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Genome technologies have defined a complex genetic architecture in major infectious, inflammatory, and autoimmune disorders. High density marker arrays and Immunochips have powered genome-wide association studies (GWAS) that have mapped nearly 450 genetic risk loci in 22 major inflammatory diseases, including a core of common genes that play a central role in pathological inflammation. Whole-exome and whole-genome sequencing have identified more than 265 genes in which mutations cause primary immunodeficiencies and rare forms of severe inflammatory bowel disease. Combined analysis of inflammatory disease GWAS and primary immunodeficiencies point to shared proteins and pathways that are required for immune cell development and protection against infections and are also associated with pathological inflammation. Finally, sequencing of chromatin immunoprecipitates containing specific transcription factors, with parallel RNA sequencing, has charted epigenetic regulation of gene expression by proinflammatory transcription factors in immune cells, providing complementary information to characterize morbid genes at infectious and inflammatory disease loci.
Assuntos
Doenças Autoimunes/genética , Síndromes de Imunodeficiência/genética , Infecções/genética , Inflamação/genética , Vacinas/imunologia , Animais , Epigênese Genética , Exoma/genética , Estudos de Associação Genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Imunidade/genética , Infecções/imunologia , RiscoRESUMO
Genome-wide association studies (GWAS) have revealed risk alleles for ulcerative colitis (UC). To understand their cell type specificities and pathways of action, we generate an atlas of 366,650 cells from the colon mucosa of 18 UC patients and 12 healthy individuals, revealing 51 epithelial, stromal, and immune cell subsets, including BEST4+ enterocytes, microfold-like cells, and IL13RA2+IL11+ inflammatory fibroblasts, which we associate with resistance to anti-TNF treatment. Inflammatory fibroblasts, inflammatory monocytes, microfold-like cells, and T cells that co-express CD8 and IL-17 expand with disease, forming intercellular interaction hubs. Many UC risk genes are cell type specific and co-regulated within relatively few gene modules, suggesting convergence onto limited sets of cell types and pathways. Using this observation, we nominate and infer functions for specific risk genes across GWAS loci. Our work provides a framework for interrogating complex human diseases and mapping risk variants to cell types and pathways.
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Colite Ulcerativa/patologia , Colo/metabolismo , Adulto , Idoso , Anticorpos Monoclonais/uso terapêutico , Bestrofinas/metabolismo , Antígenos CD8/metabolismo , Estudos de Casos e Controles , Colite Ulcerativa/tratamento farmacológico , Colite Ulcerativa/metabolismo , Colo/patologia , Enterócitos/citologia , Enterócitos/metabolismo , Feminino , Loci Gênicos , Estudo de Associação Genômica Ampla , Humanos , Interleucina-17/metabolismo , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Linfócitos T/citologia , Linfócitos T/metabolismo , Trombospondinas/metabolismo , Fator de Necrose Tumoral alfa/imunologia , Fator de Necrose Tumoral alfa/metabolismo , Adulto JovemRESUMO
Age-related hearing loss (ARHL) is a prevalent concern in the elderly population. Recent genome-wide and phenome-wide association studies (GWASs and PheWASs) have delved into the identification of causative variants and the understanding of pleiotropy, highlighting the polygenic intricacies of this complex condition. While recent large-scale GWASs have pinpointed significant SNPs and risk variants associated with ARHL, the detailed mechanisms, encompassing both genetic and epigenetic modifications, remain to be fully elucidated. This review presents the latest advances in association studies, integrating findings from both human studies and model organisms. By juxtaposing historical perspectives with contemporary genomics, we aim to catalyze innovative research and foster the development of novel therapeutic strategies for ARHL.
