Raw Reads Research Articles

Comparative genomic analysis and characterization of novel high-quality draft genomes from the coal metagenome.

Coal, a sedimentary rock harbours a complex microbial community that plays a significant role in its formation and characteristics. However, coal metagenome sequencing and studies were less, limiting our understanding of this complex ecosystem. This study aimed to reconstruct high-quality metagenome-assembled genomes (MAGs) from the coal sample collected in the Neyveli mine to explore the unrevealed diversity of the coal microbiome. Using Illumina sequencing, we obtained high-quality raw reads in FASTQ format. Subsequently, de novo assembly and binning with metaWRAP software facilitated the reconstruction of coal MAGs. Quality assessment using CheckM identified 10 High-Quality MAGs (HQ MAGs), 7 medium-quality MAGs (MQ MAGs), and 6 low-quality MAGs (LQ MAGs). Further analysis using GTDB-Tk revealed four HQ MAGs as known species like Dermacoccus abyssi, Sphingomonas aquatilis, Acinetobacter baumannii, and Burkholderia cenocepacia. The remaining six HQ MAGs were classified as Comamonas, Arthrobacter, Noviherbaspirillum, Acidovorax, Oxalicibacterium, and Bordetella and designated as novel genomes by the validation of digital DNA-DNA hybridization (dDDH). Phylogenetic analysis and further pangenome analysis across the phylogenetic groups revealed a similar pattern with a high proportion of cloud genes. We further analysed the functional potential of these MAGs and closely related genomes using COG. The comparative functional genomics revealed that novel genomes are highly versatile, potentially reflecting adaptations to the coal environment. BlastKOALA was used to conduct a detailed analysis of the metabolic pathways associated with the MAGs. This study highlights the comparative genomic analysis of novel coal genomes with their closely related genomes to understand the evolutionary relationships and functional properties.

Comprehensive genome analysis and variant detection at scale using DRAGEN.

Research and medical genomics require comprehensive, scalable methods for the discovery of novel disease targets, evolutionary drivers and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size or location. Here we present DRAGEN, which uses multigenome mapping with pangenome references, hardware acceleration and machine learning-based variant detection to provide insights into individual genomes, with ~30 min of computation time from raw reads to variant detection. DRAGEN outperforms current state-of-the-art methods in speed and accuracy across all variant types (single-nucleotide variations, insertions or deletions, short tandem repeats, structural variations and copy number variations) and incorporates specialized methods for analysis of medically relevant genes. We demonstrate the performance of DRAGEN across 3,202 whole-genome sequencing datasets by generating fully genotyped multisample variant call format files and demonstrate its scalability, accuracy and innovation to further advance the integration of comprehensive genomics. Overall, DRAGEN marks a major milestone in sequencing data analysis and will provide insights across various diseases, including Mendelian and rare diseases, with a highly comprehensive and scalable platform.

First Report of metaplexis yellow mottle-associated virus Infecting Metaplexis japonica (Thunb.) Makino in Shandong, China.

Metaplexis japonica (Thunb.) Makino, commonly known as rough potato, has a wide distribution in China, Japan, Korea, and adjacent Russia. In China, M. japonica is a traditional herbal medicinal plant, which is also cultivated as a vegetable (Shi et al. 2020; Wei et al. 2019). In July 2023, leaves of M. japonica plants growing near a soybean field in Qingdao, Shandong province, exhibited leaf crinkling, mosaic and distorting symptoms of probable virus infection (Supplementary Figure 1). The disease incidence in a 50 m2 area was approximately 40%. To identify the suspected viral etiological agents, symptomatic leaves from 10 M. japonica plants were collected and pooled to perform small RNA deep sequencing (sRNA-Seq). TransZol Up Total RNA Extraction Kit (TransGen Biotech, Beijing, China) was used to extract total RNA. Small RNA library construction and high-throughput sequencing (HTS) were performed on Illumina NovaSeq platform by Genepioneer (Nanjing, China) (Li et al. 2024). A total of 17,384,311 raw reads were obtained. Redundant reads were removed by cutadapt software (version 1.18) to obtain 11,580,876 clean reads with 18 to 26 nucleotide (nt) sizes. The clean reads were assembled using velvet software (version 1.1.07). A total of forty-six small contigs from 42 to 283 nt were identified, with 85 to 100% nucleotide sequence identities, respectively, to metaplexis yellow mottle-associated virus (MeYMaV, genus Caulimovirus, family Caulimoviridae, accession numbers: NC_077108.1). Finally, 1,355,955 reads (11.71% mapped ratio of total reads, cover 56.7% over the MeYMaV genome) were mapped to the genome of MeYMaV by bwa software (version 0.7.17-r1188). To confirm the sRNA-Seq results, PCR was performed with specific primers MeYMaV-N-F/MeYMaV-N-R (5'-TGGTATCAGAGCCTAGTTAA-3'/5'-GGAGTTGGTAATGTATTACC-3') and MeYMaV-C-F/MeYMaV-C-R (5'-AATGGAACGGCTGTTAGTAT3'/TTAATTTCTAGCCCTTGGCTACTTAC). Both the primer pairs were designed using GenBank accession numbers: NC_077108.1 (Yang et al. 2021) to obtain the N and C terminals genome fragments of 10 MeYMaV plants. Two amplicons approximately in 4000-, and 3900-bp sizes were amplified (Supplementary Figure 2), sequenced (tsingke, Beijing, China) and aligned to obtain 7,742-nt complete MeYMaV genome sequence (Accession no. PP892524). BLASTn analysis revealed 90.16% and 92.18% sequence identity, respectively, with the MeYMaV isolate LM-Cau-A (NC_077108.1) based on complete genome and coat protein sequences, respectively. Previously, cucumber mosaic virus and MeYMaV were reported in M. japonica from Jiangsu and Liaoning provinces in China, respectively (Yang et al. 2018; 2021). To our knowledge, this is the first natural infection report of MeYMaV in M. japonica in Shandong, China. The natural occurrence of MeYMaV is not only affects the quality of M. japonica, but also poses a potential threat to surrounding crops. This study enriches information on the disease distribution of MeYMaV and will be helpful for disease management.

