Benchmarking of long-read correction methods

Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates

BACKGROUND

Oxford Nanopore provides high throughput sequencing platforms able to reconstruct complete bacterial genomes with 99.95% accuracy. However, even small levels of error can obscure the phylogenetic relationships between closely related isolates. Polishing tools have been developed to correct these errors, but it is uncertain if they obtain the accuracy needed for the high-resolution source tracking of foodborne illness outbreaks.

RESULTS

We tested 132 combinations of assembly and short- and long-read polishing tools to assess their accuracy for reconstructing the genome sequences of 15 highly similar Salmonella enterica serovar Newport isolates from a 2020 onion outbreak. While long-read polishing alone improved accuracy, near perfect accuracy (99.9999% accuracy or ~ 5 nucleotide errors across the 4.8 Mbp genome, excluding low confidence regions) was only obtained by pipelines that combined both long- and short-read polishing tools. Notably, medaka was a more accurate and efficient long-read polisher than Racon. Among short-read polishers, NextPolish showed the highest accuracy, but Pilon, Polypolish, and POLCA performed similarly. Among the 5 best performing pipelines, polishing with medaka followed by NextPolish was the most common combination. Importantly, the order of polishing tools mattered i.e., using less accurate tools after more accurate ones introduced errors. Indels in homopolymers and repetitive regions, where the short reads could not be uniquely mapped, remained the most challenging errors to correct.

CONCLUSIONS

Short reads are still needed to correct errors in nanopore sequenced assemblies to obtain the accuracy required for source tracking investigations. Our granular assessment of the performance of the polishing pipelines allowed us to suggest best practices for tool users and areas for improvement for tool developers.

Sequencing and characterizing short tandem repeats in the human genome

Short tandem repeats (STRs) are highly polymorphic sequences throughout the human genome that are composed of repeated copies of a 1-6-bp motif. Over 1 million variable STR loci are known, some of which regulate gene expression and influence complex traits, such as height. Moreover, variants in at least 60 STR loci cause genetic disorders, including Huntington disease and fragile X syndrome. Accurately identifying and genotyping STR variants is challenging, in particular mapping short reads to repetitive regions and inferring expanded repeat lengths. Recent advances in sequencing technology and computational tools for STR genotyping from sequencing data promise to help overcome this challenge and solve genetically unresolved cases and the 'missing heritability' of polygenic traits. Here, we compare STR genotyping methods, analytical tools and their applications to understand the effect of STR variation on health and disease. We identify emergent opportunities to refine genotyping and quality-control approaches as well as to integrate STRs into variant-calling workflows and large cohort analyses.

SWIGH-SCORE: A translational light-weight approach in computational detection of rearranged immunoglobulin heavy chain to be used in monoclonal lymphoproliferative disorders

We present a lightweight tool for clonotyping and measurable residual disease (MRD) assessment in monoclonal lymphoproliferative disorders. It is a translational method that enables computational detection of rearranged immunoglobulin heavy chain gene sequences.•The swigh-score clonotyping tool emphasizes parallelization and applicability across sequencing platforms.•The algorithm is based on an adaptation of the Smith-Waterman algorithm for local alignment of reads generated by 2nd and 3rd generation of sequencers.For method validation, we demonstrate the targeted sequences of immunoglobulin heavy chain genes from diagnostic bone marrow using serial dilutions of CD138+ plasma cells from a patient with multiple myeloma. Sequencing libraries from diagnostic samples were prepared for the three sequencing platforms, Ion S5 (Thermo Fisher Scientific), MiSeq (Illumina), and MinION (Oxford Nanopore), using the LymphoTrack assay. Basic quality filtering was performed, and a Smith-Waterman-based swigh-score algorithm was developed in shell and C for clonotyping and MRD assessment using FASTQ data files. Performance is demonstrated across the three different sequencing platforms.

