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Diagnostic tests based on reverse transcription–quantitative polymerase chain reaction (RT–qPCR) are the gold standard approach to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from clinical specimens. However, unless specifically optimized, this method is usually unable to recognize the specific viral strain responsible of coronavirus disease 2019, a crucial information that is proving increasingly important in relation to virus spread and treatment effectiveness. Even if some RT–qPCR commercial assays are currently being developed for the detection of viral strains, they focus only on single/few genetic variants that may not be sufficient to uniquely identify a specific strain. Therefore, genome sequencing approaches remain the most comprehensive solution for virus genotyping and to recognize viral strains, but their application is much less widespread due to higher costs. Starting from the well-established ARTIC protocol coupled to nanopore sequencing, in this work, we developed STArS (STrain-Amplicon-Seq), a cost/time-effective sequencing-based workflow for both SARS-CoV-2 diagnostics and genotyping. A set of 10 amplicons was initially selected from the ARTIC tiling panel, to cover: (i) all the main biologically relevant genetic variants located on the Spike gene; (ii) a minimal set of variants to uniquely identify the currently circulating strains; (iii) genomic sites usually amplified by RT–qPCR method to identify SARS-CoV-2 presence. PCR-amplified clinical samples (both positive and negative for SARS-CoV-2 presence) were pooled together with a serially diluted exogenous amplicon at known concentration and sequenced on a MinION device. Thanks to a scoring rule, STArS had the capability to accurately classify positive samples in agreement with RT–qPCR results, both at the qualitative and quantitative level. Moreover, the method allowed to effectively genotype strain-specific variants and thus also return the phylogenetic classification of SARS-CoV-2-postive samples. Thanks to the reduced turnaround time and costs, the proposed approach represents a step towards simplifying the clinical application of sequencing for viral genotyping, hopefully aiding in combatting the global pandemic.

Background Patients with glioblastoma (GBM) have a dramatically poor prognosis. The recent REGOMA trial suggested an overall survival (OS) benefit of regorafenib in recurrent GBM patients. Considering the extreme genetic heterogeneity of GBMs, we aimed to identify molecular biomarkers predictive of differential response to the drug. Methods Total RNA was extracted from tumor samples of patients enrolled in the REGOMA trial. Genome-wide transcriptome and micro (mi)RNA profiles were associated with patients’ OS and progression-free survival. Results In the first step, a set of 11 gene transcripts (HIF1A, CTSK, SLC2A1, KLHL12, CDKN1A, CA12, WDR1, CD53, CBR4, NIFK-AS1, RAB30-DT) and 10 miRNAs (miR-93-5p, miR-203a-3p, miR-17-5p, let-7c-3p, miR-101-3p, miR-3607-3p, miR-6516-3p, miR-301a-3p, miR-23b-3p, miR-222-3p) was filtered by comparing survival between regorafenib and lomustine arms. In the second step, a mini-signature of 2 gene transcripts (HIF1A, CDKN1A) and 3 miRNAs (miR-3607-3p, miR-301a-3p, miR-93-5p) identified a subgroup of patients showing prolonged survival after regorafenib administration (median OS range, 10.6–20.8 mo). Conclusions The study provides evidence that a signature based on the expression of 5 biomarkers could help identify a subgroup of GBM patients exhibiting a striking survival advantage when treated with regorafenib. Although the presented results must be confirmed in larger replication cohorts, the study highlights potential biomarker options to help guide the clinical decision among regorafenib and other treatments in patients with relapsing GBM.

Traditional methods for the analysis of repeat expansions, which underlie genetic disorders, such as fragile X syndrome (FXS), lack single-nucleotide resolution in repeat analysis and the ability to characterize causative variants outside the repeat array. These drawbacks can be overcome by long-read and short-read sequencing, respectively. However, the routine application of next-generation sequencing in the clinic requires target enrichment, and none of the available methods allows parallel analysis of long-DNA fragments using both sequencing technologies. In this study, we investigated the use of indirect sequence capture (Xdrop technology) coupled to Nanopore and Illumina sequencing to characterize FMR1, the gene responsible of FXS. We achieved the efficient enrichment (> 200×) of large target DNA fragments (~60–80 kbp) encompassing the entire FMR1 gene. The analysis of Xdrop-enriched samples by Nanopore long-read sequencing allowed the complete characterization of repeat lengths in samples with normal, pre-mutation, and full mutation status (> 1 kbp), and correctly identified repeat interruptions relevant for disease prognosis and transmission. Single-nucleotide variants (SNVs) and small insertions/deletions (indels) could be detected in the same samples by Illumina short-read sequencing, completing the mutational testing through the identification of pathogenic variants within the FMR1 gene, when no typical CGG repeat expansion is detected. The study successfully demonstrated the parallel analysis of repeat expansions and SNVs/indels in the FMR1 gene at single-nucleotide resolution by combining Xdrop enrichment with two next-generation sequencing approaches. With the appropriate optimization necessary for the clinical settings, the system could facilitate both the study of genotype–phenotype correlation in FXS and enable a more efficient diagnosis and genetic counseling for patients and their relatives.

Mummified remains of relevant historical figures are nowadays an important source of information to retrace data concerning their private life and health, especially when historical archives are not available. Next-generation-sequencing was proved to be a valuable tool to unravel the characteristics of these individuals through their genetic heritage. Using the strictest criteria currently available for the validation of ancient DNA sequences, whole-genome and whole-exome sequencing were generated from the mummy remains of an Italian nobleman died almost 700 years ago, Cangrande della Scala. While its genome sequencing could not yield sufficient coverage for in depth investigation, exome sequencing could overcome the limitations of this approach to achieve significantly high coverage on coding regions, thus allowing to perform the first extensive exome analysis of a mummy genome. Similar to a standard “clinical exome analysis” conducted on modern DNA, an in-depth variant annotation, high-quality filtering and interpretation was performed, leading to the identification of a genotype associated with late-onset Pompe disease (glycogen storage disease type II). This genetic diagnosis was concordant with the limited clinical history available for Cangrande della Scala, who likely represents the earliest known case of this autosomal recessive metabolic disorder.

Sequencing the SARS-CoV-2 genome from clinical samples can be challenging, especially in specimens with low viral titer. Here we report Accurate SARS-CoV-2 genome Reconstruction (ACoRE), an amplicon-based viral genome sequencing workflow for the complete and accurate reconstruction of SARS-CoV-2 sequences from clinical samples, including suboptimal ones that would usually be excluded even if unique and irreplaceable. The protocol was optimized to improve flexibility and the combination of technical replicates was established as the central strategy to achieve accurate analysis of low-titer/suboptimal samples. We demonstrated the utility of the approach by achieving complete genome reconstruction and the identification of false-positive variants in >170 clinical samples, thus avoiding the generation of inaccurate and/or incomplete sequences. Most importantly, ACoRE was crucial to identify the correct viral strain responsible of a relapse case, that would be otherwise mis-classified as a re-infection due to missing or incorrect variant identification by a standard workflow.

The exome contains many obscure regions difficult to explore with current short-read sequencing methods. Repetitious genomic regions prevent the unique alignment of reads, which is essential for the identification of clinically-relevant genetic variants. Long-read technologies attempt to resolve multiple-mapping regions, but they still produce many sequencing errors. Thus, a new approach is required to enlighten the obscure regions of the genome and rescue variants that would be otherwise neglected. This work aims to improve the alignment of multiple-mapping reads through the extension of the standard DNA fragment size. As Illumina can sequence fragments up to 550 bp, we tested different DNA fragment lengths using four major commercial WES platforms and found that longer DNA fragments achieved a higher genotypability. This metric, which indicates base calling calculated by combining depth of coverage with the confidence of read alignment, increased from hundreds to thousands of genes, including several associated with clinical phenotypes. While depth of coverage has been considered crucial for the assessment of WES performance, we demonstrated that genotypability has a greater impact in revealing obscure regions, with ~1% increase in variant calling in respect to shorter DNA fragments. Results confirmed that this approach enlightened many regions previously not explored.

Terrestrial Caenogastropoda form an important but threatened component of the Borneo tropical rainforest malacofauna, where the group is nearly as rich in species as the Stylommatophora. They are, however, more sensitive to drought, temperature extremes and forest degradation. On a field course at Kuala Belalong Field Studies Centre in Brunei Darussalam (Borneo), a new caenogastropod species, belonging to the genus Craspedotropis, was discovered by the course participants. The participants decided to name the species Craspedotropis gretathunbergae n. sp., in honour of the climate change activist Greta Thunberg, as caenogastropod land snails, such as this species, are likely to suffer because of climate change.

Whole-exome sequencing (WES) enrichment platforms are usually evaluated by measuring the depth of coverage at target regions. However, variants called in WES are reported in the variant call format (VCF) file, which is filtered by minimum site coverage and mapping quality. Therefore, genotypability (base calling calculated by combining depth of coverage with the confidence of read alignment) should be considered as a more informative parameter to assess the performance of WES. We found that the mapping quality of reads aligned to difficult target regions was improved by increasing the DNA fragment length well above the average exon size. We tested three different DNA fragment lengths using four major commercial WES platforms and found that longer DNA fragments achieved a higher percentage of callable bases in the target regions and thus improved the genotypability of many genes, including several associated with clinical phenotypes. DNA fragment size also affected the uniformity of coverage, which in turn influences genotypability, indicating that different platforms are optimized for different DNA fragment lengths. Finally, we found that although the depth of coverage continued to increase in line with the sequencing depth (overall number of reads), base calling reached saturation at a depth of coverage that depended on the enrichment platform and DNA fragment length. This confirmed that genotypability provides better estimates for the optimal sequencing depth of each fragment size/enrichment platform combination.