GCI: A continuity inspector for complete genome assembly.

Recent advances in long-read sequencing technologies have significantly facilitated the production of high-quality genome assembly. The telomere-to-telomere (T2T) gapless assembly has become the new golden standard of genome assembly efforts. Several recent efforts have claimed to produce T2T level reference genomes. However, a universal standard is still missing to qualify a genome assembly to be at T2T standard. Traditional genome assembly assessment metrics (N50 and its derivatives) have no capacity in differentiating between nearly T2T assembly and the truly T2T assembly in continuity either globally and locally. Additionally, these metrics are independent of raw reads, making them inflated easily by artificial operations. Therefore, a gaplessness evaluation tool at single nucleotide resolution to reflect true completeness is urgently needed in the era of complete genomes. Here, we present a tool called Genome Continuity Inspector (GCI), designed to assess genome assembly continuity at single-base resolution, and evaluate how close an assembly is to the T2T level. GCI utilizes multiple aligners to map long reads from various sequencing platforms back to the assembly. By incorporating curated mapping coverage of high-confidence read alignments, GCI identifies potential assembly issues. Meanwhile, it provides GCI scores that quantify overall assembly continuity on the whole genome or chromosome scales. The open-source GCI code is freely available on Github (https://github.com/yeeus/GCI) under the MIT license. Supplementary data are available at Bioinformatics online.

De novo transcriptome assembly and differential gene expression analysis in different developmental stages of Agriotes sputator (click beetle)

Wireworms, the larva of click beetle (Agriotes species), are one of the most destructive pests of horticultural crops in North America, responsible for considerable economic losses in Canada. Agriotes sputator (A. sputator) species is a predominant wireworm pest attacking potato fields in Eastern Canada. However, no information about its genome-wide gene expression profile, specifically for the genes involved with development is available to date. Therefore, we generated the transcriptome profile of A. sputator during five developmental stages, including the three larval stages and adult male and female click beetle. Out of 714.7 million raw reads, de novo assembly generated 564,561 transcripts. The data were subjected to differential expression analysis using DESeq2, gene ontology, annotation, and pathway analyses. A total of 34,709 differentially expressed genes (DEGs) were significant (log2 fold change > 2, padj < 0.05) across the developmental stages. Functional analysis of DEGs identified development signaling, metabolism, transport, cellular mechanisms, and drug metabolism (cytochrome p450) pathways. This study provides comprehensive sequence resources and potential gene differences at different developmental stages of A. sputator. These findings will represent a major step towards developing sustainable methods to control this widely distributed pest in agricultural fields.

