Abstract
Beet cyst nematodes depend on a set of secretory proteins (effectors) for the induction and maintenance of their syncytial feeding sites in plant roots. In order to understand the relationship between the beet cyst nematode H. schachtii and its host, identification of H. schachtii effectors is crucial and to this end, we sequenced a whole animal pre-infective J2-stage transcriptome in addition to pre- and post-infective J2 gland cell transcriptome using Next Generation Sequencing (NGS) and identified a subset of sequences representing putative effectors. Comparison between the transcriptome of H. schachtii and previously reported related cyst nematodes and root-knot nematodes revealed a subset of esophageal gland related sequences and putative effectors in common across the tested species. Structural and functional annotation of H. schachtii transcriptome led to the identification of nearly 200 putative effectors. Six putative effector expressions were quantified using qPCR and three of them were functionally analyzed using RNAi. Phenotyping of the RNAi nematodes indicated that all tested genes decrease the level of nematodes pathogenicity and/or the average female size, thereby regulating cyst nematode parasitism. These discoveries contribute to further understanding of the cyst nematode parasitism.
Highlights
Beet cyst nematode Heterodera schachtii causes severe economic losses on several crops[1,2]
Our prediction procedures based on the RNAseq using a whole worm as well as esophageal glands of H. schachtii provides an innovative way to identify key effectors involved in cyst nematode parasitism in pre-infective and early parasitic (5 dpi) stages
The trimmed reads were assembled without scaffolding, which resulted in a de novo transcriptome assembly of H. schachtii (HsT), which contained 66,885 contigs
Summary
Beet cyst nematode Heterodera schachtii causes severe economic losses on several crops[1,2]. Expressed sequence tags (ESTs) of parasitic stage of multiple plant parasitic nematodes (PPNs) are available and serve as a useful source for effectors mining[9]. RNAseq libraries were sequenced using Illumina Paired-End sequencing technique, enhancing sequencing depth assembly and, at the same time, reaching a high sensitivity to detect transcripts that are expressed at a very low level. In this way, we predicted 178 putative effectors in H. schachtii. Our prediction procedures based on the RNAseq using a whole worm as well as esophageal glands of H. schachtii provides an innovative way to identify key effectors involved in cyst nematode parasitism in pre-infective and early parasitic (5 dpi) stages. Knocking down three of the 6 putative effectors using RNAi has dramatically inhibited H. schachtii parasitism
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
