破坏性入侵害虫白腹大蠊成虫的综合性别和组织特异性转录组。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Zhiwei Kang, Aoli Lin, Mengqi Ji, Shizhao Jing, Zichao Song, Zhenxaing Li, Limei Song, Jianghua Sun, Cheng Qu
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引用次数: 0

摘要

南美番茄蛲虫(Tuta absoluta (Meyrick))是一种新出现的入侵害虫,对全球番茄生产造成了毁灭性的损失。基于半化学的管理是一种很有前途的控制害虫的方法。然而,人们对绝对t如何识别这些符号化合物知之甚少。在这项研究中,我们生成了一个全面的性别和组织特异性的T. absoluta成虫转录组数据,这是最近发布的染色体水平基因组数据的完美续集。我们选择的几种组织对昆虫的化学感知很重要。因此,研究不同组织和性别间的差异表达基因,为研究赤杨的嗅觉功能奠定了良好的基础。这些转录组学数据不仅有助于对绝对t嗅觉感知的分子研究,而且为开发基于绝对t嗅觉过程的创新控制方法提供了重要信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Comprehensive sex- and tissue-specific transcriptome of the destructive invasive pest Tuta absoluta adults.

Comprehensive sex- and tissue-specific transcriptome of the destructive invasive pest Tuta absoluta adults.

Comprehensive sex- and tissue-specific transcriptome of the destructive invasive pest Tuta absoluta adults.

Comprehensive sex- and tissue-specific transcriptome of the destructive invasive pest Tuta absoluta adults.

The South American tomato pinworm, Tuta absoluta (Meyrick) is a newly emerged invasive pests causing devastating loss on tomato production globally. Semiochemical-based management is a promising method for controlling this pest. However, there is little known about how T. absoluta recognizes the semiochemical compounds. In this study, we generated a comprehensive sex- and tissue-specific transcriptome data of T. absoluta adults, which is a perfect sequel to the recently released chromosome-level genome data. Several tissues that we selected are important for semiochemicals perceptions in insects. Thus, the differentially expressed genes among the different tissues and sexes lays a good foundation for the olfaction researches in T. absoluta. Taken together, this transcriptomic data not only contribute to the molecular investigations about olfactory perception of T. absoluta, but also provided important information to developing innovative controlling methods based on the olfaction process of T. absoulta.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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