Sequence-matching adapter trimmers generate consistent quality and assembly metrics for Illumina sequencing of RNA viruses

Trimming adapters and low-quality bases from next-generation sequencing (NGS) data is crucial for optimal analysis. We evaluated six trimming programs, implementing five different algorithms, for their effectiveness in trimming adapters and improving quality, contig assembly, and single-nucleotide polymorphism (SNP) quality and concordance for poliovirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and norovirus paired data sequenced on Illumina iSeq and MiSeq platforms. Trimmomatic and BBDuk effectively removed adapters from all datasets, unlike FastP, AdapterRemoval, SeqPurge, and Skewer. All trimmers improved read quality (Q ≥ 30, 87.8 − 96.1%) compared to raw reads (83.6 − 93.2%). Trimmers implementing traditional sequence-matching (Trimmomatic and AdapterRemoval) and overlapping algorithm (FastP) retained the highest-quality reads. While all trimmers improved the maximum contig length and genome coverage for iSeq and MiSeq viral assemblies, BBDuk-trimmed reads assembled the shortest contigs. SNP concordance was consistently high (> 97.7 − 100%) across trimmers. However, BBDuk-trimmed reads had the lowest quality SNPs. Overall, the two adapter trimmers that utilized the traditional sequence-matching algorithm performed consistently across the viral datasets analyzed. Our findings guide software selection and inform future versatile trimmer development for viral genome analysis.

Kallisto, bustools and kb-python for quantifying bulk, single-cell and single-nucleus RNA-seq.

The term 'RNA-seq' refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, single cells or single nuclei. The kallisto, bustools and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples or both. Additionally, these tools allow gene expression values to be classified as originating from nascent RNA species or mature RNA species, making this workflow amenable to both cell-based and nucleus-based assays. This protocol describes in detail how to use kallisto and bustools in conjunction with a wrapper, kb-python, to preprocess RNA-seq data. Execution of this protocol requires basic familiarity with a command line environment. With this protocol, quantification of a moderately sized RNA-seq dataset can be completed within minutes.

What Quality Suffices for Nanopore Metabarcoding? Reconsidering Methodology and Ectomycorrhizae in Decaying Fagus sylvatica Bark as Case Study.

Nanopore raw read accuracy has improved to over 99%, making it a potential tool for metabarcoding. For broad adoption, guidelines on quality filtering are needed to ensure reliable taxonomic unit recovery. This study aims to provide those guidelines for a fungal metabarcoding context and to apply them to a case study of ectomycorrhizae in the decaying bark of Fagus sylvatica. We introduce the eNano pipeline to test two standard metabarcoding approaches: (1) Reference-based mapping leveraging UNITE's species hypothesis system (SH approach); (2) Constructing 98% OTUs (OTU approach). Our results demonstrate that both approaches are effective with Nanopore data. When using a reference database, we recommend strict mapping criteria rather than Phred-based filtering. Leveraging the SH-system further enhances reproducibility and facilitates cross-study communication. For the 98% OTUs, filtering reads at ≥Q25 is recommended. Our case study reveals that the decay gradient is a primary determinant of community composition and that specific mycorrhizal fungi colonize decaying bark. Complementing our metabarcoding results with root tip morphotypification, we identify Laccaria amethystina and Tomentella sublilacina as key ectomycorrhizae of saplings on decaying logs. These findings demonstrate that Nanopore sequencing can provide valuable ecological insights and support its broader use in fungal metabarcoding as read quality continues to improve.

First Report of Paprika mild mottle virus Infecting pepper (Capsicum annuum L.) in China.

