Lineage tracing on transcriptional landscapes links state to fate during differentiation.
Lineage tracing on transcriptional landscapes links state to fate during differentiation.
复制标题
DOI：
10.1126/science.aaw3381
复制
发表时间：
2020-02-14
期刊：
影响因子：
--
通讯作者：
Klein AM
中科院分区：
文献类型：
--
作者：
Weinreb C;Rodriguez-Fraticelli A;Camargo FD;Klein AM
生物学上的一个挑战是将祖细胞之间的分子差异与它们产生成熟细胞类型的能力联系起来。在这里，我们使用表达的DNA条形码随着时间的推移克隆跟踪转录本，应用于研究造血中的命运决定。我们识别启动的命运潜力的状态，并在连续的转录景观上定位它们。我们确定了在成熟细胞上留下印记的两种单核细胞分化途径。克隆分析还揭示了命运偏向于多个谱系，这些谱系依赖于单细胞RNA测序隐藏的稳定细胞属性。最后，我们对从单细胞快照进行动态推理的计算方法进行了基准测试，结果表明，命运选择发生得比最先进的算法检测到的更早，细胞在伪时间中以精确和一致的动力学稳步前进。单细胞条形码揭示了从单细胞转录组图谱进行谱系推断的局限性。
A challenge in biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Here, we use expressed DNA barcodes to clonally trace transcriptomes over time, applied to study fate determination in hematopoiesis. We identify states of primed fate potential, and locate them on a continuous transcriptional landscape. We identify two routes of monocyte differentiation that leave an imprint on mature cells. Clonal analysis also reveals fate biases into multiple lineages that depend on stable cellular properties hidden from single-cell RNA sequencing. Finally, we benchmark computational methods of dynamic inference from single-cell snapshots, showing that fate choice occurs earlier than is detected by state-of the-art algorithms, and that cells progress steadily through pseudotime with precise and consistent dynamics. Single-cell barcoding reveals limits of lineage inference from single-cell transcriptome atlases.
登录
查看更多内容
影响因子：
2.6
作者：
Naik, Shalin H.;Schumacher, Ton N.;Perie, Leila
通讯作者：
Perie, Leila
影响因子：
64.8
作者：
Montoro DT;Haber AL;Biton M;Vinarsky V;Lin B;Birket SE;Yuan F;Chen S;Leung HM;Villoria J;Rogel N;Burgin G;Tsankov AM;Waghray A;Slyper M;Waldman J;Nguyen L;Dionne D;Rozenblatt-Rosen O;Tata PR;Mou H;Shivaraju M;Bihler H;Mense M;Tearney GJ;Rowe SM;Engelhardt JF;Regev A;Rajagopal J
通讯作者：
Rajagopal J
影响因子：
64.8
作者：
La Manno G;Soldatov R;Zeisel A;Braun E;Hochgerner H;Petukhov V;Lidschreiber K;Kastriti ME;Lönnerberg P;Furlan A;Fan J;Borm LE;Liu Z;van Bruggen D;Guo J;He X;Barker R;Sundström E;Castelo-Branco G;Cramer P;Adameyko I;Linnarsson S;Kharchenko PV
通讯作者：
Kharchenko PV
影响因子：
20.3
作者：
Nestorowa, Sonia;Hamey, Fiona K.;Gottgens, Berthold
通讯作者：
Gottgens, Berthold
影响因子：
64.8
作者：
Chan, Michelle M.;Smith, Zachary D.;Weissman, Jonathan S.
通讯作者：
Weissman, Jonathan S.