Improving Prediction of Helminth Aminoacyl‐tRNA Synthetases through Manual Analysis of Genomic Data

Helminth is a generic term for the parasitic worms that negatively impact health outcomes for a roughly a quarter of the global population. Although more than 150 helminth genomes have now been sequenced, protein sequence predictions available in compiled genomes and public databases are often incor...

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Bibliographic Details
Published in:The FASEB journal Vol. 35; no. S1
Main Authors: Block, Alison, Gjertson, Max, Robinson, Jevon, Warner, Seth, Wilson, David, Chihade, Joseph
Format: Journal Article
Language:English
Published: The Federation of American Societies for Experimental Biology 01-05-2021
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Summary:Helminth is a generic term for the parasitic worms that negatively impact health outcomes for a roughly a quarter of the global population. Although more than 150 helminth genomes have now been sequenced, protein sequence predictions available in compiled genomes and public databases are often incorrect. These errors hinder identification of novel drug targets in helminth genomes. We have focused on identifying and correcting predictions for aminoacyl‐tRNA synthetase genes. These enzymes are targets of effective antiparasitic therapies in in other organisms. Using published genomic information available in WormBase from a set of twelve human‐infecting helminths, we initially corrected exon boundary predictions using RNAseq data. The proposed protein sequences were then validated using multiple‐sequence alignments of enzymes from helminths and other organisms, allowing us to identify helminth‐specific features. We confirmed a high error rate in predictions of the studied genes, with 60% requiring at least one correction and an average of 4.3 corrections made per gene. Our analysis also identified several unique features of helminth aminoacyl‐tRNA synthetases, particularly among trematode (fluke) and platyhelminth (flatworm) proteins and in mitochondrially‐targeted enzymes.
Bibliography:Support from Carleton College, the Towsley Foundation, and the NSF funded Northstar STEM Alliance.
ISSN:0892-6638
1530-6860
DOI:10.1096/fasebj.2021.35.S1.04436