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The accuracy of polygenic scores (PGS) remains limited and poorly transferable across ancestries. In this Comment, Zeng and Visscher discuss how integrating functional annotations with whole-genome sequencing data can improve PGS by prioritizing likely causal variants shared across populations and by assigning greater weight to variants in biologically relevant regions.
Prompt-based methods, which involve the careful design of inputs to guide large language model (LLM) outputs, are beginning to reshape bioinformatic analytical workflows. The authors compare prompt-driven approaches to conventional bioinformatics pipelines, outline their potential for multi-omics analysis and explore how these models may shape the future of computational biology.
In this Tools of the Trade article, Kellie Wise and Anna Pascual-Reguant introduce STAMP (single-cell transcriptomics analysis and multimodal profiling), which harnesses imaging to measure RNA and/or protein expression in fixed cells or nuclei.
Gerald Mboowa reflects on the dual legacy of a 2021 study by Frangoul et al., which demonstrated safe and effective CRISPR-based editing to treat sickle-cell disease and β-thalassemia, as both a triumph of modern science and a call to action for global health.
Nina Wedell discusses how a study by Dunning Hotopp et al., which found widespread lateral gene transfer (LGT) from the bacterium Wolbachia to a variety of arthropod and nematode hosts, catalysed the debate on the extent and functional relevance of LGT-derived genes.
In this Review, Coyle and King explore how genomic and functional data from diverse species are providing new insights into the types of mechanistic changes that accompanied the evolutionary origin of animals.
Cell-type deconvolution methods are often needed to analyse spatial transcriptomic data to recover cell-type distributions. In this Review, the authors describe the process of cell-type deconvolution, contrast the tools available and highlight important considerations for which tool to use.
Fine-mapping aims to distinguish between the causal and non-causal genetic variants identified in genome-wide association studies of complex traits. In this Review, Li and Zhou cover the recent methodological advances of fine-mapping, including the refined modelling assumptions, improved computational efficiency and incorporation of additional information to expand biological insights.
Genomic advances have enhanced our understanding of schizophrenia, bipolar disorder and major depressive disorder, revealing genetic architectures and risk mechanisms through large-scale genome-wide association studies and sequencing, which could address limitations in current diagnostic frameworks and treatment strategies in the future.
