Neural macro connectivity and gene expression

French et al explore this link, looking at the correlation between gene expression in the mouse in and connectivity in homologous brain regions of the rat. This is their conceptual scheme:

Of their 142 common regions, 112 have efferent (outgoing) connections, and 141 have afferent (incoming) connections. There are 5216 outgoing connections and 6110 incoming connections.

To see whether the similarity of the connectivity between two regions is related to the similarity of gene expression between those two regions, they looked at the correlation between the connectivity and gene expression matrices. Specifically, they used a Mantel test, which measures the Pearson correlation between every entry in the matrices, and gets significance by permuting the order of the entries and recalculating the correlation after each permutation.

They find that brain regions with similar connectivity tend to have similar gene expression. The Mantel correlation between expression and incoming connectivity patterns (141 regions) is 0.248, with a permutation (exact) p-value < 0.0001, and for outgoing the correlation is 0.226, p also very low.

This is a really good proof of principle that expression and brain connectivity feed back upon one another. As the gene expression and connectivity measures become more precise, these types of analyses will yield valuable insights related to neural development and disease.

Reference

French L, Pavlidis P (2011) Relationships between Gene Expression and Brain Wiring in the Adult Rodent Brain. PLoS Comput Biol 7(1): e1001049. doi:10.1371/journal.pcbi.1001049