Targeted single-cell RNA sequencing of transcription factors enhances the identification of cell types and trajectories.
Targeted single-cell RNA sequencing of transcription factors enhances the identification of cell types and trajectories.
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DOI：
10.1101/gr.273961.120
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发表时间：
2021-06
期刊：
影响因子：
7
通讯作者：
Cader MZ
中科院分区：
文献类型：
--
作者：
Pokhilko A;Handel AE;Curion F;Volpato V;Whiteley ES;Bøstrand S;Newey SE;Akerman CJ;Webber C;Clark MB;Bowden R;Cader MZ
单细胞RNA测序（scRNA-seq）是一种广泛使用的方法，用于识别生物异质性样本中的细胞类型和轨迹，但它在低表达基因的检测和定量方面受到限制。这导致丢失重要的生物信号，例如驱动细胞分化的关键转录因子（TF）的表达。我们表明，在iPSC衍生的神经元培养物中对1000个TF（scCapture-seq）进行靶向测序极大地改善了从scRNA-seq获得的生物信息。TF分辨率的提高增强了细胞类型识别、发育轨迹和基因调控网络。这使我们能够解决神经元群体之间的差异，这些群体是在两个不同的实验室使用相同的分化方案产生的。ScCapture-seq改进了TF-基因调控网络推断，从而将神经发生的不同模式鉴定为兴奋性皮层神经元或抑制性中间神经元。此外，scCapture-seq揭示了视黄酸信号在这些不同神经元群体之间的发育分化中的作用。我们的研究结果表明，TF靶向改善了人类细胞模型的表征，并允许识别细胞群体之间的本质差异，否则在传统的scRNA-seq中会错过这些差异。scCapture-seq TF靶向代表了scRNA-seq的具有成本效益的增强，其可以广泛应用于提高scRNA-seq分辨率。
Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution.
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DOI：
10.1093/bioinformatics/btw216
发表时间：
2016-07-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Lachmann A;Giorgi FM;Lopez G;Califano A
通讯作者：
Califano A
影响因子：
14.9
作者：
Kuleshov MV;Jones MR;Rouillard AD;Fernandez NF;Duan Q;Wang Z;Koplev S;Jenkins SL;Jagodnik KM;Lachmann A;McDermott MG;Monteiro CD;Gundersen GW;Ma'ayan A
通讯作者：
Ma'ayan A
影响因子：
23.9
作者：
Inoue, Fumitaka;Kreimer, Anat;Yosef, Nir
通讯作者：
Yosef, Nir
影响因子：
14.9
作者：
Ranu N;Villani AC;Hacohen N;Blainey PC
通讯作者：
Blainey PC
影响因子：
64.5
作者：
Kinchen J;Chen HH;Parikh K;Antanaviciute A;Jagielowicz M;Fawkner-Corbett D;Ashley N;Cubitt L;Mellado-Gomez E;Attar M;Sharma E;Wills Q;Bowden R;Richter FC;Ahern D;Puri KD;Henault J;Gervais F;Koohy H;Simmons A
通讯作者：
Simmons A