New software to detect horizontal gene transfer in microbiomes: from forage to the rumen

假设水平基因转移(HGT)是在非垂直遗传关系的有机体之间，即在父母和后代之间共享遗传物质。HGT被广泛认为是一种进化适应机制。虽然它在细菌和古菌中的研究已经有一段时间了，但它对于理解真核进化也越来越重要。最近对HGT的综述强调了开发更好的计算方法来检测HGT的必要性，特别是在真核生物中。检测HGT事件的方法可以分为两种。第一个涉及使用序列比对来构建系统发生树，以检测物种的进化史和单个基因序列的进化史之间的差异。第二种方法涉及分析基因组序列的内在属性，即有序和无序的模式、重复、密码子使用偏向和k-mer含量(k-mers是小的寡核苷酸)。这些方法统称为无比对序列分析：Swain博士最近发表了一种新的机器学习方法，该方法演示了如何通过使用训练数据集进行校准来改进无比对方法。我们假设，与现有方法相比，我们新的校准非对齐方法的过程将带来显著的性能提升。校准过程指示要使用的最佳参数集，并提供检测到真阳性的可能性的概率分数。根据要检测的序列特征，可以以不同的方式执行校准。这些概率然后可以合并，例如使用贝叶斯统计，并与系统发育分析相结合。这种方法优于现有的方法，因为它们估计了适当的参数，并且不能分配概率分数。我们改进的HGT检测方法将对假设HGT发挥重要作用的系统产生新的见解。通常，HGT发生在生活在生物混杂中的物种之间，如寄生虫、病原体(包括病毒)、共生体及其宿主。目的1.开发新的检测水平基因转移的软件，该软件可以应用于现有的不同基因组序列的集合。通过与其他当前方法的比较，展示性能提升。2.假设HGT产生进化适应，允许内生植物(原核生物)与它们的寄主植物进入共生关系，例如获得某些代谢功能。我们将把我们的软件应用于一个独特的Aberystwyth收集的大约100个来自牧草的内生菌基因组，以检测这些表型中的HGT事件。内生菌基因组将与它们的自由生活或致病近亲以及在瘤胃内发现的基因组进行比较，以更好地了解HGT在发展它们目前的遗传结构中的作用。3.15年多前的研究表明，通过来自细菌的HGT，瘤胃中的纤毛虫(真核生物)获得了46个与碳水化合物降解有关的基因。最近的数据将使我们能够使用我们的软件对这一重要发现进行更深入的分析。此外，我们计划将我们的方法扩展到探索纤毛虫中的水平转座元件转移(HTT)。纤毛虫是研究真核生物种系与体细胞系相互作用的模式系统，特别是在入侵和防御转座因子方面。纤毛虫HGT和HTT是帮助生物适应和产生新表型的关键过程，因此提高我们对它在农业生态系统中的作用的理解是很重要的。更好地了解HGT将有助于监测整个农业系统中抗菌素耐药性的传播。此外，对HGT的更好理解将为Me的发展提供洞察力

HypothesisHorizontal gene transfer (HGT) is the sharing of genetic material between organisms that are not in a vertical relationship of inheritance i.e. between parents and offspring. HGT is widely recognized as a mechanism for evolutionary adaptation. While it is has been studied in bacteria and archaea for some time, it is also being seen of increasing importance for understanding eukaryotic evolution. Recent reviews of HGT emphasise the need to develop better computational methods to detect HGT, especially in eukaryotes. Approaches to detecting HGT events can be divided into two. The first involves the construction of phylogenetic trees using sequence alignment, to detect differences between the evolutionary history of a species and the evolutionary history of individual gene sequences. The second approach involves the analysis of properties intrinsic to genome sequences i.e. the patterns of order and disorder, repeats, codon usage biases, and k-mer content (k-mers are small oligonucleotides). These approaches are collectively known as alignment-free sequence analysis: Dr Swain has recently published a novel machine learning methodology that demonstrates how alignment-free methods can be improved through calibration using training data sets. We hypothesise that our novel process of calibrating alignment-free methods will give significant performance gains over existing approaches. The process of calibration indicates the optimal parameter set to use, and provides a probability score for the likelihood of detecting a true positive. Calibration can be performed in different ways, according to the sequence feature to be detected. These probabilities can then be amalgamated e.g. using Bayesian statistics, and combined with phylogeny analysis. This approach is superior to existing approaches because they estimate appropriate parameters, and cannot allocate probability scores. Our improved approach to HGT detection will generate novel insights into systems where HGT is hypothesised to play an important role. Typically HGTs occur between species that live in biological promiscuity, such as parasites, pathogens (including viruses), symbionts, and their hosts. Objectives1.To develop novel software for detecting horizontal gene transfer that can be applied to existing collections of diverse genome sequences. Demonstrate performance gains through comparison to other current approaches. 2.HGT is hypothesised to generate evolutionary adaptions that allow endophytes (prokaryotes) to enter a symbiotic relationship with their host plants, such as the acquisition of certain metabolic functions. We will apply our software to a unique Aberystwyth collection of approximately 100 endophyte genomes derived from grasses, to detect HGT events in these phenotypes. Endophyte genomes will be compared to their free-living or pathogenic relatives, and those found within the rumen, to better understand the role of HGT in developing their current genetic structure.3.Over fifteen years ago it was shown that ciliates (eukaryotes) in the rumen have acquired, through HGT from bacteria, 46 genes related to carbohydrate degradation. More recent data will enable a much deeper analysis of this important finding, using our software. In addition, we plan to expand our approach to explore horizontal transposable element transfer (HTT) in the ciliates. Ciliates are a model system for the study of the interaction between eukaryotic germlines and somatic lines, especially with regard to the invasion and defence against transposable elements.JustificationHGT and HTT are key processes that help organisms to adapt and generate new phenotypes, it is therefore important to improve our understanding of the roles it plays in ecological systems relating to agriculture. Better understanding of HGT will help monitor the spread of antimicrobial resistance throughout the agricultural system. Moreover, an improved understanding of HGT will provide insights into the development me