Intronomics-MIP: a snakemake pipeline for analyzing multilocus intron polymorphisms in species identification and population genomics

In this Research Note, we introduce Intronomics-MIP, a snakemake-based pipeline for the automated analysis of multi-locus intron polymorphisms (MIPs) using intron-targeted amplicon sequencing. Building on established methodologies, our pipeline integrates tools such as Cutadapt, FLASH, and SeekDeep to efficiently process and analyze highly variable intron regions. These MIPs serve as powerful multiple-allelic markers, primarily useful for distinguishing species, identifying cryptic species, disentangling species complexes and detecting hybridization, but can also be informative for assessing population structure without prior species knowledge. Our pipeline enhances reproducibility and scalability, making it adaptable to a wide range of taxa, with a specific demonstration on teleost species. We provide a comprehensive overview of the pipeline's design, along with performance assessments using representative datasets.

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Publication Details

Journal
BMC Research Notes
Published
2025-05-06
DOI
https://doi.org/10.1186/s13104-025-07264-6
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.00

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article

Intronomics-MIP: a snakemake pipeline for analyzing multilocus intron polymorphisms in species identification and population genomics

Nicola Vitulo, Leonardo de Lucca Schiavon, Elisa Boscari, Leonardo Congiu et al.
BMC Research Notes
Identification and Quantification in Food
article

Intronomics-MIP: a snakemake pipeline for analyzing multilocus intron polymorphisms in species identification and population genomics

Nicola Vitulo, Leonardo de Lucca Schiavon, Elisa Boscari, Leonardo Congiu, Annalisa Scapolatiello
article en

Abstract

In this Research Note, we introduce Intronomics-MIP, a snakemake-based pipeline for the automated analysis of multi-locus intron polymorphisms (MIPs) using intron-targeted amplicon sequencing. Building on established methodologies, our pipeline integrates tools such as Cutadapt, FLASH, and SeekDeep to efficiently process and analyze highly variable intron regions. These MIPs serve as powerful multiple-allelic markers, primarily useful for distinguishing species, identifying cryptic species, disentangling species complexes and detecting hybridization, but can also be informative for assessing population structure without prior species knowledge. Our pipeline enhances reproducibility and scalability, making it adaptable to a wide range of taxa, with a specific demonstration on teleost species. We provide a comprehensive overview of the pipeline's design, along with performance assessments using representative datasets.

BMC Research NotesVol. 18(1)
University of Verona (IT), University of Padua (IT), CoNISMa (IT)
Università degli Studi di Padova
Life in Land
Openalex Percentile: Top 91%
Identification and Quantification in Food
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