DISSERTATION RESEARCH: Evaluating Methods to Study the Phylogenetic Distribution of Genome Sizes in Carabid Beetles, including Next-Generation Sequencing of Old Museum Specimens

该项目的目标是测量和研究地甲虫的基因组大小，地甲虫是一种多种多样且具有重要经济意义的昆虫，使用新技术和传统技术相结合。基因组大小是对单个细胞核内DNA数量的测量。关于基因组大小的一个令人困惑的问题是，为什么它在不同的生物体中差异如此之大。最大的动物基因组比最小的大3000多倍。了解这些差异的原因可以为了解形成生物体的进化过程和历史提供重要的见解，因为基因组大小的差异可能是由生物体获得或失去基因或基因组的其他部分引起的。在规划DNA测序项目时，基因组的大小也很重要，因为较大的基因组比较小的基因组需要更多的资源。理解导致基因组大小变化的模式的一个重要障碍是测量的数量太少。目前，仅对0.4%的动物物种进行了基因组大小估算。这个数字是如此之小，因为很难得到一个可靠的估计。传统的方法依赖于从生物体中特别制备的细胞。然而，对于稀有、濒危或灭绝的物种，活标本很难或不可能获得。幸运的是，有新的方法可以利用DNA测序来估计基因组的大小，而不需要活体组织。该项目将检验基于DNA序列的基因组大小估计的可靠性，既包括活甲虫，也包括博物馆收藏的古老保存标本。以前没有实验专门比较这些方法或测试它们在旧标本中的可靠性。该项目还将为更广泛地研究生命之树的基因组大小提供额外的数据点，并将进一步利用博物馆收藏来研究世界的多样性。下一代测序（NGS）为研究人员提供了一套估算基因组大小的新工具。本项目将通过流式细胞术和浅层Illumina测序，研究基于NGS覆盖的甲虫基因组大小测定方法的可行性。它还将通过对相同10个物种的旧博物馆标本重复浅层Illumina测序，确定通过覆盖分析估算的基因组大小是否可以可靠地用于博物馆收藏的保存材料。总共36个基因组文库将在Illumina的四个通道中准备和测序。将对所有结果序列进行基于覆盖率的分析，然后将结果基因组大小估计值与流式细胞术获得的估计值进行单向方差分析，以确定基于覆盖率的估计值是否适用于新鲜和博物馆标本。如果浅层基因组测序在估算基因组大小方面取得成功，它将允许研究来自世界自然历史博物馆的材料，而无需花费大量的实地调查来收集新材料。这可能会改变基因组大小的研究，因为它增加了物种的数量，可以按数量级进行分析。

The goal of this project is to measure and investigate genome sizes in ground beetles, a diverse and economically important group of insects, using a combination of new and traditional techniques. Genome size is a measurement of the amount of DNA found inside the nucleus of a single cell. A puzzling question about genome size is why it varies so much in different organisms. The largest animal genome is over 3,000 times bigger than the smallest. Understanding the cause of these differences can provide important insights into the evolutionary processes and history that shaped organisms, since differences in genome size may be caused by organisms gaining or loosing genes or other parts of the genome. Genome size is also important to consider when planning DNA sequencing projects, as larger genomes require more resources than small ones. An important barrier to understanding the patterns that cause genome size variation is how few measurements there are. Currently, genome size estimates exist for only 0.4% of animal species. This number is so small due to how difficult it is to get a reliable estimate. Traditional methods rely on specially prepared cells from living organisms. However, live specimens can be difficult or impossible to obtain for species that are rare, endangered, or extinct. Fortunately, there are new methods to estimate genome size using DNA sequencing that do not require living tissue. This project will examine the reliability of DNA sequence-based genome size estimates on both live beetles and old, preserved specimens from museum collections. No previous experiments have specifically compared these methods or tested their reliability in old specimens. This project will also contribute additional data points for the broader study of genome sizes across the tree of life, and will further the use of museum collections in the study of the world's diversity. Next generation sequencing (NGS) has given researchers a new set of tools for estimating genome size. This project will investigate the viability of NGS coverage-based methods for determining genome size in carabid beetles by performing flow cytometry and shallow Illumina sequencing on ten species of carabid beetle. It will also determine if genome size estimation by coverage analysis can be reliably employed on preserved material from museum collections by repeating shallow Illumina sequencing on old museum specimens of the same ten species. A total of 36 genomic libraries will be prepared and sequenced across four Illumina lanes. Coverage-based analyses will be performed on all resulting sequences, and the resulting genome size estimates will then be compared with those obtained by flow cytometry using a one-way ANOVA test to determine if coverage-based estimation is a viable alternative for both fresh and museum specimens. If shallow genome sequencing is successful in estimating genomes sizes, it will allow for the study of material from the world's natural history museums without the cost of extensive fieldwork to collect fresh material. This could potentially transform the study of genome size by increasing the number of species it is possible to analyze by orders of magnitude.