Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data

Description

The coffee leaf miner ( Leucoptera coffeella ) is one of the major pests of coffee crops in the neotropical regions, and causes major economic losses. Few molecular data are available to identify this pest and advances in the knowledge of the genome of L. coffeella will contribute to improving pest identification and also clarify taxonomy of this microlepidoptera. L. coffeella DNA was extracted and sequenced using PacBio HiFi technology. Here we report the complete L. coffeella circular mitochondrial genome (16,407 bp) assembled using Aladin software. We found a total of 37 genes, including 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA genes (rRNAs) and an A + T rich-region and a D-loop. The L. coffeella mitochondrial gene organization is highly conserved with similarities to lepidopteran mitochondrial gene rearrangements (trnM-trnI-trnQ). We concatenated the 13 PCG to construct a phylogenetic tree and inferred the relationship between L. coffeella and other lepidopteran species. L. coffeella is found in the Lyonetiidae clade together with L. malifoliella and Lyonetia clerkella , both leaf miners. Interestingly, this clade is assigned in the Yponomeutoidea superfamily together with Gracillariidae, and both superfamilies displayed species with leaf-mining feeding habits.

Abstract

International audience

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