BMC BiologyGenomicsPeer-reviewed journal article
Developmental dynamic transcriptomics reveals multiple effectors and transcription factors critical for Ditylenchus destructor parasitism
Yangyang CheniD, Shurong ZhangiD, Yayi ZhouiD, Xueyu Wang, Dexin BoiD, Yucheng Liao, Boyan Hu, Yali ZhangiD, Noha Mohamed Ashry, Donghai PengiD, Ming SuniD, Dadong DaiiD
Abstract
Plant-parasitic nematodes (PPNs) pose a major threat to global agricultural production, yet fundamental research on their biology remains limited. The origin and evolutionary trajectory of PPNs remain elusive, largely due to the scarcity of chromosome-level genomic data. Among them, migratory PPNs are considered a key transitional form between free-living and obligate parasitic lifestyles, as they exhibit both plant parasitism and fungal feeding behaviors. In this study, we assembled a chromosome-level genome of the sweet potato rot nematode Ditylenchus destructor and confirmed the presence of four chromosomes through Hi-C scaffolding and karyotype analysis. Comparative genomic analysis with two other migratory PPNs, Bursaphelenchus xylophilus and Aphelenchoides besseyi, revealed that the Nigon elements in B. xylophilus are largely conserved with those of the model organism Caenorhabditis elegans, while D. destructor and A. besseyi exhibit extensive Nigon element rearrangements. These rearrangements were strongly correlated with patterns of protein sequence collinearity. Moreover, transcriptomic profiling across five developmental stages of D. destructor identified numerous stage-specific effectors and transcription factors. Functional analysis via RNA interference demonstrated that many of these genes play essential roles in embryogenesis and parasitic activity. Together, our results provide valuable genomic and transcriptomic resources for studying PPNs, uncovering critical insights into their genome evolution and parasitism-related gene functions, and laying a crucial foundation for advancing the understanding of PPN biology and their impact on agricultural systems.
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- approach: experimental assay
- Citations
- 1
- FWCI
- 0.54
- Field percentile
- top 29%
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