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07/2026 - The PRECISE European initiative for cancer-vulnerability mapping and prediction

PRECISE is a European initiative to move cancer research beyond descriptive atlases toward predictive, mechanistically informed models of tumor vulnerability. By integrating patient cohorts, disease-relevant model systems, perturbation biology, multimodal profiling and artificial intelligence-driven inference, the PRECISE consortium aims to learn generalizable and predictive rules that govern genetic dependencies and synthetic lethality. Understanding and exploiting […]

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07/2026 - SpatioTemporal Omics Consortium: a global effort for biological discovery across species, space and time

In this Comment we introduce the SpatioTemporal Omics Consortium (STOC), a global, open network collaborating to integrate spatial and temporal omics across species, development, disease and evolution. The pace of innovation in spatial technologies has been extraordinary, rapidly transforming our ability to study biological systems within their native tissue environments. Throughout the history of biology, […]

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07/2026 - Insulin synthesis is sustained by Tent5 poly(A) polymerases

Insulin is an essential regulator of glucose homeostasis in vertebrates, and impairment of its synthesis or action leads to diabetes with severe health complications in humans. It is therefore essential to understand how beta cells control insulin synthesis and secretion, including the transcription, translation and decay of its messenger RNA. Using sequencing-based poly(A) tail length […]

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06/2026 - Genomic codes governing enhancer RNA fate

Long-read sequencing has transformed transcriptome profiling, yet capturing full-length, non-polyadenylated transcripts like enhancer RNAs (eRNAs) remains challenging. Here, we introduce CFC-seq, combining cap-trapping and in vitro poly(A)-tailing to sequence poly(A) and non-poly(A) RNAs with precise transcription start site. Paired with our assembler, SALA, we identified 39,425 novel transcriptional units, including ∼24,000 eRNAs. Our data reveal […]

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