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

假设水平基因转移（HGT）是指在非垂直遗传关系（即父母和后代之间）的生物体之间共享遗传物质。HGT被广泛认为是一种进化适应机制。虽然它已经在细菌和古细菌中研究了一段时间，但它对于理解真核生物的进化也越来越重要。最近关于HGT的综述强调需要开发更好的计算方法来检测HGT，特别是在真核生物中。探测HGT事件的方法可以分为两种。第一种方法是利用序列比对构建系统发育树，以检测物种进化史和个体基因序列进化史之间的差异。第二种方法涉及基因组序列固有特性的分析，即有序和无序模式、重复序列、密码子使用偏差和k-mer含量（k-mers是小的寡核苷酸）。这些方法统称为无对齐序列分析：Swain博士最近发表了一种新颖的机器学习方法，演示了如何通过使用训练数据集进行校准来改进无对齐方法。我们假设我们的校准无对齐方法的新过程将比现有方法获得显着的性能收益。校准过程表明要使用的最佳参数集，并为检测真阳性的可能性提供概率分数。根据要检测的序列特征，可以以不同的方式进行校准。然后，这些概率可以合并，例如使用贝叶斯统计，并结合系统发育分析。这种方法优于现有的方法，因为它们估计适当的参数，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发生在生物滥交的物种之间，如寄生虫、病原体（包括病毒）、共生体及其宿主。Objectives1。开发用于检测水平基因转移的新型软件，该软件可应用于现有的不同基因组序列集合。通过与其他当前方法的比较来展示性能提升。2.HGT被假设产生进化适应，允许内生菌（原核生物）与其宿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个来自草的内生菌基因组，以检测这些表型中的HGT事件。将内生菌基因组与它们的自由生活或致病亲属以及在瘤胃内发现的基因组进行比较，以更好地了解HGT在形成其当前遗传结构中的作用。早在15年前就有研究表明，瘤胃中的纤毛虫（真核生物）通过细菌的HGT获得了46个与碳水化合物降解相关的基因。使用我们的软件，更多的最新数据将能够对这一重要发现进行更深入的分析。此外，我们计划扩大我们的方法来探索水平转座因子转移（HTT）在纤毛虫。纤毛虫是研究真核生殖系与体细胞相互作用的一个模型系统，特别是在转座因子的入侵和防御方面。hgt和HTT是帮助生物体适应和产生新表型的关键过程，因此，提高我们对其在与农业有关的生态系统中所起作用的理解非常重要。更好地了解HGT将有助于监测抗菌素耐药性在整个农业系统中的传播。此外，提高对HGT的理解将为我的发展提供见解

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