Chromosome-scale Genome assembly of the critically endangered White-eared Night-Heron (Gorsachius magnificus).

The White-eared Night-Heron (Gorsachius magnificus, G. magnificus) is a critically endangered heron that is very poorly known and only found in southern China and northern Vietnam, with an estimated population of 250 to 999 mature individuals. However, the lack of a reference genome has hindered the implementation of conservation management efforts. In this study, we present the first high-quality chromosome-scale reference genome, which was assembled by integrating PacBio long-reads sequencing, Illumina paired-end sequencing, and Hi-C technology. The genome has a total length of 1.176 Gb, with a scaffold N50 of 84.77 Mb and a contig N50 of 18.46 Mb. Utilizing Hi-C data, we anchored 99.89% of the scaffold sequences onto 29 pairs of chromosomes. Additionally, we identified 18,062 protein-coding genes in the genome, with 95.00% of which were functionally annotated. Notably, BUSCO assessment confirmed the presence of 97.2% of highly conserved Aves genes within the genome. This chromosome-level genome assembly and annotation will be valuable for future investigating the G. magnificus's evolutionary adaptation and conservation.

Multi-Classifier Fusion Based on MI-SFFS for Cross-Subject Emotion Recognition.

With the widespread use of emotion recognition, cross-subject emotion recognition based on EEG signals has become a hot topic in affective computing. Electroencephalography (EEG) can be used to detect the brain's electrical activity associated with different emotions. The aim of this research is to improve the accuracy by enhancing the generalization of features. A Multi-Classifier Fusion method based on mutual information with sequential forward floating selection (MI_SFFS) is proposed. The dataset used in this paper is DEAP, which is a multi-modal open dataset containing 32 EEG channels and multiple other physiological signals. First, high-dimensional features are extracted from 15 EEG channels of DEAP after using a 10 s time window for data slicing. Second, MI and SFFS are integrated as a novel feature-selection method. Then, support vector machine (SVM), k-nearest neighbor (KNN) and random forest (RF) are employed to classify positive and negative emotions to obtain the output probabilities of classifiers as weighted features for further classification. To evaluate the model performance, leave-one-out cross-validation is adopted. Finally, cross-subject classification accuracies of 0.7089, 0.7106 and 0.7361 are achieved by the SVM, KNN and RF classifiers, respectively. The results demonstrate the feasibility of the model by splicing different classifiers' output probabilities as a portion of the weighted features.

Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest.

Understanding the genetic basis of climatic adaptation is essential for predicting species' responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.

Characterization and expression of the cytochrome P450 gene family in diamondback moth, Plutella xylostella (L.).

Cytochrome P450 monooxygenases are present in almost all organisms and can play vital roles in hormone regulation, metabolism of xenobiotics and in biosynthesis or inactivation of endogenous compounds. In the present study, a genome-wide approach was used to identify and analyze the P450 gene family of diamondback moth, Plutella xylostella, a destructive worldwide pest of cruciferous crops. We identified 85 putative cytochrome P450 genes from the P. xylostella genome, including 84 functional genes and 1 pseudogene. These genes were classified into 26 families and 52 subfamilies. A phylogenetic tree constructed with three additional insect species shows extensive gene expansions of P. xylostella P450 genes from clans 3 and 4. Gene expression of cytochrome P450s was quantified across multiple developmental stages (egg, larva, pupa and adult) and tissues (head and midgut) using P. xylostella strains susceptible or resistant to insecticides chlorpyrifos and fiprinol. Expression of the lepidopteran specific CYP367s predominantly occurred in head tissue suggesting a role in either olfaction or detoxification. CYP340s with abundant transposable elements and relatively high expression in the midgut probably contribute to the detoxification of insecticides or plant toxins in P. xylostella. This study will facilitate future functional studies of the P. xylostella P450s in detoxification.

A heterozygous moth genome provides insights into herbivory and detoxification.

How an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants, but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood. We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.

Developmental and insecticide-resistant insights from the de novo assembled transcriptome of the diamondback moth, Plutella xylostella.

We present here the de novo assembly and annotation of the transcriptome of Plutella xylostella (diamondback moth (DBM)), a widespread destructive pest of cruciferous plants, using short reads generated by Illumina sequencing from different developmental stages and insecticide-resistant strains. A total of 171,262 non-redundant sequences, denoted as unigenes, were obtained. They represented approximately 100-fold of all DBM mRNA and EST sequences in GenBank thus far. We identified 38,255 unigenes highly similar to the known functional protein-coding genes, most of which were annotated using gene ontology (GO) and orthologous groups of proteins (COG). Global profiling of differentially expressed unigenes revealed enriched GOs and biological pathways that were related to specific developmental stages and insecticide resistance. We also evaluated the resistance-related single nucleotide polymorphism (SNP) using this high-throughput genotyping method. The newly developed transcriptome will facilitate researches on the DBM developmental biology and insecticide resistance evolution, and ultimately provide better pest management systems.