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Presbiacusia , Humanos , Idoso , Presbiacusia/genética , Presbiacusia/epidemiologia , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
Mass coral bleaching is one of the clearest threats of climate change to the persistence of marine biodiversity. Despite the negative impacts of bleaching on coral health and survival, some corals may be able to rapidly adapt to warming ocean temperatures. Thus, a significant focus in coral research is identifying the genes and pathways underlying coral heat adaptation. Here, we review state-of-the-art methods that may enable the discovery of heat-adaptive loci in corals and identify four main knowledge gaps. To fill these gaps, we describe an experimental approach combining seascape genomics with CRISPR/Cas9 gene editing to discover and validate heat-adaptive loci. Finally, we discuss how information on adaptive genotypes could be used in coral reef conservation and management strategies.
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Antozoários , Animais , Antozoários/genética , Recifes de Corais , Temperatura , Genótipo , Mudança ClimáticaRESUMO
Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.
Assuntos
Estudo de Associação Genômica Ampla , Locos de Características Quantitativas , Humanos , Locos de Características Quantitativas/genética , Estudo de Associação Genômica Ampla/métodos , Predisposição Genética para Doença , Polimorfismo de Nucleotídeo Único/genética , Redes Reguladoras de Genes/genéticaRESUMO
The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function.
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Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.
Assuntos
Frequência do Gene , Genótipo , Polimorfismo de Nucleotídeo Único , Software , Humanos , Estudos de Coortes , Desequilíbrio de Ligação , Estudo de Associação Genômica Ampla/métodos , Genoma Humano , Controle de Qualidade , Aprendizado de Máquina , Sequenciamento Completo do Genoma/normas , Sequenciamento Completo do Genoma/métodosRESUMO
Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.
Assuntos
Bancos de Espécimes Biológicos , Estudo de Associação Genômica Ampla , Herança Multifatorial , Humanos , Herança Multifatorial/genética , Fenótipo , Diabetes Mellitus Tipo 1/genética , Polimorfismo de Nucleotídeo Único , Aprendizado de MáquinaRESUMO
Single-nucleotide polymorphisms in ETS1 are associated with systemic lupus erythematosus (SLE). Ets1-/- mice develop SLE-like symptoms, suggesting that dysregulation of this transcription factor is important to the onset or progression of SLE. We used conditional deletion approaches to examine the impact of Ets1 expression in different immune cell types. Ets1 deletion on CD4+ T cells, but not B cells or dendritic cells, resulted in the SLE autoimmunity, and this was associated with the spontaneous expansion of T follicular helper type 2 (Tfh2) cells. Ets1-/- Tfh2 cells exhibited increased expression of GATA-3 and interleukin-4 (IL-4), which induced IgE isotype switching in B cells. Neutralization of IL-4 reduced Tfh2 cell frequencies and ameliorated disease parameters. Mechanistically, Ets1 suppressed signature Tfh and Th2 cell genes, including Cxcr5, Bcl6, and Il4ra, thus curbing the terminal Tfh2 cell differentiation process. Tfh2 cell frequencies in SLE patients correlated with disease parameters, providing evidence for the relevance of these findings to human disease.
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Diferenciação Celular/imunologia , Lúpus Eritematoso Sistêmico/imunologia , Proteína Proto-Oncogênica c-ets-1/imunologia , Células Th2/imunologia , Animais , Autoimunidade/genética , Autoimunidade/imunologia , Linfócitos B/imunologia , Linfócitos B/metabolismo , Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD4-Positivos/metabolismo , Diferenciação Celular/genética , Proliferação de Células/efeitos dos fármacos , Proliferação de Células/genética , Expressão Gênica/imunologia , Perfilação da Expressão Gênica , Humanos , Lúpus Eritematoso Sistêmico/genética , Lúpus Eritematoso Sistêmico/metabolismo , Camundongos Endogâmicos C57BL , Camundongos Knockout , Camundongos Transgênicos , Proteína Proto-Oncogênica c-ets-1/genética , Proteína Proto-Oncogênica c-ets-1/metabolismo , Células Th2/metabolismoRESUMO
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
Assuntos
Biomarcadores , Estudo de Associação Genômica Ampla , Inflamação , Medicina de Precisão , Sequenciamento Completo do Genoma , Humanos , Medicina de Precisão/métodos , Inflamação/genética , Estudo de Associação Genômica Ampla/métodos , Sequenciamento Completo do Genoma/métodos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Predisposição Genética para Doença , Feminino , Interleucina-6/genéticaRESUMO
Distilling insomnia genome-wide association study (GWAS) variants, Palermo and colleagues identified several genes that participate in sleep regulation in two different model organisms. This workflow sets off an innovative strategy to extract biological relevance from large human genomic databases.
