For many crops, wild relatives constitute an extraordinary resource for cultivar improvement [1, 2] and also help to better understand the history of their domestication [3]. However, the wild ancestor species of several perennial crops have not yet been identified. Perennial crops generally present a weak domestication syndrome allowing cultivated individuals to establish feral populations difficult to distinguish from truly wild populations, and there is frequently ongoing gene flow between wild relatives and the crop that might erode most genetic differences [4]. Here we report the discovery of populations of the wild ancestor species of the date palm (Phoenix dactylifera L.), one of the oldest and most important cultivated fruit plants in hot and arid regions of the Old World. We discovered these wild individuals in remote and isolated mountainous locations of Oman. They are genetically more diverse than and distinct from a representative sample of Middle Eastern cultivated date palms and exhibit rounded seed shapes resembling those of a close sister species and archeological samples, but not modern cultivars. Whole-genome sequencing of several wild and cultivated individuals revealed a complex domestication history involving the contribution of at least two wild sources to African cultivated date palms. The discovery of wild date palms offers a unique chance to further elucidate the history of this iconic crop that has constituted the cornerstone of traditional oasis polyculture systems for several thousand years [5].

Studying repeated adaptation can provide insights into the mechanisms allowing species to adapt to novel environments. Here, we investigate repeated evolution driven by habitat specialization in the common bottlenose dolphin. Parapatric pelagic and coastal ecotypes of common bottlenose dolphins have repeatedly formed across the oceans. Analyzing whole genomes of 57 individuals, we find that ecotype evolution involved a complex reticulated evolutionary history. We find parallel linked selection acted upon ancient alleles in geographically distant coastal populations, which were present as standing genetic variation in the pelagic populations. Candidate loci evolving under parallel linked selection were found in ancient tracts, suggesting recurrent bouts of selection through time. Therefore, despite the constraints of small effective population size and long generation time on the efficacy of selection, repeated adaptation in long-lived social species can be driven by a combination of ecological opportunities and selection acting on ancestral standing genetic variation.

Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10−8) lead SNPs—one at FURIN (rs11372849; p = 9.54 × 10−10) and two OPRM1 variants (rs1799971, p = 4.92 × 10−09; rs79704991, p = 1.11 × 10−08; r2 = 0.02). Rs1799971 (p = 4.91 × 10−08) and another OPRM1 variant (rs9478500; p = 1.95 × 10−08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10−47) and AUD (rg = 0.77; p = 6.36 × 10−78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10−16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10−13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

BackgroundDespite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci.MethodsWe performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program (MVP), Psychiatric Genomics Consortium (PGC), iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N=639,709 (Ncases=20,858) across ancestries. OUD cases were defined as having lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD).ResultsThe EUR meta-analysis identified three genome-wide significant (GWS; p≤5×10−8) lead SNPs—one at FURIN (rs11372849; p=9.54×10−10) and two OPRM1 variants (rs1799971, p=4.92×10−09 ; rs79704991, p=1.37×10−08; r2=0.02). Rs1799971 (p=4.91×10−08) and another OPRM1 variant (rs9478500; p=1.95×10−8; r2=0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg =0.82; p=1.14×10−47) and AUD (rg=0.77; p=6.36×10−78). The OUD-MTAG resulted in 18 GWS loci, all of which map to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes.ConclusionsWe identified multiple OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allele frequency differences among populations connected by migration is the F-model, which measures differences in allele frequencies by population specific FST coefficients. This model readily accounts for multiple evolutionary forces by partitioning FST coefficients into locus and population specific components reflecting selection and drift, respectively. Here we present an extension of this model to linked loci by means of a hidden Markov model (HMM), which characterizes the effect of selection on linked markers through correlations in the locus specific component along the genome. Using extensive simulations we show that the statistical power of our method is up to two-fold that of previous implementations that assume sites to be independent. We finally evidence selection in the human genome by applying our method to data from the Human Genome Diversity Project (HGDP).

ImportanceAlcohol genome-wide association studies (GWASs) have generally focused on alcohol consumption and alcohol use disorder (AUD); few have examined habitual drinking behaviors like maximum habitual alcohol intake (MaxAlc).ObjectivesTo identify genetic loci associated with MaxAlc and to elucidate the genetic architecture across alcohol traits.Design, Setting, and ParticipantsThis MaxAlc genetic association study was performed among Million Veteran Program participants enrolled from January 10, 2011, to September 30, 2020. Ancestry-specific GWASs were conducted in participants with European (n = 218 623) and African (n = 29 132) ancestry, then meta-analyzed (N = 247 755). Linkage-disequilibrium score regression was used to estimate single nucleotide variant (SNV)–heritability and genetic correlations (rg) with other alcohol and psychiatric traits. Genomic structural equation modeling (gSEM) was used to evaluate genetic associations between MaxAlc and other alcohol traits. Mendelian randomization was used to examine potential causal relationships between MaxAlc and liver enzyme levels. MTAG (multitrait analysis of GWAS) was used to analyze MaxAlc and problematic alcohol use (PAU) jointly.ExposuresGenetic associations.Main Outcomes and MeasuresMaxAlc was defined from the following survey item: “in a typical month, what is/was the largest number of drinks of alcohol you may have had in one day?” with ordinal responses from 0 to 15 or more drinks.ResultsGWASs were conducted on sample sizes of as many as 247 455 US veterans. Participants were 92.68% male and had mean (SD) age of 65.92 (11.70) years. The MaxAlc GWAS resulted in 15 genome-wide significant loci. Top associations in European-ancestry and African-ancestry participants were with known functional variants in the ADH1B gene, namely rs1229984 (P = 3.12 × 10−101) and rs2066702 (P = 6.30 × 10−17), respectively. Novel associations were also found. SNV-heritability was 6.65% (SE, 0.41) in European-ancestry participants and 3.42% (SE, 1.46) in African-ancestry participants. MaxAlc was positively correlated with PAU (rg = 0.79; P = 3.95 × 10−149) and AUD (rg = 0.76; P = 1.26 × 10−127) and had negative rg with the UK Biobank “alcohol usually taken with meals” (rg = −0.53; P = 1.40 × 10−50). For psychiatric traits, MaxAlc had the strongest genetic correlation with suicide attempt (rg = 0.40; P = 3.02 × 10−21). gSEM supported a 2-factor model with MaxAlc loading on a factor with PAU and AUD and other alcohol consumption measures loading on a separate factor. Mendelian randomization supported an association between MaxAlc and the liver enzyme gamma-glutamyltransferase (β = 0.012; P = 2.66 × 10−10). MaxAlc MTAG resulted in 31 genome-wide significant loci.Conclusions and RelevanceThe findings suggest that MaxAlc closely aligns genetically with PAU traits. This study improves understanding of the mechanisms associated with normative alcohol consumption vs problematic habitual use and AUD as well as how MaxAlc relates to psychiatric and medical conditions genetically and biologically.