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Neuron, Volume 62 Supplemental Data Neuron, Volume 62 Supplemental Data Functional and Evolutionary Insights into Human Brain Development Through Global Transcriptome Analysis Matthew B. Johnson, Yuka Imamura Kawasawa, Christopher E. Mason, Željka Krsnik, Giovanni Coppola, Darko Bogdanović, Daniel H. Geschwind, Shrikant M. Mane, Matthew W. State, and Nenad Šestan Supplemental Material: Supplemental Figures Supplemental Experimental Procedures Supplemental References Supplemental Tables Supplemental Figures Supplemental Figure 1. Normal Cytoarchitecture of Brain Specimens Used for Exon Array Analysis Nissl staining of the tissue remaining after microdissection from all four brains used for microarray analysis (specimens 1-4), confirming normal cytoarchitecture and the absence of microscopic neuropathological defects such as periventricular lesions commonly present at this developmental stage. MZ, marginal zone; CP, cortical plate; SP, subplate; SVZ, subventricular zone; VZ, ventricular zone. Scale bar, 250 µm. 2 Supplemental Figure 2. Normal Laminar Position of Cortical Neurons in Brain Specimens Used for Exon Array Analysis Various immunohistochemical markers were used to confirm the presence of all major neuronal and glial cell types present at this developmental age in all four brains. Shown here are selected examples of immunohistochemical staining for markers of layer selective of projection neurons (FOXP2, SOX5, BCL11B, and POU3F3), MZ Cajal-Retzius neurons (RELN) and interneurons (GABA) in the neocortex of the 19 wg brain. The normal laminar position of these neurons indicates absence of obvious defects in neuronal specification and migration. Scale bar, 250 µm. 3 Supplemental Figure 3. Predicted Rates of Copy Number Variation in Brain Specimens Used for Exon Array Analysis Illumina genotyping microarray data were analyzed for putative copy number variations (CNVs) using the PennCNV algorithm (Wang et al., 2007). We found a total of 88 predicted CNVs, with a median 17 CNVs per individual (Table S2). To place these predictions in the context of expected human genetic variation, we used the same algorithm to analyze 120 well-characterized HapMap samples. We found that predicted CNV rates from our samples (large blue diamonds) fell within the range of expected CNVs per individual (small blue diamonds), and this remained true when predictions were partitioned into putative deletions (red circles) and duplications (green triangles). One brain (18 wg) displayed a higher rate of predicted deletions, but only one predicted duplication; this was likely an effect of a slightly lower call rate on this chip (95%), which may have been due to DNA sample degradation or technical error in the chip. All other call rates were above 99%. Finally, the majority (59%) of predicted CNVs in our samples overlapped known CNVs or segmental duplications, further indicating that these brains were within the normal range of human genetic variation. 4 Supplemental Figure 4. Comparison of Exon 1.0 ST and U133 Plus 2 GeneChip Microarrays Using Human Fetal Brain Tissue The Exon Array features more comprehensive coverage of the human genome than previous generations of arrays (e.g., 1.4 million probesets on the Exon Array, versus 54,000 probesets on the U133 Plus 2 array). However, because of its novelty, the Exon Array lacks a comparable accumulation of biological validation. Therefore, to compare the old 3’-biased array platform with the new exon-based design specifically in terms of detecting gene expression differences in fetal human brain, we hybridized selected samples to both Exon and U133 arrays and compared gene expression levels and log ratios between DLPFC, VLPFC, and OCC. These plots show signal log ratios for DLPFC (red) and VLPFC (green) versus OCC. The two platforms were well correlated in all comparisons (R2>0.5), providing us with confidence in making meaningful comparisons between Exon Array and extant U133 data from adult human brain, as well as from other tissues and species (see, e.g., Table S11). In addition to this analysis, other published studies using human adult brain and other non-neural tissues have since demonstrated the reliability of the Exon Array platform and its performance in comparison to the U133 Plus 2 Array (Abdueva et al., 2007; Kapur et al., 2007; Clark et al., 2007; Gardina et al., 2006). 