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Estudo de Associação Genômica Ampla , Locos de Características Quantitativas , Humanos , Fenótipo , Sono/genética , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
Polygenic risk score (PRS) has demonstrated its great utility in biomedical research through identifying high-risk individuals for different diseases from their genotypes. However, the broader application of PRS to the general population is hindered by the limited transferability of PRS developed in Europeans to non-European populations. To improve PRS prediction accuracy in non-European populations, we develop a statistical method called SDPRX that can effectively integrate genome wide association study summary statistics from different populations. SDPRX automatically adjusts for linkage disequilibrium differences between populations and characterizes the joint distribution of the effect sizes of a variant in two populations to be both null, population specific, or shared with correlation. Through simulations and applications to real traits, we show that SDPRX improves the prediction performance over existing methods in non-European populations.
Assuntos
Estudo de Associação Genômica Ampla , Herança Multifatorial , Humanos , Herança Multifatorial/genética , Estudo de Associação Genômica Ampla/métodos , Predisposição Genética para Doença , Fatores de Risco , GenótipoRESUMO
Response to the anti-IL17 monoclonal antibody secukinumab is heterogeneous, and not all participants respond to treatment. Understanding whether this heterogeneity is driven by genetic variation is a key aim of pharmacogenetics and could influence precision medicine approaches in inflammatory diseases. Using changes in disease activity scores across 5,218 genotyped individuals from 19 clinical trials across four indications (psoriatic arthritis, psoriasis, ankylosing spondylitis, and rheumatoid arthritis), we tested whether genetics predicted response to secukinumab. We did not find any evidence of association between treatment response and common variants, imputed HLA alleles, polygenic risk scores of disease susceptibility, or cross-disease components of shared genetic risk. This suggests that anti-IL17 therapy is equally effective regardless of an individual's genetic background, a finding that has important implications for future genetic studies of biological therapy response in inflammatory diseases.
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Artrite Psoriásica , Artrite Reumatoide , Psoríase , Humanos , Artrite Psoriásica/tratamento farmacológico , Artrite Psoriásica/genética , Psoríase/tratamento farmacológico , Psoríase/genética , Artrite Reumatoide/tratamento farmacológico , Artrite Reumatoide/genética , GenótipoRESUMO
Despite extensive research on global heritability estimation for complex traits, few methods accurately dissect local heritability. A precise local heritability estimate is crucial for high-resolution mapping in genetics. Here, we report the effective heritability estimator (EHE) that can use p values from genome-wide association studies (GWASs) for local heritability estimation by directly converting marginal heritability estimates of SNPs to a non-redundant heritability estimate of a gene or a small genomic region. EHE provides higher accuracy and precision for local heritability estimation among seven compared methods. Importantly, EHE can be applied to estimate the conditional heritability of nearby genes, where redundant heritability among the genes can also be removed further. The conditional estimation can be guided by tissue-specific expression profiles (or other functional scores) to prioritize and quantify more functionally important genes of complex phenotypes. Applying EHE to 42 complex phenotypes from the UK Biobank, we revealed the existence of two types of distinct genetic architectures for various complex phenotypes and found that highly pleiotropic genes are not enriched for more heritability compared to other candidate susceptibility genes. EHE provides an accurate and robust way to dissect the genetic architecture of complex phenotypes.
