Evidence map›Paper›PMID 40634442›Full record

ArticleScientific reports2025

Two-way transcriptome approach for the identification of common gene targets across four insect orders and its validation in Oxycarenus laetus.

Julie Rebecca Joseph Mathari, Habeeb Shaik Mohideen

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Julie Rebecca Joseph MathariBioinformatics and Integrative Omics Laboratory, Department of Genetic Engineering, School of Bioengineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, 603203, India.
Habeeb Shaik MohideenBioinformatics and Integrative Omics Laboratory, Department of Genetic Engineering, School of Bioengineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, 603203, India. habeeb_skm@yahoo.co.in.ORCID http://orcid.org/0000-0003-4217-5063

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cotton production is negatively impacted by many insect pests from multiple orders, resulting in significant agronomic and economic losses. This study utilized a comparative transcriptomic methodology to discover conserved gene targets with potential applications in pest management across four insect orders that infest cotton: Hemiptera, Lepidoptera, Orthoptera, and Thysanoptera. A total of 104 publicly available RNA-Seq datasets, representing 17 pest species were de novo assembled in two ways, first was classified by read length (PE100 and PE150) and secondly as species-specific transcriptomes, and their qualities were assessed (alignment ≥ 90%, BUSCO ≥ 80%). Functional annotation utilizing insect-specific databases and orthology-based filtering identified three highly conserved genes, namely Arginine kinase (ArgK), Ryanodine receptor (RyR), and Serine/Threonine Protein phosphatase (STPP). These genes are involved in critical physiological functions, including ATP regeneration, calcium ion homeostasis, and phosphorylation-dependent signaling, and were enriched in pathways associated with insect development and stress response, including as JAK/STAT signaling and chitin metabolism. The study aimed to find broad-spectrum targets across several taxa; however, Oxycarenus laetus, a prominent sap-sucking pest of cotton, was chosen for downstream validation because of its increasing importance and ease of access for experimental research. The expression of ArgK, RyR, and STPP in O. laetus was validated by qPCR, affirming the biological significance of these targets and their functional conservation. This integrated methodology, which includes cross-order comparative transcriptome analysis and species-specific validation, illustrates a scalable approach for discovering essential molecular targets with translational potential in pest control. The results establish a basis for the development of RNAi-based or chemical strategies designed for cotton pest control.

Indexed as

Gene Expression ProfilingInsectaTranscriptomeAnimalsArginine KinaseGossypiumInsect ProteinsRyanodine Receptor Calcium Release ChannelArginine KinaseInsect ProteinsRyanodine Receptor Calcium Release ChannelBioinformaticsBroad-spectrum pesticide targetCottonInsectSDG12Transcriptomics

Identifiers

PMID40634442
PMCPMC12241319

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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.