Human utilization of the mulberry–silkworm interaction started at least 5,000 years ago and greatly influenced world history through the Silk Road. Complementing the silkworm genome sequence, here we describe the genome of a mulberry species Morus notabilis. In the 330-Mb genome assembly, we identify 128 Mb of repetitive sequences and 29,338 genes, 60.8% of which are supported by transcriptome sequencing. Mulberry gene sequences appear to evolve ~3 times faster than other Rosales, perhaps facilitating the species’ spread worldwide. The mulberry tree is among a few eudicots but several Rosales that have not preserved genome duplications in more than 100 million years; however, a neopolyploid series found in the mulberry tree and several others suggest that new duplications may confer benefits. Five predicted mulberry miRNAs are found in the haemolymph and silk glands of the silkworm, suggesting interactions at molecular levels in the plant–herbivore relationship. The identification and analyses of mulberry genes involved in diversifying selection, resistance and protease inhibitor expressed in the laticifers will accelerate the improvement of mulberry plants.

Cotton fibers are differentiated epidermal cells originating from the outer integuments of the ovule. To identify genes involved in cotton fiber elongation, we performed subtractive PCR using cDNA prepared from 10 days post anthesis (d.p.a.) wild-type cotton fiber as tester and cDNA from a fuzzless-lintless (fl) mutant as driver. We recovered 280 independent cDNA fragments including most of the previously published cotton fiber-related genes. cDNA macroarrays showed that 172 genes were significantly up-regulated in elongating cotton fibers as confirmed by in situ hybridization in representative cases. Twenty-nine cDNAs, including a putative vacuolar (H+)-ATPase catalytic subunit, a kinesin-like calmodulin binding protein, several arabinogalactan proteins and key enzymes involved in long chain fatty acid biosynthesis, accumulated to greater than 50-fold in 10 d.p.a. fiber cells when compared to that in 0 d.p.a. ovules. Various upstream pathways, such as auxin signal transduction, the MAPK pathway and profilin- and expansin-induced cell wall loosening, were also activated during the fast fiber elongation period. This report constitutes the first systematic analysis of genes involved in cotton fiber development. Our results suggest that a concerted mechanism involving multiple cellular pathways is responsible for cotton fiber elongation.

Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although >99% of reads were correctly classified at the genus level, up to ≈40% were misclassified at the species level. Both technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.

Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are “fit-for-purpose” and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a “push-button” pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.

Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016–2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.

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Keywords: marginal division; neostriatum; functional magnetic resonance imaging; learning and memory; digital working memory; human brain; immunohistochemistry Previous studies identified a new brain area, the marginal division (MrD), at the caudomedial border of the neostriatum in the brain of the rat, cat and monkey. The MrD was distinguishable from the rest of the striatum by the presence of spindle-shaped neurons, specific connections, and dense immunoreactivity for neuropeptides and monoamines in fibers, terminals and neuronal somata. Behavioral testing demonstrated that the MrD contributes to learning and memory in the rat. In the present study, the structure and the function of the MrD were investigated in the human brain In previous studies we discovered a structure we termed the marginal division (MrD) on the basis of its location at the caudomedial margin of the neostriatum surrounding the rostral border of the globus pallidus in rat, 1 cat 2 and monkey 3 brains. A three dimensional reconstruction from Nissl-stained sections of the rat brain showed that the MrD is a flat, pan-shaped structure. The MrD was easily distinguishable from the rest of the striatum by the presence of spindle-shaped neurons and a variety of intensely expressed neuropeptides and monoamines in nerve fibers, terminals and neuronal somata. 4 Most of the neuropeptides in the MrD have been considered to be functionally involved in learning and memory. 5,6 Functional neuronal connections between the MrD and the hippocampus, amygdala and basal nucleus of Meynert (NBM) were identified by chemically induced c-fos protein (c-Fos) expression. 7 The MrD was shown to contribute to learning and memory in the rat with the double-blind Y-maze test. 8 The presence of the MrD in the neostriatum was confirmed by other investigators in immunohistochemical and physiological studies. Talley et al reported a higher level of expression of ␣2A adrenergic receptors in the marginal division than in the rest of the striatum. 9 Lavoie and Parent demonstrated that pedunculopontine nuclear projections to the basal ganglia terminated exclusively in the MrD, 10 distinguishing it from other parts of the striatum. Nociceptive neurons were reported localized solely in the MrD of the rat striatum, using neurophysiological techniques, 11 and the MrD was described as part of the ventral striatal area by Heimer and coworkers. 12,13 In the present study we wished to determine whether the MrD is also present in the human brain and to assess its possible function in vivo with a non-invasive imaging technique. Neuroanatomical and immunocytochemical studies were carried out on brains autopsied from 12 children and five adults to assess any differences between the young and the mature brain; no staining differences between them were observed. Brains were dissected and sectioned to study the structure of the neostriatum. The cytoarchitecture of brain sections was investigated with Nissl staining. Neurotransmitter distribution was identified with primary and secondary antibod...

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a ‘push-button’ pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.