{"entity": "researcher", "timestamp": "2026-08-11T15:15:37.893Z", "family": "Bailey", "given": "Mark E S", "initials": "MES", "orcid": "0000-0002-9788-2278", "affiliations": [], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/3919edd84f254870a5644770152360b6.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/3919edd84f254870a5644770152360b6"}}, "publications": [{"entity": "publication", "iuid": "2e2f52aecc4a4656a0714ceb413d1ac4", "links": {"self": {"href": "https://publications.scilifelab.se/publication/2e2f52aecc4a4656a0714ceb413d1ac4.json"}, "display": {"href": "https://publications.scilifelab.se/publication/2e2f52aecc4a4656a0714ceb413d1ac4"}}, "title": "Adaptive Introgression Facilitates Adaptation to High Latitudes in European Aspen (Populus tremula L.).", "authors": [{"family": "Rend\u00f3n-Anaya", "given": "Martha", "initials": "M"}, {"family": "Wilson", "given": "Jonathan", "initials": "J"}, {"family": "Sveinsson", "given": "S\u00e6mundur", "initials": "S"}, {"family": "Fedorkov", "given": "Aleksey", "initials": "A"}, {"family": "Cottrell", "given": "Joan", "initials": "J"}, {"family": "Bailey", "given": "Mark E S", "initials": "MES", "orcid": "0000-0002-9788-2278", "researcher": {"href": "https://publications.scilifelab.se/researcher/3919edd84f254870a5644770152360b6.json"}}, {"family": "Ru\u0146is", "given": "Dainis", "initials": "D"}, {"family": "Lexer", "given": "Christian", "initials": "C"}, {"family": "Jansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-7906-6891", "researcher": {"href": "https://publications.scilifelab.se/researcher/fb9d3c17f4514903b3731d15c622a53d.json"}}, {"family": "Robinson", "given": "Kathryn M", "initials": "KM"}, {"family": "Street", "given": "Nathaniel R", "initials": "NR", "orcid": "0000-0001-6031-005X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cb9ceb237a724046a1454179a32de1b0.json"}}, {"family": "Ingvarsson", "given": "P\u00e4r K", "initials": "PK", "orcid": "0000-0001-9225-7521", "researcher": {"href": "https://publications.scilifelab.se/researcher/52a2c210ff754465a69f839b40fe8312.json"}}], "type": "journal article", "published": "2021-10-27", "journal": {"title": "Mol. Biol. Evol.", "issn": "1537-1719", "volume": "38", "issue": "11", "pages": "5034-5050", "issn-l": "0737-4038"}, "abstract": "Understanding local adaptation has become a key research area given the ongoing climate challenge and the concomitant requirement to conserve genetic resources. Perennial plants, such as forest trees, are good models to study local adaptation given their wide geographic distribution, largely outcrossing mating systems, and demographic histories. We evaluated signatures of local adaptation in European aspen (Populus tremula) across Europe by means of whole-genome resequencing of a collection of 411 individual trees. We dissected admixture patterns between aspen lineages and observed a strong genomic mosaicism in Scandinavian trees, evidencing different colonization trajectories into the peninsula from Russia, Central and Western Europe. As a consequence of the secondary contacts between populations after the last glacial maximum, we detected an adaptive introgression event in a genome region of \u223c500 kb in chromosome 10, harboring a large-effect locus that has previously been shown to contribute to adaptation to the short growing seasons characteristic of Northern Scandinavia. Demographic simulations and ancestry inference suggest an Eastern origin-probably Russian-of the adaptive Nordic allele which nowadays is present in a homozygous state at the north of Scandinavia. The strength of introgression and positive selection signatures in this region is a unique feature in the genome. Furthermore, we detected signals of