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用于生物多样性基因组学的-mer方法。

-mer approaches for biodiversity genomics.

作者信息

Jenike Katharine M, Campos-Domínguez Lucía, Boddé Marilou, Cerca José, Hodson Christina N, Schatz Michael C, Jaron Kamil S

机构信息

Johns Hopkins University, School of Medicine, Baltimore, Maryland 21205, USA.

Centre for Research in Agricultural Genomics, CRAG (CSIC-IRTA-UAB-UB), Campus UAB, Cerdanyola del Vallès, 08193 Barcelona, Spain.

出版信息

Genome Res. 2025 Feb 14;35(2):219-230. doi: 10.1101/gr.279452.124.

Abstract

The wide array of currently available genomes displays a wonderful diversity in size, composition, and structure and is quickly expanding thanks to several global biodiversity genomics initiatives. However, sequencing of genomes, even with the latest technologies, can still be challenging for both technical (e.g., small physical size, contaminated samples, or access to appropriate sequencing platforms) and biological reasons (e.g., germline-restricted DNA, variable ploidy levels, sex chromosomes, or very large genomes). In recent years, -mer-based techniques have become popular to overcome some of these challenges. They are based on the simple process of dividing the analyzed sequences (e.g., raw reads or genomes) into a set of subsequences of length , called -mers, and then analyzing the frequency or sequences of those -mers. Analyses based on -mers allow for a rapid and intuitive assessment of complex sequencing data sets. Here, we provide a comprehensive review to the theoretical properties and practical applications of -mers in biodiversity genomics with a special focus on genome modeling.

摘要

目前可用的基因组种类繁多,在大小、组成和结构上呈现出惊人的多样性,并且由于多项全球生物多样性基因组计划,其数量正在迅速增加。然而,即使使用最新技术,基因组测序对于技术(例如,物理尺寸小、样本受污染或无法使用合适的测序平台)和生物学原因(例如,种系限制性DNA、可变倍性水平、性染色体或非常大的基因组)来说仍然具有挑战性。近年来,基于k - mer的技术已变得流行起来,以克服其中一些挑战。它们基于将分析的序列(例如,原始读数或基因组)划分为一组长度为k的子序列(称为k - mer)的简单过程,然后分析这些k - mer的频率或序列。基于k - mer的分析允许对复杂的测序数据集进行快速直观的评估。在这里,我们对k - mer在生物多样性基因组学中的理论特性和实际应用进行全面综述,特别关注基因组建模。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f3a/11874746/dde24c451ab6/219f01.jpg

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