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Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population stratification. More generally, our results imply that typical constructions of polygenic scores are sensitive to population stratification and that population-level differences should be interpreted with caution. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter). Peer reviewed

We analyse new genomic data (0.05–2.95x) from 14 ancient individuals from Portugal distributed from the Middle Neolithic (4200–3500 BC) to the Middle Bronze Age (1740–1430 BC) and impute genomewide diploid genotypes in these together with published ancient Eurasians. While discontinuity is evident in the transition to agriculture across the region, sensitive haplotype-based analyses suggest a significant degree of local hunter-gatherer contribution to later Iberian Neolithic populations. A more subtle genetic influx is also apparent in the Bronze Age, detectable from analyses including haplotype sharing with both ancient and modern genomes, D-statistics and Y-chromosome lineages. However, the limited nature of this introgression contrasts with the major Steppe migration turnovers within third Millennium northern Europe and echoes the survival of non-Indo-European language in Iberia. Changes in genomic estimates of individual height across Europe are also associated with these major cultural transitions, and ancestral components continue to correlate with modern differences in stature. Index for VCF fileIndex for VCF filepost_imputation_Martiniano_et_al_2017_public.vcf.gz.tbiVCF file containing imputed genotype data belonging to 67 newly sequenced and publicly available ancient samples.VCF file containing imputed genotype data belonging to 67 newly sequenced and publicly available ancient samples which we analysed in Martiniano et al. (2017).post_imputation_Martiniano_et_al_2017_public.vcf.gzREADME_Martiniano_et_al_2017Description of the methods used for genotype imputation.

UK Biobank custom height association statistics on ~700k genotyped SNPsThe zip file contains six files: (1) ukb_cal_v2_height_allancestry_10pcs_assoc_linear.tsv (2) ukb_cal_v2_height_allancestry_nopcs_assoc_linear.tsv (3) ukb_cal_v2_height_britishancestry_10pcs_assoc_linear.tsv (4) ukb_cal_v2_height_britishancestry_nopcs_assoc_linear.tsv (5) ukb_cal_v2_height_sibs_perm_qfam.tsv (6) ukb_cal_v2_height_wbsibs_perm_qfam.tsv (1) - (4) are height GWAS estimates on all samples / white British samples using 10 PCs as covariates or no PCs as covariates. Sex was included as covariate in all analyses. (3) is equivalent to the UK Biobank height GWAS from the Neale lab. The remaining small differences can be explained by genotype differences in the UK Biobank imputed data and genotyped data. (5) and (6) are family based estimates from 20166 sibling pairs of any ancestry (5) and 17358 sibling pairs where both siblings are of white British ancestry (6) in the UK Biobank. Pairs of samples with IBS0 > 0.0018 and Kinship coefficient > 0.185 were identified as sibling pairs. For the analyses in Sohail, Maier et al., only the subset of ~300,000 SNPs with SDS scores was used. For a description of the columns in files (1)-(4) please see the PLINK documentation for the ‘--linear’ command. Column “A2” has been added and denotes the non-effect allele. For a description of the columns in files (5) and (6) please see the PLINK documentation for the ‘--qfam’ command. Column “A2” has been added and denotes the non-effect allele. “EMP1” and “NP” refer to permutation p-value and number of permutations, respectively. Please note: These data are derived from the UK Biobank Resource under Application Number 18597.sohail_maier_2018.zip Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure. More generally, our results imply that typical constructions of polygenic scores are sensitive to population structure and that population-level differences should be interpreted with caution.

We analyse new genomic data (0.05-2.95x) from 14 ancient individuals from Portugal distributed from the Middle Neolithic (4200-3500 BC) to the Middle Bronze Age (1740-1430 BC) and impute genomewide diploid genotypes in these together with published ancient Eurasians. While discontinuity is evident in the transition to agriculture across the region, sensitive haplotype-based analyses suggest a significant degree of local hunter-gatherer contribution to later Iberian Neolithic populations. A more subtle genetic influx is also apparent in the Bronze Age, detectable from analyses including haplotype sharing with both ancient and modern genomes, D-statistics and Y-chromosome lineages. However, the limited nature of this introgression contrasts with the major Steppe migration turnovers within third Millennium northern Europe and echoes the survival of non-Indo-European language in Iberia. Changes in genomic estimates of individual height across Europe are also associated with these major cultural transitions, and ancestral components continue to correlate with modern differences in stature. BEAN project of the Marie Curie Initial Training Network [289966]; Irish Research Council Government of Ireland Scholarship Scheme [GOIPG/2013/1219] info:eu-repo/semantics/publishedVersion

