Gjoni Ketrin, Ren Xingjie, Everitt Amanda, Shen Yin, Pollard Katherine S
Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158.
Department of Epidemiology & Biostatistics, University of California, San Francisco, CA 94158.
bioRxiv. 2024 Nov 7:2024.11.06.621353. doi: 10.1101/2024.11.06.621353.
Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We developed a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implemented it in the SuPreMo-Akita software (Gjoni and Pollard 2024). With this tool, we ranked hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This revealed that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritized candidate variants that disrupt ASD CREints and validated our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study establishes disrupted genome folding as a potential genetic mechanism in ASD and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.
三维基因组组织在基因调控中起着关键作用，其破坏可通过改变基因与其远端调控元件之间的接触导致发育障碍。结构变异（SVs）可扰乱局部基因组组织，例如边界缺失时拓扑相关结构域的合并。通过实验测试大量SVs对染色质结构和基因表达的影响既耗时又成本高昂。为了解决这个问题，我们提出了一种计算方法来预测SVs对基因组折叠的影响，这有助于为功能测试确定因果假设的优先级。我们开发了一种加权评分方法，该方法可测量特别影响感兴趣区域（如调控元件或启动子）的染色质接触变化，并将其应用于SuPreMo-Akita软件（Gjoni和Pollard，2024年）。利用这个工具，我们根据对附近神经元调控相互作用的预测破坏，对来自自闭症谱系障碍（ASD）个体及其未受影响的兄弟姐妹的数百个新生SVs（dnSVs）进行了排名。这表明，与未受影响的兄弟姐妹相比，来自ASD先证者的dnSVs对假定的顺式调控元件相互作用（CREints）的破坏更大。我们对破坏ASD CREints的候选变异进行了优先级排序，并使用带有和不带有dnSV的同基因兴奋性神经元验证了我们排名最高的位点，证实了对染色质接触破坏的准确预测。这项研究确定基因组折叠破坏是ASD中的一种潜在遗传机制，并提供了一种通用策略，用于对预测会破坏跨组织调控相互作用的变异进行优先级排序。
