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

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES
A Scapolatiello, E Boscari, L Schiavon, N Vitulo, L Congiu
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引用次数: 0

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.

Intronomics-MIP:一种在物种鉴定和种群基因组学中分析多位点内含子多态性的蛇形管道。
在本研究报告中,我们介绍了Intronomics-MIP,这是一种基于蛇形基因的流水线,用于使用内含子靶向扩增子测序自动分析多位点内含子多态性(MIPs)。在现有方法的基础上,我们的产品线集成了Cutadapt, FLASH和SeekDeep等工具,以有效地处理和分析高度可变的内含子区域。这些MIPs作为强大的多等位基因标记,主要用于区分物种,识别隐种,解开物种复合物和检测杂交,但也可以在没有先验物种知识的情况下评估种群结构。我们的管道提高了可重复性和可扩展性,使其适用于广泛的分类群,并对硬骨鱼物种进行了具体演示。我们提供了管道设计的全面概述,以及使用代表性数据集的性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Research Notes
BMC Research Notes Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.60
自引率
0.00%
发文量
363
审稿时长
15 weeks
期刊介绍: BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.
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