{
  "id": 15007120,
  "title": "MOFI reveals dynamic multi-omics coordination during cell fate progression",
  "url": "https://urgent.news/2026/10/16/mofi-reveals-dynamic-multi-omics-coordination-during-cell-fate",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-16T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757904v1?rss=1"
  },
  "original_language": "en",
  "account": "Cell fate decisions are influenced by dynamic coordination between various molecular layers, including transcriptomic, chromatin, and protein levels. Recent advancements in time-series single-cell multi-omics allow for profiling these molecular layers across different developmental stages; however, understanding the continuous trajectories linking discrete snapshots remains challenging. The primary obstacle is to effectively integrate paired omics measurements while reconstructing their shared developmental progression.\n\nIntroducing Multi-Omics Fate Inference (MOFI), a novel framework designed to dynamically integrate multi-omics data and reconstruct continuous cell fate transitions from paired snapshots collected at various time points. MOFI simultaneously models the dynamics of each omics layer, identifies cross-omics correspondences, and considers shared population growth within a unified framework. This integration enables the analysis of cross-omics perturbation responses and the identification of potential transformation programs connecting different molecular layers.\n\nMOFI has been evaluated using both simulated benchmarks and paired RNA-ATAC/RNA-protein time-series datasets. The results demonstrate MOFI's ability to accurately reconstruct continuous fate transitions, population dynamics, and cross-omics changes that align with observed measurements. In kidney organoids, MOFI effectively captured the coordinated progression of RNA-ATAC in nephron lineage specification. In hematopoietic progenitors, MOFI successfully predicted lineage redistribution in response to perturbations and proposed multi-omics transformation programs that link transcriptional modules with protein-level responses. Furthermore, MOFI was able to resolve the gradual maturation of brain organoids in neural developmental systems and identify interneuron lineage allocation during human cortical development.\n\nIn conclusion, MOFI offers a dynamics-grounded approach for transforming discrete paired multi-omics snapshots into interpretable models of cell fate progression, perturbation response, and cross-omics transformation analysis. By providing a comprehensive understanding of the complex interactions between multiple molecular layers during cell fate decisions, MOFI represents a significant advancement in the field of single-cell multi-omics research.",
  "summary": "Cell fate decisions are shaped by dynamic coordination across transcriptomic, chromatin, and protein layers. Time-series single-cell multi-omics assays now enable these molecular layers to be profiled across developmental stages, yet each cell is still observed only once, and the continuous multi-omics trajectories connecting discrete snapshots remain unresolved. A central challenge is therefore…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}