Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology.
C Bardy, M van den Hurk, B Kakaradov, J A Erwin, B N Jaeger, R V Hernandez, T Eames, A A Paucar, M Gorris, C Marchand, R Jappelli, J Barron, A K Bryant, M Kellogg, R S Lasken, B P F Rutten, H W M Steinbusch, G W Yeo, F H Gage
Molecular psychiatry · 2016 · Vol. 21 (11) · pp. 1573-1588
Abstract
Human neural progenitors derived from pluripotent stem cells develop into electrophysiologically active neurons at heterogeneous rates, which can confound disease-relevant discoveries in neurology and psychiatry. By combining patch clamping, morphological and transcriptome analysis on single-human neurons in vitro, we defined a continuum of poor to highly functional electrophysiological states of differentiated neurons. The strong correlations between action potentials, synaptic activity, dendritic complexity and gene expression highlight the importance of methods for isolating functionally comparable neurons for in vitro investigations of brain disorders. Although whole-cell electrophysiology is the gold standard for functional evaluation, it often lacks the scalability required for disease modeling studies. Here, we demonstrate a multimodal machine-learning strategy to identify new molecular features that predict the physiological states of single neurons, independently of the time spent in vitro. As further proof of concept, we selected one of the potential neurophysiological biomarkers identified in this study-GDAP1L1-to isolate highly functional live human neurons in vitro.
Linked datasets 1
Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology
Homo sapiens
112 data files
| File | Type | Size |
|---|---|---|
| C003_R1.fastq.gz | RNA-Seq | 2.1 GB |
| C004_R1.fastq.gz | RNA-Seq | 2.1 GB |
| C013_R1.fastq.gz | RNA-Seq | 3.0 GB |
| C014_R1.fastq.gz | RNA-Seq | 2.6 GB |
| C016_R1.fastq.gz | RNA-Seq | 2.9 GB |
| C022_R1.fastq.gz | RNA-Seq | 3.4 GB |
| C024_R1.fastq.gz | RNA-Seq | 885.7 MB |
| C028_R1.fastq.gz | RNA-Seq | 2.6 GB |
| C042_R1.fastq.gz | RNA-Seq | 646.2 MB |
| C044_R1.fastq.gz | RNA-Seq | 1.1 GB |
| C045_R1.fastq.gz | RNA-Seq | 918.6 MB |
| C046_R1.fastq.gz | RNA-Seq | 1.0 GB |
| C053_R1.fastq.gz | RNA-Seq | 2.8 GB |
| C055_R1.fastq.gz | RNA-Seq | 1.3 GB |
| C057_R1.fastq.gz | RNA-Seq | 1.5 GB |
| C060_R1.fastq.gz | RNA-Seq | 303.8 MB |
| C061_R1.fastq.gz | RNA-Seq | 374.9 MB |
| C063_R1.fastq.gz | RNA-Seq | 307.9 MB |
| C086_R1.fastq.gz | RNA-Seq | 376.0 MB |
| C098_R1.fastq.gz | RNA-Seq | 416.3 MB |
| C099_R1.fastq.gz | RNA-Seq | 424.4 MB |
| C100_R1.fastq.gz | RNA-Seq | 348.6 MB |
| C101_R1.fastq.gz | RNA-Seq | 376.9 MB |
| C105_R1.fastq.gz | RNA-Seq | 399.2 MB |
| C107_R1.fastq.gz | RNA-Seq | 310.9 MB |
| C110_R1.fastq.gz | RNA-Seq | 378.8 MB |
| C111_R1.fastq.gz | RNA-Seq | 463.6 MB |
| C115_R1.fastq.gz | RNA-Seq | 501.8 MB |
| C116_R1.fastq.gz | RNA-Seq | 463.0 MB |
| C119_R1.fastq.gz | RNA-Seq | 396.2 MB |
| C124_R1.fastq.gz | RNA-Seq | 978.1 MB |
| C125_R1.fastq.gz | RNA-Seq | 1.2 GB |
| C129_R1.fastq.gz | RNA-Seq | 1.8 GB |
| C130_R1.fastq.gz | RNA-Seq | 1.2 GB |
| C132_R1.fastq.gz | RNA-Seq | 1.3 GB |
| C133_R1.fastq.gz | RNA-Seq | 1.1 GB |
| C155_R1.fastq.gz | RNA-Seq | 961.6 MB |
| C156_R1.fastq.gz | RNA-Seq | 1.7 GB |
| C158_R1.fastq.gz | RNA-Seq | 2.0 GB |
| C165_R1.fastq.gz | RNA-Seq | 675.2 MB |
| C166_R1.fastq.gz | RNA-Seq | 724.9 MB |
| C167_R1.fastq.gz | RNA-Seq | 814.5 MB |
| C168_R1.fastq.gz | RNA-Seq | 570.5 MB |
| C169_R1.fastq.gz | RNA-Seq | 798.8 MB |
| C172_R1.fastq.gz | RNA-Seq | 619.6 MB |
