Cells integrate exogenous and endogenous signals, likely through dynamic functional associations between genes, but measuring these relationships is non-trivial. Here, we evaluate genetic associations in response to cell-cycle interruption, genotoxic perturbation, and nutrient deprivation using genetic interaction mapping in human cells.
We present MULTI-evolve, a rapid evolution framework that systematically engineers multimutants. Our approach combines protein language models or existing functional data with epistatic modelling to predict synergistic combinations.
High-altitude conditions improve glucose tolerance and reduce diabetes risk, but the physiological mechanism is not well understood. Using mouse models, we found that hypoxia alone robustly improved glucose tolerance and that the effect persisted for weeks after returning to normal oxygen levels.
Standard fixed-vocabulary tokenizers fragment biologically meaningful motifs, while nucleotide-level models preserve biological coherence but incur prohibitive computational costs for long contexts. We introduce dnaHNet, a state-of-the-art tokenizer-free autoregressive model that segments and models genomic sequences end-to-end.
Local hypoxia is a hallmark of solid tumors and a negative prognostic factor in the progression and treatment of cancer. Here, we showed that systemic hypoxia, in contrast to localized tumor hypoxia, decreases tumor growth in vivo across multiple cancer types and preclinical models.
Here, we report the development of RNA-guided trans-splicing with Cas editor (RESPLICE). RESPLICE uses two orthogonal RNA-targeting CRISPR effectors to co-localize a trans-splicing pre-mRNA and to inhibit the cis-splicing reaction, respectively.
From extrachromosomal DNA to neo-peptides, reprogramming of cancer genomes leads to the emergence of cancer state-specific molecules. Here, we systematically identify and characterize a large repertoire of orphan non-coding RNAs (oncRNAs), a class of cancer-emergent small RNAs, across 32 tumor types.
Single-cell genomics is rapidly scaling toward billion-cell atlases, but computational analysis has become a critical bottleneck. Here we present cyto, an ultra highthroughput processor for 10x Genomics Flex single-cell sequencing optimized for production-scale analysis.
Single-cell transcriptomics offers the promise of measuring the diversity of cellular phenotypes across species and diseases. Here, we present Stack, a foundation model trained on 149 million uniformly preprocessed human single cells that leverages tabular attention to generate representations for each cell informed by the cells in its context.
Generative genomic models can design increasingly complex biological systems. However, controlling these models to generate novel sequences with desired functions remains challenging. Here, we show that Evo can leverage genomic context to perform function-guided design that accesses novel regions of sequence space.