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Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

机译:适用于下一代测序的植物细胞DNA富集方法的优化和比较分析

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摘要

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic fragments. Organellar genomes also exist in admixtures within a given cell or tissue type (heteroplasmy), and an abundance of subtypes may change throughout development or when under stress (sub-stoichiometric shifting). Next-generation sequencing (NGS) technologies are required to obtain deeper understanding of organellar genome structure and function. Traditional sequencing studies use several methods to obtain organellar DNA: (1) If a large amount of starting tissue is used, it is homogenized and subjected to differential centrifugation and/or gradient purification. (2) If a smaller amount of tissue is used (i.e., if seeds, material, or space is limited), the same process is performed as in (1), followed by whole-genome amplification to obtain sufficient DNA. (3) Bioinformatics analysis can be used to sequence the total genomic DNA and to parse out organellar reads. All these methods have inherent challenges and tradeoffs. In (1), it may be difficult to obtain such a large amount of starting tissue; in (2), whole-genome amplification could introduce a sequencing bias; and in (3), homology between nuclear and organellar genomes could interfere with assembly and analysis. In plants with large nuclear genomes, it is advantageous to enrich for organellar DNA to reduce sequencing costs and sequence complexity for bioinformatics analyses. Here, we compare a traditional differential centrifugation method with a fourth method, an adapted CpG-methyl pulldown approach, to separate the total genomic DNA into nuclear and organellar fractions. Both methods yield sufficient DNA for NGS, DNA that is highly enriched for organellar sequences, albeit at different ratios in mitochondria and chloroplasts. We present the optimization of these methods for wheat leaf tissue and discuss major advantages and disadvantages of each approach in the context of sample input, protocol ease, and downstream application.
机译:植物细胞基因组包含大量的重复元件,这些元件可能会进行配对或重组以形成复杂的结构和/或亚基因组片段。有机体基因组也存在于给定细胞或组织类型(异质性)内的混合物中,并且在整个发育过程中或处于压力下(亚化学计量的变化),亚型的丰富性可能会发生变化。需要下一代测序(NGS)技术来更深入地了解细胞器基因组的结构和功能。传统的测序研究使用几种方法来获得细胞器DNA:(1)如果使用了大量的起始组织,则将其匀浆并进行差异离心和/或梯度纯化。 (2)如果使用较少量的组织(即,如果种子,材料或空间有限),则进行与(1)中相同的过程,然后进行全基因组扩增以获得足够的DNA。 (3)生物信息学分析可用于对总基因组DNA进行测序并解析细胞器读数。所有这些方法都有固有的挑战和折衷。在(1)中,可能难以获得如此大量的起始组织。在(2)中,全基因组扩增可能会导致测序偏倚。 (3)中,核基因组和细胞器基因组之间的同源性可能会干扰组装和分析。在具有大核基因组的植物中,丰富细胞器DNA以降低测序成本和生物信息学分析的序列复杂性是有利的。在这里,我们将传统的差异离心方法与第四种方法(一种经过改进的CpG-甲基下拉法)进行了比较,以将总基因组DNA分为核部分和细胞器部分。两种方法都能产生足够的DNA用于NGS,尽管线粒体和叶绿体的比例不同,但DNA高度富含细胞器序列。我们介绍了针对小麦叶片组织的这些方法的优化,并讨论了每种方法在样品输入,方案简便性和下游应用方面的主要优缺点。

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