BOMA, a machine-learning framework for comparative gene expression analysis across brains and organoids.
BOMA, a machine-learning framework for comparative gene expression analysis across brains and organoids.
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DOI：
10.1016/j.crmeth.2023.100409
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发表时间：
2023-02-27
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我们的机器学习框架，大脑和类器官歧管比对（BOMA），首先执行了大脑和类器官之间发育基因表达数据的全局比对。然后，它应用多种学习来局部地改进排列，揭示大脑和类器官之间保守和特定的发育轨迹。使用BOMA，我们发现人类皮质类器官比其他非皮质区域更好地与某些大脑皮质区域对齐，这意味着类器官保留了特定于大脑区域的发育基因表达程序。此外，我们对非人类灵长类动物和人类大脑的比对揭示了出生前后高度保守的基因表达。此外，我们整合并分析了人类大脑和类器官发育单细胞RNA测序（scRNA-seq）数据，显示了保守和特定的细胞轨迹和集群。进一步鉴定这些簇的表达基因和富集分析揭示了脑或类器官特异性发育功能和途径。最后，我们通过使用免疫荧光实验验证了重要的特异性表达基因。BOMA是一个开源的网络工具，供社区使用。人类和非人类灵长类动物脑区域和类器官的发育相似性大脑和类器官中保守的和特定的细胞轨迹和基因已成为理解人类发育（包括大脑发育）中细胞和分子机制的有价值的模型。然而，发育基因表达程序是否在人类类器官和大脑之间，特别是在特定的细胞类型中保留，仍然不清楚。重要的是，缺乏有效的计算方法来比较类器官和发育中的人类大脑之间的数据分析。为了解决这个问题，我们开发了一个机器学习框架，用于比较大脑和类器官的基因表达分析，以识别保守和特定的发育轨迹以及发育表达的基因和功能，特别是在细胞分辨率上。他等人开发了一个机器学习框架，脑和类器官歧管比对（BOMA），用于脑和类器官的比较基因表达分析。它的应用揭示了人类和非人类灵长类动物大脑区域和类器官的保守和特定的发育轨迹，以及发育表达的基因和基因功能。
Our machine-learning framework, brain and organoid manifold alignment (BOMA), first performs a global alignment of developmental gene expression data between brains and organoids. It then applies manifold learning to locally refine the alignment, revealing conserved and specific developmental trajectories across brains and organoids. Using BOMA, we found that human cortical organoids better align with certain brain cortical regions than with other non-cortical regions, implying organoid-preserved developmental gene expression programs specific to brain regions. Additionally, our alignment of non-human primate and human brains reveals highly conserved gene expression around birth. Also, we integrated and analyzed developmental single-cell RNA sequencing (scRNA-seq) data of human brains and organoids, showing conserved and specific cell trajectories and clusters. Further identification of expressed genes of such clusters and enrichment analyses reveal brain- or organoid-specific developmental functions and pathways. Finally, we experimentally validated important specific expressed genes through the use of immunofluorescence. BOMA is open-source available as a web tool for community use. Manifold alignment for comparing gene expression of organoids with developing brains Global alignment by given development time and local refinement by common manifolds Developmental similarity of brain regions and organoids in human and non-human primates Conserved and specific cell trajectories and genes across brains and organoids Organoids have become valuable models for understanding cellular and molecular mechanisms in human development, including development of brains. However, whether developmental gene expression programs are preserved between human organoids and brains, especially in specific cell types, remains unclear. Importantly, there is a lack of effective computational approaches for comparative data analyses between organoids and developing human brains. To address this, we developed a machine-learning framework for comparative gene expression analysis of brains and organoids to identify conserved and specific developmental trajectories as well as developmentally expressed genes and functions, especially at cellular resolution. He et al. develop a machine-learning framework, brain and organoid manifold alignment (BOMA), for comparative gene expression analysis of brains and organoids. Its applications reveal conserved and specific developmental trajectories across brain regions and organoids of humans and non-human primates, as well as developmentally expressed genes and gene functions.