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2022
DOI: 10.3389/fmicb.2022.866523
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Metatranscriptomic Assessment of the Microbial Community Associated With the Flavescence dorée Phytoplasma Insect Vector Scaphoideus titanus

Abstract: Phytoplasmas are insect-borne pathogenic bacteria that cause major economic losses to several crops worldwide. The dynamic microbial community associated with insect vectors influences several aspects of their biology, including their vector competence for pathogens. Unraveling the diversity of the microbiome of phytoplasma insect vectors is gaining increasing importance in the quest to develop novel microbe-based pest control strategies that can minimize the use of insecticides for better environmental qualit… Show more

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Cited by 4 publications
(2 citation statements)
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References 75 publications
(95 reference statements)
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“…Quantitative RT‐PCR (qRT‐PCR) was used to quantify the possible effect of the cultivar on the expression of female vitellogenin mRNA (Table 1), in order to correlate the vitellogenin expression level with egg count. The vitellogenin sequences were retrieved from S. titanus transcriptome (Abbà et al, 2022). For each sample, cDNA was synthesized from total RNA (250 ng) with random hexamers using a High‐Capacity cDNA Reverse Transcription Kit (Applied Biosystems).…”
Section: Methodsmentioning
confidence: 99%
“…Quantitative RT‐PCR (qRT‐PCR) was used to quantify the possible effect of the cultivar on the expression of female vitellogenin mRNA (Table 1), in order to correlate the vitellogenin expression level with egg count. The vitellogenin sequences were retrieved from S. titanus transcriptome (Abbà et al, 2022). For each sample, cDNA was synthesized from total RNA (250 ng) with random hexamers using a High‐Capacity cDNA Reverse Transcription Kit (Applied Biosystems).…”
Section: Methodsmentioning
confidence: 99%
“…Some developments in data collection result in increasingly larger datasets, which can be obtained through various techniques, such as metagenomics, metatranscriptomics, and metabolomics, providing observations of patterns with robustness to enrich the analyzes and exploration of microbes and their natural products from underexplored resources. 375–380 The integration of omics data, including genomics, transcriptomics, proteomics, and metabolomics, can provide a comprehensive understanding of the interactions among insect hosts, their microbiomes, and the metabolites produced. 381–383 Furthermore, the constant evolution of computational frameworks and bioinformatic tools can help to handle the vast amounts of data generated in terms of data storage, processing, integration and analysis.…”
Section: Conclusion and Future Prospectsmentioning
confidence: 99%