Assuntos
Estudo de Associação Genômica Ampla , Genômica , Herança Multifatorial/genética , Fenótipo , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
Accurate polygenic scores (PGSs) facilitate the genetic prediction of complex traits and aid in the development of personalized medicine. Here, we develop a statistical method called multi-trait assisted PGS (mtPGS), which can construct accurate PGSs for a target trait of interest by leveraging multiple traits relevant to the target trait. Specifically, mtPGS borrows SNP effect size similarity information between the target trait and its relevant traits to improve the effect size estimation on the target trait, thus achieving accurate PGSs. In the process, mtPGS flexibly models the shared genetic architecture between the target and the relevant traits to achieve robust performance, while explicitly accounting for the environmental covariance among them to accommodate different study designs with various sample overlap patterns. In addition, mtPGS uses only summary statistics as input and relies on a deterministic algorithm with several algebraic techniques for scalable computation. We evaluate the performance of mtPGS through comprehensive simulations and applications to 25 traits in the UK Biobank, where in the real data mtPGS achieves an average of 0.90%-52.91% accuracy gain compared to the state-of-the-art PGS methods. Overall, mtPGS represents an accurate, fast, and robust solution for PGS construction in biobank-scale datasets.
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Estudo de Associação Genômica Ampla , Herança Multifatorial , Humanos , Herança Multifatorial/genética , Estudo de Associação Genômica Ampla/métodos , Fenótipo , Algoritmos , Projetos de PesquisaRESUMO
The ongoing release of large-scale sequencing data in the UK Biobank allows for the identification of associations between rare variants and complex traits. SAIGE-GENE+ is a valid approach to conducting set-based association tests for quantitative and binary traits. However, for ordinal categorical phenotypes, applying SAIGE-GENE+ with treating the trait as quantitative or binarizing the trait can cause inflated type I error rates or power loss. In this study, we propose a scalable and accurate method for rare-variant association tests, POLMM-GENE, in which we used a proportional odds logistic mixed model to characterize ordinal categorical phenotypes while adjusting for sample relatedness. POLMM-GENE fully utilizes the categorical nature of phenotypes and thus can well control type I error rates while remaining powerful. In the analyses of UK Biobank 450k whole-exome-sequencing data for five ordinal categorical traits, POLMM-GENE identified 54 gene-phenotype associations.
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Exoma , Estudo de Associação Genômica Ampla , Estudo de Associação Genômica Ampla/métodos , Exoma/genética , Bancos de Espécimes Biológicos , Fenótipo , Análise de Dados , Reino UnidoRESUMO
Common genetic variants and susceptibility loci associated with Alzheimer's disease (AD) have been discovered through large-scale genome-wide association studies (GWAS), GWAS by proxy (GWAX) and meta-analysis of GWAS and GWAX (GWAS+GWAX). However, due to the very low repeatability of AD susceptibility loci and the low heritability of AD, these AD genetic findings have been questioned. We summarize AD genetic findings from the past 10 years and provide a new interpretation of these findings in the context of statistical heterogeneity. We discovered that only 17% of AD risk loci demonstrated reproducibility with a genome-wide significance of P < 5.00E-08 across all AD GWAS and GWAS+GWAX datasets. We highlighted that the AD GWAS+GWAX with the largest sample size failed to identify the most significant signals, the maximum number of genome-wide significant genetic variants or maximum heritability. Additionally, we identified widespread statistical heterogeneity in AD GWAS+GWAX datasets, but not in AD GWAS datasets. We consider that statistical heterogeneity may have attenuated the statistical power in AD GWAS+GWAX and may contribute to explaining the low repeatability (17%) of genome-wide significant AD susceptibility loci and the decreased AD heritability (40-2%) as the sample size increased. Importantly, evidence supports the idea that a decrease in statistical heterogeneity facilitates the identification of genome-wide significant genetic loci and contributes to an increase in AD heritability. Collectively, current AD GWAX and GWAS+GWAX findings should be meticulously assessed and warrant additional investigation, and AD GWAS+GWAX should employ multiple meta-analysis methods, such as random-effects inverse variance-weighted meta-analysis, which is designed specifically for statistical heterogeneity.