S.J.O., T.W.J.G., L.Br., A.Lo., A.A.C., D.S.S., E.A.C., C.M., J.B., D.M.A., F.C., and M.C.F. were supported through NERC (standard grant NE/K014455/1). S.J.O. acknowledges a Microsoft Azure for Research Sponsorship (subscription ID: ab7cd695-49cf-4a83-910a-ef71603e708b). T.W.J.G., A.Lo., A.A.C., D.S.S., E.A.C., C.M., J.B., D.M.A., F.C., and M.C.F. were also supported by the EU BiodivERsA scheme (RACE, funded through NERC directed grant NE/G002193/1 and ANR08-Biodiversa-002-03) and NERC (standard grant NE/K012509/1). M.C.F., E.A.C., and C.M. acknowledge the Nouragues Travel Grant Program 2014. R.A.F. was supported by an MIT/Wellcome Trust Fellowship. T.W.J.G. was supported by the People’s Trust for Endangered Species and the Morris Animal Foundation (D12ZO002). J.M.G.S. and M.C.F. were supported by the Leverhulme Trust (RPG-2014-273) and the Morris Animal Foundation (D16ZO-022). F.B. was supported by the ERC (grant ERC 260801–Big_Idea). D.M.A. was funded by Wellcome Trust grant 099202. J.V. was supported by the Hungarian Scientific Research Fund (OTKA K77841) and Bolyai János Research Scholarship, Hungarian Academy of Sciences (BO/00579/14/8). D.J.G. was supported by the Conservation Leadership Programme (grant 0134010) with additional assistance from F. Gebresenbet, R. Kassahun, and S. P. Loader. C.S.-A. was supported by Fondecyt Nº11140902 and 1181758. T.M.D.-B. was supported by the Royal Geographical Society and the Royal Zoological Society of Scotland with assistance from M. Hirschfeld and the Budongo Conservation Field Station. B.W. was supported by the National Research Foundation of Korea (2015R1D1A1A01057282). L.F.T. was supported by FAPESP (#2016/25358-3) and CNPq (#300896/2016-6). L.Be., L.F.S., and R.J.W. were supported by the Australian Research Council (FT100100375, DP120100811). A.A.C. was supported by a Royal Society Wolfson Research Merit award. J.H., A.La., and S.M. were funded by the Swedish Research Council Formas (grant no. 2013- 1389-26445-20). C.W. was funded by the National Research Foundation, South Africa. T.Y.J. and T.S.J. acknowledge NSF grant DEB-1601259. W.E.H. was funded by the NSERC Strategic and Discovery grant programs Globalized infectious diseases are causing species declines worldwide, but their source often remains elusive. We used whole-genome sequencing to solve the spatiotemporal origins of the most devastating panzootic to date, caused by the fungus Batrachochytrium dendrobatidis, a proximate driver of global amphibian declines. We traced the source of B. dendrobatidis to the Korean peninsula, where one lineage, BdASIA-1, exhibits the genetic hallmarks of an ancestral population that seeded the panzootic. We date the emergence of this pathogen to the early 20th century, coinciding with the global expansion of commercial trade in amphibians, and we show that intercontinental transmission is ongoing. Our findings point to East Asia as a geographic hotspot for B. dendrobatidis biodiversity and the original source of these lineages that now parasitize amphibians worldwide.

UKBB_noPCsA GWAS for human height in the UK Biobank. Linear regression without any structure correction---with only genotype, age, sex and sequencing array as covariates (unrelated British ancestry individuals only). See the paper for the plink command and more details.UKBB_sib_gwasA GWAS for human height in the UK Biobank sibs. Family-based sib-pair analysis. See the paper for the plink command and more details.IRL-GBR allele frequency differencesLogistic regression using self-identified as "White British" or "White Irish" in the UK Biobank were compared with distinct phenotype labels. See paper for plink command line and more details.BvI.nocovar.Irish.glm.logistic.gzGBR-TSI allele frequency differencesIndividuals from the GBR and TSI populations from 1000G Phase 3 were assigned binary phenotype labels and a chi square test was performed for allele frequency differences. See paper for the plink command line and more details.gwas.hwe1e6.geno05.nocovar.chisq.British.assoc.gzUK Biobank Acknowledgement Several recent papers have reported strong signals of selection on European polygenic height scores. These analyses used height effect estimates from the GIANT consortium and replication studies. Here, we describe a new analysis based on the the UK Biobank (UKB), a large, independent dataset. We find that the signals of selection using UKB effect estimates are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification. Therefore, the conclusion of strong polygenic adaptation now lacks support. Moreover, these discrepancies highlight (1) that methods for correcting for population stratification in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of differences in polygenic scores between populations should be treated with caution until these issues are better understood.