MTaxi

MTaxi assigns mitochondrial sequencing reads to discriminate between pairs of closely related species by analyzing mtDNA transversion-type substitutions for taxonomic identification of low-coverage and ancient samples.


Key Features:

  • Mitochondrial DNA Utilization: Focuses on mtDNA transversion-type substitutions to differentiate between candidate species, avoiding reliance on high-quality nuclear reference genomes.
  • Read Assignment and Statistical Testing: Assigns sequencing reads to candidate species based on identified mtDNA variations and employs a binomial test to ascertain taxonomic identity.
  • Efficiency at Low Coverage: Demonstrated performance at mitochondrial coverages as low as 0.5x, enabling analysis of degraded ancient samples with limited sequencing depth.
  • Accuracy and Reliability: In tests with simulated ancient genomes and archaeological samples (n=18 sheep/goat and n=10 horse/donkey), achieved 100% accuracy without false positives.

Scientific Applications:

  • Zooarchaeology: Distinguishes between morphologically similar taxa such as sheep and goat or horse and donkey from small bone fragments using mtDNA markers.
  • Taxonomic classification of degraded samples: Enables reliable species identification from low-coverage and ancient DNA where traditional morphological or nuclear-genome-based methods are limited.

Methodology:

Detect transversion-type mtDNA substitutions between candidate species, assign sequencing reads to species based on those substitutions, and validate taxonomic identity using a binomial test.

Topics

Details

License:
CC-BY-4.0
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Linux, Windows
Programming Languages:
Python
Added:
2/26/2023
Last Updated:
11/24/2024

Operations

Publications

Atağ G, Vural KB, Kaptan D, Özkan M, Koptekin D, Sağlıcan E, Doğramacı S, Köz M, Yılmaz A, Söylev A, Togan İ, Somel M, Özer F. MTaxi : A comparative tool for taxon identification of ultra low coverage ancient genomes. Unknown Journal. 2022. doi:10.1101/2022.06.06.491147.