Pannonibacter anstelovis sp. nov. Isolated from Two Cases of Bloodstream Infections in Paediatric Patients

This study describes two cases of bacteraemia sustained by a new putative Pannonibacter species isolated at the U.O.C. of Microbiology and Virology of the Policlinico of Bari (Bari, Italy) from the blood cultures of two patients admitted to the Paediatric Oncohaematology Unit. Pannonibacter spp. is an environmental Gram-negative bacterium not commonly associated with nosocomial infections. Species identification was performed using Sanger sequencing of the 16S rRNA gene and Whole-Genome Sequencing (WGS) for both strains. Genomic analyses for the two isolates, BLAST similarity search, and phylogeny for the 16S rDNA sequences lead to an assignment to the species Pannonibacter phragmitetus. However, by performing ANIb, ANIm, tetranucleotide correlation, and DNA-DNA digital hybridization, analyses of the two draft genomes showed that they were very different from those of the species P. phragmitetus. MALDI-TOF analysis, assessment of antimicrobial susceptibility by E-test method, and Analytical Profile Index (API) tests were also performed. This result highlights how environmental bacterial species can easily adapt to the human host and, especially in nosocomial environments, also gain pathogenic potential through antimicrobial resistance.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Re-analysis of an outbreak of Shiga toxin-producing Escherichia coli O157:H7 associated with raw drinking milk using Nanopore sequencing

The aim of this study was to compare Illumina and Oxford Nanopore Technology (ONT) sequencing data to quantify genetic variation to assess within-outbreak strain relatedness and characterise microevolutionary events in the accessory genomes of a cluster of 23 genetically and epidemiologically linked isolates related to an outbreak of Shiga toxin-producing Escherichia coli O157:H7 caused by the consumption of raw drinking milk. There were seven discrepant variants called between the two technologies, five were false-negative or false-positive variants in the Illumina data and two were false-negative calls in ONT data. After masking horizontally acquired sequences such as prophages, analysis of both short and long-read sequences revealed the 20 isolates linked to the outbreak in 2017 had a maximum SNP distance of one SNP between each other, and a maximum of five SNPs when including three additional strains identified in 2019. Analysis of the ONT data revealed a 47 kbp deletion event in a terminal compound prophage within one sample relative to the remaining samples, and a 0.65 Mbp large chromosomal rearrangement (inversion), within one sample relative to the remaining samples. Furthermore, we detected two bacteriophages encoding the highly pathogenic Shiga toxin (Stx) subtype, Stx2a. One was typical of Stx2a-phage in this sub-lineage (Ic), the other was atypical and inserted into a site usually occupied by Stx2c-encoding phage. Finally, we observed an increase in the size of the pO157 IncFIB plasmid (1.6 kbp) in isolates from 2019 compared to those from 2017, due to the duplication of insertion elements within the plasmids from the more recently isolated strains. The ability to characterize the accessory genome in this way is the first step to understanding the significance of these microevolutionary events and their impact on the genome plasticity and virulence between strains of this zoonotic, foodborne pathogen.

Flexiplex: a versatile demultiplexer and search tool for omics data

MOTIVATION

The process of analyzing high throughput sequencing data often requires the identification and extraction of specific target sequences. This could include tasks, such as identifying cellular barcodes and UMIs in single-cell data, and specific genetic variants for genotyping. However, existing tools, which perform these functions are often task-specific, such as only demultiplexing barcodes for a dedicated type of experiment, or are not tolerant to noise in the sequencing data.

RESULTS

To overcome these limitations, we developed Flexiplex, a versatile and fast sequence searching and demultiplexing tool for omics data, which is based on the Levenshtein distance and thus allows imperfect matches. We demonstrate Flexiplex's application on three use cases, identifying cell-line-specific sequences in Illumina short-read single-cell data, and discovering and demultiplexing cellular barcodes from noisy long-read single-cell RNA-seq data. We show that Flexiplex achieves an excellent balance of accuracy and computational efficiency compared to leading task-specific tools.

AVAILABILITY AND IMPLEMENTATION

Flexiplex is available at https://davidsongroup.github.io/flexiplex/.

