A generic, cost-effective, and scalable cell lineage analysis platform.
A generic, cost-effective, and scalable cell lineage analysis platform.
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DOI：
10.1101/gr.202903.115
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发表时间：
2016-11
期刊：
影响因子：
7
通讯作者：
Shapiro E
中科院分区：
文献类型：
--
作者：
Biezuner T;Spiro A;Raz O;Amir S;Milo L;Adar R;Chapal-Ilani N;Berman V;Fried Y;Ainbinder E;Cohen G;Barr HM;Halaban R;Shapiro E
单细胞基因组学的进展使得揭示单个细胞之间谱系关系的方法得到相应的改进。目前用于细胞谱系分析的基于测序的方法依赖于低分辨率批量分析或依赖于广泛的单细胞测序，这是不可扩展的，并且可能因功能依赖性而产生偏差。在这里，我们展示了一个用于通用单细胞谱系分析的集成生化计算平台，该平台具有回顾性，成本效益和可扩展性。它由一个生物化学计算管道组成，该管道输入单个细胞，产生有针对性的单细胞测序数据，并使用它来生成输入细胞的谱系树。我们通过将其应用于从离体生长的树中取样的细胞来验证该平台，并通过计算机模拟分析其可行性前景。我们的结论是，该平台可以作为谱系分析的通用工具，从而为大规模人类细胞谱系发现铺平道路。
Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery.
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影响因子：
4.5
作者：
Reizel Y;Chapal-Ilani N;Adar R;Itzkovitz S;Elbaz J;Maruvka YE;Segev E;Shlush LI;Dekel N;Shapiro E
通讯作者：
Shapiro E
影响因子：
4.5
作者：
Reizel Y;Itzkovitz S;Adar R;Elbaz J;Jinich A;Chapal-Ilani N;Maruvka YE;Nevo N;Marx Z;Horovitz I;Wasserstrom A;Mayo A;Shur I;Benayahu D;Skorecki K;Segal E;Dekel N;Shapiro E
通讯作者：
Shapiro E
影响因子：
48
作者：
Carlson, Cheryl A.;Kas, Arnold;Kirkwood, Robert;Hays, Laura E.;Preston, Bradley D.;Salipante, Stephen J.;Horwitz, Marshall S.
通讯作者：
Horwitz, Marshall S.
影响因子：
30.8
作者：
Krauthammer M;Kong Y;Bacchiocchi A;Evans P;Pornputtapong N;Wu C;McCusker JP;Ma S;Cheng E;Straub R;Serin M;Bosenberg M;Ariyan S;Narayan D;Sznol M;Kluger HM;Mane S;Schlessinger J;Lifton RP;Halaban R
通讯作者：
Halaban R
影响因子：
64.8
作者：
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通讯作者：
Wigler M