Zou, Q., Wan, S., Zeng, X. & Ma, Z. S. Reconstructing evolutionary trees in parallel for massive sequences. BMC Syst. Biol. 11, 100 (2017).
Google Scholar
Mora, C., Tittensor, D. P., Adl, S., Simpson, A. G. & Worm, B. How many species are there on Earth and in the ocean? PLoS Biol. 9, e1001127 (2011).
Google Scholar
Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).
Google Scholar
Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013).
Google Scholar
Kalhor, R. et al. Developmental barcoding of whole mouse via homing CRISPR. Science 361, eaat9804 (2018).
Google Scholar
Chan, M. M. et al. Molecular recording of mammalian embryogenesis. Nature 570, 77–82 (2019).
Google Scholar
Bowling, S. et al. An engineered CRISPR–Cas9 mouse line for simultaneous readout of lineage histories and gene expression profiles in single cells. Cell 181, 1410–1422 (2020).
Google Scholar
Salvador-Martinez, I., Grillo, M., Averof, M. & Telford, M. J. Is it possible to reconstruct an accurate cell lineage using CRISPR recorders? eLife 8, e40292 (2019).
Google Scholar
McKenna, A. et al. Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science 353, aaf7907 (2016).
Google Scholar
Raj, B. et al. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat. Biotechnol. 36, 442–450 (2018).
Google Scholar
Spanjaard, B. et al. Simultaneous lineage tracing and cell-type identification using CRISPR–Cas9-induced genetic scars. Nat. Biotechnol. 36, 469–473 (2018).
Google Scholar
Alemany, A., Florescu, M., Baron, C. S., Peterson-Maduro, J. & van Oudenaarden, A. Whole-organism clone tracing using single-cell sequencing. Nature 556, 108–112 (2018).
Google Scholar
Quinn, J. J. et al. Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science 371, eabc1944 (2021).
Google Scholar
Simeonov, K. P. et al. Single-cell lineage and transcriptome reconstruction of metastatic cancer reveals selection of aggressive hybrid EMT states. Cancer Cell 39, 1150–1162.e9 (2021).
Google Scholar
Cao, J. et al. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science 357, 661–667 (2017).
Google Scholar
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
Google Scholar
Cao, J. et al. A human cell atlas of fetal gene expression. Science 370, eaba7721 (2020).
Google Scholar
Sender, R., Fuchs, S. & Milo, R. Revised estimates for the number of human and bacteria cells in the body. PLoS Biol. 14, e1002533 (2016).
Google Scholar
Barbera, P. et al. EPA-ng: massively parallel evolutionary placement of genetic sequences. Syst. Biol. 68, 365–369 (2019).
Google Scholar
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Google Scholar
Simonsen, M., Mailund, T. & Pedersen, C. N. S. in International Workshop on Algorithms in Bioinformatics 113–122 (Springer, 2008).
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).
Google Scholar
Robinson, D. F. & Foulds, L. R. Comparison of phylogenetic trees. Math. Biosci. 53, 131–147 (1981).
Yarza, P. et al. The All-Species Living Tree project: a 16S rRNA-based phylogenetic tree of all sequenced type strains. Syst. Appl. Microbiol. 31, 241–250 (2008).
Google Scholar
Parks, D. H. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 36, 996–1004 (2018).
Google Scholar
Frieda, K. L. et al. Synthetic recording and in situ readout of lineage information in single cells. Nature 541, 107–111 (2017).
Google Scholar
Jones, M. G. et al. Inference of single-cell phylogenies from lineage tracing data using Cassiopeia. Genome Biol. 21, 92 (2020).
Google Scholar
Nishida, K. et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, aaf8729 (2016).
Google Scholar
Hwang, B. et al. Lineage tracing using a Cas9-deaminase barcoding system targeting endogenous L1 elements. Nat. Commun. 10, 1234 (2019).
Google Scholar
Grünewald, J. et al. A dual-deaminase CRISPR base editor enables concurrent adenine and cytosine editing. Nat. Biotechnol. 38, 861–864 (2020).
Google Scholar
Zhang, X. et al. Dual base editor catalyzes both cytosine and adenine base conversions in human cells. Nat. Biotechnol. 38, 856–860 (2020).
Google Scholar
Sakata, R. C. et al. Base editors for simultaneous introduction of C-to-T and A-to-G mutations. Nat. Biotechnol. 38, 865–869 (2020).
Google Scholar
Du, Z., Santella, A., He, F., Tiongson, M. & Bao, Z. De novo inference of systems-level mechanistic models of development from live-imaging-based phenotype analysis. Cell 156, 359–372 (2014).
Google Scholar
Ciccarelli, F. D. et al. Toward automatic reconstruction of a highly resolved tree of life. Science 311, 1283–1287 (2006).
Google Scholar
Brown, C. T. et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature 523, 208–211 (2015).
Google Scholar
Poe, S. & Swofford, D. L. Taxon sampling revisited. Nature 398, 299–300 (1999).
Google Scholar
Chow, K. K. et al. Imaging cell lineage with a synthetic digital recording system. Science 372, eabb3099 (2021).
Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).
Google Scholar
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
Google Scholar
Yu, M. K. et al. DDOT: a Swiss army knife for investigating data-driven biological ontologies. Cell Syst. 8, 267–273 (2019).
Google Scholar
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
Google Scholar
Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).
Google Scholar
Shen, W., Le, S., Li, Y. & Hu, F. SeqKit: a cross-platform and ultrafast toolkit for FASTA/Q file manipulation. PLoS ONE 11, e0163962 (2016).
Google Scholar
Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2010).
Google Scholar
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
Google Scholar
Madeira, F. et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 47, W636–W641 (2019).
Google Scholar
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).
Google Scholar
Baum, B. R. PHYLIP: phylogeny inference package. Version 3.2. Quarterly Review of Biology 64, 539–541 (1989).
Zhao, L., Liu, Z., Levy, S. F. & Wu, S. Bartender: a fast and accurate clustering algorithm to count barcode reads. Bioinformatics 34, 739–747 (2018).
Google Scholar
Satopaa, V., Albrecht, J., Irwin, D. & Raghavan, B. in 2011 31st International Conference on Distributed Computing Systems Workshops 166–171 (IEEE, 2011).
Levenshtein, V. I. in Soviet Physics Doklady, Vol. 10 707–710 (Doklady Akademii Nauk SSSR, 1966).
Brunner, E. & Munzel, U. The nonparametric Behrens–Fisher problem: asymptotic theory and a small-sample approximation. Biom. J. 42, 17–25 (2000).