The potential of 3rd-generation nanopore sequencing for B-cell clonotyping in lymphoproliferative disorders

Lymphoid malignancies are characterized by clonal cell expansion, often identifiable by unique immunoglobulin rearrangements. Heavy (IGH) and light-chain gene usage offers diagnostic insights and enables sensitive residual disease detection via next-generation sequencing. With its adaptable throughput and variable read lengths, Oxford Nanopore thirdgeneration sequencing now holds promise for clonotyping. This study analyzed CD138+ plasma-cell DNA from eight multiple myeloma patients, comparing clonotyping performance between Nanopore sequencing, Illumina MiSeq, and Ion Torrent S5. We demonstrated clonotype consistency across platforms through Smith-Waterman local alignment of nanopore reads. The mean clonal percentage of IGH V and J gene usage in the CD138+ cells was 69% for Nanopore, 67% for S5, and 76% for MiSeq. When aligned with known clonotypes, clonal cells averaged a 91% similarity, exceeding 85%. In summary, Nanopore sequencing, with its capacity for generating millions of high-quality reads, proves effective for detecting clonal IGH rearrangements. This versatile platform offers the potential for measuring residual disease down to a sensitivity level of 10-6 at a lower cost, marking a significant advancement in clonotyping techniques.

Host DNA depletion methods and genome-centric metagenomics of bovine hindmilk microbiome

Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Three Rounds of Read Correction Significantly Improve Eukaryotic Protein Detection in ONT Reads

BACKGROUND

Eukaryotes' whole-genome sequencing is crucial for species identification, gene detection, and protein annotation. Oxford Nanopore Technology (ONT) is an affordable and rapid platform for sequencing eukaryotes; however, the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryote genome completeness, gene detection and protein annotation.

METHODS

Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively.

RESULTS

Genome completeness was dependent on the assembly method rather than on the read correction tool; however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation.

CONCLUSION

We show that three rounds of read correction significantly affect gene detection and protein annotation, which are dependent on assembly quality in preference to assembly completeness.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning

BACKGROUND

The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses.

FINDINGS

We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals.

CONCLUSIONS

IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

Whole-genome sequence of the Cooley spruce gall adelgid, Adelges cooleyi (Hemiptera: Sternorrhyncha: Adelgidae)

The adelgids (Adelgidae) are a small family of sap-feeding insects, which, together with true aphids (Aphididae) and phylloxerans (Phylloxeridae), make up the infraorder Aphidomorpha. Some adelgid species are highly destructive to forest ecosystems such as Adelges tsugae, Adelges piceae, Adelges laricis, Pineus pini, and Pineus boerneri. Despite this, there are no high-quality genomic resources for adelgids, hindering advanced genomic analyses within Adelgidae and among Aphidomorpha. Here, we used PacBio continuous long-read and Illumina RNA-sequencing to construct a high-quality draft genome assembly for the Cooley spruce gall adelgid, Adelges cooleyi (Gillette), a gall-forming species endemic to North America. The assembled genome is 270.2 Mb in total size and has scaffold and contig N50 statistics of 14.87 and 7.18 Mb, respectively. There are 24,967 predicted coding sequences, and the assembly completeness is estimated at 98.1 and 99.6% with core BUSCO gene sets of Arthropoda and Hemiptera, respectively. Phylogenomic analysis using the A. cooleyi genome, 3 publicly available adelgid transcriptomes, 4 phylloxera transcriptomes, the Daktulosphaira vitifoliae (grape phylloxera) genome, 4 aphid genomes, and 2 outgroup coccoid genomes fully resolves adelgids and phylloxerans as sister taxa. The mitochondrial genome is 24 kb, among the largest in insects sampled to date, with 39.4% composed of noncoding regions. This genome assembly is currently the only genome-scale, annotated assembly for adelgids and will be a valuable resource for understanding the ecology and evolution of Aphidomorpha.

Identification and quantification of small exon-containing isoforms in long-read RNA sequencing data

Small exons are pervasive in transcriptomes across organisms, and their quantification in RNA isoforms is crucial for understanding gene functions. Although long-read RNA-seq based on Oxford Nanopore Technologies (ONT) offers the advantage of covering transcripts in full length, its lower base accuracy poses challenges for identifying individual exons, particularly microexons (≤ 30 nucleotides). Here, we systematically assess small exons quantification in synthetic and human ONT RNA-seq datasets. We demonstrate that reads containing small exons are often not properly aligned, affecting the quantification of relevant transcripts. Thus, we develop a local-realignment method for misaligned exons (MisER), which remaps reads with misaligned exons to the transcript references. Using synthetic and simulated datasets, we demonstrate the high sensitivity and specificity of MisER for the quantification of transcripts containing small exons. Moreover, MisER enabled us to identify small exons with a higher percent spliced-in index (PSI) in neural, particularly neural-regulated microexons, when comparing 14 neural to 16 non-neural tissues in humans. Our work introduces an improved quantification method for long-read RNA-seq and especially facilitates studies using ONT long-reads to elucidate the regulation of genes involving small exons.