balancing selection, shared across regional populations, that highlight the importance of standing variation as a primary source of alleles that facilitate local adaptation. Our results, therefore, emphasize the importance of migration-selection balance underlying the genetic architecture of key adaptive quantitative traits.", "doi": "10.1093/molbev/msab229", "pmid": "34329481", "labels": {"National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Production)": "Service", "NGI Stockholm (Genomics Applications)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "6332012"}, {"db": "pmc", "key": "PMC8557470"}], "notes": [], "created": "2021-10-01T09:02:36.794Z", "modified": "2024-01-16T13:48:38.184Z"}, {"entity": "publication", "iuid": "2cb43ab5664d469db94c06796aaa296d", "links": {"self": {"href": "https://publications.scilifelab.se/publication/2cb43ab5664d469db94c06796aaa296d.json"}, "display": {"href": "https://publications.scilifelab.se/publication/2cb43ab5664d469db94c06796aaa296d"}}, "title": "Leaf shape in Populus tremula is a complex, omnigenic trait.", "authors": [{"family": "M\u00e4hler", "given": "Niklas", "initials": "N", "orcid": "0000-0003-2673-9113", "researcher": {"href": "https://publications.scilifelab.se/researcher/581734b34e9948438243f0c105e1094f.json"}}, {"family": "Schiffthaler", "given": "Bastian", "initials": "B", "orcid": "0000-0002-9771-467X", "researcher": {"href": "https://publications.scilifelab.se/researcher/12527c57f62e4a46b758e061ba3f80b1.json"}}, {"family": "Robinson", "given": "Kathryn M", "initials": "KM", "orcid": "0000-0002-5249-604X", "researcher": {"href": "https://publications.scilifelab.se/researcher/56d40626e73d49799c175a2ea14f5626.json"}}, {"family": "Terebieniec", "given": "Barbara K", "initials": "BK"}, {"family": "Vu\u010dak", "given": "Matej", "initials": "M", "orcid": "0000-0002-3181-2808", "researcher": {"href": "https://publications.scilifelab.se/researcher/4e64ed41987741f392a5c352ec92480a.json"}}, {"family": "Mannapperuma", "given": "Chanaka", "initials": "C"}, {"family": "Bailey", "given": "Mark E S", "initials": "MES", "orcid": "0000-0002-9788-2278", "researcher": {"href": "https://publications.scilifelab.se/researcher/3919edd84f254870a5644770152360b6.json"}}, {"family": "Jansson", "given": "Stefan", "initials": "S", "orcid": "0000-0002-7906-6891", "researcher": {"href": "https://publications.scilifelab.se/researcher/fb9d3c17f4514903b3731d15c622a53d.json"}}, {"family": "Hvidsten", "given": "Torgeir R", "initials": "TR", "orcid": "0000-0001-6097-2539", "researcher": {"href": "https://publications.scilifelab.se/researcher/987fbb5763c74f6895bee64630528d8d.json"}}, {"family": "Street", "given": "Nathaniel R", "initials": "NR", "orcid": "0000-0001-6031-005X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cb9ceb237a724046a1454179a32de1b0.json"}}], "type": "journal article", "published": "2020-11-00", "journal": {"title": "Ecol Evol", "issn": "2045-7758", "volume": "10", "issue": "21", "pages": "11922-11940", "issn-l": "2045-7758"}, "abstract": "Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome-wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA-Seq data that we used to perform gene co-expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population-wide co-expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small-effect variations in gene expression. Genes associated with shape variation were peripheral within the population-wide co-expression network, were not highly connected within the leaf development co-expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.", "doi": "10.1002/ece3.6691", "pmid": "33209260", "labels": {"NGI Stockholm (Genomics