[WPS] 2024.06 W2

1. LINE-1 transcription activates long-range gene expression | Nature Genetics

… L1s can physically contact their distal target genes, with these interactions becoming stronger upon L1 activation and weaker when L1 is silenced.

2. Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction | Nature Genetics

we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

MR, GSEA, TUM/Helmholtz…

3.High-resolution genome-wide mapping of chromosome-arm-scale truncations induced by CRISPR–Cas9 editing | Nature Genetics

…we performed a phenotypic CRISPR–Cas9 scan targeting 17,065 genes in primary human cells, revealing a ‘proximity bias’ in which CRISPR knockouts show unexpected similarities to unrelated genes on the same chromosome arm.

4.Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells | Nature Genetics

5. Scaling neural machine translation to 200 languages | Nature

6. Single-cell nascent RNA sequencing unveils coordinated global transcription | Nature

Our results suggest that the bursting of transcription at super-enhancers precedes bursting from associated genes. 

7. Defining the KRAS- and ERK-dependent transcriptome in KRAS-mutant cancers | Science

8. A developmental constraint model of cancer cell states and tumor heterogeneity: Cell

9. Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging: Cell

10. Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning | Nature Machine Intelligence

11. Somatic mutations associate with clonal expansion of CD8+ T cells | Science Advances

12. ReactomeGSA: new features to simplify public data reuse | Bioinformatics | Oxford Academic (oup.com)

13. Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine Learning | NEJM AI