UNASSIGNED: Spillover events of Mycoplasma ovipneumoniae have devastating effects on the wild sheep populations. Multilocus sequence typing (MLST) is used to monitor spillover events and the spread of M. ovipneumoniae between the sheep populations. Most studies involving the typing of M. ovipneumoniae have used Sanger sequencing. However, this technology is time-consuming, expensive, and is not well suited to efficient batch sample processing.
UNASSIGNED: Our study aimed to develop and validate an MLST workflow for typing of M. ovipneumoniae using Nanopore Rapid Barcoding sequencing and multiplex polymerase chain reaction (PCR). We compare the workflow with Nanopore Native Barcoding library preparation and Illumina MiSeq amplicon protocols to determine the most accurate and cost-effective method for sequencing multiplex amplicons. A multiplex PCR was optimized for four housekeeping genes of M. ovipneumoniae using archived DNA samples (N = 68) from nasal swabs.
UNASSIGNED: Sequences recovered from Nanopore Rapid Barcoding correctly identified all MLST types with the shortest total workflow time and lowest cost per sample when compared with Nanopore Native Barcoding and Illumina MiSeq methods.
UNASSIGNED: Our proposed workflow is a convenient and effective method for strain typing of M. ovipneumoniae and can be applied to other bacterial MLST schemes. The workflow is suitable for diagnostic settings, where reduced hands-on time, cost, and multiplexing capabilities are important.

Chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq) is a profiling method for protein-DNA interactions that can detect binding locations in vivo, does not require antibodies or fixation, and provides genome-wide coverage at near nucleotide resolution.The core of this method is an MNase fusion of the target protein, which allows it, when triggered by calcium exposure, to cut DNA at its binding sites and to generate small DNA fragments that can be readily separated from the rest of the genome and sequenced.Improvements since the original protocol have increased the ease, lowered the costs, and multiplied the throughput of this method to enable a scale and resolution of experiments not available with traditional methods such as ChIP-seq. This method describes each step from the initial creation and verification of the MNase-tagged yeast strains, over the ChEC MNase activation and small fragment purification procedure to the sequencing library preparation. It also briefly touches on the bioinformatic steps necessary to create meaningful genome-wide binding profiles.

As antimicrobial resistance (AMR) surveillance shifts to genomics, ensuring the quality of whole-genome sequencing (WGS) data produced across laboratories is critical. Participation in genomic proficiency tests (GPTs) not only increases individual laboratories\' WGS capacity but also provides a unique opportunity to improve species-specific thresholds for WGS quality control (QC) by repeated resequencing of distinct isolates. Here, we present the results of the EU Reference Laboratory for Antimicrobial Resistance (EURL-AR) network GPTs of 2021 and 2022, which included 25 EU national reference laboratories (NLRs). A total of 392 genomes from 12 AMR-bacteria were evaluated based on WGS QC metrics. Two percent (n = 9) of the data were excluded, due to contamination, and 11% (n = 41) of the remaining genomes were identified as outliers in at least one QC metric and excluded from computation of the adjusted QC thresholds (AQT). Two QC metric correlation groups were identified through linear regression. Eight percent (n = 28) of the submitted genomes, from 11 laboratories, failed one or more of the AQTs. However, only three laboratories (12%) were identified as underperformers, failing across AQTs for uncorrelated QC metrics in at least two genomes. Finally, new species-specific thresholds for \"N50\" and \"number of contigs > 200 bp\" are presented for guidance in routine laboratory QC. The continued participation of NRLs in GPTs will reveal WGS workflow flaws and improve AMR surveillance data. GPT data will continue to contribute to the development of reliable species-specific thresholds for routine WGS QC, standardizing sequencing data QC and ensure inter- and intranational laboratory comparability.IMPORTANCEIllumina next-generation sequencing is an integral part of antimicrobial resistance (AMR) surveillance and the most widely used whole-genome sequencing (WGS) platform. The high-throughput, relative low-cost, high discriminatory power, and rapid turnaround time of WGS compared to classical biochemical methods means the technology will likely remain a fundamental tool in AMR surveillance and public health. In this study, we present the current level of WGS capacity among national reference laboratories in the EU Reference Laboratory for AMR network, summarizing applied methodology and statistically evaluating the quality of the obtained sequence data. These findings provide the basis for setting new and revised thresholds for quality metrics used in routine WGS, which have previously been arbitrarily defined. In addition, underperforming participants are identified and encouraged to evaluate their workflows to produce reliable results.