Paprika mild mottle virus (PaMMV), a tobamovirus from the Virgaviridae family, has been reported to infect pepper (Capsicum annuum L.) in the Netherlands (García-Luque et al., 1993), Japan (Hamada et al., 2003), Bulgaria (Ruíz del Pino et al., 2003), and Israel (Luria et al., 2018). Pepper has become the most widely planted vegetable and the most heavily consumed spicy condiment, with a large planting area (>21,000 km2) in China (Zou et al., 2021). However, the crop's productivity is limited by viral diseases. In August 2021, a survey of viral diseases was conducted across five pepper-growing regions in Linyi, Shandong Province, China, revealed that 5% to 10% of plants in most fields exhibited symptoms such as stunting, leaf narrowing, chlorosis, and crinkling of leaf tissue (Fig. S1-a). Subsequently, seven symptomatic samples (Fig. S1-b) were collected from a plot (118° 29' E, 34° 65' N) where thin-skinned peppers were grown. All samples tested positive in a Western blot assay using a polyclonal antibody for tobacco mosaic virus (TMV), indicating the presence of a tobamovirus (Fig. S1-c). To identify the virus, total RNAs were extracted from 10 different symptomatic pepper plant samples, using the RNeasy Plant Mini Kit (QIAGEN, Hilden, Germany) and combined into a single sample in equal amounts (100 ng/μL each). RNA-Seq was performed on this mixture using the Illumina NovaSeq 6000 (Illumina, San Diego, USA). Raw reads (6.92G) in fastq format were processed with in-house perl scripts to yield clean reads (6.68G), which were assembled into 780 contigs (mean length: 2036 bp) using Trinity software (v2.6.6). These contigs were then analysed using the NCBI BLASTX program (http://www.ncbi.nlm.nih.gov/blast) against the viral RefSeq database. The results demonstrated that the contigs exhibited an average genome coverage of 40.16%. Notably, one unique contig (6453 bp) was mapped to the PaMMV genome (reference sequence KX187305.1) with 98.34% identity. To verify the RNA-Seq result, a PaMMV-specific primer pair (forward: 5'-GAGTTCATAGAGGCAGTACC-3'; reverse: 5'-CTTCGATTTAAGTGGAGGGAT-3') was designed for amplifying an 800-nt fragment of the PaMMV coat protein (CP) gene by RT-PCR. The 800-nt fragment was successfully amplified from all the symptomatic samples (Fig. S1-d). Sequenced RT-PCR products (GenBank No. OR365081.1) showed 99.75% nucleotide identity with PaMMV isolates (OQ198318.1, China, goat) according to BLAST analysis. Mechanical transmission of PaMMV from three infected pepper plants collected in Linyi to healthy pepper plants confirmed pathogenicity. Three pepper cultivars (trade name: Qiemen, Tianyu, Haonong11) were tested and showed varying symptoms post-inoculation (Fig. S1-e). All cultivars were confirmed in the lab to be PMMoV-sensitive and exhibited significant viral disease symptoms after PMMoV inoculation (data not shown). Each variety was inoculated with at least 3 seedlings from different field-collected virulence sources. Qiemen (cultivar: sweet pepper) exhibited severe symptoms with necrotic spots, Tianyu (cultivar: Chaotian pepper) had mild leaf wrinkling, and Haonong11 (cultivar: Pickled pepper) showed yellow mottle and leaf shrinking. All tested seedlings were positive for PaMMV by RT-PCR (Fig. S1-f). To our knowledge, this is the first report of PaMMV infecting pepper in China, highlighting the need for vigilant monitoring to protect the chili industry and prevent the virus's spread to other crops.

Transcriptome Profile and Gene Expression During Different Ovarian Maturation Stages of Macrobrachium rosenbergii (De Man, 1879).

Macrobrachium rosenbergii, or giant river prawn, is the most economically crucial cultured freshwater crustacean. A predominant challenge in developing crustacean aquaculture is reproduction management, particularly ovary maturation, where identifying regulative mechanisms at the molecular level is critical. Ovary is the primary tissue for studying gene and protein expressions involved in crustacean growth and reproduction. Despite significant interest in M. rosenbergii, its gene discovery has been at a relatively small scale compared to other genera. In this study, comprehensive transcriptomic sequencing data for different maturation stages of the ovary of M. rosenbergii were observed. The 20 female M. rosenbergii samples evaluated were categorised into four maturation stages, 1 to 4. A total of 817,793,14, 841,670,70, 914,248,78 and 878,085,88 raw reads were obtained from stages 1, 2, 3 and 4, respectively. The assembled unique sequences (unigenes) post-clustering (n = 98013) was 131,093,546 bp with an average size of 1,338 bp. The BLASTX unigene search against National Centre for Biotechnology Information (NCBI), non-redundant (NR), nucleotide sequence (NT), Kyoto Encyclopaedia of Genes and Genomes Orthology (KO), Swiss-Prot, Protein Family (PFAM), Gene Ontology (GO), and euKaryotic Orthologous Groups (KOG) databases yielded 27,680 (28.24%), 7,449 (7.59%), 13,026 (13.29%), 22,606 (23.06%), 29,907 (30.51%), 30,025 (30.63%) and 14,368 (14.65%) significant matches, respectively, totalling to 37,338 annotated unigenes (38.09%). The differentially expressed genes (DEG) analysis conducted in this study led to identifying cyclin B, insulin receptor (IR), oestrogen sulfotransferase (ESULT) and vitellogenin (Vg), which are critical in ovarian maturation. Nevertheless, some M. rosenbergii ovarian maturation-related genes, such as small ubiquitin-like modifier (SUMO)-activating enzyme subunit 1, E3 ubiquitin-protein ligase RNF25, and neuroparsin, were first identified in this study. The data obtained in the present study could considerably contribute to understanding the gene expression and genome structure in M. rosenbergii ovaries throughout its developmental stage.

DDBJ update in 2024: the DDBJ Group Cloud service for sharing pre-publication data.

