Biochemistry

Abstract

CS-6-6 - Signatures and predictions of specialized metabolism genes in Solanum lycopersicum

Sunday, July 15
4:58 PM - 5:00 PM

Plant specialized metabolites are highly diverse and important for interactions between plants and abiotic and biotic environmental factors. These compounds also have significant agronomical and pharmaceutical value. Despite their importance, genes responsible for their production remain largely unidentified. Because the ancestors of some specialized metabolism (SM) genes originally played role in general (or primary) metabolism (GM), it is challenging to distinguish the repertoire of metabolic genes as SM or GM genes. In addition, many SM pathways are incomplete due to the large number of highly variable specialized metabolites, and their restriction to specific taxa. Using cultivated tomato, Solanum lycopersicum, as a model, we use machine-learning methods to distinguish annotated tomato SM/GM genes globally as well as from different pathways. Our approach begins with identifying benchmark SM and GM genes for using Tomatocyc. Using these benchmark genes, we next assess what sequence, transcriptomic, or evolutionary features distinguish SM from GM genes, and SM/GM genes in the same pathways from genes in other pathways. These features include duplication pattern, sequence conservation and gene trees, expression pattern, domain type, and gene network properties that are integrated with machine-learning methods to generate two prediction models. The first model is capable of classifying enzymatic genes that do not have SM/GM annotation as SM or GM genes. The second model predicts the specific pathway(s) a SM or GM gene belongs to. Our study provides a comprehensive evaluation of features that can distinguish SM and GM pathway genes in tomato and an effective model for predicting SM genes that serve as the basis for further experimental studies.

Bethany M. Moore

Graduate Research Associate
Michigan State University

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CS-6-6 - Signatures and predictions of specialized metabolism genes in Solanum lycopersicum



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