Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1278 Complex Trait Genetics Beyond Additivity SIMON FORSBERG ACTA UNIVERSITATIS UPSALIENSIS ISSN 1651-6206 ISBN 978-91-554-9754-5 UPPSALA urn:nbn:se:uu:diva-307837 2016 Dissertation presented at Uppsala University to be publicly examined in B22, BMC, Husarg. 3, Uppsala, Friday, 13 January 2017 at 10:15 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in English. Faculty examiner: Assistant Professor Julien Ayroles (Princeton University). Abstract Forsberg, S. 2016. Complex Trait Genetics. Beyond Additivity. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1278. 45 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9754-5. The link between the genotype and the phenotype of an organism is immensely complex. Despite this it can, to a great extent, be captured using models that assume that gene variants combine their effects in an additive manner. This thesis explores aspects of genetics that cannot be fully captured using such additive models. Using experimental data from three different model organisms, I study two phenomena that fall outside of the additive paradigm: genetic interactions and genetic variance heterogeneity. Using the model plant Arabidopsis thaliana, we show how important biological insights can be reached by exploring loci that display genetic variance heterogeneity. In the first study, this approach identified alleles in the gene CMT2 associated with the climate at sampling locations, suggesting a role in climate adaption. These alleles affected the genome wide methylation pattern, and a complete knock down of this gene increased the plants heat tolerance. In the second study, we demonstrate how the observed genetic variance heterogeneity was the result of the partial linkage of many functional alleles near the gene MOT1, all contributing to Molybdenum levels in the leaves. Further, we explore genetic interactions using data from dogs and budding yeast (Saccharomyces cerevisiae). In the dog population, two interacting loci were associated with fructosamine levels, a biomarker used to monitor blood glucose. One of the loci displayed the pattern of a selective sweep in some of the studied breeds, suggesting that the interaction is important for the phenotypic breed-differences. In a cross between two strains of yeast, with the advantage of large population size and nearly equal allele frequencies, we identified large epistatic networks. The networks were largely centered on a number of hub-loci and altogether involved hundreds of genetic interactions. Most network hubs had the ability to either suppress or uncover the phenotypic effects of other loci. Many multi-locus allele combinations resulted in phenotypes that deviated significantly from the expectations, had the loci acted in an additive manner. Critically, this thesis demonstrates that non-additive genetic mechanisms often need to be considered in order to fully understand the genetics of complex traits. Keywords: genetic interactions, epistasis, additivity, GWAS, vGWAS, Genetic mapping, yeast, Arabidopsis Thaliana, dog Simon Forsberg, Department of Medical Biochemistry and Microbiology, Box 582, Uppsala University, SE-75123 Uppsala, Sweden. © Simon Forsberg 2016 ISSN 1651-6206 ISBN 978-91-554-9754-5 urn:nbn:se:uu:diva-307837 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-307837) I am the family face; Flesh perishes, I live on, Projecting trait and trace Through time to times anon, And leaping from place to place Over oblivion. The years-heired feature that can In curve and voice and eye Despise the human span Of durance -- that is I; The eternal thing in man, That heeds no call to die Thomas Hardy - Heredity Cover image: Illustration of allele combinations, the space of genotypic possibilities, at 2 to 5 loci. From Sewall Wrights 1932 paper The roles of mutation, inbreeding, crossbreeding, and selection in evolution. Reproduced with permission from GENETICS SOCIETY OF AMERICA List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I. Shen X, De Jonge J, Forsberg SKG, Pettersson ME, Sheng Z, Hen- nig L, & Carlborg Ö. (2014) Natural CMT2 Variation Is Associated With Genome-Wide Methylation Changes and Temperature Season- ality. PLOS Genet. 10 1–14. II. Forsberg SKG, Kierczak M, Ljungvall I, Merveille A-C, Gouni V, Wiberg M, Lundgren Willesen J, Hanås S, Lequarré A-S, Mejer Sørensen L, Tiret L, McEntee K, Seppälä E, Koch J, Battaille G, Lohi H, Fredholm M, Chetboul V, Häggström J, Carlborg Ö, Lind- blad-Toh K, & Höglund K. (2015) The Shepherds’ Tale: A Genome- Wide Study across 9 Dog Breeds Implicates Two Loci in the Regu- lation of Fructosamine Serum Concentration in Belgian Shepherds. PLoS One 10, 1–17. III. Forsberg SKG, Andreatta ME, Huang X-Y, Danku J, Salt DE, & Carlborg Ö. (2015) The Multi-allelic Genetic Architecture of a Vari- ance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance. PLOS Genet. 