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The way signals from the brain can influence behavior and vice versa is fascinating to me, so I decided to do my senior thesis on the neural signals of mouthbrooding. As I was deciding on a project though, I became interested in bioinformatics and computational biology and wanted to tie each of these fields together. In Anna\u2019s computational systems biology class, we learned about protein-protein interaction networks (i.e. interactomes) and how powerful they can be for investigating a variety of biological questions such as predicting disease genes. We also learned about how you could weight interactomes with external data to alter properties of the network (depending on what you\u2019re doing). So in one sentence, my thesis (and current research) is: use a protein-protein interactome to figure out what\u2019s going on in the brains of mouthbrooding fish.\u00a0<\/p>\n\n\n\n
Neurotensin is involved with both feeding and parental care, and seeing it connected to other neuropeptides like prodynorphin (pdyn) tells me that I mapped everything correctly. I\u2019m going to keep refining my network in the coming weeks and try a different method of constructing it but I\u2019m excited to have a usable interactome finally. Future goals include looking into NetworkX algorithms to run to find clusters of differentially expressed genes.<\/p>\n\n\n\n <\/p>\n\n\n\n References: Hey folks, my name is Gabe Preising and I\u2019m a research assistant for Suzy Renn and Anna Ritz. I\u2019ve always been a bit all over the place with my research interests, and because of that I\u2019ve always been drawn to interdisciplinary research (either that or I\u2019m just indecisive). I graduated from Reed this past May … Continue reading “Nets Full of Fish Brains”<\/span><\/a><\/p>\n","protected":false},"author":1609,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4,3,16,1],"tags":[],"class_list":["post-580","post","type-post","status-publish","format-standard","hentry","category-biology","category-computer-science","category-summer-research-2020","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/posts\/580","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/users\/1609"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/comments?post=580"}],"version-history":[{"count":5,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/posts\/580\/revisions"}],"predecessor-version":[{"id":586,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/posts\/580\/revisions\/586"}],"wp:attachment":[{"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/media?parent=580"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/categories?post=580"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.reed.edu\/compbio\/wp-json\/wp\/v2\/tags?post=580"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Since there is currently no interactome for A. burtoni<\/em>, I made my own from an existing zebrafish interactome. To do this, I took advantage of two publicly available resources: orthologous relationships [1] and a zebrafish interactome [2]. Orthologous genes are related genes in different species that originated from a common ancestor. Using the program OrthoFinder [3], I generated orthologs between zebrafish and A. burtoni<\/em>. I then created new edges between all of the corresponding orthologs for the pair of nodes in each zebrafish edge. Finally, I weighted the network with gene expression data from the brain such that redder nodes have a higher expression level in brooding fish and bluer nodes have a lower expression level. The following subnetwork focuses on neurotensin, a differentially upregulated gene in brooding fish.<\/p>\n\n\n\n![\"\"](\"https:\/\/blogs.reed.edu\/compbio\/files\/2020\/07\/A.-burtoni-Test-Graph-V2-nts.png\")
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[1] Smedley, D., Haider, S., Ballester, B., Holland, R., London, D., Thorisson, G., & Kasprzyk, A. (2009). BioMart\u2013biological queries made easy. BMC genomics, 10(1), 22.
[2] Ogris, C., Guala, D., Kaduk, M., & Sonnhammer, E. L. (2018). FunCoup 4: new species, data, and visualization. Nucleic acids research, 46(D1), D601-D607.
[3] Emms, D. M., & Kelly, S. (2019). OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome biology, 20(1), 1-14.<\/p>\n","protected":false},"excerpt":{"rendered":"