An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia-to-neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain.
Table S1 – Orthologous human brain annotations.
Table S2 – Orthologous mouse brain annotations.
Table S3 – H0351.2002 PC1 gene loadings.
Table S4 – H0351.2001 PC1 brain loadings.
Table S5 – H0351.2002 PC1 brain loadings.
Table S6 – Gene set enrichment of 100 genes with the most positive homologous gene correlations.
Table S7 – Gene-gene correlation of genes that show differential expression patterns between species in Zeng et al. (2012).
Table S8 – Gene-gene correlation of genes that show differential expression patterns between species in Miller et al. (2010).
Figure S1 – H0351.2001 cell type marker enrichment ROC curves.
Figure S2 – H0351.2002 cell type marker enrichment ROC curves.
Figure S3 – Mouse cell type marker enrichment ROC curves.
Figure S4 – Correlation distribution between orthologous genes that are expressed. Correlation distribution is skewed towards the positive compared to random where human gene labels were shuffled without replacement.
Figure S5 – Gene-gene correlation cell type marker enrichment ROC curves. Expression data were mean-centered scaled.
Figure S6 – Relative expression levels of homologous astrocyte markers across brain regions.
Recent research in C. elegans and the rodent has identified correlations between gene expression and connectivity. Here we extend this type of approach to examine complex patterns of gene expression in the rodent brain in the context of regional brain connectivity and differences in cellular populations. Using multiple large-scale data sets obtained from public sources, we identified two novel patterns of mouse brain gene expression showing a strong degree of anti-correlation, and relate this to multiple data modalities including macroscale connectivity. We found that these signatures are associated with differences in expression of neuronal and oligodendrocyte markers, suggesting they reflect regional differences in cellular populations. We also find that the expression level of these genes is correlated with connectivity degree, with regions expressing the neuron-enriched pattern having more incoming and outgoing connections with other regions. Our results exemplify what is possible when increasingly detailed large-scale cell- and gene-level data sets are integrated with connectivity data.
More relevant data is available at http://www.chibi.ubc.ca/ABAMS.