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dsRNAEngineer: a web-based tool of comprehensive dsRNA design for pest control
We provide a one-stop online platform, namely, dsRNAEngineer, to help users optimize dsRNA for RNAi-based pest control.dsRNAEngineer incorporates a range of pest and non-pest species to enable large-scale transcriptome-level analysis for dsRNA design.dsRNAEngineer contains four functionalities, namely, screen-target, on-target, off-target, and multiple-target functions, to design rational dsRNAs that sufficiently target pests but are safe for non-target organisms.
Over the past two decades, many double-stranded (ds)-RNAs have been synthesized to silence target genes for exploration of gene functions in pests. Some of these dsRNAs are lethal to pests, leading to a new category of pesticides. The generation of these environmentally friendly pesticides requires precise in silico design of dsRNA molecules that target pests but not non-pest organisms. Current efforts in dsRNA design focus mainly on the analysis of the target gene sequence, lacking comprehensive analysis of all transcripts of the whole transcriptome per given species, causing low efficiency and imprecise dsRNA target exploration. To address these limitations, we created the dsRNAEngineer online platform (https://dsrna-engineer.cn), which allows comprehensive and rational dsRNA design, incorporating hundreds of pest and non-pest transcriptomes. Developed functionalities include screen-target (screen conserved genes for cotargets of various pest species), on-target, off-target, and multi-target to generate optimal dsRNA for precise pest control.
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dsRNAEngineer incorporates hundreds of pest and non-pest transcriptomes to provide comprehensive dsRNA design for pest control. With the application of several RNA-based pesticides in the field, dsRNAEngineer illustrates a framework for designing pest-specific and biosafe dsRNA, which will greatly promote the development of RNAi biotechnology as a pest control strategy.
Over the past two decades, RNAi biotechnology has been intensively investigated for pest control, and several products have been registered and applied in the field. However, current methods of double-stranded (ds)RNA design lack a comprehensive analysis of all transcripts at the transcriptome level for both pest and non-pest species. To solve these problems, our timely developed tool, dsRNAEngineer (https://dsrna-engineer.cn), which has four functionalities (screen-target, on-target, off-target, and multi-target functions) was developed to help users design rational dsRNAs that sufficiently target pests but are otherwise safe for non-target organisms, based on large-scale transcriptome-level analysis of both pest and non-pest species. With the emergence of RNA pesticides, we believe that dsRNAEngineer can be considered as a gold standard in dsRNA design to promote pest control based on RNAi biotechnology.
Journal Article
Enhancing yield and economic benefits through sustainable pest management in Okra cultivation
Okra (
Abelmoschus esculentus
) is a prominent vegetable crop in Asia, confronting persistent threats from pests such as leafhoppers, whiteflies, and shoot and fruit borers. Conventional chemical control methods, despite their adverse ecological effects, remain the primary approach for pest management. Indiscriminate chemical use has led to reduced biodiversity among natural predators and the disruption of food webs in ecosystems. To address these challenges, this study assessed the efficacy of integrated (IM) and biointensive (BM) pest management modules in comparison to conventional chemical methods (CM) for mitigating insect damage to okra leaves and fruits, and subsequently, their impact on okra yield. Our result revealed that the BM exhibited the least effectiveness but outperformed untreated control plots significantly. In contrast, both IM and CM significantly reduced damage from sap-sucking insects and borer pests. Notably, plots treated with the chemical module found decreased populations of natural enemies. The IM demonstrated the lowest fruit infestation rate (5.06%), yielding the highest crop production (8.97 t ha
−1
), along with the maximum net return (Indian Rupees: 44,245) and incremental cost–benefit ratio (3.31). Thus, the study suggested that the implementation of integrated pest management practices can result in higher okra yields and greater economic benefits. These findings shed light on the potential of sustainable agricultural practices as a safer and more economically viable alternative to chemical-intensive pest control in okra cultivation.
Journal Article
Landscape features support natural pest control and farm income when pesticide application is reduced
Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.
The European Green Deal aims to promote biodiversity and reduce pesticide use. Here, the authors combine farm and landscape data from Europe showing that landscape features supporting natural pest control have a positive impact in productivity and farmer revenues when pesticide use is reduced.
Publication
Crop pests and predators exhibit inconsistent responses to surrounding landscape composition
The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.
Journal Article