| C174_R1.fastq.gz | RNA-Seq | 709.3 MB |
| C175_R1.fastq.gz | RNA-Seq | 1.0 GB |
| C176_R1.fastq.gz | RNA-Seq | 666.9 MB |
| C179_R1.fastq.gz | RNA-Seq | 721.2 MB |
| C188_R1.fastq.gz | RNA-Seq | 2.0 GB |
| C189_R1.fastq.gz | RNA-Seq | 561.5 MB |
| C191_R1.fastq.gz | RNA-Seq | 1.8 GB |
| C192_R1.fastq.gz | RNA-Seq | 528.0 MB |
| C194_R1.fastq.gz | RNA-Seq | 1.7 GB |
| C195_R1.fastq.gz | RNA-Seq | 1.9 GB |
| C196_R1.fastq.gz | RNA-Seq | 1.0 GB |
| SRR12778844_GSM4818780 | RNA-Seq | 2.1 GB |
| SRR12778845_GSM4818781 | RNA-Seq | 2.1 GB |
| SRR12778846_GSM4818782 | RNA-Seq | 3.0 GB |
| SRR12778847_GSM4818783 | RNA-Seq | 2.6 GB |
| SRR12778848_GSM4818784 | RNA-Seq | 2.9 GB |
| SRR12778849_GSM4818785 | RNA-Seq | 3.4 GB |
| SRR12778850_GSM4818786 | RNA-Seq | 885.0 MB |
| SRR12778851_GSM4818787 | RNA-Seq | 2.6 GB |
| SRR12778852_GSM4818788 | RNA-Seq | 646.0 MB |
| SRR12778853_GSM4818789 | RNA-Seq | 1.1 GB |
| SRR12778854_GSM4818790 | RNA-Seq | 918.0 MB |
| SRR12778855_GSM4818791 | RNA-Seq | 1.0 GB |
| SRR12778856_GSM4818792 | RNA-Seq | 2.8 GB |
| SRR12778857_GSM4818793 | RNA-Seq | 1.3 GB |
| SRR12778858_GSM4818794 | RNA-Seq | 1.5 GB |
| SRR12778859_GSM4818795 | RNA-Seq | 303.0 MB |
| SRR12778860_GSM4818796 | RNA-Seq | 374.0 MB |
| SRR12778861_GSM4818797 | RNA-Seq | 307.0 MB |
| SRR12778862_GSM4818798 | RNA-Seq | 376.0 MB |
| SRR12778863_GSM4818799 | RNA-Seq | 416.0 MB |
| SRR12778864_GSM4818800 | RNA-Seq | 424.0 MB |
| SRR12778865_GSM4818801 | RNA-Seq | 348.0 MB |
| SRR12778866_GSM4818802 | RNA-Seq | 376.0 MB |
| SRR12778867_GSM4818803 | RNA-Seq | 399.0 MB |
| SRR12778868_GSM4818804 | RNA-Seq | 310.0 MB |
| SRR12778869_GSM4818805 | RNA-Seq | 378.0 MB |
| SRR12778870_GSM4818806 | RNA-Seq | 463.0 MB |
| SRR12778871_GSM4818807 | RNA-Seq | 501.0 MB |
| SRR12778872_GSM4818808 | RNA-Seq | 463.0 MB |
| SRR12778873_GSM4818809 | RNA-Seq | 396.0 MB |
| SRR12778874_GSM4818810 | RNA-Seq | 978.0 MB |
| SRR12778875_GSM4818811 | RNA-Seq | 1.2 GB |
| SRR12778876_GSM4818812 | RNA-Seq | 1.8 GB |
| SRR12778877_GSM4818813 | RNA-Seq | 1.2 GB |
| SRR12778878_GSM4818814 | RNA-Seq | 1.3 GB |
| SRR12778879_GSM4818815 | RNA-Seq | 1.1 GB |
| SRR12778880_GSM4818816 | RNA-Seq | 961.0 MB |
| SRR12778881_GSM4818817 | RNA-Seq | 1.7 GB |
| SRR12778882_GSM4818818 | RNA-Seq | 2.0 GB |
| SRR12778883_GSM4818819 | RNA-Seq | 675.0 MB |
| SRR12778884_GSM4818820 | RNA-Seq | 724.0 MB |
| SRR12778885_GSM4818821 | RNA-Seq | 814.0 MB |
| SRR12778886_GSM4818822 | RNA-Seq | 570.0 MB |
| SRR12778887_GSM4818823 | RNA-Seq | 798.0 MB |
| SRR12778888_GSM4818824 | RNA-Seq | 619.0 MB |
| SRR12778889_GSM4818825 | RNA-Seq | 709.0 MB |
| SRR12778890_GSM4818826 | RNA-Seq | 1.0 GB |
| SRR12778891_GSM4818827 | RNA-Seq | 666.0 MB |
| SRR12778892_GSM4818828 | RNA-Seq | 721.0 MB |
| SRR12778893_GSM4818829 | RNA-Seq | 2.0 GB |
| SRR12778894_GSM4818830 | RNA-Seq | 561.0 MB |
| SRR12778895_GSM4818831 | RNA-Seq | 1.8 GB |
| SRR12778896_GSM4818832 | RNA-Seq | 527.0 MB |
| SRR12778897_GSM4818833 | RNA-Seq | 1.7 GB |
| SRR12778898_GSM4818834 | RNA-Seq | 1.9 GB |
| SRR12778899_GSM4818835 | RNA-Seq | 1.0 GB |
Analysis pipelines 1
| Pipeline | Assay | Steps | Dataset |
|---|---|---|---|
| GSE159074 RNA-seq Data Processing geo_data_processing | RNA-seq | 4 | GSE159074 |
Funding 6 grants
| Grant | Funder |
|---|---|
| R01 HG004659 | NHGRI NIH HHS (United States) |
| P30 CA023100 | NCI NIH HHS (United States) |
| P30 CA014195 | NCI NIH HHS (United States) |
| U54 HG007005 | NHGRI NIH HHS (United States) |
| R01 NS075449 | NINDS NIH HHS (United States) |
| R01 MH095741 | NIMH NIH HHS (United States) |