Production)": "Service", "National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "ECE36691"}, {"db": "pmc", "key": "PMC7663049"}, {"db": "Dryad", "key": "10.5061/dryad.3n5tb2rdt"}], "notes": [], "created": "2020-12-07T16:34:40.237Z", "modified": "2024-01-16T13:48:41.464Z"}, {"entity": "publication", "iuid": "5c89b2604ecd4e0eb9cbc8a13f7b3b5a", "links": {"self": {"href": "https://publications.scilifelab.se/publication/5c89b2604ecd4e0eb9cbc8a13f7b3b5a.json"}, "display": {"href": "https://publications.scilifelab.se/publication/5c89b2604ecd4e0eb9cbc8a13f7b3b5a"}}, "title": "Genetic variation in CADM2 as a link between psychological traits and obesity.", "authors": [{"family": "Morris", "given": "Julia", "initials": "J"}, {"family": "Bailey", "given": "Mark E S", "initials": "MES", "orcid": "0000-0002-9788-2278", "researcher": {"href": "https://publications.scilifelab.se/researcher/3919edd84f254870a5644770152360b6.json"}}, {"family": "Baldassarre", "given": "Damiano", "initials": "D"}, {"family": "Cullen", "given": "Breda", "initials": "B", "orcid": "0000-0002-7259-9505", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff824f9a62154c718c075ad56b01177b.json"}}, {"family": "de Faire", "given": "Ulf", "initials": "U"}, {"family": "Ferguson", "given": "Amy", "initials": "A"}, {"family": "Gigante", "given": "Bruna", "initials": "B", "orcid": "0000-0003-4508-7990", "researcher": {"href": "https://publications.scilifelab.se/researcher/3ac1bdc52e3241ea9eb5645f603229a3.json"}}, {"family": "Giral", "given": "Philippe", "initials": "P"}, {"family": "Goel", "given": "Anuj", "initials": "A"}, {"family": "Graham", "given": "Nicholas", "initials": "N"}, {"family": "Hamsten", "given": "Anders", "initials": "A"}, {"family": "Humphries", "given": "Steve E", "initials": "SE"}, {"family": "Johnston", "given": "Keira J A", "initials": "KJA", "orcid": "0000-0002-1370-3149", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff151def49174d388b1b3e8619c2b329.json"}}, {"family": "Lyall", "given": "Donald M", "initials": "DM", "orcid": "0000-0003-3850-1487", "researcher": {"href": "https://publications.scilifelab.se/researcher/f1b08351693e4fb5b387edd6d9a9d347.json"}}, {"family": "Lyall", "given": "Laura M", "initials": "LM"}, {"family": "Sennblad", "given": "Bengt", "initials": "B"}, {"family": "Silveira", "given": "Angela", "initials": "A"}, {"family": "Smit", "given": "Andries J", "initials": "AJ"}, {"family": "Tremoli", "given": "Elena", "initials": "E"}, {"family": "Veglia", "given": "Fabrizio", "initials": "F"}, {"family": "Ward", "given": "Joey", "initials": "J"}, {"family": "Watkins", "given": "Hugh", "initials": "H"}, {"family": "Smith", "given": "Daniel J", "initials": "DJ", "orcid": "0000-0002-2267-1951", "researcher": {"href": "https://publications.scilifelab.se/researcher/1bba9787f512483d8eaf6cffc8743271.json"}}, {"family": "Strawbridge", "given": "Rona J", "initials": "RJ", "orcid": "0000-0001-8506-3585", "researcher": {"href": "https://publications.scilifelab.se/researcher/8ac5060a3b37466dae002d4ad8f4d0ac.json"}}], "type": "journal article", "published": "2019-05-14", "journal": {"volume": "9", "issn": "2045-2322", "issue": "1", "pages": "7339", "title": "Sci Rep", "issn-l": "2045-2322"}, "abstract": "CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 \u00d7 10 -5) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 \u00d7 10-5) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.", "doi": "10.1038/s41598-019-43861-9", "pmid": "31089183", "labels": {"National Genomics Infrastructure": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service"}, "xrefs": [{"db": "pii", "key": "10.1038/s41598-019-43861-9"}, {"db": "pmc", "key": "PMC6517397"}], "notes": [], "created": "2019-05-24T13:45:02.246Z", "modified": "2021-06-16T14:52:17.199Z"}]}