Trimitomics
Trimitomics assembles mitochondrial genomes from transcriptomic (RNA-sequencing) reads to recover complete mitochondrial sequences for phylogenetic, population-genetic, and molecular analyses of nonmodel species, including invertebrates such as poriferans.
Key Features:
- Robustness Across Sequencing Depths: Processes RNA-sequencing data of varying depths to recover mitochondrial protein-coding and ribosomal genes.
- Comprehensive Genome Recovery: Enables complete assembly of mitochondrial genomes when sequencing depth is sufficient.
- Utility in Diverse Biological Contexts: Leverages mitochondrial DNA properties—high copy number and a mix of fast- and slow-evolving regions—to support phylogenetic, population, and molecular studies, including analyses of degraded samples and recent speciation events.
- Application to Nonmodel Invertebrates: Demonstrated efficacy across nonmodel invertebrate species from six phyla, including poriferans where microbiological symbionts complicate assembly.
Scientific Applications:
- Phylogenetics: Provides complete mitochondrial genomes for constructing and refining phylogenetic trees.
- Population Genetics: Enables analysis of mitochondrial DNA variation for studies of genetic diversity and population structure.
- Molecular Biology: Supports investigation of mitochondrial gene function and regulation relevant to cellular metabolism and energy production.
Methodology:
Processes Illumina next-generation RNA-sequencing reads to assemble mitochondrial genomes, accommodating variable sequencing depths and addressing assembly challenges posed by symbiont-derived sequences.
Topics
Details
- License:
- MIT
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java, Perl
- Added:
- 8/9/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Plese B, Rossi ME, Kenny NJ, Taboada S, Koutsouveli V, Riesgo A. Trimitomics: An efficient pipeline for mitochondrial assembly from transcriptomic reads in nonmodel species. Molecular Ecology Resources. 2019;19(5):1230-1239. doi:10.1111/1755-0998.13033. PMID:31070854.