Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Bayesian estimation of genomic distance.

Richard Durrett1, Rasmus Nielsen, Thomas L York

  • 1Department of Mathematics, Cornell University, Ithaca, New York 14853, USA. rtd1@cornell.edu

Genetics
|March 17, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026
Same author

Genome Scanning Reveals the Genetic Basis of a Color Pattern Morphotype in an Island Population of the European Adder (Vipera berus).

Genome biology and evolution·2026
Same author

The genomic basis of adaptive leaf variation in the Galápagos giant daisies.

Nature communications·2026
Same author

WASTER: Practical de novo Phylogenomics from Low-coverage Short Reads.

Molecular biology and evolution·2026
Same author

Diffeomorphic Independent Contrasts for Ancestral Reconstruction of Shapes.

Systematic biology·2026
Same author

Erratum to: Accuracy of thick and thin intraocular lens power formulas using paraxial vergence calculation.

Journal of cataract and refractive surgery·2026
Same journal

Coexistence of piRNA and KZFP defense systems: Evolutionary dynamics of layered defense against transposable elements.

Genetics·2026
Same journal

Creation and manipulation of bipartite expression transgenes in C. elegans using phiC31 recombinase.

Genetics·2026
Same journal

Inherited long telomeres induce a genome-wide transcriptional response in budding yeast.

Genetics·2026
Same journal

Adaptive Dynamics of Quantitative Traits in a Steadily Changing Environment.

Genetics·2026
Same journal

Functional Landscape of Zebrafish Gonadotropins and Receptors: A Comprehensive Genetic Analysis.

Genetics·2026
Same journal

Synergistic actions of Nup43 and Myosin VI drive actin cone assembly during Drosophila spermiogenesis.

Genetics·2026
See all related articles

We developed a new Bayesian method to count inversions and translocations between species. This approach provides more accurate evolutionary event counts than traditional methods, particularly for complex genomic rearrangements.

Area of Science:

  • Comparative genomics
  • Evolutionary biology
  • Bioinformatics

Background:

  • Inferring the number of chromosomal rearrangements (inversions and translocations) is crucial for understanding species evolution.
  • Existing methods, like parsimony, may not accurately reflect the true number of evolutionary events, especially with complex genomic data.
  • Testing hypotheses about the mechanisms driving these rearrangements requires robust quantitative methods.

Purpose of the Study:

  • To introduce a novel Bayesian statistical framework for estimating the number of inversions and translocations between two species.
  • To enable hypothesis testing regarding the evolutionary processes shaping chromosomal rearrangements, such as inversion size distribution and rate variation.
  • To provide a more accurate and probabilistic assessment of genomic evolutionary events compared to parsimony-based approaches.

Related Experiment Videos

Main Methods:

  • Developed a Bayesian inference model to estimate the number of inversions and translocations.
  • Applied the model to comparative genomic maps from three species pairs: eggplant-tomato, human-cat, and human-cattle.
  • Utilized datasets with varying numbers of genetic markers (170, 269, and 422, respectively) to test the method's scalability.

Main Results:

  • The Bayesian approach yielded a higher number of likely evolutionary events than parsimony for the eggplant-tomato comparison.
  • For human-cat and human-cattle comparisons, parsimony-based solutions were found to have a very low probability under the Bayesian model.
  • The results indicate that the Bayesian method offers a more nuanced and statistically supported estimation of chromosomal rearrangements.

Conclusions:

  • The proposed Bayesian method provides a powerful tool for inferring chromosomal rearrangements and testing evolutionary hypotheses.
  • This approach offers a more statistically rigorous alternative to parsimony, especially for complex evolutionary histories.
  • The findings highlight the potential for Bayesian inference in advancing our understanding of genome evolution and speciation.