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To test associations between DNA methylation levels and gene expression levels in cis (cis eQTMs), we paired each Gene to CpGs closer than 500 kb from its TSS, either upstream or downstream. For each Gene, the TSS was defined based on HTA-2.0 annotation, using the start position for transcripts in the + strand, and the end position for transcripts in the - strand. CpGs position was obtained from Illumina 450K array annotation. Only CpGs in autosomal chromosomes (from chromosome 1 to 22) were tested. In the main analysis, we fitted for each CpG-Gene pair a linear regression model between gene expression and methylation levels adjusted for age, sex, cohort, and blood cell type composition. A second model was run without adjusting for blood cellular composition and it is only reported on the online web catalog, but not discussed in this manuscript. Although some of the unique associations of the unadjusted model might be real, others might be confounded by the large methylation and expression changes among blood cell types. To ensure that CpGs paired to a higher number of Genes do not have higher chances of being part of an eQTM, multiple-testing was controlled at the CpG level, following a procedure previously applied in the Genotype-Tissue Expression (GTEx) project (Gamazon et al., 2018). Briefly, our statistic used to test the hypothesis that a pair CpG-Gene is significantly associated is based on considering the lowest p-value observed for a given CpG and all its paired Gene (e.g., those in the 1 Mb window centered at the TSS). As we do not know the distribution of this statistic under the null, we used a permutation test. We generated 100 permuted gene expression datasets and ran our previous linear regression models obtaining 100 permuted p-values for each CpG-Gene pair. Then, for each CpG, we selected among all CpG-Gene pairs the minimum p-value in each permutation and fitted a beta distribution that is the distribution we obtain when dealing with extreme values (e.g. minimum) (Dudbridge and Gusnanto, 2008). Next, for each CpG, we took the minimum p-value observed in the real data and used the beta distribution to compute the probability of observing a lower p-value. We defined this probability as the empirical p-value of the CpG. Then, we considered as significant those CpGs with empirical p-values to be significant at 5% false discovery rate using Benjamini-Hochberg method. Finally, we applied a last step to identify all significant CpG-Gene pairs for all eCpGs. To do so, we defined a genome-wide empirical p-value threshold as the empirical p-value of the eCpG closest to the 5% false discovery rate threshold. We used this empirical p-value to calculate a nominal p-value threshold for each eCpG, based on the beta distribution obtained from the minimum permuted p-values. This nominal p-value threshold was defined as the value for which the inverse cumulative distribution of the beta distribution was equal to the empirical p-value. Then, for each eCpG, we considered as significant all eCpG-Gene variants with a p-value smaller than nominal p-value. For the meQTLs catalogue, we selected 9.9 M cis and trans meQTLs with a p-value <1e-7 in the ARIES dataset consisting of data from children of 7 years old (Gaunt et al., 2016). Then, we tested whether this subset of 9.9 M SNPs were also meQTLs in HELIX by running meQTL analyses using MatrixEQTL R package (Shabalin, 2012), adjusting for cohort, sex, age, blood cellular composition and the first 20 principal components (PCs) calculated from genome-wide genetic data of the GWAS variability. We confirmed 2.8 M meQTLs in HELIX (p-value <1e-7). Trans meQTLs represented <10% of the 2.8 M meQTLs. Enrichment of eCpGs for meQTLs was computed using a Chi-square test, using non eCpGs as background. Finally, we tested whether meQTLs were also eQTLs for the eGenes linked to the eCpGs. To this end, we run eQTL analyses (gene expression being the outcome and 2.8 M SNPs the predictors) with MatrixEQTL adjusting for cohort, sex, age, blood cellular composition and the first 20 GWAS PCs in HELIX. We considered as significant eQTLs the SNP-Gene pairs with p-value <1e-7 and with the direction of the effect consistent with the direction of the meQTL and the eQTM. Background: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children’s blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods: Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results: We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGene’s TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. 40.4% of eQTMs had at least one genetic variant associated with methylation and expression levels. The overlap of autosomal cis eQTMs in children’s blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. See HELIX_Blood_eQTM_READMEfile_20210205.xlsx.

