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1.
Guo, W.* et al.: A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity. Nat. Genet. 57, 441-450 (2025)
2.
Lazarescu, O.* et al.: Human subcutaneous and visceral adipocyte atlases uncover classical and nonclassical adipocytes and depot-specific patterns. Nat. Genet. 57, 413-426 (2025)
3.
Roselli, C.* et al.: Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases. Nat. Genet. 57, 539-547 (2025)
4.
Tejada Lapuerta, A. et al.: Causal machine learning for single-cell genomics. Nat. Genet., DOI: 10.1038/s41588-025-02124-2 (2025)
5.
Clarke, B.* et al.: Integration of variant annotations using deep set networks boosts rare variant association testing. Nat. Genet., DOI: 10.1038/s41588-024-01919-z (2024)
6.
García-Marín, L.M.* et al.: Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries. Nat. Genet. 56, 2333–2344 (2024)
7.
Garg, V.* et al.: Unlocking plant genetics with telomere-to-telomere genome assemblies. Nat. Genet., DOI: 10.1038/s41588-024-01830-7 (2024)
8.
Keaton, J.M.* et al.: Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits. Nat. Genet. 56, 778-791 (2024)
9.
Kentistou, K.A.* et al.: Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum. Nat. Genet. 56, 1763-1764 (2024)
10.
Kentistou, K.A.* et al.: Understanding the genetic complexity of puberty timing across the allele frequency spectrum. Nat. Genet. 56, 1397–1411 (2024)
11.
Meng, X.* et al.: Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference. Nat. Genet. 56, 222-233 (2024)
12.
Rayner, N.W. ; Park, Y.-C. ; Fuchsberger, C.* ; Barysenska, A. & Zeggini, E.: Toward GDPR compliance with the Helmholtz Munich genotype imputation server. Nat. Genet., DOI: 10.1038/s41588-024-02012-1 (2024)
13.
Schmidt, A.* et al.: Next-generation phenotyping integrated in a national framework for patients with ultrarare disorders improves genetic diagnostics and yields new molecular findings. Nat. Genet. 56, 1644–1653 (2024)
14.
Schormair, B. et al.: Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction. Nat. Genet. 56, 1090-1099 (2024)
15.
Shrine, N.* et al.: Author Correction: New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat. Genet. 56, 1032-1033 (2024)
16.
An, U.* et al.: Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries. Nat. Genet. 55, 2269-2276 (2023)
17.
Dahl, A.* et al.: Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nat. Genet. 55, 2082-2093 (2023)
18.
Lagou, V.* et al.: GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification. Nat. Genet. 55, 1448-1461 (2023)
19.
Rahmioglu, N.* et al.: The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions. Nat. Genet. 55, 423-436 (2023)
20.
Shrine, N.* et al.: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk. Nat. Genet. 55, 410-422 (2023)
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