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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Analyze Neural Circuits Underlying Key Insect Behaviors Using Advanced Neurophysiological Techniques

Authors: Swati Singh; Dr. Shivendra Verma;

Analyze Neural Circuits Underlying Key Insect Behaviors Using Advanced Neurophysiological Techniques

Abstract

Every year, more than 50,000 people lose their lives to mosquito bites, which spread diseases like dengue, chikungunya, and yellow fever. It is necessary to construct domains of DNA-binding proteins that confer genomic sequence specificity in order to use TALENs, ZFNs, and homing endonucleases to accomplish mutagenesis in Ae. aegypti. In this article, we detail how to modify Aedes aegypti at specified sites using the Cas9-CRISPR machinery. This approach utilizes RNA-DNA base-pairing to give targeted specificity, resulting in flexible and efficient genome-editing tools. We examine the efficacy of injection mix compositions, show that CRISPR-Cas9 may produce diverse mutations via distinct repair processes, and disclose persistent germ-line alterations in many genomic locations. Using Aedes aegypti as a model, this study delves further into the usage of CRISPR-Cas9, which might open the door to genetic alteration in non-model species. In the tested setup, it failed to function as anticipated. No amount of hsp83, UAS, or tetO could prevent tTAV from upregulating the selected NIPP1 killer gene. A fatal positive-feedback loop was produced by tetO and tTAV2. When controlled by the tetO-tTAV system, the fusion proteins Gal4Groucho and Lexa Groucho, which had been used as corepressors in the past, proved to be lethal.

Keywords

Lexa Groucho, hsp83, UAS, or tetO, animals, tTAV2, RNA-DNA

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green