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Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq.

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.

SUBMITTER: Vadnal J

PROVIDER: S-EPMC6004328 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq.

Vadnal Jonathan J Granger Olivia G OG Ratnappan Ramesh R Eleftherianos Ioannis I O'Halloran Damien M DM Hawdon John M JM

International journal for parasitology 20180309 8

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 annotat ...[more]

PMID: 29530648

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Project description:The entomopathogenic nematode Heterorhabditis bacteriophora and its symbiotic bacterium, Photorhabdus luminescens, are important biological control agents of insect pests. This nematode-bacterium-insect association represents an emerging tripartite model for research on mutualistic and parasitic symbioses. Elucidation of mechanisms underlying these biological processes may serve as a foundation for improving the biological control potential of the nematode-bacterium complex. This large-scale expressed sequence tag (EST) analysis effort enables gene discovery and development of microsatellite markers. These ESTs will also aid in the annotation of the upcoming complete genome sequence of H. bacteriophora.A total of 31,485 high quality ESTs were generated from cDNA libraries of the adult H. bacteriophora TTO1 strain. Cluster analysis revealed the presence of 3,051 contigs and 7,835 singletons, representing 10,886 distinct EST sequences. About 72% of the distinct EST sequences had significant matches (E value < 1e-5) to proteins in GenBank's non-redundant (nr) and Wormpep190 databases. We have identified 12 ESTs corresponding to 8 genes potentially involved in RNA interference, 22 ESTs corresponding to 14 genes potentially involved in dauer-related processes, and 51 ESTs corresponding to 27 genes potentially involved in defense and stress responses. Comparison to ESTs and proteins of free-living nematodes led to the identification of 554 parasitic nematode-specific ESTs in H. bacteriophora, among which are those encoding F-box-like/WD-repeat protein theromacin, Bax inhibitor-1-like protein, and PAZ domain containing protein. Gene Ontology terms were assigned to 6,685 of the 10,886 ESTs. A total of 168 microsatellite loci were identified with primers designable for 141 loci.A total of 10,886 distinct EST sequences were identified from adult H. bacteriophora cDNA libraries. BLAST searches revealed ESTs potentially involved in parasitism, RNA interference, defense responses, stress responses, and dauer-related processes. The putative microsatellite markers identified in H. bacteriophora ESTs will enable genetic mapping and population genetic studies. These genomic resources provide the material base necessary for genome annotation, microarray development, and in-depth gene functional analysis.

Dataset Information

Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq.

Publications

Refined ab initio gene predictions of Heterorhabditis bacteriophora using RNA-seq.

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