The coffee leaf miner (CLM) Leucoptera coffeella moth is a major threat to coffee production. Insect damage is related to the feeding behavior of the larvae on the leaf. During the immature life stages, the insect feeds in the mesophyll triggering necrosis and causing loss of photosynthetic capacity, defoliation and significant yield loss to coffee crops. Chemical control is used to support the coffee production chain, though market requirements move toward conscious consumption claiming for more sustainable methods. In this overview, we discuss aspects about the CLM concerning biology, history, geographical distribution, economic impacts, and the most relevant control strategies in progress. Insights to develop an integrated approach for a safer and eco-friendly control of the CLM are discussed here, including bio-extracts, nanotechnology, pheromones, and tolerant cultivars.

Invasive insects cost the global economy around USD 70 billion per year. Moreover, increasing agricultural insect pests raise concerns about global food security constraining and infestation rising after climate changes. Current agricultural pest management largely relies on plant breeding—with or without transgenes—and chemical pesticides. Both approaches face serious technological obsolescence in the field due to plant resistance breakdown or development of insecticide resistance. The need for new modes of action (MoA) for managing crop health is growing each year, driven by market demands to reduce economic losses and by consumer demand for phytosanitary measures. The disabling of pest genes through sequence-specific expression silencing is a promising tool in the development of environmentally-friendly and safe biopesticides. The specificity conferred by long dsRNA-base solutions helps minimize effects on off-target genes in the insect pest genome and the target gene in non-target organisms (NTOs). In this review, we summarize the status of gene silencing by RNA interference (RNAi) for agricultural control. More specifically, we focus on the engineering, development and application of gene silencing to control Lepidoptera through non-transforming dsRNA technologies. Despite some delivery and stability drawbacks of topical applications, we reviewed works showing convincing proof-of-concept results that point to innovative solutions. Considerations about the regulation of the ongoing research on dsRNA-based pesticides to produce commercialized products for exogenous application are discussed. Academic and industry initiatives have revealed a worthy effort to control Lepidoptera pests with this new mode of action, which provides more sustainable and reliable technologies for field management. New data on the genomics of this taxon may contribute to a future customized target gene portfolio. As a case study, we illustrate how dsRNA and associated methodologies could be applied to control an important lepidopteran coffee pest.

Global crop yields are estimated to be reduced by 30–40% per year on account of plant pests and pathogens. Agricultural insect pests raise concerns about constraining global food security and climate changes contributing to the rise of infestation. The current management relies on plant breeding, associated or not with transgenes and chemical pesticides. Both approaches face serious technology obsolescence on the field due to resistance breakdown or development of insecticide resistance. The need for new Modes of Action (MoA) approaches in managing crop health grows each year, driven by market demands to reduce economic losses and phytosanitary requirements to meet the consumer perception. Disabling pest genes by sequence-specific expression silencing is considered a promising tool in the development of environment and health respectful biopesticides. The specificity conferred by long dsRNA-base solutions give support to minimizing effects on off-targeted genes in the insect pest genome and the target gene in non-target organisms (NTOs). In this review, we summarize the current status of gene silencing by RNA interference (RNAi) for agricultural control. More specifically, we focus on the engineering, development and application of gene silencing to control Lepidoptera by the employment of non-transforming dsRNA technologies. Despite some delivery and stability drawbacks of topical applications, we reviewed works showing convincing proof-of-concept results that point to imminent innovative solutions. Considerations about the regulamentation of the ongoing research on dsRNA-based pesticides to produce commercialized products for exogenous application are discussed. Academic and industry initiatives reveal a worthy effort to accomplish controlling Lepidoptera pests with this new mode of action to provide more sustainable and reliable technologies to field management. New data on genomics of this taxon encourage the increment of a customized target genes portfolio. As a case of study, we illustrate how dsRNA and associated methodologies could be applied to control an important Lepidopteran coffee pest.

Background, Leucoptera coffeella (Guerin-Meneville, 1842) is a moth species (Lyonetiidae, Lepidoptera) pest that causes severe losses to coffee crops. Further information about its genomic data is required to allow molecular strategies for the development of sustainable pesticides and to gain in-depth knowledge on phylogenetics. However, the closest complete genome available is within the superfamily level (Yponomeutoidea). Here we report the generation of the first long-read genome, transcriptome and proteome results of L. coffeella and the in silico analysis performed in these molecular levels to investigate genes involved in the siRNA processing. Results, PACBio and paired-end Illumina combined DNA sequencing from pupae samples resulted in more than 436 Gb subreads and 31Mb reads with N50 read length of 15,512 nt, mean read length 13.8 Kb and max read length 420.7 Kb. Additionally, 20Gb data of short DNA sequencing was combined to produce 1,984 contigs comprising 397 Mb in total. The longest and shortest scaffold sizes are 10,809,567 nt and 15,247 nt, respectively (mean size 200,178 nt). The N50 scaffold was 275,598 nt and the GC content was 36.10%. Predicted coding DNA sequences counted 39.930 gene models. Searching of 5286 BUSCO groups revealed 91.7 percent of completeness (single and duplicated genes combined) compared to lepidoptera genomes (lepidoptera_odb10). Flow cytometry showed the 1C DNA content is approximately 295 Mb. RNA-Seq from seven development stages resulted in 28294 identified transcripts. Additionally, proteomics from immature stages resulted in 2045 proteins matching the gene models. Conclusions, This first nuclear genome of the Lyonetiidae family brings valuable molecular resources to study Lepidoptera genomes. Genome, transcriptome and proteome sequencing to raise genome annotation precision may resolve uncovered taxonomic issues. In addition, these combined approaches provide insights into plant-insect interaction players, as horizontally transferred genes (HGT) and endosymbionts. Put together, the generated data enables the development of molecular tools towards sustainable biotechnology solutions for lepidopteran pest control.