Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees

Wuming Gong, Alejandro A. Granados, Jingyuan Hu, Matthew G. Jones, Ofir Raz, Irepan Salvador-Martínez, Hanrui Zhang, Ke Huan K. Chow, Il Youp Kwak, Renata Retkute, Alidivinas Prusokas, Augustinas Prusokas, Alex Khodaverdian, Richard Zhang, Suhas Rao, Robert Wang, Phil Rennert, Vangala G. Saipradeep, Naveen Sivadasan, Aditya RaoThomas Joseph, Rajgopal Srinivasan, Jiajie Peng, Lu Han, Xuequn Shang, Daniel J. Garry, Thomas Yu, Verena Chung, Michael Mason, Zhandong Liu, Yuanfang Guan, Nir Yosef, Jay Shendure, Maximilian J. Telford, Ehud Shapiro, Michael B. Elowitz, Pablo Meyer

Research output: Contribution to journalArticlepeer-review

Abstract

The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.

Original languageEnglish (US)
Pages (from-to)810-826.e4
JournalCell Systems
Volume12
Issue number8
DOIs
StatePublished - Aug 18 2021

Bibliographical note

Funding Information:
Funding: the research was funded by the Paul G. Allen Frontiers Group Prime Awarding Agency and HFSP (RGP0002/2016) to I.S.-M. and M.J.T. A.A.G. I.S.-M. O.R. Y.G. Z.L. N.Y. J.S. M.J.T. E.S. M.B.E. and P.M. designed research; A.A.G. O.R. I.S.-M. W.G. J.H. H.Z. R.R. M.G.J. and P.M. analyzed data; K.-H.K.C. I.-Y.K. Al.P. Au.P. A.K. R.Z. S.R. R.W. P.R. V.G.S. N.S. A.R. T.J. R.S. J.P. L.H. and X.S. analyzed data; A.A.G. O.R. I.S. W.G. J.H. H.Z. R.R. M.G.J. and P.M. wrote the manuscript. The authors declare no competing interests. Worm image in Figure 1 was modified from Caenorhabditis elegans hermaphrodite adult-en.svg from Wikimedia Commons by K. D. Schroeder, CC-BY-SA 3.0. The schematic cell lineage of C. elegans in Figures 1 and 6 was generated using the cell lineage web visualization tool CeLaVi available at http://celavi.pro (Salvador-Mart?nez et al. 2020).

Funding Information:
Funding: the research was funded by the Paul G. Allen Frontiers Group Prime Awarding Agency and HFSP (RGP0002/2016) to I.S.-M. and M.J.T.

Publisher Copyright:
© 2021 The Authors

Keywords

  • C. elegans
  • CRISPR
  • M. musculus
  • benchmarking
  • cell lineage tracing
  • crowdsourcing
  • intmemoir
  • lineage reconstruction
  • machine learning
  • simulation

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

Fingerprint

Dive into the research topics of 'Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees'. Together they form a unique fingerprint.

Cite this