Dataset Information

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

ABSTRACT: During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function.

SUBMITTER: Richiardi J

PROVIDER: S-EPMC4829082 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

Richiardi Jonas J Altmann Andre A Milazzo Anna-Clare AC Chang Catie C Chakravarty M Mallar MM Banaschewski Tobias T Barker Gareth J GJ Bokde Arun L W AL Bromberg Uli U Büchel Christian C Conrod Patricia P Fauth-Bühler Mira M Flor Herta H Frouin Vincent V Gallinat Jürgen J Garavan Hugh H Gowland Penny P Heinz Andreas A Lemaître Hervé H Mann Karl F KF Martinot Jean-Luc JL Nees Frauke F Paus Tomáš T Pausova Zdenka Z Rietschel Marcella M Robbins Trevor W TW Smolka Michael N MN Spanagel Rainer R Ströhle Andreas A Schumann Gunter G Hawrylycz Mike M Poline Jean-Baptiste JB Greicius Michael D MD

Science (New York, N.Y.) 20150611 6240

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched f ...[more]

PMID: 26068849

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Project description:BackgroundCo-expression networks are a tool widely used for analysis of "Big Data" in biology that can range from transcriptomes to proteomes, metabolomes and more recently even microbiomes. Several methods were proposed to answer biological questions interrogating these networks. Differential co-expression analysis is a recent approach that measures how gene interactions change when a biological system transitions from one state to another. Although the importance of differentially co-expressed genes to identify dysregulated pathways has been noted, their role in gene regulation is not well studied. Herein we investigated differentially co-expressed genes in a relatively simple mono-causal process (B lymphocyte deficiency) and in a complex multi-causal system (cervical cancer).MethodsCo-expression networks of B cell deficiency (Control and BcKO) were reconstructed using Pearson correlation coefficient for two mus musculus datasets: B10.A strain (12 normal, 12 BcKO) and BALB/c strain (10 normal, 10 BcKO). Co-expression networks of cervical cancer (normal and cancer) were reconstructed using local partial correlation method for five datasets (total of 64 normal, 148 cancer). Differentially correlated pairs were identified along with the location of their genes in BcKO and in cancer networks. Minimum Shortest Path and Bi-partite Betweenness Centrality where statistically evaluated for differentially co-expressed genes in corresponding networks. Results: We show that in B cell deficiency the differentially co-expressed genes are highly enriched with immunoglobulin genes (causal genes). In cancer we found that differentially co-expressed genes act as "bottlenecks" rather than causal drivers with most flows that come from the key driver genes to the peripheral genes passing through differentially co-expressed genes. Using in vitro knockdown experiments for two out of 14 differentially co-expressed genes found in cervical cancer (FGFR2 and CACYBP), we showed that they play regulatory roles in cancer cell growth.ConclusionIdentifying differentially co-expressed genes in co-expression networks is an important tool in detecting regulatory genes involved in alterations of phenotype.

Dataset Information

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

Publications

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

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