The Bioinformation and DNA Data Bank of Japan Center (DDBJ Center, https://www.ddbj.nig.ac.jp) provides public databases that cover a wide range of fields in life sciences. As a founding member of the International Nucleotide Sequence Database Collaboration (INSDC), the DDBJ Center accepts and distributes nucleotide sequence data ranging from raw reads to assembled and annotated sequences with the National Center for Biotechnology Information and the European Bioinformatics Institute. Besides INSDC databases, the DDBJ Center provides databases for functional genomics (Genomic Expression Archive), metabolomics (MetaboBank), human genetic variations (TogoVar-repository) and human genetic and phenotypic data (Japanese Genotype-phenotype Archive). These database systems have been built on the National Institute of Genetics supercomputer, which is also a platform for the DDBJ Group Cloud (DGC) services for sharing and analysis of pre-publication data among research groups. This paper reports recent updates on the databases and the services of the DDBJ Center, highlighting the DGC service.

Transformer-based representation learning and multiple-instance learning for cancer diagnosis exclusively from raw sequencing fragments of bisulfite-treated plasmacell-free DNA.

Early cancer diagnosis from bisulfite-treated cell-free DNA (cfDNA) fragments requires tedious data analytical procedures. Here, we present a deep-learning-based approach for early cancer interception and diagnosis (DECIDIA) that can achieve accurate cancer diagnosis exclusively from bisulfite-treated cfDNA sequencing fragments. DECIDIA relies on transformer-based representation learning of DNA fragments and weakly supervised multiple-instance learning for classification. We systematically evaluate the performance of DECIDIA for cancer diagnosis and cancer type prediction on a curated dataset of 5389 samples that consist of colorectal cancer (CRC; n = 1574), hepatocellular cell carcinoma (HCC; n = 1181), lung cancer (n = 654), and non-cancer control (n = 1980). DECIDIA achieved an area under the receiver operating curve (AUROC) of 0.980 (95% CI, 0.976-0.984) in 10-fold cross-validation settings on the CRC dataset by differentiating cancer patients from cancer-free controls, outperforming benchmarked methods that are based on methylation intensities. Noticeably, DECIDIA achieved an AUROC of 0.910 (95% CI, 0.896-0.924) on the externally independent HCC testing set in distinguishing HCC patients from cancer-free controls, although there was no HCC data used in model development. In the settings of cancer-type classification, we observed that DECIDIA achieved a micro-average AUROC of 0.963 (95% CI, 0.960-0.966) and an overall accuracy of 82.8% (95% CI, 81.8-83.9). In addition, we distilled four sequence signatures from the raw sequencing reads that exhibited differential patterns in cancer versus control and among different cancer types. Our approach represents a new paradigm towards eliminating the tedious data analytical procedures for liquid biopsy that uses bisulfite-treated cfDNA methylome.

Deciphering the multi- partite mitochondrial genome of Crataegus pinnatifida: insights into the evolution and genetics of cultivated Hawthorn

Flowering plant (angiosperm) mitochondrial genomes are remarkably dynamic in their structures. We present the complete mitochondrial genome of hawthorn (Crataegus pinnatifida Bunge), a shrub that bears fruit and is celebrated for its extensive medicinal history. We successfully assembled the hawthorn mitogenome utilizing the PacBio long-read sequencing technique, which yielded 799,862 reads, and the Illumina novaseq6000 sequencing platform, which producing 6.6 million raw paired reads. The C. pinnatifida mitochondria sequences encompassed a total length of 440,295 bp with a GC content of 45.42%. The genome annotates 54 genes, including 34 that encode proteins, 17 that encode tRNA, and three genes for rRNA. A fascinating interplay was observed between the chloroplast and mitochondrial genomes, which share 17 homologous sequences sequences that rotal 1,933 bp. A total of 134 SSRs, 22 tandem repeats and 42 dispersed repeats were identified in the mitogenome. Four conformations of C. pinnatifida mitochondria sequences recombination were verified through PCR experiments and Sanger sequencing, and C. pinnatifida mitogenome is more likely to be assembled into three circular-mapping chromosomes. All the RNA editing sites that were identified C-U edits, which predominantly occurred at the first and second positions of the codons. Phylogenetic and collinearity analyses identified the evolutionary trajectory of C. pinnatifida, which reinforced the genetic identity of the hawthorn section. This unveiling of the unique multi-partite structure of the hawthorn mitogenome offers a foundational reference for future study into the evolution and genetics of C. pinnatifida.

Analysis of Differential Gene Expression under Acute Lead or Mercury Exposure in Larval Zebrafish Using RNA-Seq.