Objective: We employed Mendelian Randomization to explore whether the effects of blood pressure (BP) and BP lowering through different antihypertensive drug classes on stroke risk vary by stroke etiology. Methods: We selected genetic variants associated with systolic and diastolic BP and BP-lowering variants in genes encoding antihypertensive drug targets from a GWAS on 757,601 individuals. Applying two-sample Mendelian randomization, we examined associations with any stroke (67,162 cases; 454,450 controls), ischemic stroke and its subtypes (large artery, cardioembolic, small vessel stroke), intracerebral hemorrhage (ICH, deep and lobar), and the related small vessel disease phenotype of WMH. Results: Genetic predisposition to higher systolic and diastolic BP was associated with higher risk of any stroke, ischemic stroke, and ICH. We found associations between genetically determined BP and all ischemic stroke subtypes with a higher risk of large artery and small vessel stroke compared to cardioembolic stroke, as well as associations with deep, but not lobar ICH. Genetic proxies for calcium channel blockers, but not beta blockers, were associated with lower risk of any stroke and ischemic stroke. Proxies for CCBs showed particularly strong associations with small vessel stroke and the related radiological phenotype of WMH. Conclusions: This study supports a causal role of hypertension in all major stroke subtypes except lobar ICH. We find differences in the effects of BP and BP lowering through antihypertensive drug classes between stroke subtypes and identify calcium channel blockade as a promising strategy for preventing manifestations of cerebral small vessel disease. Objective: We employed Mendelian Randomization to explore whether the effects of blood pressure (BP) and BP lowering through different antihypertensive drug classes on stroke risk vary by stroke etiology. Methods: We selected genetic variants associated with systolic and diastolic BP and BP-lowering variants in genes encoding antihypertensive drug targets from a GWAS on 757,601 individuals. Applying two-sample Mendelian randomization, we examined associations with any stroke (67,162 cases; 454,450 controls), ischemic stroke and its subtypes (large artery, cardioembolic, small vessel stroke), intracerebral hemorrhage (ICH, deep and lobar), and the related small vessel disease phenotype of WMH. Results: Genetic predisposition to higher systolic and diastolic BP was associated with higher risk of any stroke, ischemic stroke, and ICH. We found associations between genetically determined BP and all ischemic stroke subtypes with a higher risk of large artery and small vessel stroke compared to cardioembolic stroke, as well as associations with deep, but not lobar ICH. Genetic proxies for calcium channel blockers, but not beta blockers, were associated with lower risk of any stroke and ischemic stroke. Proxies for CCBs showed particularly strong associations with small vessel stroke and the related radiological phenotype of WMH. Conclusions: This study supports a causal role of hypertension in all major stroke subtypes except lobar ICH. We find differences in the effects of BP and BP lowering through antihypertensive drug classes between stroke subtypes and identify calcium channel blockade as a promising strategy for preventing manifestations of cerebral small vessel disease. 1

The marine silicon cycle is intrinsically linked with carbon cycling in the oceans via biological production of silica by a wide range of organisms. The stable silicon isotopic composition (denoted by δ30Si) of siliceous microfossils extracted from sediment cores can be used as an archive of past oceanic silicon cycling. However, the silicon isotopic composition of biogenic silica has only been measured in diatoms, sponges and radiolarians, and isotopic fractionation relative to seawater is entirely unknown for many other silicifiers. Furthermore, the biochemical pathways and mechanisms that determine isotopic fractionation during biosilicification remain poorly understood. Here, we present the first measurements of the silicon isotopic fractionation during biosilicification by loricate choanoflagellates, a group of protists closely related to animals. We cultured two species of choanoflagellates, Diaphanoeca grandis and Stephanoeca diplocostata, which showed consistently greater isotopic fractionation (approximately −5 ‰ to −7 ‰) than cultured diatoms (−0.5 ‰ to −2.1 ‰). Instead, choanoflagellate silicon isotopic fractionation appears to be more similar to sponges grown under similar dissolved silica concentrations. Our results highlight that there is a taxonomic component to silicon isotope fractionation during biosilicification, possibly via a shared or related biochemical transport pathway. These findings have implications for the use of biogenic silica δ30Si produced by different silicifiers as proxies for past oceanic change.

Tools for complex DWI denoising using SVD shrinkage, adult and neonatal examples THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Dogs were present in the Americas prior to the arrival of European colonists, but the origin and fate of these pre-contact dogs are largely unknown. We sequenced 71 mitochondrial and seven nuclear genomes from ancient North American and Siberian dogs spanning ~9,000 years. Our analysis indicates that American dogs were not domesticated from North American wolves. Instead, American dogs form a monophyletic lineage that likely originated in Siberia and dispersed into the Americas alongside people. After the arrival of Europeans, native American dogs almost completely disappeared, leaving a minimal genetic legacy in modern dog populations. Remarkably, the closest detectable extant lineage to pre-contact American dogs is the canine transmissible venereal tumor, a contagious cancer clone derived from an individual dog that lived up to 8,000 years ago. Mitochondrial DNA FASTA fileFASTA file containing 1166 dog mtDNA genomes used in this studyfull_mtDNA_alignment.fastaNEXUS treeMaximum likelihood tree (RAxML) of 1166 dogs mtDNA genomes used in this studyfull_mtDNA_alignment.treExcel sheetPublication source of the 1166 mtDNA genomes used in this studyfull_mtDNA_alignment.xlsxPlink (bed) fileContains genotype for dogs 54 dogsfull_data.bedPlink file (bim)Contains genotype for 54 dogsfull_data.bimPlink file (fam)Contains genotype for 54 dogsfull_data.famNJ tree in Figure 2bNJ tree in Figure 2b (see Table S2 for more info)Figure_b.treNexus fileNexus file used for producing Figure S12 (MKV model in MrBayes)Binary_char_MKV.nexNEXUS treeBayesian tree in Figure S12 (see Table S2 for more info)Figure_S12.tre

