Abstract
Traditional detection of aquatic invasive species, via morphological identification is often time-consuming and can require a high level of taxonomic expertise, leading to delayed mitigation responses. Environmental DNA (eDNA) detection approaches of multiple species using Illumina-based sequencing technology have been used to overcome these hindrances, but sample processing is often lengthy. More recently, portable nanopore sequencing technology has become available, which has the potential to make molecular detection of invasive species more widely accessible and to substantially decrease sample turnaround times. However, nanopore-sequenced reads have a much higher error rate than those produced by Illumina platforms, which has so far hindered the adoption of this technology. We provide a detailed laboratory protocol and bioinformatic tools to increase the reliability of nanopore sequencing to detect invasive species, and we test its application using invasive bivalves. We sampled water from sites with pre-existing bivalve occurrence and abundance data, and contrasting bivalve communities, in Italy and Portugal. We extracted, amplified and sequenced eDNA with a turnaround of 3.5 days. The majority of processed reads were = 99 % identical to reference sequences. There were no taxa detected other than those known to occur. The lack of detections of some species at some sites could be explained by their known low abundances. The approach is now being tested on other target taxa such as fish and other vertebrates.

Abstract
Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR=1.63, p=5.24 x 10(-5)) and overall survival (HR=1.61, p=1.67 x 10(-4)), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (p(AUROC) = 7.03 x 10(-4)), or published prognostic signatures (p(AUROC) < 0.05). The signature score negatively correlated with measures of immune cell infiltration (=-0.75, p<2.2 x 10(-16)), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials. The identification of prognostic biomarkers can help stratify cancer patients. Here, the authors apply deep RNA sequencing from primary melanomas coupled with long-term clinical outcome data from a prospective multicentre phase III trial, to develop and validate a 121 metastasis-associated gene signature identifying early-stage melanoma patients at higher risk of metastasis and worse survival.

Abstract
The recent report of distinct Xanthomonas lineages of Xanthomonas arboricola pv. juglandis and Xanthomonas euroxanthea within the same walnut tree revealed that this consortium of walnut-associated Xanthomonas includes both pathogenic and nonpathogenic strains. As the implications of this co-colonization are still poorly understood, in order to unveil niche-specific adaptations, the genomes of three X. euroxanthea strains (CPBF 367, CPBF 424(T), and CPBF 426) and of an X. arboricola pv. juglandis strain (CPBF 427) isolated from a single walnut tree in Loures (Portugal) were sequenced with two different technologies, Illumina and Nanopore, to provide consistent single scaffold chromosomal sequences. General genomic features showed that CPBF 427 has a genome similar to other X. arboricola pv. juglandis strains, regarding its size, number, and content of CDSs, while X. euroxanthea strains show a reduction regarding these features comparatively to X. arboricola pv. juglandis strains. Whole genome comparisons revealed remarkable genomic differences between X. arboricola pv. juglandis and X. euroxanthea strains, which translates into different pathogenicity and virulence features, namely regarding type 3 secretion system and its effectors and other secretory systems, chemotaxis-related proteins, and extracellular enzymes. Altogether, the distinct genomic repertoire of X. euroxanthea may be particularly useful to address pathogenicity emergence and evolution in walnut-associated Xanthomonas.

Abstract
We report the genome sequence of Xanthomonas arboricola pv. juglandis strain CPBF 427, which was isolated from early-season buds of a diseased walnut tree, suggesting overwinter potential. This study provides a consistent genomic reference for this pathovar and may contribute to addressing the overwinter survival of these walnut pathogens.

Abstract
Recent developments on ethanol-based DNA (etDNA) metabarcoding have shown that it is possible to extract meaningful information about macroinvertebrate community diversity and composition from the ethanol used to preserve bulk samples. The major advantages of this molecular approach are the reduced processing time and costs, and the possibility to keep specimens intact for other experiments. Yet, organisms with highly sclerotised exoskeleton or that are rare in the sample have been found to release a lower amount of DNA into solution and tend to be consistently missed by etDNA metabarcoding, thereby compromising the viability of the method. Few studies have shown that the first steps of the metabarcoding workflow are crucial for the good performance of etDNA-based assays, such as the decision on storage time before sampling and the ethanol phase to be analysed, the inclusion of pre-treatment strategies (i.e., freezing), and the choice of the DNA extraction protocol. In this study, we aimed to evaluate the combined effect of various technical choices on the performance of etDNA metabarcoding, considering factors such as sample volume, ethanol phase of sorted and unsorted samples, pre-capture treatments (evaporation vs filtration) and bioinformatic pipelines. Through the application of decision-tree models, our preliminary data revealed that the increase of volume (by itself) is enough to improve PCR amplification yields and proportion of families matching the morphological identifications, with great impact on the detection of hard-bodied and cased taxa. Also, no major differences among phases with or without a sorting step nor among bioinformatic pipelines were detected, particularly at higher volumes. Our results suggest that the higher performance (with lower observed variation) in taxonomic detection at higher volumes is likely a consequence of a higher availability of longer fragments of DNA in solution. This study highlights the importance of understanding the impact of technical choices to improve the efficiency of a DNA-based method, and reinstates etDNA metabarcoding as a potential method in the context of biomonitoring.

Abstract
The orders Neuroptera and Raphidioptera include the species of insects known as lacewings and snake flies, respectively. In Portugal, these groups account for over 100 species, some of which are very difficult to identify by morphological analysis. This work is the first to sample and DNA sequence lacewings and snakeflies of Portugal. A reference collection was built with captured specimens that were identified morphologically. DNA barcode sequences of 658 bp were obtained from 243 specimens of 54 species. The results showed that most species can be successfully identified through DNA barcoding, with the exception of seven species of Chrysopidae (Neuroptera). Additionally, the first published distribution data are presented for Portugal for the neuropterans Gymnocnemia variegata (Schneider, 1845) and Myrmecaelurus (Myrmecaelurus) trigrammus (Pallas, 1771).