Genomic stability of self-inactivating rabies

Transsynaptic viral vectors provide means to gain genetic access to neurons based on synaptic connectivity and are essential tools for the dissection of neural circuit function. Among them, the retrograde monosynaptic ΔG-Rabies has been widely used in neuroscience research. A recently developed engineered version of the ΔG-Rabies, the non-toxic self-inactivating (SiR) virus, allows the long term genetic manipulation of neural circuits. However, the high mutational rate of the rabies virus poses a risk that mutations targeting the key genetic regulatory element in the SiR genome could emerge and revert it to a canonical ΔG-Rabies. Such revertant mutations have recently been identified in a SiR batch. To address the origin, incidence and relevance of these mutations, we investigated the genomic stability of SiR in vitro and in vivo. We found that "revertant" mutations are rare and accumulate only when SiR is extensively amplified in vitro, particularly in suboptimal production cell lines that have insufficient levels of TEV protease activity. Moreover, we confirmed that SiR-CRE, unlike canonical ΔG-Rab-CRE or revertant-SiR-CRE, is non-toxic and that revertant mutations do not emerge in vivo during long-term experiments.

Mabs, a suite of tools for gene-informed genome assembly

BACKGROUND

Despite constantly improving genome sequencing methods, error-free eukaryotic genome assembly has not yet been achieved. Among other kinds of problems of eukaryotic genome assembly are so-called "haplotypic duplications", which may manifest themselves as cases of alleles being mistakenly assembled as paralogues. Haplotypic duplications are dangerous because they create illusions of gene family expansions and, thus, may lead scientists to incorrect conclusions about genome evolution and functioning.

RESULTS

Here, I present Mabs, a suite of tools that serve as parameter optimizers of the popular genome assemblers Hifiasm and Flye. By optimizing the parameters of Hifiasm and Flye, Mabs tries to create genome assemblies with the genes assembled as accurately as possible. Tests on 6 eukaryotic genomes showed that in 6 out of 6 cases, Mabs created assemblies with more accurately assembled genes than those generated by Hifiasm and Flye when they were run with default parameters. When assemblies of Mabs, Hifiasm and Flye were postprocessed by a popular tool for haplotypic duplication removal, Purge_dups, genes were better assembled by Mabs in 5 out of 6 cases.

CONCLUSIONS

Mabs is useful for making high-quality genome assemblies. It is available at https://github.com/shelkmike/Mabs.

Nanopore Cas9-targeted sequencing enables accurate and simultaneous identification of transgene integration sites, their structure and epigenetic status in recombinant Chinese hamster ovary cells

The integration of a transgene expression construct into the host genome is the initial step for the generation of recombinant cell lines used for biopharmaceutical production. The stability and level of recombinant gene expression in Chinese hamster ovary (CHO) can be correlated to the copy number, its integration site as well as the epigenetic context of the transgene vector. Also, undesired integration events, such as concatemers, truncated, and inverted vector repeats, are impacting the stability of recombinant cell lines. Thus, to characterize cell clones and to isolate the most promising candidates, it is crucial to obtain information on the site of integration, the structure of integrated sequence and the epigenetic status. Current sequencing techniques allow to gather this information separately but do not offer a comprehensive and simultaneous resolution. In this study, we present a fast and robust nanopore Cas9-targeted sequencing (nCats) pipeline to identify integration sites, the composition of the integrated sequence as well as its DNA methylation status in CHO cells that can be obtained simultaneously from the same sequencing run. A Cas9-enrichment step during library preparation enables targeted and directional nanopore sequencing with up to 724× median on-target coverage and up to 153 kb long reads. The data generated by nCats provides sensitive, detailed, and correct information on the transgene integration sites and the expression vector structure, which could only be partly produced by traditional Targeted Locus Amplification-seq data. Moreover, with nCats the DNA methylation status can be analyzed from the same raw data without prior DNA amplification.

