MapGL

MapGL infers evolutionary gain and loss of short genomic sequence features to enable phylogenetic analysis of cis-regulatory element turnover across eutherian genomes.


Key Features:

  • Targeted sequence features: Infers gain and loss events for short genomic sequence features, specifically cis-regulatory elements.
  • Phylogenetic algorithm: Implements phylogenetic maximum parsimony for ancestral-state reconstruction.
  • Ancestral-state reconstruction: Reconstructs ancestral presence/absence states by minimizing the number of evolutionary changes.
  • Phylogenetic scope: Supports analysis across a wide range of phylogenetic topologies and evolutionary distances.
  • Taxonomic application: Applied to comparative analyses of eutherian genomes.
  • Evolutionary context: Places species-specific sequence features within an explicit phylogenetic framework to assess regulatory sequence turnover.

Scientific Applications:

  • Comparative genomics: Elucidates shared and divergent regulatory sequence content between species using phylogenetic inference.
  • Regulatory sequence turnover: Quantifies gain and loss of cis-regulatory elements to study turnover dynamics.
  • Phenotypic divergence: Investigates how genomic sequence gain and loss contribute to species-specific phenotypic differences.
  • Genome evolution and regulatory biology: Supports studies on genome evolution, regulatory element evolution, and the genetic basis of adaptation.

Methodology:

Uses phylogenetic maximum parsimony to reconstruct ancestral states by minimizing the number of evolutionary changes.

Topics

Details

License:
MIT
Tool Type:
command-line tool, library
Programming Languages:
Python, Shell, R
Added:
1/18/2021
Last Updated:
2/19/2021

Operations

Publications

Diehl AG, Boyle AP. MapGL: inferring evolutionary gain and loss of short genomic sequence features by phylogenetic maximum parsimony. BMC Bioinformatics. 2020;21(1). doi:10.1186/s12859-020-03742-9. PMID:32962625. PMCID:PMC7510305.

PMID: 32962625
PMCID: PMC7510305
Funding: - Alfred P. Sloan Foundation: FG-2015-65465 - National Institutes of Health: DBI-1651614

Links