Common genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

中文翻译：

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跨多巴胺能神经元分化的种群规模单细胞RNA-seq分析

常见的遗传变异会对细胞功能产生深远的影响，但是要在人体原始组织样本中以及发育过程中研究这些影响却具有挑战性。人类诱导多能干细胞（iPSC）技术在评估不同分化背景下的这些效应方面具有广阔的前景。在这里，我们使用有效的合并策略将215 iPS细胞系朝着中脑神经命运（包括多巴胺能神经元）分化，并使用单细胞RNA测序在三个分化时间点对超过一百万个细胞进行了分析。我们发现，在不同的实验批次中，每个细胞系产生的神经元细胞的比例可高度重现，并在多能细胞中鉴定出了能预测细胞命运的线对线差异的稳健分子标记。我们通过将细胞暴露于鱼藤酮，确定了表达数量性状基因座（eQTL），其在神经元发育的不同阶段表现出来，并响应氧化应激。我们发现有超过一千个eQTL与已知的神经性状危险源共定位，其中近一半不在GTEx中。我们的研究表明，如何将单细胞转录组学与长期iPSC分化相结合，可以描述在其他情况下无法访问的细胞状态下与人类性状相关的遗传变异的机制效应。