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Related Experiment Video

Updated: Jul 8, 2025

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Published on: March 22, 2016

Time-resolved, integrated analysis of clonally evolving genomes.

Carine Legrand^1,2, Ranja Andriantsoa¹, Peter Lichter^3,4

¹Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Heidelberg, Germany.

|December 14, 2023

Summary

This study introduces a new framework to analyze clonal genome evolution, estimating key parameters like mutation rates and time. It successfully predicted the marbled crayfish speciation date and revealed insights into glioblastoma tumor progression.

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Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers MADM

Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers MADM

Published on: May 8, 2020

Area of Science:

Evolutionary Biology
Genomics
Cancer Research

Background:

Clonal genome evolution is fundamental to asexual reproduction and cancer.
Existing studies often describe evolutionary landscapes but lack quantitative parameter estimation from molecular data.
Integrating theoretical models with empirical data for clonal evolution analysis remains a challenge.

Purpose of the Study:

To develop a theoretical framework linking mutation rate, time, and expansion dynamics to biological/clinical parameters.
To infer time-resolved evolutionary parameters from molecular data, including mutation accumulation and signatures.
To apply this framework to understand the evolutionary history of the marbled crayfish and glioblastoma progression.

Main Methods:

Derived theoretical results connecting evolutionary parameters.
Inferred evolutionary parameters using mutation accumulation, mutational signatures, and selection analyses.
Applied the framework to whole-genome sequencing data from marbled crayfish and glioblastoma samples.

Main Results:

Predicted marbled crayfish speciation between 1986-1990, aligning with biological records.
Identified distinct evolutionary subgroups within glioblastoma.
Demonstrated that tumor cell survival dynamics can be inferred from primary tumor genomic data.

Conclusions:

The developed framework enables time-resolved, integrated analysis of clonal genome evolution parameters.
Provides novel insights into the evolutionary age of the invasive marbled crayfish.
Offers new perspectives on glioblastoma progression and potential for early genomic inference of tumor behavior.