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Background'Nebbiolo' is a grapevine cultivar typical of north-western Italy, appreciated for producing high-quality red wines. Grapevine cultivars are characterized by possessing highly heterozygous genomes, including a great incidence of genomic rearrangements larger than 50 bp, so called structural variations (SVs). Even though abundant, SVs are an under-explored source of genetic variation mainly due to methodological limitations at their detection.ResultsWe employed a multiple platform approach to produce long-range genomic data for two different 'Nebbiolo' clones, namely: optical mapping, long-reads and linked-reads. We performed a haplotype-resolved de novo assembly for cultivar 'Nebbiolo' (clone CVT 71) and used an ab-initio strategy to annotate it. The annotated assembly enhanced our ability to detect SVs, enabling the study of genomic regions not present in the grapevines' reference genome and accounting for their functional implications. We performed variant calling analyses at three different organizational levels: i) between haplotypes of clone CVT 71 (primary assembly vs haplotigs), ii) between 'Nebbiolo' and 'Cabernet Sauvignon' assemblies and iii) between clones CVT 71 and CVT 185, representing different 'Nebbiolo' biotypes. The cumulative size of non-redundant merged SVs indicated a total of 79.6 Mbp for the first comparison and 136.1 Mbp for the second one, while no SVs were detected for the third comparison. Interestingly, SVs differentiating cultivars and haplotypes affected similar numbers of coding genes.ConclusionsOur results suggest that SVs accumulation rate and their functional implications in 'Nebbiolo' genome are highly-dependent on the organizational level under study. SVs are abundant when comparing 'Nebbiolo' to a different cultivar or the two haplotypes of the same individual, while they turned absent between the two analysed clones.

Eukaryotes are important components of primate gut communities. Despite their role in the diversity and structure of the gut ecosystem, microbiome research has focused on the prokaryotic component of the gut community. While gut bacteria are shaped by host phylogeny and diet, these factors are known to have negligible effects on eukaryotic diversity, which is expected to be modulated by the characteristics of the habitat. We assess the influence of landscape composition and configuration on the eukaryome of black and gold howler monkeys (Alouatta caraya). We collected fecal samples from 10 independent social groups inhabiting small forest fragments or orchards enriched with native tree species and applied an 18S rRNA gene fragment metabarcoding approach to describe their eukaryotic communities. We used generalized linear models to assess the power of landscape metrics in predicting the richness, diversity, evenness, and phylogenetic diversity of the eukaryome. Most communities were dominated by Ascomycota, and it is likely that many of the reads had an environmental origin. Forest cover affected eukaryome richness positively and patch density showed a positive relationship with the Simpson’s diversity and Pielou’s evenness indexes. Howler monkeys living in landscapes with lower habitat coverage had a lower eukaryotic alpha-diversity in the fecal microbiome. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) is the most abundant internal eukaryotic mRNA modification, and is involved in the regulation of various biological processes. Direct Nanopore sequencing of native RNA (dRNA-seq) emerged as a leading approach for its identification. Several software were published for m6A detection and there is a strong need for independent studies benchmarking their performance on data from different species, and against various reference datasets. Moreover, a computational workflow is needed to streamline the execution of tools whose installation and execution remains complicated. We developed NanOlympicsMod, a Nextflow pipeline exploiting containerized technology for comparing 14 tools for m6A detection on dRNA-seq data. NanOlympicsMod was tested on dRNA-seq data generated from in vitro (un)modified synthetic oligos. The m6A hits returned by each tool were compared to the m6A position known by design of the oligos. In addition, NanOlympicsMod was used on dRNA-seq datasets from wild-type and m6A-depleted yeast, mouse and human, and each tool's hits were compared to reference m6A sets generated by leading orthogonal methods. The performance of the tools markedly differed across datasets, and methods adopting different approaches showed different preferences in terms of precision and recall. Changing the stringency cut-offs allowed for tuning the precision-recall trade-off towards user preferences. Finally, we determined that precision and recall of tools are markedly influenced by sequencing depth, and that additional sequencing would likely reveal additional m6A sites. Thanks to the possibility of including novel tools, NanOlympicsMod will streamline the benchmarking of m6A detection tools on dRNA-seq data, improving future RNA modification characterization. [ABSTRACT FROM AUTHOR]

Genetic markers (DNA barcodes) are often used to support and confirm species identification. Barcode sequences can be generated in the field using portable systems based on the Oxford Nanopore Technologies (ONT) MinION sequencer. However, to achieve a broader application, current proof-of-principle workflows for on-site barcoding analysis must be standardized to ensure a reliable and robust performance under suboptimal field conditions without increasing costs. Here, we demonstrate the implementation of a new on-site workflow for DNA extraction, PCR-based barcoding, and the generation of consensus sequences. The portable laboratory features inexpensive instruments that can be carried as hand luggage and uses standard molecular biology protocols and reagents that tolerate adverse environmental conditions. Barcodes are sequenced using MinION technology and analyzed with ONTrack, an original de novo assembly pipeline that requires as few as 1000 reads per sample. ONTrack-derived consensus barcodes have a high accuracy, ranging from 99.8 to 100%, despite the presence of homopolymer runs. The ONTrack pipeline has a user-friendly interface and returns consensus sequences in minutes. The remarkable accuracy and low computational demand of the ONTrack pipeline, together with the inexpensive equipment and simple protocols, make the proposed workflow particularly suitable for tracking species under field conditions. [ABSTRACT FROM AUTHOR]

The emergence of novel viral epidemics that could affect major crops represents a serious threat to global food security. The early and accurate identification of the causative viral agent is the most important step for a rapid and effective response to disease outbreaks. Over the last years, the Oxford Nanopore Technologies (ONT) MinION sequencer has been proposed as an effective diagnostic tool for the early detection and identification of emerging viruses in plants, providing many advantages compared with different high-throughput sequencing (HTS) technologies. Here, we provide a step-by-step protocol that we optimized to obtain the virome of "Lamon bean" plants (Phaseolus vulgaris L.), an agricultural product with Protected Geographical Indication (PGI) in North-East of Italy, which is frequently subjected to multiple infections caused by different RNA viruses. The conversion of viral RNA in ds-cDNA enabled the use of Genomic DNA Ligation Sequencing Kit and Native Barcoding DNA Kit, which have been originally developed for DNA sequencing. This allowed the simultaneous diagnosis of both DNA- and RNA-based pathogens, providing a more versatile alternative to the use of direct RNA and/or direct cDNA sequencing kits., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)