LinRace: single cell lineage reconstruction using paired lineage barcode and gene expression data.
LinRace: single cell lineage reconstruction using paired lineage barcode and gene expression data.
复制标题
LinRace：使用配对谱系条形码和基因表达数据进行单细胞谱系重建。
DOI：
10.1101/2023.04.12.536601
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Zhang,Xiuwei
中科院分区：
文献类型：
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作者：
Pan,Xinhai;Li,Hechen;Putta,Pranav;Zhang,Xiuwei
了解单个细胞如何在发育器官中分裂和分化为不同类型的细胞是发育和干细胞生物学的主要任务之一。最近，使用CRISPR/Cas9基因组编辑的谱系追踪技术已经能够同时读出单个细胞中的基因表达和谱系条形码，这使得可以重建细胞分裂树，甚至可以在整个生物体水平上检测细胞类型和分化轨迹。虽然大多数最先进的血统重建方法只利用血统条形码数据，但结合基因表达数据的方法正在出现，旨在提高血统重建的准确性。然而，要有效地整合基因表达数据，需要一个关于基因表达数据如何随着几代人的分裂而变化的合理模型。在此，我们提出了一种利用非对称细胞分裂模型集成谱系条形码和基因表达数据，并在结合邻接法和最大似然启发式算法的框架下推断细胞谱系的方法LinRace。在模拟和真实数据上，LinRace输出的细胞分裂树比现有方法更准确。此外，LinRace可以输出祖先细胞的细胞状态(细胞类型)，这在现有的谱系重建方法中很少执行。关于祖细胞的信息可以用来分析祖细胞如何产生具有各种功能的大量细胞。LinRace的网址是：https://github.com/ZhangLabGT/LinRace.。
Understanding how single cells divide and differentiate into different cell types in developed organs is one of the major tasks of developmental and stem cell biology. Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes in single cells, which allows for the reconstruction of the cell division tree, and even the detection of cell types and differentiation trajectories at the whole organism level. While most state-of-the-art methods for lineage reconstruction utilize only the lineage barcode data, methods that incorporate gene expression data are emerging, aiming to improve the accuracy of lineage reconstruction. However, effectively incorporating the gene expression data requires a reasonable model on how gene expression data changes along generations of divisions. Here, we present LinRace (Lineage Reconstruction with asymmetric cell division model), a method that integrates the lineage barcode and gene expression data using the asymmetric cell division model and infers cell lineage under a framework combining Neighbor Joining and maximum-likelihood heuristics. On both simulated and real data, LinRace outputs more accurate cell division trees than existing methods. Moreover, LinRace can output the cell states (cell types) of ancestral cells, which is rarely performed with existing lineage reconstruction methods. The information on ancestral cells can be used to analyze how a progenitor cell generates a large population of cells with various functionalities. LinRace is available at: https://github.com/ZhangLabGT/LinRace.