Connectome studies have revealed how neurodegenerative diseases like Alzheimer’s disease (AD) disrupt functional and structural connectivity among brain regions, but the molecular basis of such disruptions is less studied, with most genomic studies focusing on within-brain-region molecular analyses. We performed an inter-brain-region differential correlation (DC) analysis of postmortem human brain RNA-seq data available for four brain regions – frontal pole, superior temporal gyrus, parahippocampal gyrus, and inferior frontal gyrus – from Mount Sinai Brain Bank for hundreds of AD vs. control samples. For any two brain regions, our DC analysis identifies all pairs of genes across these regions whose coexpression/correlation strength in the AD group differs significantly from that in the Control group, after adjusting for cell type compositional effects to better capture cell-intrinsic changes. Such DC gene pairs provided information complementary to known differentially expressed genes in AD, and highlighted extensive rewiring of the network of cross-region coexpression-based couplings among genes. The most vulnerable region in AD, parahippocampal gyrus, showed the most rewiring in its coupling with other brain regions. Decomposing the DC network into bipartite (region-region) gene modules revealed enrichment for synaptic signaling and ion transport pathways in several modules, revealing the dominance of five genes (BSN, CACNA1B, GRIN1, IQSEC2, and SYNGAP1). AD cerebrospinal fluid biomarkers (AD-CSF), neurotransmitters, secretory proteins, ligand and receptors were found to be part of the DC network, suggesting how pathways comprising such signaling molecules could mediate region-region communication. A module enriched for AD GWAS (Genome-wide Association Studies) signals is also enriched for NF-κβ signaling pathway, a key mediator of brain inflammation in AD. Beyond modules, we also identified individual genes that act as hubs of AD dysregulation across regions, such as ZKSCAN1 (Zinc Finger with KRAB And SCAN Domains) – this gene is known to be linked to AD in GWAS studies but via unknown mechanisms, and the specific DC interactions of ZKSCAN1 found in this study can be used to dissect these mechanisms. Thus, our inter-region DC framework provides a valuable new perspective to comprehend AD aetiology.

Background Functional imaging has revealed how Alzheimer’s disease (AD) disrupts functional connectivity between brain regions, but the molecular basis of such changes has been less explored1. Genomic studies can reveal molecular/gene biomarkers in AD, but they have mostly been confined to within‐region analyses2. Here, we perform inter‐region analysis to explore how synchronized activities across brain regions are disrupted by gene‐pair rewiring in AD. Method We retrieved data on 264 AD and 372 control human post‐mortem RNA‐seq samples from Mount Sinai Brain Bank dataset for four brain regions: frontal pole (FP), superior temporal gyrus (STG), parahippocampal gyrus (PHG), and inferior frontal gyrus (IFG)3. Considering two brain regions at a time, we identified all pairs of genes across the two regions whose correlation strength is significantly altered in the AD group relative to the Control group4 (Fig. 1). The network of such differentially correlated (DC) genes provides information complementary to known differentially expressed genes in AD, and probably reflects cell‐intrinsic changes5 since we adjust for cell compositional effects. Result We found extensive DC gene pair rewiring in AD between pairs of brain regions, the most prominent being the coupling of PHG with other brain regions. Our analyses revealed that each brain region mostly uses a unique set of genes while interacting with other brain regions. Decomposing the bipartite DC network into gene modules revealed that certain gene modules affected in AD were enriched for synaptic signaling and ion transport pathways, whereas several others were enriched for AD GWAS (Genome‐wide Association Studies) signals. A module enriched for AD GWAS signal is also enriched for NF‐κβ signaling pathway, a key mediator of brain inflammation in AD. Beyond modules, we also identified individual genes such as ZKSCAN1 (Zinc Finger with KRAB And SCAN Domains) acting as a hub gene for most of the inter‐region comparisons and were enriched for AD GWAS signal. Conclusion These findings provide novel insights into the network of pairwise gene relations underlying the functional connectivity between brain regions and highlights how disruption of different factors rewires this network in AD patients. 1. Science, 1241‐4,2015. 2. Genome Med., 104,2016. 3. Sci Data., 180185,2018. 4. BMC Res Notes., 54,2017. 5. Bioinformatics, 1584‐91,2015.

ChassiDex is an open-source, non-profit online host organism database that houses a repository of molecular, biological and genetic data for model organisms with applications in synthetic biology. The structured user-friendly environment makes it easy to browse information. The database consists of a page for each model organism subdivided into sections such as Growth Characteristics, Strain diversity, Culture sources, Maintenance protocol, Transformation protocol, BioBrick parts and commonly used vectors. With tools such as CUTE built for codon usage table generator, it is also easy to generate and download accurate novel codon tables for unconventional hosts in suitable formats. This database was built as a project for the International Genetically Engineered Machine Competition in 2017 with the mission of making it easy to shift from working with one host organism to another unconventional host organism for any researcher in the field of synthetic biology. The code along with other instructions for the usage of the database and tools are publicly available at the GitHub page. We encourage the synthetic biology community to contribute to the database by adding data for any additional or existing host organism.https://chassidex.org; https://github.com/ChassiDex