Mining NCBI Sequence Read Archive Database: An Untapped Source of Organelle Genomes for Taxonomic and Comparative Genomics Research

The NCBI SRA database is constantly expanding due to the large amount of genomic and transcriptomic data from various organisms generated by next-generation sequencing, and re-searchers worldwide regularly deposit new data into the database. This high-coverage genomic and transcriptomic information...

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Vydané v:Diversity (Basel) Ročník 16; číslo 2; s. 104
Hlavní autori: Eldem, Vahap, Balcı, Mehmet Ali
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.02.2024
Predmet:
Archives & records
Automation
Bioinformatics
Biology
chloroplast genome
Chloroplasts
Data mining
Gene sequencing
Genetics
Genomes
Genomics
Identification and classification
Invertebrates
Metadata
Methods
mitochondria
Mitochondrial DNA
mitochondrial genome
Mollusks
Next-generation sequencing
organelle genome
Organelles
Organisms
Phenetics
Plant species
Population genetics
sequence read archive
Software utilities
Sperm
systematics
Taxonomy
Transcriptomics
Vertebrates
Workflow
Turkey
ISSN:1424-2818, 1424-2818
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Popis
Shrnutí:The NCBI SRA database is constantly expanding due to the large amount of genomic and transcriptomic data from various organisms generated by next-generation sequencing, and re-searchers worldwide regularly deposit new data into the database. This high-coverage genomic and transcriptomic information can be re-evaluated regardless of the original research subject. The database-deposited NGS data can offer valuable insights into the genomes of organelles, particularly for non-model organisms. Here, we developed an automated bioinformatics workflow called “OrgaMiner”, designed to unveil high-quality mitochondrial and chloroplast genomes by data mining the NCBI SRA database. OrgaMiner, a Python-based pipeline, automatically orchestrates various tools to extract, assemble, and annotate organelle genomes for non-model organisms without available organelle genome sequences but with data in the NCBI SRA. To test the usability and feasibility of the pipeline, “mollusca” was selected as a keyword, and 76 new mitochondrial genomes were de novo assembled and annotated automatically without writing one single code. The applicability of the pipeline can be expanded to identify organelles in diverse invertebrate, vertebrate, and plant species by simply specifying the taxonomic name. OrgaMiner provides an easy-to-use, end-to-end solution for biologists mainly working with taxonomy and population genetics.
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ISSN:1424-2818
1424-2818
DOI:10.3390/d16020104