Evidence map›Paper›PMID 29115956›Full record

ArticleBMC biotechnology2017

De novo characterization of venom apparatus transcriptome of Pardosa pseudoannulata and analysis of its gene expression in response to Bt protein.

Rong Li, Zhenzhen Yan, Juan Wang, Qisheng Song, Zhi Wang

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Article in BMC biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

  1. The complete mitogenome of the pond wolf spiderMitochondrial DNA. Part B, Resources · 2024
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5 · Who and what money

Authors and funding

5 authors.

Rong LiCollege of Bioscience & Biotechnology, Hunan Agriculture University, Changsha, 410128, China.
Zhenzhen YanCollege of Bioscience & Biotechnology, Hunan Agriculture University, Changsha, 410128, China.
Juan WangCollege of Bioscience & Biotechnology, Hunan Agriculture University, Changsha, 410128, China.
Qisheng SongDivision of Plant Sciences, University of Missouri, Columbia, MO, 65211, USA.
Zhi WangCollege of Bioscience & Biotechnology, Hunan Agriculture University, Changsha, 410128, China. wangzhispider@aliyun.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPardosa pseudoannulata is a prevailing spider species, and has been regarded as an important bio-control agent of insect pests in farmland of China. However, the available genomic and transcriptomic databases of P. pseudoannulata and their venom are limited, which severely hampers functional genomic analysis of P. pseudoannulata. Recently high-throughput sequencing technology has been proved to be an efficient tool for profiling the transcriptome of relevant non-target organisms exposed to Bacillus thuringiensis (Bt) protein through food webs.

resultsIn this study, the transcriptome of the venom apparatus was analyzed. A total of 113,358 non-redundant unigenes were yielded, among which 34,041 unigenes with complete or various length encoding regions were assigned biological function annotations and annotated with gene ontology and karyotic orthologous group terms. In addition, 3726 unigenes involved in response to stimulus and 720 unigenes associated with immune-response pathways were identified. Furthermore, we investigated transcriptomic changes in the venom apparatus using tag-based DGE technique. A total of 1724 differentially expressed genes (DEGs) were detected, while 75 and 372 DEGs were functionally annotated with KEGG pathways and GO terms, respectively. qPCR analyses were performed to verify the DEGs directly or indirectly related to immune and stress responses, including genes encoding heat shock protein, toll-like receptor, GST and NADH dehydrogenase.

conclusionThis is the first study conducted to specifically investigate the venom apparatus of P. pseudoannulata in response to Bt protein exposure through tritrophic chain. A substantial fraction of transcript sequences was generated by high-throughput sequencing of the venom apparatus of P. pseudoannulata. Then a comparative transcriptome analysis showing a large number of candidate genes involved in immune response were identified by the tag-based DGE technology. This transcriptome dataset will provide a comprehensive sequence resource for furture molecular genetic research of the venom apparatus of P. pseudoannulata.

Indexed as

AnimalsArachnidaBacillus thuringiensis ToxinsBacterial ProteinsEndotoxinsGene Expression RegulationGenes, InsectHemolysin ProteinsHigh-Throughput Nucleotide SequencingRNA, MessengerSequence Analysis, DNASpider VenomsTranscriptomeBacillus thuringiensis ToxinsBacterial ProteinsEndotoxinsHemolysin Proteinsinsecticidal crystal protein, Bacillus ThuringiensisRNA, MessengerSpider VenomsBt proteinImmune systemPardosa pseudoannulataThe venom apparatusTranscriptome

Identifiers

PMID29115956
PMCPMC5678584

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.