Assuntos
Doença de Alzheimer , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Doença de Alzheimer/genética , Humanos , Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único , Heterogeneidade GenéticaRESUMO
Large sample datasets have been regarded as the primary basis for innovative discoveries and the solution to missing heritability in genome-wide association studies. However, their computational complexity cannot consider all comprehensive effects and all polygenic backgrounds, which reduces the effectiveness of large datasets. To address these challenges, we included all effects and polygenic backgrounds in a mixed logistic model for binary traits and compressed four variance components into two. The compressed model combined three computational algorithms to develop an innovative method, called FastBiCmrMLM, for large data analysis. These algorithms were tailored to sample size, computational speed, and reduced memory requirements. To mine additional genes, linkage disequilibrium markers were replaced by bin-based haplotypes, which are analyzed by FastBiCmrMLM, named FastBiCmrMLM-Hap. Simulation studies highlighted the superiority of FastBiCmrMLM over GMMAT, SAIGE and fastGWA-GLMM in identifying dominant, small α (allele substitution effect), and rare variants. In the UK Biobank-scale dataset, we demonstrated that FastBiCmrMLM could detect variants as small as 0.03% and with α ≈ 0. In re-analyses of seven diseases in the WTCCC datasets, 29 candidate genes, with both functional and TWAS evidence, around 36 variants identified only by the new methods, strongly validated the new methods. These methods offer a new way to decipher the genetic architecture of binary traits and address the challenges outlined above.
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Algoritmos , Estudo de Associação Genômica Ampla , Estudo de Associação Genômica Ampla/métodos , Humanos , Modelos Logísticos , Estudos de Casos e Controles , Desequilíbrio de Ligação , Polimorfismo de Nucleotídeo Único , Genômica/métodos , Simulação por Computador , Haplótipos , Modelos GenéticosRESUMO
Human cortical expansion has occurred non-uniformly across the brain. We assessed the genetic architecture of cortical global expansion and regionalization by comparing two sets of genome-wide association studies of 24 cortical regions with and without adjustment for global measures (i.e., total surface area, mean cortical thickness) using a genetically informed parcellation in 32,488 adults. We found 393 and 756 significant loci with and without adjusting for globals, respectively, where 8% and 45% loci were associated with more than one region. Results from analyses without adjustment for globals recovered loci associated with global measures. Genetic factors that contribute to total surface area of the cortex particularly expand anterior/frontal regions, whereas those contributing to thicker cortex predominantly increase dorsal/frontal-parietal thickness. Interactome-based analyses revealed significant genetic overlap of global and dorsolateral prefrontal modules, enriched for neurodevelopmental and immune system pathways. Consideration of global measures is important in understanding the genetic variants underlying cortical morphology.
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Estudo de Associação Genômica Ampla , Imageamento por Ressonância Magnética , Adulto , Humanos , Córtex Cerebral/anatomia & histologia , Córtex Pré-Frontal , EncéfaloRESUMO
Scots pine (Pinus sylvestris L.) is one of the most widespread and economically important conifer species in the world. Applications like genomic selection and association studies, which could help accelerate breeding cycles, are challenging in Scots pine because of its large and repetitive genome. For this reason, genotyping tools for conifer species, and in particular for Scots pine, are commonly based on transcribed regions of the genome. In this article, we present the Axiom Psyl50K array, the first single nucleotide polymorphism (SNP) genotyping array for Scots pine based on whole-genome resequencing, that represents both genic and intergenic regions. This array was designed following a two-step procedure: first, 192 trees were sequenced, and a 430K SNP screening array was constructed. Then, 480 samples, including haploid megagametophytes, full-sib family trios, breeding population, and range-wide individuals from across Eurasia were genotyped with the screening array. The best 50K SNPs were selected based on quality, replicability, distribution across the draft genome assembly, balance between genic and intergenic regions, and genotype-environment and genotype-phenotype associations. Of the final 49 877 probes tiled in the array, 20 372 (40.84%) occur inside gene models, while the rest lie in intergenic regions. We also show that the Psyl50K array can yield enough high-confidence SNPs for genetic studies in pine species from North America and Eurasia. This new genotyping tool will be a valuable resource for high-throughput fundamental and applied research of Scots pine and other pine species.