Download Global analysis of correlated gene expression across the

Global analysis of correlated gene expression across the brain
To understand genetic relationships between different regions of the brain, correlations
were performed between fine 3D anatomical locations across a large set of genes. As
described in “Supplemental document 4: Informatics Data Processing,” expression
statistics computed from in situ hybridation (ISH) images are generated for each
deformed 300µm3 voxel throughout the brain1. For the current analysis, the statistic used
was the fractional area within each voxel occupied by pixels identified as ISH signal.
Averaged across all voxels in the brain, values for this variable are in the range [0.0,0.16]
across the entire ABA data set. 5195 genes were selected for this analysis by selecting
genes with fractions of expressing pixels between 0.02 and 0.14. This set represents
genes with regional expression but omitting genes with extremely low or widespread
expression.
To assess global correlations between different brain regions, the Pearson
correlation coefficient of the fraction of expressing pixels is computed between pairs of
300µm3 voxels. To reduce data processing requirements, 1500 representative voxels were
selected out of the 7000 voxels in one hemisphere of the brain. For most structures, a
simple 4:1 decimation of the voxel set was performed to maintain consistent
representation of voxels across the brain. Several brain structures provide additional
challenges due to their highly heterogeneous cellular distribution. For example, the
olfactory bulb, hippocampus and cerebellum consistent of dense cell layers with a large
proportion of cell-sparse neuropil surrounding the dense layers. Even very small errors in
registration of the ISH data to the Nissl-based reference atlas result in misalignment of
the predominant cell populations, and have the effect of reducing gene to gene
correlations for a given voxel in these structures. To reduce these effects, we over
sampled in these regions (analyzing all voxels instead of 1 in 4), and then preferentially
selected voxels with higher expression levels (1390 voxels were used.)
Although voxels have a natural 3D relationship to one another, 3D correlations can be
difficult to interpret. To facilitate visualization of correlations between voxels,, 3D to 1D
projections of these data were performed for Figure 5 of the manuscript. These voxels,
color-scored for the average correlation across the entire gene set, can then be clustered
in several ways to reveal different types of relationships.
Voxel Ordering
The natural order for voxels is scanned linearly in (rostral-caudal), (dorsal-ventral), and
(lateral-medial) order. Voxels towards the top/left of the axis are closer to the front
(olfactory bulb) and voxels towards the bottom/right of the axis are closer to the back
(cerebellum). Repeating blocks can be observed that represent the splitting and
intermixing of large, relatively homogenous brain structures by linear scanning across
those structures.
Ordering by Conventional Anatomy
Each 300µm3 voxel is associated with an anatomical structure in the reference atlas
volume, represented by a unique number and RGB color combination (see “Supplemental
document 5: Allen Reference Atlases”). In the present ordering, a hierarchically
organized set of 209 structures from the reference atlas was used to group voxels by their
inclusion in a given structure. A secondary linear scan ordering was used for voxels
within each structure. The identification label for each voxel is displayed as a color-
coded strip on the left, using the exact colors from the Allen Reference Atlas. Displayed
in this way, large spans of “red/orange” blocks are observed along the diagonal
corresponding to high correlations between voxels within a given structure.
Hierarchical Clustering Based on Correlations between Voxels
Voxels can also be ordered by hierarchical clustering, based on the Pearson correlation
between each voxel’s value and all other voxel values. The basic aim is to maximize the
average distance between all pairs of objects/voxels in two distinct clusters. Groups of
highly correlated voxels can be related to the anatomical structures they belong to
comparison to color-coded strip shown next to the correlation plots. Organized in this
way, large clusters of highly correlated voxels are observed that belong to large
anatomical structures with relatively uniform internal structure (e.g. CTX, STR). On the
other hand, smaller interleaved clusters from other structures (e.g. P, MY, HY, MB)
indicate that higher correlations occur between fine divisions across rather than within
those structures.
Bibliography
1.
Ng, L. et al. Neuroinformatics for Genome-wide 3-D Gene Expression Mapping
in the Mouse Brain. IEEE Transactions on Computational Biology and Bioinformatics
(In press).