Astrocytes play important roles in neurological disorders such as stroke, injury, and neurodegeneration. Most knowledge on astrocyte biology is based on studies of mouse models and the similarities and differences between human and mouse astrocytes are insufficiently characterized, presenting a barrier in translational research. Based on analyses of acutely purified astrocytes, serum-free cultures of primary astrocytes, and xenografted chimeric mice, we find extensive conservation in astrocytic gene expression between human and mouse samples. However, the genes involved in defense response and metabolism show species-specific differences. Human astrocytes exhibit greater susceptibility to oxidative stress than mouse astrocytes, due to differences in mitochondrial physiology and detoxification pathways. In addition, we find that mouse but not human astrocytes activate a molecular program for neural repair under hypoxia, whereas human but not mouse astrocytes activate the antigen presentation pathway under inflammatory conditions. Here, we show species-dependent properties of astrocytes, which can be informative for improving translation from mouse models to humans.

The mammalian suprachiasmatic nucleus (SCN) drives daily rhythmic behavior and physiology, yet a detailed understanding of its coordinated transcriptional programmes is lacking. To reveal the finer details of circadian variation in the mammalian SCN transcriptome we combined laser-capture microdissection (LCM) and RNA-seq over a 24 hr light / dark cycle. We show that 7-times more genes exhibited a classic sinusoidal expression signature than previously observed in the SCN. Another group of 766 genes unexpectedly peaked twice, near both the start and end of the dark phase; this twin-peaking group is significantly enriched for synaptic transmission genes that are crucial for light-induced phase shifting of the circadian clock. 341 intergenic non-coding RNAs, together with novel exons of annotated protein-coding genes, including Cry1, also show specific circadian expression variation. Overall, our data provide an important chronobiological resource (www.wgpembroke.com/shiny/SCNseq/) and allow us to propose that transcriptional timing in the SCN is gating clock resetting mechanisms.DOI: http://dx.doi.org/10.7554/eLife.10518.001

No abstract

Background Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological, and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human- or primate-specific and therefore which components can be faithfully recapitulated in mouse models. Results We compare conservation of co-expression in 116 independent data sets derived from human, mouse, and non-human primate representing more than 15,000 total samples. We observe greater changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Glia, notably microglia, astrocytes, and oligodendrocytes are the most divergent cell type, three times more on average than neurons. We show that cis-regulatory sequence divergence explains a significant fraction of co-expression divergence. Moreover, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We identify dozens of human neuropsychiatric and neurodegenerative disease risk genes, such as COMT, PSEN-1, LRRK2, SHANK3, and SNCA, with highly divergent co-expression between mouse and human and show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types. Conclusions We identify robust co-expression modules reflecting whole-brain and regional patterns of gene expression. Compared with those that represent basic metabolic processes, cell-type-specific modules, most prominently glial modules, are the most divergent between species. These data and analyses serve as a foundational resource to guide human disease modeling and its interpretation.

Human-mouse differences are a major barrier in translational research.Astrocytes play important roles in neurological disorders such as stroke, injury, and neurodegeneration. However, the similarities and differences between human and mouse astrocytes are largely unknown. Combining analyses of acutely purified astrocytes, experiments using serum-free cultures of primary astrocytes, and xenografted chimeric mice, we found extensive conservation in astrocytic gene expression between human and mouse. However, genes involved in defense response and metabolism showed species differences. Human astrocytes exhibited greater susceptibility to oxidative stress than mouse astrocytes, due to differences in mitochondria physiology and detoxification pathways. Mouse astrocytes, but not human astrocytes, activate a molecular program for neural repair under hypoxia. Human astrocytes, but not mouse astrocytes, activate the antigen presentation pathway under inflammatory conditions. These species-dependent properties of astrocytes may contribute to differences between mouse models and human neurological and psychiatric disorders.

Gene networks have proven their utility for elucidating transcriptome structure in the brain, yielding numerous biological insights. Most analyses have focused on expression relationships within a circumspect number of regions -how these relationships vary across a broad array of brain regions is largely unknown. By leveraging RNAsequencing in 864 samples representing 12 brain regions in a cohort of 131 phenotypically normal individuals, we identify 12 brain-wide, 114 region-specific, and 50 cross-regional co-expression modules. We replicate the majority (81%) of modules in regional microarray datasets. Nearly 40% of expressed genes fall into brain-wide modules corresponding to major cell classes and conserved biological processes.Region-specific modules comprise 25% of expressed genes and correspond to regionspecific cell types and processes, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. We further leverage these modules to capture cell-type-specific lncRNA and gene isoforms, both of which contribute substantially to regional synaptic diversity. We identify enrichment of neuropsychiatric disease risk variants in brain wide and multi-regional modules, consistent with their broad impact on cell classes, and highlight specific roles in neuronal proliferation and activity-dependent processes. Finally, we examine the manner in which gene coexpression and gene regulatory networks reflect genetic risk, including the recently framed omnigenic model of disease architecture.Using this hierarchy, we form a tree of consensus co-expression networks for each split, thereby generating co-expression modules for 20 hierarchical expression categories: 12 brain region specific categories (corresponding to each sampled region), 7 multiregional categories (corresponding to multiple, structurally-linked regions, figure 1b), and a brain-wide category. The majority of the resulting modules are highly overlapping, therefore we group these modules hierarchically into groups of highly similar modules which we term "module sets" (Methods). In total, we identify 311 modules at all levels, of which 173/199 (87%) of the tissue-level modules are replicated with strong support in at least one other independent dataset (figure 1c; Methods). Finally, by using network preservation statistics on all samples within regions and meta regions, we verify that module sets are supported by strong evidence within their own regions and little evidence outside of them (figure 1d).To test whether co-expression modules vary substantially by the method used for co-expression network construction, we build modules at the tissue level using three alternative approaches: ARACNe, 34 PAM-guided graphical LASSO, 35 and Fisher-von-Mises mixture modeling. 36 We find that all methods show high pairwise clustering coefficients (figure S1e), and differ predominantly by module splitting (figure 1e). For instance, most of the differences between ARACNe clusters and WGCNA clusters come from large ARACNe modules represented as...

Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human or primate-specific and therefore, which components can be faithfully recapitulated in mouse models. We identify robust co-expression modules reflecting whole brain and regional patterns of gene expression and compare conservation of co-expression in 116 independent data sets derived from human, mouse and non-human primate representing more than 15,000 total samples. We observe greater coexpression changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Cell type specific modules are the most divergent across the brain, compared with those that represent basic metabolic processes. Among these, glia are the most divergent, three times that of neurons. We show that regulatory sequence divergence explains a significant fraction of co-expression divergence.Similarly, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We also identify dozens of human disease risk genes, such as COMT, PSEN-1, LRRK2, and SNCA, with highly divergent co-expression between mouse and primates or human. We show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types, which along with our analysis of human-mouse disease gene divergence, serve as a foundational resource to guide disease modeling and its interpretation. 3 1 2 3 Zsum

The mammalian suprachiasmatic nucleus (SCN) drives daily rhythmic behavior and physiology, yet a detailed understanding of its coordinated transcriptional programmes is lacking. To reveal the finer details of circadian variation in the mammalian SCN transcriptome we combined laser-capture microdissection (LCM) and RNA-seq over a 24 hr light / dark cycle. We show that 7-times more genes exhibited a classic sinusoidal expression signature than previously observed in the SCN. Another group of 766 genes unexpectedly peaked twice, near both the start and end of the dark phase; this twin-peaking group is significantly enriched for synaptic transmission genes that are crucial for light-induced phase shifting of the circadian clock. 341 intergenic non-coding RNAs, together with novel exons of annotated protein-coding genes, including Cry1, also show specific circadian expression variation. Overall, our data provide an important chronobiological resource (www.wgpembroke.com/shiny/SCNseq/) and allow us to propose that transcriptional timing in the SCN is gating clock resetting mechanisms.