Outbreaks are a risk to public health particularly when pathogenic, hypervirulent, and/or multidrug-resistant organisms (MDROs) are involved. In a hospital setting, vulnerable populations such as the immunosuppressed, intensive care patients, and neonates are most at risk. Rapid and accurate outbreak detection is essential to implement effective interventions in clinical areas to control and stop further transmission. Advances in the field of whole genome sequencing (WGS) have resulted in lowered costs, increased capacity, and improved reproducibility of results. WGS now has the potential to revolutionize the investigation and management of outbreaks replacing conventional genotyping and other discrimination systems. Here, we outline specific procedures and protocols to implement WGS into investigation of outbreaks in healthcare settings.

RNA sequencing (RNA-Seq) has emerged as a powerful and versatile tool for the comprehensive analysis of transcriptomes and has been widely used to investigate gene expression, copy number variation, alternative splicing, and novel transcript discovery. This chapter outlines the methodology for conducting short-read RNA-Seq, starting from RNA enrichment to library preparation and sequencing. Throughout the chapter, practical tips and best practices are provided to guide researchers in order to optimize each step of the RNA-Seq workflow. Multiple quality control steps throughout the workflow that are critical to obtain high-quality RNA-Seq data are also discussed.

Tandem duplication (TD) is a major type of structural variations (SVs) that plays an important role in novel gene formation and human diseases. However, TDs are often missed or incorrectly classified as insertions by most modern SV detection methods due to the lack of specialized operation on TD-related mutational signals. Herein, we developed a TD detection module for the Pindel tool, referred to as Pindel-TD, based on a TD-specific pattern growth approach. Pindel-TD is capable of detecting TDs with a wide size range at single nucleotide resolution. Using simulated and real read data from HG002, we demonstrated that Pindel-TD outperforms other leading methods in terms of precision, recall, F1-score, and robustness. Furthermore, by applying Pindel-TD to data generated from the K562 cancer cell line, we identified a TD located at the seventh exon of SAGE1, providing an explanation for its high expression. Pindel-TD is available for non-commercial use at https://github.com/xjtu-omics/pindel.

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Extrachromosomal circular DNA (eccDNA) is currently attracting considerable attention from researchers due to its significant impact on tumor biogenesis. High-throughput sequencing (HTS) methods for eccDNA identification are continually evolving. However, an efficient pipeline for the integrative and comprehensive analysis of eccDNA obtained from HTS data is still lacking. Here, we introduce eccDNA-pipe, an accessible software package that offers a user-friendly pipeline for conducting eccDNA analysis starting from raw sequencing data. This dataset includes data from various sequencing techniques such as whole-genome sequencing (WGS), Circle-seq and Circulome-seq, obtained through short-read sequencing or long-read sequencing. eccDNA-pipe presents a comprehensive solution for both upstream and downstream analysis, encompassing quality control and eccDNA identification in upstream analysis and downstream tasks such as eccDNA length distribution analysis, differential analysis of genes enriched with eccDNA and visualization of eccDNA structures. Notably, eccDNA-pipe automatically generates high-quality publication-ready plots. In summary, eccDNA-pipe provides a comprehensive and user-friendly pipeline for customized analysis of eccDNA research.

We present the closed genome sequence of the Clostridium botulinum BT-22100019 strain isolated from the stool specimen of an infant diagnosed with botulism. With 4.33-Mb genome size and 28.0% G + C content, the bont/B1 gene encoded for botulinum neurotoxin serotype B was found on a 262 kb plasmid arranged in a ha+ orfx - cluster.

When resequencing animal genomes, some short reads cannot be mapped to the reference genome and are usually discarded. In this study, unmapped reads from 302 German Black Pied cattle were analyzed to identify potential pathogenic DNA. These unmapped reads were assembled and blasted against NCBI\'s database to identify bacterial and viral sequences. The results provided evidence for the presence of pathogens. We found sequences of Bovine parvovirus 3 and Mycoplasma species. These findings emphasize the information content of unmapped reads for gaining insight into bacterial and viral infections, which is important for veterinarians and epidemiologists.