This study was first conducted to investigate the effects of acute lead exposure on developing zebrafish embryos or larvae from 24 to 120 h post-fertilization (hpf). Our data showed that treatment with 50-200 μM lead significantly affected larval survivability and morphology compared to the respective control. Second, we chose 120 hpf larvae treated with 12.5 μM lead for RNA sequencing due to its exposure level being sufficient to produce toxic effects with minimum death and lead bioaccumulation in developing zebrafish. A total of 137.45 million raw reads were obtained, and more than 86% of clean data were mapped to the zebrafish reference genome. Differential expression profiles generated 116 up- and 34 down-regulated genes upon lead exposure. The most enriched GO terms for representative DEGs were ion transport and lipid metabolism. Third, a comparison with the dataset of mercury-regulated gene expression identified 94 genes (64 up-regulated and 30 down-regulated) for exposure specific to lead, as well as 422 genes (338 up-regulated and 84 down-regulated) for exposure specific to mercury. In addition, 56 genes were co-regulated by micromolar mercury and lead treatment, and the expression of thirteen genes, including mt2, ctssb.1, prdx1, txn, sqrdl, tmprss13a, socs3a, trpv6, abcb6a, gsr, hbz, fads2, and zgc:92590 were validated by qRT-PCR. These genes were mainly associated with metal ion binding, proteolysis, antioxidant activity, signal transduction, calcium ion or oxygen transport, the fatty acid biosynthetic process, and protein metabolism. Taken together, these findings help better understand the genome-wide responses of developing zebrafish to lead or mercury and provide potential biomarkers for acute exposure to toxic metals.

High accuracy meets high throughput for near full-length 16S ribosomal RNA amplicon sequencing on the Nanopore platform.

Small subunit (SSU) ribosomal RNA (rRNA) gene amplicon sequencing is a foundational method in microbial ecology. Currently, short-read platforms are commonly employed for high-throughput applications of SSU rRNA amplicon sequencing, but at the cost of poor taxonomic classification due to limited fragment lengths. The Oxford Nanopore Technologies (ONT) platform can sequence full-length SSU rRNA genes, but its lower raw-read accuracy has so-far limited accurate taxonomic classification and de novo feature generation. Here, we present a sequencing workflow, termed ssUMI, that combines unique molecular identifier (UMI)-based error correction with newer (R10.4+) ONT chemistry and sample barcoding to enable high throughput near full-length SSU rRNA (e.g. 16S rRNA) amplicon sequencing. The ssUMI workflow generated near full-length 16S rRNA consensus sequences with 99.99% mean accuracy using a minimum subread coverage of 3×, surpassing the accuracy of Illumina short reads. The consensus sequences generated with ssUMI were used to produce error-free de novo sequence features with no false positives with two microbial community standards. In contrast, Nanopore raw reads produced erroneous de novo sequence features, indicating that UMI-based error correction is currently necessary for high-accuracy microbial profiling with R10.4+ ONT sequencing chemistries. We showcase the cost-competitive scalability of the ssUMI workflow by sequencing 87 time-series wastewater samples and 27 human gut samples, obtaining quantitative ecological insights that were missed by short-read amplicon sequencing. ssUMI, therefore, enables accurate and low-cost full-length 16S rRNA amplicon sequencing on Nanopore, improving accessibility to high-resolution microbiome science.

Exploring uncatalogued genetic variation in antimicrobial resistance gene families in Escherichia coli: an observational analysis