5 Supplemental Figure 5. Principal Component Analysis of Exon Array Core Transcripts We performed principal component analysis (PCA) of all core transcripts on the Exon Array to assess variability of the data across brain regions, individuals, and hybridizations. Batch effect removal was performed in Partek GS to remove effects of hybridization date or brain specimen (inter-individual variations). Following batch effect removal, separation between individuals was reduced (compare A and C), while separation between brain regions was improved, especially for subcortical areas (compare B and D). PCA confirmed that inter-individual differences had a smaller effect on gene expression data across all 17,000+ core transcripts than did variation between brain regions, especially between NCTX and sub-cortical areas (compare C and D). The same data in D is shown in E and F with axes rotated to better reveal the separation between brain regions. Finally, ellipses in F show that three NCTX samples lie more than three standard deviations from the cluster center, suggesting potential outlier status. ANOVA analysis excluding these samples did not alter the results for the most significantly DEX genes. Notably, PCA of all core transcripts did not segregate NCTX areas, although some clustering of individuals was apparent, consistent with the observations of Khaitovich et al. (2004) that inter- individual gene expression differences outweighed inter-areal differences in adult human cortex. 6 7 Supplemental Figure 6. In Situ Hybridization of Selected Exon Array Candidate Genes We selected candidate genes from the clusters shown in Figure 2 for further confirmation based on putative function, apparent divergence from expression in mouse, gene novelty, and maximum and fold- change expression levels. In the schematic illustrations at left, the cortical plate (CP) is shaded in beige, the caudate and putamen (STR) in blue, the thalamus (THM) in pink, and the cerebellar cortex (CBL) in green. The grey areas in (A-C) are the forebrain neurogenic regions, the cortical ventricular zone and the ganglionic eminence. (A) and (D) are sagittal sections through the forebrain and cerebellum/brainstem, respectively, while (B) and (C) are coronal sections through the forebrain, with (B) more rostral than (C). All sections are from late mid-fetal brain specimens (19 to 22 wg). (A) TMOD1 and THBS1 were 6.8- and 7.5-fold enriched in NCTX by Exon Array analysis, respectively, and this specific enrichment was confirmed by qRT-PCR (p<0.0005). In situ hybridizations shown here indicate that TMOD1 is specifically enriched in the upper CP, while THBS1 is expressed throughout the CP, and neither gene is noticeably expressed in the STR or THM. Tmod1 is an actin regulatory protein and a possible transcriptional target of the non-canonical Wnt pathway. Although it has been shown to be expressed in neurons in the adult mouse forebrain, its specific role in neuronal development or function remains unknown. THBS1 is a member of a family of genes involved in synaptogenesis and plasticity, two others of which have been implicated in primate cortical evolution. (B) FAM40B was one of the most enriched genes in STR (~24-fold), while NRXN3 was also highly enriched in this structure (~4-fold). Both were confirmed by qRT-PCR as well as ISH, with the in situs shown here suggesting restricted expression in the putamen and caudate nucleus. FAM40B is a completely unknown transcript encoding a protein with multiple predicted transmembrane domains. According to the Allen Brain Atlas, its mouse homolog is enriched in the upper cortical pyramidal layers, CA fields of the hippocampus, the striatum, and the Purkinje cell layer of the cerebellum. NRXN3 is one of the lesser known members of the neurexin-neuroligin gene families involved in cell adhesion at the synapse. NRXN3 polymorphisms have been linked to opioid and alcohol dependence in humans, and the mouse homolog has been shown to be upregulated in the striatum of animals developing cocaine addiction. NRXN3 has also been shown to be alternatively spliced; our Exon Array and qRT-PCR data suggest that while the full-length isoform is enriched in STR, as shown here also by ISH, the truncated isoform (NM_138970) is specifically enriched in THM relative to other brain regions (data not shown). (C) TCF7L2 was one of the most highly THM-enriched genes (>30-fold), consistent with a previous report of its significant enrichment in the macaque monkey thalamus (Murray et al., 2007). ISH shows this Wnt-pathway transcription factor to be specifically enriched in the ventrolateral thalamus. PGM2L1 was ~4-fold enriched in THM by Exon Array analysis and confirmed by qRT-PCR. ISH shows specific enrichment in the dorsolateral nucleus. PGM2L1 encodes an enzyme involved in glucose metabolism, and has not yet been studied in the context of the nervous system. (D) PAX3 and MCC (mutated in colorectal cancer) were 6.5- and 2.8-fold enriched in CBL by Exon Array analysis and were confirmed by qRT-PCR (Figure 2 and data not shown) and ISH. 8 Supplemental Figure 7. Differential Gene Expression in the Mid-Fetal Human Neocortex Unsupervised hierarchical cluster analysis of 1,753 genes differentially expressed (FDR<0.01) within the late mid-fetal human neocortex. Clustering of areas suggests a broad separation of PFC (r=0.37) from non-frontal (r=0.25) cortical areas. The most similar areas in this analysis were TAU+PAS (r=0.67) followed by OPFC+DLPFC (r=0.57). The MS sample, taken from the border area of the frontal and parietal lobes, does not correlate with either PFC or PAS; rather, genes enriched in MS are divided into those that cluster with PFC and those that cluster with non-PFC areas, reflecting the mixed frontoparietal nature of the sample.
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