| Literature DB >> 29530648 |
Jonathan Vadnal1, Olivia G Granger1, Ramesh Ratnappan1, Ioannis Eleftherianos2, Damien M O'Halloran3, John M Hawdon4.
Abstract
Interest has recently grown in developing the entomopathogenic nematode Heterorhabditis bacteriophora as a model to genetically dissect the process of parasitic infection. Despite the availability of a full genome assembly, there is substantial variation in gene model accuracy. Here, a methodology is presented for leveraging RNA-seq evidence to generate improved annotations using ab initio gene prediction software. After alignment of reads and subsequent generation of a RNA-seq supported annotation, the new gene prediction models were verified on a selection of genes by comparison with sequenced 5' and 3' rapid amplification of cDNA ends products. By utilising a whole transcriptome for genome annotation, the current reference annotation was enriched, demonstrating the importance of coupling transcriptional data with genome assemblies.Entities:
Keywords: Gene annotation; Gene modelling; Heterorhabditis bacteriophora; Nematode; RNA-seq
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Year: 2018 PMID: 29530648 PMCID: PMC6004328 DOI: 10.1016/j.ijpara.2018.02.001
Source DB: PubMed Journal: Int J Parasitol ISSN: 0020-7519 Impact factor: 3.981