Evolution of cellular traits

Many processes in biology, including organ development, tumor growth, and adaptive immunity unfold over time in a way that originates from a small progenitor population and progresses through cell division and selective expansion of sub-clones. The emerging field of single-cell lineage tracing provides a unique opportunity to study these processes at an unparalleled resolution by tracking the clonal history of individual cells, while at the same time recording their transcriptomes.  Our group is harnessing Cas9- based lineage tracing technologies  to study clonal processes, with the current emphasis on tumor growth and its association with immunity. To enable these studies, we are developing the accompanying algorithms and software, targeting different aspects of the work such as inference of lineage trees and its theoretical guarantees, estimation of divergence times, analysis of heritable transcriptional programs,  and analysis of transcriptional changes that take place during the evolution of clonal populations. This work brings together ideas from graph algorithms, statistical phylogenetics and generative modeling, with most tools available as open-source under our Hotspot, Cassiopeia and  Pycea projects. 

Genetic tools for tracking cellular progenies (lineage tracing) provide powerful ways for studying how cellular populations evolve, and have powered numerous studies of clonal expansion and fate choices in cancer, immunity and development. While useful in many applications, the traditional approach for lineage tracing provides a limited level of resolution, such that it can only distinguish between clones, but not inform on more nuanced sub-clonal structures. Recent work, to which we have contributed now employs CRISPR/Cas9 coupled with single-cell RNA- sequencing to enable lineage tracing at a single cell level, and for thousands of cells at a time. Generally, this approach begins with progenitor cells engineered with one or more synthetic target sites, where Cas9-induced heritable indels accumulate and are subsequently read out by RNA sequencing. These heritable scars provide a way to estimate the clonal and subclonal relationships between cells, which can be summarized in phylogenetic trees. Application of this approach in mouse tumor models, powered by computational tools from the Cassiopeia and Hotspot projects, helped us shed new light on the trajectories of cell states that lead from a transformed progenitor population to metastatic tumors and identify transcriptional correlates that distinguish rapidly expanding sub-clones. 

 

 

 

 

 

 

 

Relevant publications

  • ConvexML: Scalable and accurate inference of single-cell chronograms from CRISPR/Cas9 lineage tracing data. S. Prillo, A. Ravoor, N. Yosef†, YS. Song† (bioRxiv)
     
  • Tree reconstruction guarantees from CRISPR-Cas9 lineage tracing data using Neighbor-Joining. S.  Prillo, K. An, W. Wu, I. Kristanto, MG. Jones, YS. Song† , N. Yosef† (bioRxiv)
     
  • Theoretical Guarantees for Phylogeny Inference from Single-Cell Lineage Tracing. R. Wang*, RY. Zhang*, A. Khodaverdian*, Nir Yosef. Proceedings of the National Academy of Science, 202
     
  • Lineage Recording Reveals the Phylodynamics, Plasticity and Paths of Tumor Evolution. D. Yang*, MG. Jones*, S. Naranjo, WM. Rideout III, KH. Min, R. Ho, W. Wu, RM. Replogle, JL. Page, JJ. Quinn, F. Horns, X. Qiu, MZ. Chen, WA. Freed-Pastor, CS. McGinnis, DM. Patterson, ZJ. Gartner, ED. Chow, TG. Bivona, MM. Chan, N. Yosef†, T. Jacks†, JS. Weissman† Cell, 2022
     
  • PhyloVision: Interactive Software for Integrated Analysis of Single-Cell Transcriptomic and Phylogenetic Data. MG. Jones*, Y. Rosen*, N. Yosef. Cell Reports Methods, 2022
     
  • Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. JJ. Quinn*, MG. Jones*, RA. Okimoto, N. Yosef †, TG. Bivona †, JS. Weissman † Science. 2021. 371(6532):eabc1944. doi: 10.1126/science.abc1944
     
  • Reconstructing unobserved cellular states from paired single-cell lineage tracing and transcriptomics data. K. Ouardini, R. Lopez, MG. Jones, S. Prillo, R. Zhang, MI. Jordan, N. Yosef ICML 2021 Workshop on Computational Biology, 2021. doi.org/10.1101/2021.05.28.446021
     
  • Inference of Single-Cell Phylogenies from Lineage Tracing Data MG. Jones*, A. Khodaverdian*, JJ. Quinn*, MM. Chan, JA. Hussmann, R. Wang, C. Xu, JS. Weissman†, N. Yosef † Genome Biology 21, 92 (2020) https://doi.org/10.1186/s13059-020-02000-8