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

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