Antimicrobial resistance (AMR) in Escherichia coli is a global problem associated with substantial morbidity and mortality. AMR-associated genes are typically annotated based on similarity to variants in a curated reference database, with the implicit assumption that uncatalogued genetic variation within these is phenotypically unimportant. In this study, we evaluated the performance of the AMRFinder tool and, subsequently, the potential for discovering new AMR-associated gene families and characterising variation within existing ones to improve genotype-to-susceptibility phenotype predictions in Ecoli. In this cross-sectional study of international genome sequence data, we assembled a global dataset of 9001 Ecoli sequences from five publicly available data collections predominantly deriving from human bloodstream infections from: Norway, Oxfordshire (UK), Thailand, the UK, and Sweden. 8555of these sequences had linked antibiotic susceptibility data. Raw reads were assembled using Shovill and AMR genes (relevant to amoxicillin-clavulanic acid, ampicillin, ceftriaxone, ciprofloxacin, gentamicin, piperacillin-tazobactam, and trimethoprim) extracted using the National Center for Biotechnology Information AMRFinder tool (using both default and strict [100%] coverage and identity filters). We assessed the predictive value of the presence of these genes for predicting resistance or susceptibility against US Food and Drug Administration thresholds for major and very major errors. Mash was used to calculate the similarity between extracted genes using Jaccard distances. We empirically reclustered extracted gene sequences into AMR-associated gene families (≥70% match) and antibiotic-resistance genes (ARGs; 100% match) and categorised these according to their frequency in the dataset. Accumulation curves were simulated and correlations between gene frequency in the Oxfordshire and other datasets calculated using the Spearman coefficient. Firth regression was used to model the association between the presence of blaTEM-1 variants and amoxicillin-clavulanic acid or piperacillin-tazobactam resistance, adjusted for the presence of other relevant ARGs. The performance of the AMRFinder database for genotype-to-phenotype predictions using strict 100% identity and coverage thresholds did not meet US Food and Drug Administration thresholds for any of the seven antibiotics evaluated. Relaxing filters to default settings improved sensitivity with a specificity cost. For all antibiotics, most explainable resistance was associated with the presence of a small number of genes. There was a proportion of resistance that could not be explained by known ARGs; this ranged from 75·1% for amoxicillin-clavulanic acid to 3·4% for ciprofloxacin. Only 18 199 (51·5%) of the 35 343ARGs detected had a 100% identity and coverage match in the AMRFinder database. After empirically reclassifying genes at 100% nucleotide sequence identity, we identified 1042unique ARGs, of which 126 (12·1%) were present ten times or more, 313 (30·0%) were present between two and nine times, and 603 (57·9%) were present only once. Simulated accumulation curves revealed that discovery of new (100% match) ARGs present more than once in the dataset plateaued relatively quickly, whereas new singleton ARGs were discovered even after many thousands of isolates had been included. We identified a strong correlation (Spearman coefficient 0·76 [95% CI 0·73-0·80], p<0·0001) between the number of times an ARG was observed in Oxfordshire and the number of times it was seen internationally, with ARGs that were observed six times in Oxfordshire always being found elsewhere. Finally, using the example of blaTEM-1, we showed that uncatalogued variation, including synonymous variation, is associated with potentially important phenotypic differences; for example, two common, uncatalogued blaTEM-1 alleles with only synonymous mutations compared with the known reference were associated with reduced resistance to amoxicillin-clavulanic acid (adjusted odds ratio 0·58 [95% CI 0·35-0·95], p=0·031) and piperacillin-tazobactam (0·50 [95% CI 0·29-0·82], p=0·005). We highlight substantial uncatalogued genetic variation with respect to known ARGs, although a relatively small proportion of these alleles are repeatedly observed in a large international dataset suggesting strong selection pressures. The current approach of using fuzzy matching for ARG detection, ignoring the unknown effects of uncatalogued variation, is unlikely to be acceptable for future clinical deployment. The association of synonymous mutations with potentially important phenotypic differences suggests that relying solely on amino acid-based gene detection to predict resistance is unlikely to be sufficient. Finally, the inability to explain all resistance using existing knowledge highlights the importance of new target gene discovery. National Institute for Health and Care Research, Wellcome, and UK Medical Research Council.

Whole genome sequencing reveals antibiotic resistance pattern and virulence factors in Klebsiella quasipneumoniae subsp. similipneumoniae from Hospital wastewater in South-West, Nigeria.

Klebsiella quasipneumoniae is a distinct species from K. pneumoniae, even though it is sometimes mistaken phenotypically for the latter in clinical situations. K. quasipneumoniae is a pathogen and this study aims at understanding the genomic antibiotic resistance and virulence characteristics of Klebsiella quasipneumoniae subsp. similipneumoniae (B105 strain) isolated from tertiary hospital wastewater and the potential risks associated with its environmental spread.The Illumina platform was used for whole-genome sequencing (WGS), the generated raw reads (de novo) was assembled using RAPT NCBI, while other standardized bioinformatics tools were utilized to validate and examine the landscape of the genome’s antibiotic resistance and virulence factors. The K. quasipneumoniae subsp. similipneumoniae (B105 strain), belonged to sequence type 1422 and was resistant to ampicillin, amoxicillin-clavulanic acid, ceftazidime, cefepime, meropenem, tetracycline, but susceptible to gentamicin. The annotated genome acknowledged the presence of blaOKP-B-2, ompK 36, fosA5, oqxAB, virulence genes responsible for capsule formation, lipopolysaccharide, iron uptake aerobactin (iutA), salmochelins (iroE, iroN), enterobactin siderophore, efllux pump (acrA, acrB) adherence, (mrkC, mrkD, and fimD) and two plasmids replicon IncFIB(K) and IncR. The study resonates the inadequacy of conventional microbiological identification methods to distinguish K. pneumoniae and K. quasipneumoniae and at the same time heightens the importance of using a genomic platform to extol the identity of K. quasipneumoniae subsp. similipneumoniae strain. Furthermore, the peculiarities of the acquired antimicrobial resistance and virulence genes, in this strain, are a potential risk to the environment.

Identification of non-model mammal species using the MinION DNA sequencer from Oxford Nanopore.

The Neotropics harbors the largest species richness of the planet; however, even in well-studied groups, there are potentially hundreds of species that lack a formal description, and likewise, many already described taxa are difficult to identify using morphology. Specifically in small mammals, complex morphological diagnoses have been facilitated by the use of molecular data, particularly from mitochondrial sequences, to obtain accurate species identifications. Obtaining mitochondrial markers implies the use of PCR and specific primers, which are largely absent for non-model organisms. Oxford Nanopore Technologies (ONT) is a new alternative for sequencing the entire mitochondrial genome without the need for specific primers. Only a limited number of studies have employed exclusively ONT long-reads to assemble mitochondrial genomes, and few studies have yet evaluated the usefulness of such reads in multiple non-model organisms. We implemented fieldwork to collect small mammals, including rodents, bats, and marsupials, in five localities in the northern extreme of the Cordillera Central of Colombia. DNA samples were sequenced using the MinION device and Flongle flow cells. Shotgun-sequenced data was used to reconstruct the mitochondrial genome of all the samples. In parallel, using a customized computational pipeline, species-level identifications were obtained based on sequencing raw reads (Whole Genome Sequencing). ONT-based identifications were corroborated using traditional morphological characters and phylogenetic analyses. A total of 24 individuals from 18 species were collected, morphologically identified, and deposited in the biological collection of Universidad EAFIT. Our different computational pipelines were able to reconstruct mitochondrial genomes from exclusively ONT reads. We obtained three new mitochondrial genomes and eight new molecular mitochondrial sequences for six species. Our species identification pipeline was able to obtain accurate species identifications for up to 75% of the individuals in as little as 5 s. Finally, our phylogenetic analyses corroborated the identifications from our automated species identification pipeline and revealed important contributions to the knowledge of the diversity of Neotropical small mammals. This study was able to evaluate different pipelines to reconstruct mitochondrial genomes from non-model organisms, using exclusively ONT reads, benchmarking these protocols on a multi-species dataset. The proposed methodology can be applied by non-expert taxonomists and has the potential to be implemented in real-time, without the need to euthanize the organisms and under field conditions. Therefore, it stands as a relevant tool to help increase the available data for non-model organisms, and the rate at which researchers can characterize life specially in highly biodiverse places as the Neotropics.

Scalable and unsupervised discovery from raw sequencing reads using SPLASH2.

We introduce SPLASH2, a fast, scalable implementation of SPLASH based on an efficient k-mer counting approach for regulated sequence variation detection in massive datasets from a wide range of sequencing technologies and biological contexts. We demonstrate biological discovery by SPLASH2 in single-cell RNA sequencing (RNA-seq) data and in bulk RNA-seq data from the Cancer Cell Line Encyclopedia, including unannotated alternative splicing in cancer transcriptomes and sensitive detection of circular RNA.

Root Endophytic Microorganisms Contribute to the Attribute of Full-Year Shooting in Woody Bamboo Cephalostachyum pingbianense.

Cephalostachyum pingbianense (Hsueh & Y.M. Yang ex Yi et al.) D.Z. Li & H.Q. Yang is unique among bamboo species for its ability to produce bamboo shoots in all seasons under natural conditions. Apart from the physiological mechanism, information regarding the effects of endophytic microorganisms on this full-year shooting characteristic is limited. We hypothesize that root endophytic microorganisms will have a positive impact on the full-year bamboo shooting characteristic of C. pingbianense by increasing the availability or supply of nutrients. To identify the seasonal variations in the root endophytic bacterial and fungal communities of C. pingbianense, and to assess their correlation with bamboo shoot productivity, the roots of C. pingbianense were selected as research materials, and the 16S rRNA and ITS rDNA genes of root endophytic microorganisms were sequenced using the Illumina platform. Following this sequencing, raw sequencing reads were processed, and OTUs were annotated. Alpha and beta diversity, microbial composition, and functional predictions were analyzed, with correlations to bamboo shoot numbers assessed. The results showed that seasonal changes significantly affected the community diversity and structure of root endophytic microbes of C. pingbianense. Bacterial communities in root samples from all seasons contained more nitrogen-fixing microorganisms, with members of the Burkholderiales and Rhizobiales predominating. The relative abundances of ectomycorrhizal and arbuscular mycorrhizal fungi in the autumn sample were significantly higher than in other seasons. Correlation analysis revealed that the bamboo shoot productivity was significantly and positively correlated with bacterial functions of nitrogen fixation, arsenate detoxification, and ureolysis, as well as with symbiotrophic fungi, ectomycorrhizal fungi, and arbuscular mycorrhizal fungi. At the genus level, the bacterial genus Herbaspirillum and the fungal genera Russula, unclassified_f_Acaulosporaceae, and unclassified_f_Glomeraceae were found to have a significant positive correlation with bamboo shoot number. Our study provides an ecological perspective for understanding the highly productive attribute of C. pingbianense and offers new insights into the forest management of woody bamboos.