Multi-omics Differential Inference for Functional Interpretation (MoDIFI): A Statistical Framework to Prioritize Cell Lines for Neurodevelopmental Variants

Noncoding variants contribute to neurodevelopmental disorders (NDDs), but their regulatory effects are often cell-type specific, making it difficult to choose an in vitro model for high-throughput assays such as massively parallel reporter assays. We asked: given a set of noncoding variants, which cell line and regulatory regions are most likely to reveal measurable allele-specific effects? We generated matched multiomics profiles across commonly used NDD in vitro models: human neuronal lines (i.e., IMR-32, SH-SY5Y, SK-N-SH), mouse neuronal lines (i.e., HT-22, Neuro-2a), and a non-neuronal line (i.e., HEK-293), using RNA-seq, ATAC-seq, and Hi-C under consistent conditions. To integrate these orthogonal data types, we developed MoDIFI (Multi-omics Differential Inference for Functional Interpretation), a Bayesian framework that quantifies cell-line-specific regulatory activity by computing posterior inclusion probabilities (PIPs) for differential gene-loop interactions. MoDIFI identifies regulatory regions supported by coordinated 3D contacts, accessibility, and transcriptional output, producing cell-line-resolved regulatory maps that highlight both shared synaptic programs and context-dependent mechanisms. These results provide a practical strategy for prioritizing the most informative cell lines and candidate regulatory elements for targeted functional testing of NDD-relevant noncoding variation.非编码变异（noncoding variants）与神经发育障碍（neurodevelopmental disorders, NDDs）的发病机制密切相关，但其调控效应通常具有细胞类型特异性，这为针对大规模平行报告基因检测（massively parallel reporter assays）等高通量实验筛选合适的体外（in vitro）模型带来了挑战。本研究提出核心科学问题：给定一组非编码变异，何种细胞系与调控区域最有可能展现出可检测的等位基因特异性效应？ 我们在统一实验条件下，针对神经发育障碍研究中常用的体外模型构建了匹配的多组学（multiomics）图谱：涵盖人源神经细胞系（IMR-32、SH-SY5Y、SK-N-SH）、小鼠神经细胞系（HT-22、Neuro-2a）及非神经细胞系（HEK-293），检测手段包括RNA测序（RNA-seq）、转座酶可及性测序（ATAC-seq）与染色质构象捕获（Hi-C）。 为整合这些正交异质性数据类型，我们开发了MoDIFI（Multi-omics Differential Inference for Functional Interpretation，功能解读多组学差异推断框架）——一种贝叶斯（Bayesian）框架，其通过计算差异基因环相互作用的后验包含概率（posterior inclusion probabilities, PIPs）来量化细胞系特异性调控活性。MoDIFI可识别由协同三维（3D）染色质接触、染色质可及性及转录输出共同佐证的调控区域，进而生成细胞系分辨率的调控图谱，该图谱既可凸显共享的突触程序，也能揭示依赖于细胞背景的调控机制。本研究结果可为针对神经发育障碍相关非编码变异的靶向功能检测，提供一套优先筛选最优信息细胞系与候选调控元件的实用策略。