos M. Guerrero-Bosagna, Per Jensen & Dominic Wright

  2. NBIS, Department of Molecular Biology, Umeå University, Umeå, Sweden

    Allison M. Churcher

  3. Evolutionary Biology Centrum, Dept of Organismal Biology, Uppsala University, Uppsala, Sweden

    Carlos M. Guerrero-Bosagna

  4. NBIS, SciLifeLab, Uppsala University, Uppsala, Sweden

    Alvaro Martinez-Barrio

  5. The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK

    Martin Johnsson

  6. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden

    Martin Johnsson

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  1. Andrey Höglund
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Contributions

D.W. and P.J. conceived the study. D.W., A.H., M.J., R.H. and J.F. collected data. A.H., R.H., C.M.G.-B., A.M.C., A.M.-B., M.J. and J.F. performed the analyses. D.W., A.H., R.H. and P.J. wrote the initial draft of the manuscript; all authors revised and contributed to the initial and final drafts.

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Correspondence to Dominic Wright.

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Extended data

Extended Data Fig. 1 Percentage of variation in gene expression explained by methylation and genotype in the significantly correlated methQTL/ eQTL candidates.

Percentage of variation in gene expression explained by methylation and genotype in the significantly correlated methQTL/ eQTL candidates. Genes possessing an eQTL are subdivided into the total % of variation that can be accounted for in a model including eQTL genotype, sex and methylation from any significant methQTL (that is genotype, sex and methylation together explain 10–20% of variation in gene expression in the smallest category, and over 50% of gene expression variation in the largest category). The explained gene expression variation in each category is then separated into the % of variation explained by the eQTL genotype and sex and the % variation explained by methylation. In the case of the category for >50% variation explained in gene expression, only four methQTL/ eQTL models fell into this bracket.

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Höglund, A., Henriksen, R., Fogelholm, J. et al. The methylation landscape and its role in domestication and gene regulation in the chicken. Nat Ecol Evol 4, 1713–1724 (2020). https://doi.org/10.1038/s41559-020-01310-1

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