On Expression Patterns and Developmental Origin of Human Brain Regions

<div><p>Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions.</p></div

Specialization of Gene Expression during Mouse Brain Development

<div><p>The transcriptome of the brain changes during development, reflecting processes that determine functional specialization of brain regions. We analyzed gene expression, measured using in situ hybridization across the full developing mouse brain, to quantify functional specialization of brain regions. Surprisingly, we found that during the time that the brain becomes anatomically regionalized in early development, transcription specialization actually decreases reaching a low, “neurotypic”, point around birth. This decrease of specialization is brain-wide, and mainly due to biological processes involved in constructing brain circuitry. Regional specialization rises again during post-natal development. This effect is largely due to specialization of plasticity and neural activity processes. Post-natal specialization is particularly significant in the cerebellum, whose expression signature becomes increasingly different from other brain regions. When comparing mouse and human expression patterns, the cerebellar post-natal specialization is also observed in human, but the regionalization of expression in the human Thalamus and Cortex follows a strikingly different profile than in mouse.</p></div

Comparison with human data.

<p>(A) Cross correlation between mouse and human gene expression. The black line is taken from known developmental timeline of the two species based on anchor events <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003185#pcbi.1003185-Clancy1" target="_blank">[27]</a>. Region-specific dissimilarity curves of four brain regions in mouse and human. (B) mouse thalamus, (C) human mediodorsal nucleus of the thalamus, (D) mouse dorsal pallium, (E) human cortical regions, (F) mouse striatum, (G) human striatum, (H) mouse rhombomere 1 and isthmus and (I) human cerebellar cortex. Error bars denote standard deviation across regions.</p

The distribution of BRO-agreement scores on different subsets of genes.

<p>The two top panels show a scatter plot of BRO scores in <i>ABA6-2013</i> and <i>Kang-2011</i>. The corresponding lower two panels show the (marginal) distributions in the <i>ABA6-2013</i> dataset. <b>(A)</b> Cell-type specific genes have higher agreement scores than all genes (Wilcoxonon tail test; neurons median = 0.33: <i>p</i>-value < 10⁻⁷⁰ oligoodendrocytes median = 0.19: <i>p</i>-value = 10⁻⁵, astrocytes median = 0.16: <i>p</i>-value = 10⁻³). <b>(B)</b> Axon guidance genes receive higher scores than general genes (Wilcoxon median = 0.21; <i>p</i>-value = 10⁻⁷). Hox genes are less in agreement with region-ontology than the full set of genes. 21 Hox genes are BRO significant (67%) (compared to the randomized scores, with alpha = 0.01). <i>PAX2</i>, <i>PAX3</i> and <i>PAX6</i> obtain high BRO scores.</p

Changes in dissimilarity across individual brain regions.

<p>Embedding of all regions onto a 2D plane using multidimensional scaling. Each circle corresponds to a brain region, with a size that corresponds to the within-region expression standard deviation and a color that corresponds to its embryonic origins. Red: forebrain, telencephalon; pink: forebrain, diencephalon; cyan: midbrain; blue: hindbrain. Rhombomere 1 and Isthmus in the developing post-natal time points are and the cerebellar cortex and cerebellar nuclei at P56 are marked with a black arrow.</p

Functional characterization of hourglass shape.

<p>(A), (B) Clusters of gene profiles that are functionally enriched. Each profile is a measure of contribution to dissimilarity D (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003185#s4" target="_blank">Methods</a>). Black bold curve is the mean of the cluster. Blue lines - all the genes in the cluster; red lines - genes that are in the cluster and in the category; grey lines - genes that are not in the cluster even though belong to the category. (A) <i>Neuron migration</i> shows decreasing dissimilarity (B) <i>Learning or memory</i> shows a post-natal increase in dissimilarity. (C) Spatial expression of the genes <i>Neurog1</i> and <i>Neurog2</i> at E11.5 in 11 coarse regions, selected as <i>neuron differentiation</i> genes with highly similar sequence.</p

Inter-region distances are minimized around birth.

<p>(A) The data: ISH for each gene was performed at eight time points during development. Shown here are mid-sagittal slices for the gene <i>Hmgn2</i>, taken with permission from Allen Institute for Brain Science. Allen Mouse Brain Atlas [Internet] Available from: <a href="http://mouse.brain-map.org/" target="_blank">http://mouse.brain-map.org/</a><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003185#pcbi.1003185-Lein1" target="_blank">[17]</a> (B) Mean pair-wise dissimilarities between the regions. The curve is a second-order polynomial which minimizes the squared error of the fit to the data. Error bars encompass data within 1.5 times the inter-quartile range, and the boxes show the lower and upper quartiles together with the median. (C) The hourglass shape is robust throughout the dataset: Inter-region distance curve was calculated for the data withholding top k most variable genes for each time point. Error bars represent standard error between brain regions. (D) The hourglass shape is robust throughout the brain. Inter-region distance curve was calculated for the data withholding one region at a time. The blue curve is the mean across brain regions, error bars represent standard deviations from mean. (E) The dissimilarity curve using sets of regions taken from different levels of the reference atlas regional ontology tree, starting from the leaf regions (level 1).</p

Brain-region ontology and the BRO-agreement score.

<p><b>(A)</b> Illustration of the ontology region tree showing 16 brain structures studied. The full ontology contains 1534 regions, not shown. <b>(B)</b> A 3D model brain illustrating 16 brain regions using the same colors as in A. The left cortex is not shown in order to expose the inner structures. <b>(C)</b> Hierarchical clustering of 16 human brain structures. Agglomerative linking of regions by their average expression profile yields a tree structure that agrees the with ontology tree. The color above the region name matches the colors in the region ontology tree in Fig 1A. <b>(D)</b> The joint distribution of expression distances and ontology distances across all pairs of tissue samples, as computed for the gene <i>NEUROD1</i>. The two distance measures are strongly correlated (Spearman ρ = 0.65, n = 6.85M, <i>p</i>-value < 10⁻¹⁵), showing that the spatial expression pattern agrees with the ontology.</p

Projection of the samples from the human6 dataset on the 1st and 2nd principal componenets with two coloring schemes.

<p>(A) The samples are colored according to the position of the corresponding embryonic region, using the same color scheme as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005064#pcbi.1005064.g001" target="_blank">Fig 1A</a>. (B) The samples are colored according to one of the six donors.</p

Mean contribution values of GO categories at E11.5 and P28.

<p>The contribution of each GO categories C to inter-region dissimilarity was computed as the mean contribution of all genes assigned to C (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003185#s4" target="_blank">Methods</a>).</p