Target capture and genome skimming for plant diversity studies

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-08-10 DOI:10.1002/aps3.11537
Flávia Fonseca Pezzini, Giada Ferrari, Laura L. Forrest, Michelle L. Hart, Kanae Nishii, Catherine A. Kidner
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引用次数: 2

Abstract

Recent technological advances in long-read high-throughput sequencing and assembly methods have facilitated the generation of annotated chromosome-scale whole-genome sequence data for evolutionary studies; however, generating such data can still be difficult for many plant species. For example, obtaining high-molecular-weight DNA is typically impossible for samples in historical herbarium collections, which often have degraded DNA. The need to fast-freeze newly collected living samples to conserve high-quality DNA can be complicated when plants are only found in remote areas. Therefore, short-read reduced-genome representations, such as target capture and genome skimming, remain important for evolutionary studies. Here, we review the pros and cons of each technique for non-model plant taxa. We provide guidance related to logistics, budget, the genomic resources previously available for the target clade, and the nature of the study. Furthermore, we assess the available bioinformatic analyses, detailing best practices and pitfalls, and suggest pathways to combine newly generated data with legacy data. Finally, we explore the possible downstream analyses allowed by the type of data generated using each technique. We provide a practical guide to help researchers make the best-informed choice regarding reduced genome representation for evolutionary studies of non-model plants in cases where whole-genome sequencing remains impractical.

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植物多样性研究的靶捕获和基因组撷取
长读高通量测序和组装方法的最新技术进步促进了注释染色体尺度全基因组序列数据的生成,用于进化研究;然而,对许多植物物种来说,生成这样的数据仍然很困难。例如,对于历史植物标本馆收藏的样本来说,获得高分子量的DNA通常是不可能的,因为它们通常具有降解的DNA。当植物只在偏远地区发现时,需要快速冷冻新收集的活样本以保存高质量的DNA可能会很复杂。因此,短读的减少基因组表示,如靶捕获和基因组略读,对进化研究仍然很重要。本文综述了各种技术在非模式植物分类群中的优缺点。我们提供与后勤、预算、先前可用于目标进化的基因组资源和研究性质相关的指导。此外,我们评估了可用的生物信息学分析,详细说明了最佳实践和缺陷,并提出了将新生成的数据与遗留数据相结合的途径。最后,我们探讨了使用每种技术生成的数据类型所允许的可能的下游分析。我们提供了一个实用的指南,以帮助研究人员在全基因组测序仍然不切实际的情况下,在非模式植物的进化研究中做出关于减少基因组表示的最佳明智选择。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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