The response of ATP-sensitive K+ channels (KATP) to cellular metabolism is coordinated by three classes of nucleotide binding site (NBS). We used a novel approach involving labeling of intact channels in a native, membrane environment with a non-canonical fluorescent amino acid and measurement (using FRET with fluorescent nucleotides) of steady-state and time-resolved nucleotide binding to dissect the role of NBS2 of the accessory SUR1 subunit of KATP in channel gating. Binding to NBS2 was Mg2+-independent, but Mg was required to trigger a conformational change in SUR1. Mutation of a lysine (K1384A) in NBS2 that coordinates bound nucleotides increased the EC50 for trinitrophenyl-ADP binding to NBS2, but only in the presence of Mg2+, indicating that this mutation disrupts the ligand-induced conformational change. Comparison of nucleotide-binding with ionic currents suggests a model in which each nucleotide binding event to NBS2 of SUR1 is independent and promotes KATP activation by the same amount. Puljung_data_sets

orthologous groups of genes in the H. melpomene and the H. erato transcriptomesOrthoFinder was used to identify orthologous groups of genes in the H. melpomene and the H. erato transcriptomes (options: -t 48 -a 6). 1-1 orthologous gene sequences were selected for use in subsequent analysis (Supporting Information Table S2)1_1_melpomene_erato_ortho.txtdivergence_autosomesCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratodivergence_ZCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratopolymorphism_autosomesCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratopolymorphism_autosomesCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratopolymorphism_Z.csvresults_heliconius-otherLepsOverall results for calculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. erato & other Leps for comparisonresults_heliconius-1.csvtotal_alignement_autosomes_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignement_autosomes_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignement_autosomes_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignment_Z_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignement_Z_heliconius.SFS_DoFEtotal_alignment_Z_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignement_Z_heliconius.SFS_sumtotal_alignment_Z_heliconiusCalculation of diversity and selection statistics for 1-1 ortholog alignments between H. melpomene and H. eratototal_alignement_Z_heliconius.sum Sex chromosomes have different evolutionary properties compared to autosomes due to their hemizygous nature. In particular, recessive mutations are more readily exposed to selection, which can lead to faster rates of molecular evolution. Here, we report patterns of gene expression and molecular evolution for a group of butterflies. First, we improve the completeness of the Heliconius melpomene reference annotation, a neotropical butterfly with a ZW sex determination system. Then, we analyse RNA from male and female whole abdomens and sequence female ovary and gut tissue to identify sex and tissue specific gene expression profiles in H. melpomene. Using these expression profiles we compare: 1) sequence divergence and polymorphism; 2) the strength of positive and negative selection; and 3) rates of adaptive evolution, for Z and autosomal genes between two species of Heliconius butterflies, H. melpomene and H. erato. We show that the rate of adaptive substitutions is higher for Z than autosomal genes, but contrary to expectation, it is also higher for male biased than female biased genes. Additionally, we find no significant increase in the rate of adaptive evolution or purifying selection on genes expressed in ovary tissue, a heterogametic specific tissue. Our results contribute to a growing body of literature from other ZW systems that also provide mixed evidence for a fast-Z effect where hemizygosity influences the rate of adaptive substitutions.

Full genomes location summaryTab-delimited text file detailing locations and lineages of 2,651 full-length influenza B virus genomes in this study (Fig 1 source data).fluB_location_summary.txtFull genomes time summaryTab-delimited text file detailing year of isolation and lineage of 2,651 full-length influenza B virus genomes from this study (Fig 1 source data).fluB_timeseries_summary.txtMaximum likelihood treesCompressed file of bootstrapped ML phylogenies inferred using RAxML and used to characterise influenza B virus genotypes.maximum-likelihood-trees.zipBEAST XML filesCompressed file of BEAST input files (xml) used to infer the molecular clock phylogenies as well as ancestral reconstruction and phylodynamic analysis for influenza B virus genes.beast-xml-files.zipMaximum clade credibility (MCC) treesCompressed file comprising of BEAST output MCC trees.mcc-trees.zipSummary of genotypesTab-delimited text file detailing inferred genotypes for influenza B viruses, representing over 10,000 strains including 2,651 complete genomes.genotypes-summary.txtMCC trees annotated with trunk substitutionsCompressed file containing MCC trees for B/Yamagata HA, B/Victoria HA, B/Yamagata PB1, and B/Victoria NA annotated with inferred mutations along the trunk lineages.trunk-substitutions-mcc-trees.zipInput files for antigenic analysisCompressed file comprising of: tab-delimited HI data file, BEAST XML file for generation of set of empirical trees and XML file for running BMDS models for B/Yamagata and B/Victoria.antigenic-evolution-input.zipOutput files from antigenic analysisCompressed file containing MCC trees from BMDS analysis (source data for Figure 4) and tab-delimited file summaries of mean antigenic distance from phylogenetic root inferred across 2,000 posterior trees to calculate mean antigenic drift rates (source data for Table 2). Posterior trees files were too large (>50 MB in compressed form each) to be included.antigenic-evolution-output.zip The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally.