Here, to enable researchers to more fully harness the collective discovery potential of multiomic data in the public domain, we have assembled gene-level transcriptomic data from ~200 studies of neocortical development and in vitro models. Applying joint matrix decomposition to mouse, macaque and human data, we define transcriptome dynamics that are conserved across neocortical neurogenesis and identify a program that emerges in ventricular progenitors, is later expressed in neurogenic outer, or basal, radial glia of primates, but is limited to gliogenic precursors in the rodent. Decomposition of adult human neocortical data identified layer-specific signatures in excitatory neurons, enabling the charting of their developmental emergence and protracted maturation, which is in stark contrast to the early peaking expression of layer-defining transcription factors. Interrogation of data from cerebral organoids demonstrated that, although broad elements of in vivo development are recapitulated in vitro, many layer-specific transcriptomic programs in neuronal maturation are absent. We invite cell biologists without coding expertise to use NeMO Analytics in their research and to fuel it with their own emerging data at nemoanalytics.org/landing/neocortex . NeMO Analytics is a compendium of public transcriptomic data focused on the neocortex, enabling biologists without coding expertise to explore hundreds of datasets. Joint decomposition of these data yields insight into brain development and its modeling.
Sonthalia et al. (Wed,) studied this question.
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