Immunoinformatics: towards an understanding of species-specific protein evolution using phylogenomics and network theory
Institution: | Dublin City University |
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Department: | School of Biotechnology |
Year: | 2015 |
Keywords: | Genetics; Bioinformatics; Immunology |
Record ID: | 1181127 |
Full text PDF: | http://doras.dcu.ie/20405/ |
In immunology, the mouse is unquestionably the predominant model organism. However, an increasing number of reports suggest that mouse models do not always mimic human innate immunology. To better understand this discordance at the molecular level, we are investigating two mechanisms of gene evolution: positive selection and gene remodeling by introgression/domain shuffling. We began by creating a bioinformatic pipeline for large-scale evolutionary analyses. We next investigated bowhead genomic data to test our pipeline and to determine if there is lineage specific positive selection in particular whale lineages. Positive selection is a molecular signature of adaptation, and therefore, potential protein functional divergence. Once we had the pipeline troubleshot using the low quality bowhead data we moved on to test our innate immune dataset for lineage specific selective pressures. When possible, we applied population genomics theory to identify potential false-positives and date putative positive selection events in human. The final phase of our analysis uses network (graph) theory to identify genes remodeled by domain shuffling/introgression and to identify species-specific introgressive events. Introgressive events potentially impart novel function and may also alter interactions within a protein network. By identifying genes displaying evidence of positive selection or introgression, we may begin to understand the molecular underpinnings of phenotypic discordance between human and mouse immune systems.