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 Rao; Thomas 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

doi:10.1016/j.cels.2021.05.008

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

Medicine - Cardiology Division

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

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 language	English (US)
Pages (from-to)	810-826.e4
Journal	Cell Systems
Volume	12
Issue number	8
DOIs	https://doi.org/10.1016/j.cels.2021.05.008
State	Published - 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.

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-Martínez et al. 2020).

Publisher Copyright:
© 2021 The Authors

Keywords

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

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10.1016/j.cels.2021.05.008

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Gong, W., Granados, A. A., Hu, J., Jones, M. G., Raz, O., Salvador-Martínez, I., Zhang, H., Chow, K. H. K., Kwak, I. Y., Retkute, R., Prusokas, A., Prusokas, A., Khodaverdian, A., Zhang, R., Rao, S., Wang, R., Rennert, P., Saipradeep, V. G., Sivadasan, N., ... Meyer, P. (2021). Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees. Cell Systems, 12(8), 810-826.e4. https://doi.org/10.1016/j.cels.2021.05.008

Gong, W, Granados, AA, Hu, J, Jones, MG, Raz, O, Salvador-Martínez, I, Zhang, H, Chow, KHK, Kwak, IY, Retkute, R, Prusokas, A, Prusokas, A, Khodaverdian, A, Zhang, R, Rao, S, Wang, R, Rennert, P, Saipradeep, VG, Sivadasan, N, Rao, A, Joseph, T, Srinivasan, R, Peng, J, Han, L, Shang, X, Garry, DJ, Yu, T, Chung, V, Mason, M, Liu, Z, Guan, Y, Yosef, N, Shendure, J, Telford, MJ, Shapiro, E, Elowitz, MB & Meyer, P 2021, 'Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees', Cell Systems, vol. 12, no. 8, pp. 810-826.e4. https://doi.org/10.1016/j.cels.2021.05.008

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

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.",

keywords = "C. elegans, CRISPR, M. musculus, benchmarking, cell lineage tracing, crowdsourcing, intmemoir, lineage reconstruction, machine learning, simulation",

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

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. 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{\'i}nez et al. 2020). Publisher Copyright: {\textcopyright} 2021 The Authors",

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doi = "10.1016/j.cels.2021.05.008",

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T1 - Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees

AU - Gong, Wuming

AU - Granados, Alejandro A.

AU - Hu, Jingyuan

AU - Jones, Matthew G.

AU - Raz, Ofir

AU - Salvador-Martínez, Irepan

AU - Zhang, Hanrui

AU - Chow, Ke Huan K.

AU - Kwak, Il Youp

AU - Retkute, Renata

AU - Prusokas, Alidivinas

AU - Prusokas, Augustinas

AU - Khodaverdian, Alex

AU - Zhang, Richard

AU - Rao, Suhas

AU - Wang, Robert

AU - Rennert, Phil

AU - Saipradeep, Vangala G.

AU - Sivadasan, Naveen

AU - Rao, Aditya

AU - Joseph, Thomas

AU - Srinivasan, Rajgopal

AU - Peng, Jiajie

AU - Han, Lu

AU - Shang, Xuequn

AU - Garry, Daniel J.

AU - Yu, Thomas

AU - Chung, Verena

AU - Mason, Michael

AU - Liu, Zhandong

AU - Guan, Yuanfang

AU - Yosef, Nir

AU - Shendure, Jay

AU - Telford, Maximilian J.

AU - Shapiro, Ehud

AU - Elowitz, Michael B.

AU - Meyer, Pablo

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N2 - 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.

AB - 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.

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KW - CRISPR

KW - M. musculus

KW - benchmarking

KW - cell lineage tracing

KW - crowdsourcing

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KW - lineage reconstruction

KW - machine learning

KW - simulation

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JO - Cell Systems

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ER -

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

Abstract

Bibliographical note

Keywords

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