Scholarlink

<p>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 <a href="http://nemoanalytics.org/landing/neocortex/">nemoanalytics.org/landing/neocortex</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月25日

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

摘要

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.