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Nature neuroscience · 2026

NeMO Analytics: a compendium of transcriptomic data for the exploration of neocortical development.

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Sonthalia Shreyash, Herb Brian, Adkins Ricky S, Orvis Joshua, Li Guangyan, Liao Xiangyu, Yu Qingjie, Blanco Xoel Mato, Casella Alex, Liu Jinrui, Stein-O'Brien Genevieve, Caffo Brian, Hertzano Ronna, Mahurkar Anup, Xu Jin-Chong, Gillis Jesse, Werner Jonathan, Ma Shaojie, Kim Suel-Kee, Micali Nicola, Sestan Nenad, Rakic Pasko, Santpere Gabriel, Ament Seth A, Colantuoni Carlo

Аннотация

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 .

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты