Next-generation Sequencing Reads Research Articles

A Standardized Pipeline for Assembly and Annotation of African Swine Fever Virus Genome.

Obtaining a complete good-quality sequence and annotation for the long double-stranded DNA genome of the African swine fever virus (ASFV) from next-generation sequencing (NGS) technology has proven difficult, despite the increasing availability of reference genome sequences and the increasing affordability of NGS. A gap analysis conducted by the global African swine fever research alliance (GARA) partners identified that a standardized, automatic pipeline for NGS analysis was urgently needed, particularly for new outbreak strains. Whilst there are several diagnostic and research labs worldwide that collect isolates of the ASFV from outbreaks, many do not have the capability to analyze, annotate, and format NGS data from outbreaks for submission to NCBI, and some publicly available ASFV genomes have missing or incorrect annotations. We developed an automated, standardized pipeline for the analysis of NGS reads that directly provides users with assemblies and annotations formatted for their submission to NCBI. This pipeline is freely available on GitHub and has been tested through the GARA partners by examining two previously sequenced ASFV genomes; this study also aimed to assess the accuracy and limitations of two strategies present within the pipeline: reference-based (Illumina reads) and de novo assembly (Illumina and Nanopore reads) strategies.

Intratumoral Escherichia Is Associated With Improved Survival to Single-Agent Immune Checkpoint Inhibition in Patients With Advanced Non-Small-Cell Lung Cancer.

The impact of the intratumoral microbiome on immune checkpoint inhibitor (ICI) efficacy in patients with non-small-cell lung cancer (NSCLC) is unknown. Preclinically, intratumoral Escherichia is associated with a proinflammatory tumor microenvironment and decreased metastases. We sought to determine whether intratumoral Escherichia is associated with outcome to ICI in patients with NSCLC. We examined the intratumoral microbiome in 958 patients with advanced NSCLC treated with ICI by querying unmapped next-generation sequencing reads against a bacterial genome database. Putative environmental contaminants were filtered using no-template controls (n = 2,378). The impact of intratumoral Escherichia detection on overall survival (OS) was assessed using univariable and multivariable analyses. The findings were further validated in an external independent cohort of 772 patients. Escherichia fluorescence in situ hybridization (FISH) and transcriptomic profiling were performed. In the discovery cohort, read mapping to intratumoral Escherichia was associated with significantly longer OS (16 v 11 months; hazard ratio, 0.73 [95% CI, 0.59 to 0.92]; P = .0065) in patients treated with single-agent ICI, but not combination chemoimmunotherapy. The association with OS in the single-agent ICI cohort remained statistically significant in multivariable analysis adjusting for prognostic features including PD-L1 expression (P = .023). Analysis of an external validation cohort confirmed the association with improved OS in univariable and multivariable analyses of patients treated with single-agent ICI, and not in patients treated with chemoimmunotherapy. Escherichia localization within tumor cells was supported by coregistration of FISH staining and serial hematoxylin and eosin sections. Transcriptomic analysis correlated Escherichia-positive samples with expression signatures of immune cell infiltration. Read mapping to potential intratumoral Escherichia was associated with survival to single-agent ICI in two independent cohorts of patients with NSCLC.

Comparing Gold-Standard Sanger Sequencing with Two Next-Generation Sequencing Platforms of HIV-1 gp160 Single Genome Amplicons.

Our goal was to assess the accuracy of next generation sequencing (NGS) compared with Sanger. We performed single genome amplification (SGA) of HIV-1 gp160 on extracted tissue DNA from two HIV+ individuals. Amplicons (n = 30) were sequenced with Sanger or reamplified with barcoded primers and pooled before sequencing using Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PB). For each amplicon, a consensus sequence for NGS reads was obtained by (1) mapping reads to the Sanger sequence when available ("reference-based") or (2) mapping reads to a "pseudo-reference" sequence, i.e., a consensus sequence of a subset of NGS reads ("reference-free"). PB reads were clustered based on genetic similarity. A Sanger consensus sequence was obtained for 23/30 amplicons, for which all NGS consensus sequences were identical (n = 9) or nearly identical (n = 14) compared with Sanger. For the nine mismatches between Sanger/NGS, the nucleotide in the NGS sequence matched all other sequences from that patient. Of the 7/30 amplicons without a Sanger sequence, NGS sequences had ≥35 ambiguous calls in five amplicons and 0 ambiguitiesin two amplicons. Analysis of the electropherograms showed failure of a single sequencing primer for the latter two amplicons (consistent with a single template) and overlapping peaks for the other five (consistent with multiple templates). Clustering results closely followed the Sanger/NGS consensus results, where amplicons derived from a single template also had a single cluster and vice versa (with one exception, which could be the result of barcode misidentification). Representative sequences from the clusters contained 2-13 differences compared with Sanger/NGS. In summary, we show that both ONT and PB can produce amplicon consensus sequences with similar or higher accuracy compared with Sanger and, importantly, without the need for a known reference sequence. Clustering could be useful in some circumstances to predict or confirm the presence of multiple starting templates.

Performance of the Applied Biosystems HIV-1 Genotyping Kit with Integrase.

HIV genotyping is used to assess HIV susceptibility to antiretroviral drugs. The Applied Biosystems HIV-1 Genotyping Kit with Integrase (AB kit, Thermo Fisher Scientific) detects resistance-associated mutations (RAMs) in HIV protease (PR), reverse transcriptase (RT), and integrase (IN). We compared results from the AB kit with results obtained previously with the ViroSeq HIV-1 Genotyping System. DNA amplicons from the AB kit were also analyzed using next-generation sequencing (NGS). HIV RNA was extracted using the MagNA Pure 24 instrument (Roche Diagnostics; 96 plasma samples, HIV subtype B, viral load range: 530-737,741 copies/mL). FASTA files were generated from AB kit data using Exatype (Hyrax Biosciences). DNA amplicons from the AB kit were also analyzed by NGS using the Nextera XT kit (Illumina). Drug resistance was predicted using the Stanford HIV Drug Resistance Database. The mean genetic distance for sequences from ViroSeq and the AB kit was 0.02% for PR/RT and 0.04% for IN; 103 major RAMs were detected by both methods. Four additional major RAMs were detected by the AB kit only. These four major RAMs were also detected by NGS (detected in 18.1%-38.2% of NGS reads). NGS detected 27 major RAMs that were not detected with either of the Sanger sequencing-based kits. All major RAMs detected with ViroSeq were detected with the AB kit; additional RAMs were detected with the AB kit only. DNA amplicons from the AB kit can be used for NGS for more sensitive detection of RAMs.

Impact of electrolyzed water treatment on bacterial communities in food washing processes

Electrolyzed water is expected to have a sterilizing effect on bacteria and viruses, which makes it useful for hygiene management, such as cleaning dishes or medical equipment. Electrolyzed water treatment may affect the cellular structure of microbes, leading to DNA leakage or degradation. Here, we conducted a next-generation sequencing (NGS) analysis of bacterial diversity in washing solution to elucidate the impact of cleaning food surfaces with electrolyzed water. Modified primers were used to evaluate the differences between the existing primers used to obtain NGS sequences and through statistical analysis. The NGS reads obtained using the modified primers tended to reveal more Enterobacteriaceae sequences, and fewer mitochondrial sequences than did those obtained with conventional primers. An UniFrac distance analysis and Nonmetric multidimensional scaling (NMDS) revealed that the results obtained with the modified primer set made the differences between samples more distinct. Real-time polymerase chain reaction (PCR) using the template DNA obtained from an electrolyzed water or sodium hypochlorite solution wash revealed that some of the DNA could not be amplified using PCR of the 16S rRNA genes suggesting that the DNA fragmentation had occurred due to the electrolyzed water treatment. Our results revealed that the bacterial species removed from the food surfaces varied depending on the washing treatment. Electrolyzed water treatment may be advantageous for removing Enterobacteriaceae from leafy vegetables.

The development of non-destructive sampling methods of parchment skins for genetic species identification.

Parchment, the skins of animals prepared for use as writing surfaces, offers a valuable source of genetic information. Many have clearly defined provenance, allowing for the genetic findings to be evaluated in temporal and spatial context. While these documents can yield evidence of the animal sources, the DNA contained within these aged skins is often damaged and fragmented. Previously, genetic studies targeting parchment have used destructive sampling techniques and so the development and validation of non-destructive sampling methods would expand opportunities and facilitate testing of more precious documents, especially those with historical significance. Here we present genetic data obtained by non-destructive sampling of eight parchments spanning the 15th century to the modern day. We define a workflow for enriching the mitochondrial genome (mtGenome), generating next-generation sequencing reads to permit species identification, and providing interpretation guidance. Using sample replication, comparisons to destructively sampled controls, and by establishing authentication criteria, we were able to confidently assign full/near full mtGenome sequences to 56.3% of non-destructively sampled parchments, each with greater than 90% of the mtGenome reference covered. Six of eight parchments passed all four established thresholds with at least one non-destructive sample, highlighting promise for future studies.

A compressive seeding algorithm in conjunction with reordering-based compression.

Seeding is a rate-limiting stage in sequence alignment for next-generation sequencing reads. The existing optimization algorithms typically utilize hardware and machine-learning techniques to accelerate seeding. However, an efficient solution provided by professional next-generation sequencing compressors has been largely overlooked by far. In addition to achieving remarkable compression ratios by reordering reads, these compressors provide valuable insights for downstream alignment that reveal the repetitive computations accounting for more than 50% of seeding procedure in commonly used short read aligner BWA-MEM at typical sequencing coverage. Nevertheless, the exploited redundancy information is not fully realized or utilized. In this study, we present a compressive seeding algorithm, named CompSeed, to fill the gap. CompSeed, in collaboration with the existing reordering-based compression tools, finishes the BWA-MEM seeding process in about half the time by caching all intermediate seeding results in compact trie structures to directly answer repetitive inquiries that frequently cause random memory accesses. Furthermore, CompSeed demonstrates better performance as sequencing coverage increases, as it focuses solely on the small informative portion of sequencing reads after compression. The innovative strategy highlights the promising potential of integrating sequence compression and alignment to tackle the ever-growing volume of sequencing data. CompSeed is available at https://github.com/i-xiaohu/CompSeed.

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This introduces the need to utilize different approaches to detect and filtrate errors, and data quality assurance is moved from the hardware space to the software preprocessing stages. We introduce MAC-ErrorReads, a novel Machine learning-Assisted Classifier designed for filtering Erroneous NGS Reads. MAC-ErrorReads transforms the erroneous NGS read filtration process into a robust binary classification task, employing five supervised machine learning algorithms. These models are trained on features extracted through the computation of Term Frequency-Inverse Document Frequency (TF_IDF) values from various datasets such as E. coli, GAGE S. aureus, H. Chr14, Arabidopsis thaliana Chr1 and Metriaclima zebra. Notably, Naive Bayes demonstrated robust performance across various datasets, displaying high accuracy, precision, recall, F1-score, MCC, and ROC values. The MAC-ErrorReads NB model accurately classified S. aureus reads, surpassing most error correction tools with a 38.69% alignment rate. For H. Chr14, tools like Lighter, Karect, CARE, Pollux, and MAC-ErrorReads showed rates above 99%. BFC and RECKONER exceeded 98%, while Fiona had 95.78%. For the Arabidopsis thaliana Chr1, Pollux, Karect, RECKONER, and MAC-ErrorReads demonstrated good alignment rates of 92.62%, 91.80%, 91.78%, and 90.87%, respectively. For the Metriaclima zebra, Pollux achieved a high alignment rate of 91.23%, despite having the lowest number of mapped reads. MAC-ErrorReads, Karect, and RECKONER demonstrated good alignment rates of 83.76%, 83.71%, and 83.67%, respectively, while also producing reasonable numbers of mapped reads to the reference genome. This study demonstrates that machine learning approaches for filtering NGS reads effectively identify and retain the most accurate reads, significantly enhancing assembly quality and genomic coverage. The integration of genomics and artificial intelligence through machine learning algorithms holds promise for enhancing NGS data quality, advancing downstream data analysis accuracy, and opening new opportunities in genetics, genomics, and personalized medicine research.

Diversity of Mycorrhizal Fungi in Temperate Orchid Species: Comparison of Culture-Dependent and Culture-Independent Methods.

Many orchid species are endangered due to anthropogenic pressures such as habitat destruction and overharvesting, meanwhile, all orchids rely on orchid mycorrhizal fungi (OMF) for seed germination and seedling growth. Therefore, a better understanding of this intimate association is crucial for orchid conservation. Isolation and identification of OMF remain challenging as many fungi are unculturable. In our study, we tested the efficiency of both culture-dependent and culture-independent methods to describe OMF diversity in multiple temperate orchids and assessed any phylogenetic patterns in cultivability. The culture-dependent method involved the cultivation and identification of single pelotons (intracellular hyphal coils), while the culture-independent method used next-generation sequencing (NGS) to identify root-associated fungal communities. We found that most orchid species were associated with multiple fungi, and the orchid host had a greater impact than locality on the variability in fungal communities. The culture-independent method revealed greater fungal diversity than the culture-dependent one, but despite the lower detection, the isolated fungal strains were the most abundant OMF in adult roots. Additionally, the abundance of NGS reads of cultured OTUs was correlated with the extent of mycorrhizal root colonization in orchid plants. Finally, this limited-scale study tentatively suggests that the cultivability character of OMF may be randomly distributed along the phylogenetic trees of the rhizoctonian families.

Hybrid-hybrid correction of errors in long reads with HERO

Although generally superior, hybrid approaches for correcting errors in third-generation sequencing (TGS) reads, using next-generation sequencing (NGS) reads, mistake haplotype-specific variants for errors in polyploid and mixed samples. We suggest HERO, as the first “hybrid-hybrid” approach, to make use of both de Bruijn graphs and overlap graphs for optimal catering to the particular strengths of NGS and TGS reads. Extensive benchmarking experiments demonstrate that HERO improves indel and mismatch error rates by on average 65% (27∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document}95%) and 20% (4∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim$$\\end{document}61%). Using HERO prior to genome assembly significantly improves the assemblies in the majority of the relevant categories.

Buried treasure in a public repository: Mining mitochondrial genes of 32 annelid species from sequence reads deposited in the Sequence Read Archive (SRA).

The mitochondrial genomes (mitogenomes) of metazoans generally include the same set of protein-coding genes, which ensures the homology of mitochondrial genes between species. The mitochondrial genes are often used as reference data for species identification based on genetic data (DNA barcoding). The need for such reference data has been increasing due to the application of environmental DNA (eDNA) analysis for environmental assessments. Recently, the number of publicly available sequence reads obtained with next-generation sequencing (NGS) has been increasing in the public database (the NCBI Sequence Read Archive, SRA). Such freely available NGS reads would be promising sources for assembling mitochondrial protein-coding genes (mPCGs) of organisms whose mitochondrial genes are not available in GenBank. The present study aimed to assemble annelid mPCGs from raw data deposited in the SRA. The recent progress in the classification of Annelida was briefly introduced. In the present study, the mPCGs of 32 annelid species of 19 families in clitellates and allies in Sedentaria (echiurans and polychaetes) were newly assembled from the reads deposited in the SRA. Assembly was performed with a recently published pipeline mitoRNA, which includes cycles of Bowtie2 mapping and Trinity assembly. Assembled mPCGs were deposited in GenBank as Third Party Data (TPA) data. A phylogenetic tree was reconstructed with maximum likelihood (ML) analysis, together with other mPCGs deposited in GenBank. mPCG assembly was largely successful except for Travisia forbesii; only four genes were detected from the assembled contigs of the species probably due to the reads targeting its parasite. Most genes were largely successfully obtained, whereas atp8, nad2, and nad4l were only successful in 22-24 species. The high nucleotide substitution rates of these genes might be relevant to the failure in the assembly although nad6, which showed a similarly high substitution rate, was successfully assembled. Although the phylogenetic positions of several lineages were not resolved in the present study, the phylogenetic relationships of some polychaetes and leeches that were not inferred by transcriptomes were well resolved probably due to a more dense taxon sampling than previous phylogenetic analyses based on transcriptomes. Although NGS data are generally better sources for resolving phylogenetic relationships of both higher and lower classifications, there are ensuring needs for specific loci of the mitochondrial genes for analyses that do not require high resolutions, such as DNA barcoding, eDNA, and phylogenetic analysis among lower taxa. Assembly from publicly available NGS reads would help design specific primers for the mitochondrial gene sequences of species, whose mitochondrial genes are hard to amplify by Sanger sequencing using universal primers.

Exploratory Analyses of Lymph Node Tissue, Serum, and Peripheral Blood Mononuclear Cells Do Not Reveal Pathogen Signatures in Idiopathic Multicentric Castleman Disease

Background : Castleman disease (CD) encompasses a group of hematologic disorders that share characteristic histopathological features. Unicentric CD (UCD) involves a solitary enlarged lymph node with typically mild symptoms. Multicentric CD (MCD) involves generalized lymphadenopathy and often severe cytokine-driven multi-organ dysfunction. MCD is further subdivided into cases caused by Human Herpesvirus-8 (HHV-8-associated MCD) infection, POEMS syndrome (POEMS-associated MCD), and those with an idiopathic cause (iMCD). The underlying pathological mechanisms and etiologies of UCD and iMCD are not well understood. Given that a viral pathogen, HHV-8, causes HHV-8-associated MCD, we pursued multiple approaches to identify potential pathogens that may trigger iMCD and UCD. Methods: We used 2 distinct detection methods to identify potential pathogens in CD. PathoChIP is a microarray-based assay that uses ~60,000 DNA/RNA probes to detect 4,000+ pathogens associated with human diseases. Viral Track is a computational method that can be applied to unmapped next-generation sequencing (NGS) reads to search for the presence of viral RNA. Formalin-fixed paraffin-embedded (FFPE) lymph node tissue was analyzed by PathoChIP from iMCD (n=6), UCD (n=8), HHV8-associated MCD (n=1, HHV8-MCD), EBV-driven post-transplant lymphoproliferative disorder (n=1, EBV-PTLD), reactive samples without a clear etiology (n=1), and POEMS-associated MCD (n=2) patients. We also analyzed serum from iMCD patients (n=2) and healthy donors (n=8). A ‘positive’ probe for a given microorganism was defined as exceeding the 95 th percentile on a per-probe basis of the optical signal captured across all probes in the dataset. Data from single-cell RNA sequencing of cryopreserved peripheral blood mononuclear cells (iMCD, n=4; EBV, n=2; HHV8, n=1; healthy donor, n=2) and bulk RNA sequencing of FFPE lymph node tissue (iMCD, n=9; sentinel, n=7; systemic lupus erythematosus (SLE), n=3; Diffuse large B-cell lymphoma (DLBCL), n=3) were used as input into the Viral Track program. To detect a positive viral signal, standard thresholds were required: >50 uniquely mapped reads to a given virus, a read complexity threshold >1.2, and >10% coverage of the length of the respective viral genome. Results: After quality control, 49,657 probes from the PathoCHIP assay were mapped to 4,000+ known pathogens. As expected, the HHV-8 MCD and EBV-PTLD samples identified significantly more positive probes compared to the rest of the cohort for HHV-8 (65/259 vs 1/259) and EBV (38/235 vs 1/235), respectively. Importantly, no other microorganisms were detected in UCD or MCD lymph nodes or serum samples at a significantly increased rate than controls. For Viral Track, human endogenous retrovirus K113 and Escherichia phages were detected at low levels throughout all results. Excluding these viruses, positive controls including HHV-8-MCD, and EBV solely identified their respective predicted virally mapped NGS reads and no viral signature was detected in healthy donors. Importantly, there was no significant viral signature specific to CD in PBMCs or LN tissue. Interestingly, 1 iMCD sample did contain a significant number of NGS sequencing reads mapping to HHV5. These results were confirmed with clinical data reporting a positive IgG, negative PCR, and negative IgM test within 2 weeks of the biopsy date, suggesting that the HHV5 positive result was likely detecting a previous, now latent infection rather than a potential pathological driver of CD. Conclusions: Although there are limitations to this study, including small cohorts and viral mRNA single-cell capture limitations, we were able to use 2 orthogonal pathogen detection methods on multiple tissue types from iMCD patients. Taken together, our results suggest that an active infectious agent is unlikely to be a major contributor or pathological mechanism driving UCD or iMCD. The continued search for potential causative microorganisms in iMCD patients should continue, but our results suggest that alternative hypotheses related to the pathology and etiology of iMCD and UCD should be prioritized.

GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads

Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.

Human immunodeficiency virus 1 5'-leader mutations in plasma viruses before and after the development of reverse transcriptase inhibitor-resistance mutations.

Human immunodeficiency virus 1 (HIV-1) reverse transcriptase (RT) initiation depends on interaction between viral 5'-leader RNA, RT and host tRNA3Lys. Therefore, we sought to identify co-evolutionary changes between the 5'-leader and RT in viruses developing RT-inhibitor resistance mutations. We sequenced 5'-leader positions 37-356 of paired plasma virus samples from 29 individuals developing the nucleoside RT inhibitor (NRTI)-resistance mutation M184V, 19 developing a non-nucleoside RT inhibitor (NNRTI)-resistance mutation and 32 untreated controls. 5'-Leader variants were defined as positions where ≥20 % of next-generation sequencing (NGS) reads differed from the HXB2 sequence. Emergent mutations were defined as nucleotides undergoing a ≥4-fold change in proportion between baseline and follow-up. Mixtures were defined as positions containing ≥2 nucleotides each present in ≥20 % of NGS reads. Among 80 baseline sequences, 87 positions (27.2 %) contained a variant; 52 contained a mixture. Position 201 was the only position more likely to develop a mutation in the M184V (9/29 vs 0/32; P=0.0006) or NNRTI-resistance (4/19 vs 0/32; P=0.02; Fisher's exact test) groups than the control group. Mixtures at positions 200 and 201 occurred in 45.0 and 28.8 %, respectively, of baseline samples. Because of the high proportion of mixtures at these positions, we analysed 5'-leader mixture frequencies in two additional datasets: five publications reporting 294 dideoxyterminator clonal GenBank sequences from 42 individuals and six National Center for Biotechnology Information (NCBI) BioProjects reporting NGS datasets from 295 individuals. These analyses demonstrated position 200 and 201 mixtures at proportions similar to those in our samples and at frequencies several times higher than at all other 5'-leader positions. Although we did not convincingly document co-evolutionary changes between RT and 5'-leader sequences, we identified a novel phenomenon, wherein positions 200 and 201 immediately downstream of the HIV-1 primer binding site exhibited an extraordinarily high likelihood of containing a nucleotide mixture. Possible explanations for the high mixture rates are that these positions are particularly error-prone or provide a viral fitness advantage.

Metagenomic analysis of herbivorous mammalian viral communities in the Northwest Plateau

BackgroundMammals are potential hosts for many infectious diseases. However, studies on the viral communities of herbivorous mammals in the Northwest Plateau are limited. Here, we studied the viral communities of herbivorous mammals in the Northwest Plateau using virus metagenomic analysis to analyze and compare the viral community composition of seven animal species.ResultsBy library construction and next-generation sequencing, contigs and singlets reads with similar viral sequences were classified into 24 viral families. Analyzed from the perspective of sampling areas, the virus community composition was relatively similar in two areas of Wuwei and Jinchang, Gansu Province. Analyzed from the perspective of seven animal species, the viral reads of seven animal species were mostly ssDNA and dominated by CRESS-DNA viruses. Phylogenetic analysis based on viral marker genes indicated that CRESS-DNA viruses and microviruses have high genetic diversity. In addition to DNA viruses, nodaviruses, pepper mild mottle viruses and picornaviruses were RNA viruses that we performed by phylogenetic analysis. The CRESS-DNA viruses and nodaviruses are believed to infect plants and insects, and microviruses can infect bacteria, identifying that they were likely from the diet of herbivorous mammals. Notably, two picornaviruses were identified from red deer and wild horse, showing that the picornavirus found in red deer had the relatively high similarity with human hepatitis A virus, and the picornavirus carried by wild horse could potentially form a new species within the Picornaviridae family.ConclusionsThis study explored the herbivorous mammalian virus community in the Northwest Plateau and the genetic characteristics of viruses that potentially threaten human health. It reveals the diversity and stability of herbivorous mammalian virus communities in the Northwest Plateau and helps to expand our knowledge of various herbivorous mammalian potentially pathogenic viruses.

High incidence of AZF duplications in clan-structured Iranian populations detected through Y chromosome sequencing read depth analysis

The ampliconic region of the human Y chromosome consists of large duplicated sequences that can undergo non-allelic homologous recombination (NAHR), resulting in structural rearrangements that may cause infertility, especially when they occur in the azoospermia factor b/c (AZFb/c) region. Although AZF duplications have long been neglected due to the technical limitations of STS-based studies that focused mainly on deletions, recent next generation sequencing (NGS) technologies provided evidence for their importance in fertility. In this study, a NGS read depth approach was used to detect AZFb/c rearrangements in 87 Iranians from different ethnic groups. The duplication frequency in Iran proved to be twice as high as in the "1000 Genomes" dataset. Interestingly, most duplications were found in patrilineal ethnic groups, possibly as a consequence of their lower male effective population size which can counteract negative selection. Moreover, we found a large 8.0 Mb duplication, resulting in a fourfold increase in the copy number of AZFc genes, which to our knowledge is the largest duplication ever reported in this region. Overall, our results suggest that it is important to consider not only AZF deletions but also duplications to investigate the causes of male infertility, especially in patrilineal clan-based populations.

Population genomics-guided engineering of phenazine biosynthesis in Pseudomonas chlororaphis

The emergence of next-generation sequencing (NGS) technologies has made it possible to not only sequence entire genomes, but also identify metabolic engineering targets across the pangenome of a microbial population. This study leverages NGS data as well as existing molecular biology and bioinformatics tools to identify and validate genomic signatures for improving phenazine biosynthesis in Pseudomonas chlororaphis. We sequenced a diverse collection of 34 Pseudomonas isolates using short- and long-read sequencing techniques and assembled whole genomes using the NGS reads. In addition, we assayed three industrially relevant phenotypes (phenazine production, biofilm formation, and growth temperature) for these isolates in two different media conditions. We then provided the whole genomes and phenazine production data to a unitig-based microbial genome-wide association study (mGWAS) tool to identify novel genomic signatures responsible for phenazine production in P. chlororaphis. Post-processing of the mGWAS analysis results yielded 330 significant hits influencing the biosynthesis of one or more phenazine compounds. Based on a quantitative metric (called the phenotype score), we elucidated the most influential hits for phenazine production and experimentally validated them in vivo in the most optimal phenazine producing strain. Two genes significantly increased phenazine-1-carboxamide (PCN) production: a histidine transporter (ProY_1), and a putative carboxypeptidase (PS__04251). A putative MarR-family transcriptional regulator decreased PCN titer when overexpressed in a high PCN producing isolate. Overall, this work seeks to demonstrate the utility of a population genomics approach as an effective strategy in enabling the identification of targets for metabolic engineering of bioproduction hosts.

Complete mitochondrial genome of the Galápagos sea lion, Zalophuswollebaeki (Carnivora, Otariidae): paratype specimen confirms separate species status.

The endangered Galápagos sea lion (Zalophuswollebaeki) inhabits the Galápagos Islands off the coast of Ecuador. We present a complete mitochondrial genome (16 465 bp) of a female paratype from the collections of the Natural History Museum Oslo, Norway, assembled from next-generation sequencing reads. It contains all canonical protein-coding, rRNA, tRNA genes, and the D-loop region. Sequence similarity is 99.93% to a previously published conspecific mitogenome sequence and 99.37% to the mitogenome sequence of the sister species Z.californianus. Sequence similarity of the D-loop region of the Z.wollebaeki paratype mitogenome is >99%, while the sequence difference to the Z.californianus sequences exceeds 2.5%. The paratype mitogenome sequence supports the taxonomic status of Z.wollebaeki as a separate species.

PfaSTer: a machine learning-powered serotype caller for Streptococcus pneumoniae genomes.

Streptococcus pneumoniae (pneumococcus) is a leading cause of morbidity and mortality worldwide. Although multi-valent pneumococcal vaccines have curbed the incidence of disease, their introduction has resulted in shifted serotype distributions that must be monitored. Whole genome sequence (WGS) data provide a powerful surveillance tool for tracking isolate serotypes, which can be determined from nucleotide sequence of the capsular polysaccharide biosynthetic operon (cps). Although software exists to predict serotypes from WGS data, most are constrained by requiring high-coverage next-generation sequencing reads. This can present a challenge in respect of accessibility and data sharing. Here we present PfaSTer, a machine learning-based method to identify 65 prevalent serotypes from assembled S. pneumoniae genome sequences. PfaSTer combines dimensionality reduction from k-mer analysis with a Random Forest classifier for rapid serotype prediction. By leveraging the model's built-in statistical framework, PfaSTer determines confidence in its predictions without the need for coverage-based assessments. We then demonstrate the robustness of this method, returning >97 % concordance when compared to biochemical results and other in silico serotyping tools. PfaSTer is open source and available at: https://github.com/pfizer-opensource/pfaster.

IRIDA-ARIES Genomics, a key player in the One Health surveillance of diseases caused by infectious agents in Italy.

Pathogen genomics is transforming surveillance of infectious diseases, deepening our understanding of evolution and diffusion of etiological agents, host-pathogen interactions and antimicrobial resistance. This discipline is playing an important role in the development of One Health Surveillance with public health experts of various disciplines integrating methods applied to pathogen research, monitoring, management and prevention of outbreaks. Especially with the notion that foodborne diseases may not be transmitted by food only, the ARIES Genomics project aimed to deliver an Information System for the collection of genomic and epidemiological data to enable genomics-based surveillance of infectious epidemics, foodborne outbreaks and diseases at the animal-human interface. Keeping in mind that the users of the system comprised persons with expertise in a wide variety of domains, the system was expected to be used with a low learning curve directly by the persons target of the analyses' results, keeping the information exchange chains as short as possible. As a result, the IRIDA-ARIES platform (https://irida.iss.it/) provides an intuitive web-based interface for multisectoral data collection and bioinformatic analyses. In practice, the user creates a sample and uploads the Next-generation sequencing reads, then an analysis pipeline is launched automatically performing a series of typing and clustering operations fueling the information flow. Instances of IRIDA-ARIES host the Italian national surveillance system for infections by Listeria monocytogenes (Lm) and the surveillance system for infections by Shigatoxin-producing Escherichia coli (STEC). As of today, the platform does not provide tools to manage epidemiological investigations but serves as an instrument of aggregation for risk monitoring, capable of triggering alarms on possible critical situations that might go unnoticed otherwise.