11, 1–24. IV. Forsberg SKG, Bloom JS, Sadhu M, Kruglyak L, & Carlborg Ö, Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast. bioRxiv (2016). doi:10.1101/059485. Manuscript in review. Reprints were made with permission from the respective publishers. List of Papers (not included in the thesis) 1. Saha I, Zubek J, Klingström T, Forsberg S, Wikander J, Kierczak M, Maulik U, & Plewczynski D. (2014) Ensemble learning predic- tion of protein-protein interactions using proteins functional annota- tions. Mol. Biosyst. 10, 820–30. 2. Sjöstrand K, Wess G, Ljungvall I, Häggström J, Merveille A-C, Wi- berg M, Gouni V, Lundgren Willesen J, Hanås S, Lequarré A.-S, Mejer Sørensen L, Wolf J, Tiret L, Kierczak M, Forsberg S, McEntee K, Battaille G, Seppälä E, Lindblad-Toh K, Georges M, Lohi H, Chetboul V, Fredholm M, & Höglund K, (2014) Breed Dif- ferences in Natriuretic Peptides in Healthy Dogs. J. Vet. Intern. Med. 28, 451–457. 3. Kierczak M, Jabłońska J, Forsberg SKG, Bianchi M, Tengvall K, Pettersson M, Scholz V, Meadows JRS, Jern P, Carlborg Ö, & Lind- blad-Toh K. (2015) cgmisc: enhanced genome-wide association analyses and visualization. Bioinformatics 31, 3830. 4. Höglund K, Lequarré A-S, Ljungvall I, Mc Entee K, Merveille A-C, Wiberg M, Gouni V, Lundgren Willesen J, Hanås S, Wess G, Mejer Sørensen L, Tiret L, Kierczak M, Forsberg SKG, Seppälä E, Lind- blad-Toh K, Lohi H, Chetboul V, Fredholm M, & Häggström J. (2016) Effect of Breed on Plasma Endothelin-1 Concentration, Plasma Renin Activity, and Serum Cortisol Concentration in Healthy Dogs. J. Vet. Intern. Med. 30, 566–573. 5. Zan Y, Shen X, Forsberg SKG, & Carlborg Ö. (2016) Genetic Regulation of Transcriptional Variation in Natural Arabidopsis tha- liana Accessions. G3 Genes|Genomes|Genetics 6, 2319–2328. Contents Introduction ........................................................................................ 11 Historical Background .............................................................................. 12 Genetics Terminology ............................................................................... 13 Non-additivity ........................................................................................... 13 1. Epistasis ............................................................................................ 14 2. Genetic variance heterogeneity ........................................................ 20 Present investigations ........................................................................ 24 Paper I ....................................................................................................... 24 Paper II ...................................................................................................... 27 Paper III .................................................................................................... 28 Paper IV .................................................................................................... 30 Summary and future perspectives ....................................................... 34 Supplements ........................................................................................ 38 Statistical Models ...................................................................................... 38 Acknowledgements ............................................................................ 40 References .......................................................................................... 42 Abbreviations bp basepair CMT2 chromomethylase 2 COPT6 copper transporter 6 DNA deoxyribonucleic acid GAPDH glyceraldehyde-3-phosphate dehydrogenase GWAS genome wide association study kb kilobase LD linkage disequilibrium LETM1 leucine zipper and EF-hand containing trans- membrane protein 1 MC1R melanocortin 1 receptor MOT1 molybdate transporter 1 QTL quantitative trait locus SNP single nucleotide polymorphism TE transposable element vGWAS variance heterogeneity GWAS vQTL variance heterogeneity QTL Introduction Man has probably always had some conception of inheritance. By looking around us, we realize that offspring inherit characteristics from their parents. The field of genetics involves the formal study of inheritance. As far as we know, all organisms carry a genome containing the information necessary to produce said organism. The overall goal of genetics is to understand the