Reconstructing context-specific gene regulatory network and identifying modules and network rewiring through data integration
Abstract
Reconstructing context-specific transcriptional regulatory network is crucial for deciphering principles of regulatory mechanisms underlying various conditions. Recently studies that reconstructed transcriptional networks have focused on individual organisms or cell types and relied on data repositories of context-free regulatory relationships. Here we present a comprehensive framework to systematically derive putative regulator-target pairs in any given context by integrating context-specific transcriptional profiling and public data repositories of gene regulatory networks. Moreover, our framework can identify core regulatory modules and signature genes underlying global regulatory circuitry, and detect network rewiring and core rewired modules in different contexts by considering gene modules and edge (gene interaction) modules collaboratively. We applied our methods to analyzing Autism RNA-seq experiment data and produced biologically meaningful results. In particular, all 11 hub genes in a predicted rewired autistic regulatory subnetwork have been linked to autism based on literature review. The predicted rewired autistic regulatory network may shed some new insight into disease mechanism.
References
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Citations
Related Concepts
Related Feeds
Autism
Autism spectrum disorder is associated with challenges with social skills, repetitive behaviors, and often accompanied by sensory sensitivities and medical issues. Here is the latest research on autism.