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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Phylogeny

Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire...
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Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
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Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
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Updated: Jun 12, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

SciPhy: A Bayesian phylogenetic framework using sequential genetic lineage tracing data.

Sophie Seidel1,2, Antoine Zwaans3,4, Samuel Regalado5

  • 1Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland. soseidel@uw.edu.

Nature Communications
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

CRISPR lineage tracing now has a powerful tool, SciPhy, for reconstructing cell family trees. This Bayesian phylogenetic approach accurately models cell populations and developmental dynamics.

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Last Updated: Jun 12, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Area of Science:

  • Genetics
  • Computational Biology
  • Developmental Biology

Background:

  • CRISPR-based lineage tracing enables single-cell lineage tree reconstruction, particularly in challenging organisms.
  • Sequential genome editing captures both genetic modifications and their temporal order.

Purpose of the Study:

  • Introduce SciPhy, a novel simulation and inference tool for CRISPR lineage tracing data.
  • Leverage Bayesian phylogenetics to jointly estimate phylogenies and cell population dynamics.

Main Methods:

  • SciPhy is implemented in BEAST 2, employing a Bayesian phylogenetic approach.
  • The tool was validated using simulated data and benchmarked against existing methods with real data.

Main Results:

  • SciPhy accurately reconstructs phylogenies from CRISPR lineage tracing data.
  • It outperforms UPGMA, providing estimates of uncertainty and proliferation rates.
  • The tool successfully models time-varying population dynamics in murine gastruloids.

Conclusions:

  • SciPhy establishes a robust phylodynamic framework for quantitative lineage tracing analysis.
  • This tool enhances the study of cellular development and population dynamics.