Hepatitis B virus serum RNA transcript isoform composition and proportion in chronic hepatitis B patients by nanopore long-read sequencing

Introduction

Serum hepatitis B virus (HBV) RNA is a promising new biomarker to manage and predict clinical outcomes of chronic hepatitis B (CHB) infection. However, the HBV serum transcriptome within encapsidated particles, which is the biomarker analyte measured in serum, remains poorly characterized. This study aimed to evaluate serum HBV RNA transcript composition and proportionality by PCR-cDNA nanopore sequencing of samples from CHB patients having varied HBV genotype (gt, A to F) and HBeAg status.

Methods

Longitudinal specimens from 3 individuals during and following pregnancy (approximately 7 months between time points) were also investigated. HBV RNA extracted from 16 serum samples obtained from 13 patients (73.3% female, 84.6% Asian) was sequenced and serum HBV RNA isoform detection and quantification were performed using three bioinformatic workflows; FLAIR, RATTLE, and a GraphMap-based workflow within the Galaxy application. A spike-in RNA variant (SIRV) control mix was used to assess run quality and coverage. The proportionality of transcript isoforms was based on total HBV reads determined by each workflow.

Results

All chosen isoform detection workflows showed high agreement in transcript proportionality and composition for most samples. HBV pregenomic RNA (pgRNA) was the most frequently observed transcript isoform (93.8% of patient samples), while other detected transcripts included pgRNA spliced variants, 3' truncated variants and HBx mRNA, depending on the isoform detection method. Spliced variants of pgRNA were primarily observed in HBV gtB, C, E, or F-infected patients, with the Sp1 spliced variant detected most frequently. Twelve other pgRNA spliced variant transcripts were identified, including 3 previously unidentified transcripts, although spliced isoform identification was very dependent on the workflow used to analyze sequence data. Longitudinal sampling among pregnant and post-partum antiviral-treated individuals showed increasing proportions of 3' truncated pgRNA variants over time.

Conclusions

This study demonstrated long-read sequencing as a promising tool for the characterization of the serum HBV transcriptome. However, further studies are needed to better understand how serum HBV RNA isoform type and proportion are linked to CHB disease progression and antiviral treatment response.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology, especially by enabling the comprehensive identification and quantification of full length mRNA isoforms. However, inherently high error rates make the analysis of long-read sequencing data challenging. While these error rates have been characterized for sequence and splice site identification, it is still unclear how accurately LRS reads represent transcript start and end sites. Here, we systematically assess the variability and accuracy of mRNA terminal ends identified by LRS reads across multiple sequencing platforms. We find substantial inconsistencies in both the start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. To address this challenge, we introduce an approach to condition reads based on empirically derived terminal ends and identified a subset of reads that are more likely to represent full-length transcripts. Our approach can improve transcriptome analyses by enhancing the fidelity of transcript terminal end identification, but may result in lower power to quantify genes or discover novel isoforms. Thus, it is necessary to be cautious when selecting sequencing approaches and/or interpreting data from long-read RNA sequencing.

Nanopore long-read next-generation sequencing for detection of mitochondrial DNA large-scale deletions

Primary mitochondrial diseases are progressive genetic disorders affecting multiple organs and characterized by mitochondrial dysfunction. These disorders can be caused by mutations in nuclear genes coding proteins with mitochondrial localization or by genetic defects in the mitochondrial genome (mtDNA). The latter include point pathogenic variants and large-scale deletions/rearrangements. MtDNA molecules with the wild type or a variant sequence can exist together in a single cell, a condition known as mtDNA heteroplasmy. MtDNA single point mutations are typically detected by means of Next-Generation Sequencing (NGS) based on short reads which, however, are limited for the identification of structural mtDNA alterations. Recently, new NGS technologies based on long reads have been released, allowing to obtain sequences of several kilobases in length; this approach is suitable for detection of structural alterations affecting the mitochondrial genome. In the present work we illustrate the optimization of two sequencing protocols based on long-read Oxford Nanopore Technology to detect mtDNA structural alterations. This approach presents strong advantages in the analysis of mtDNA compared to both short-read NGS and traditional techniques, potentially becoming the method of choice for genetic studies on mtDNA.

Accurate profiling of full-length Fv in highly homologous antibody libraries using UMI tagged short reads

Deep parallel sequencing (NGS) is a viable tool for monitoring scFv and Fab library dynamics in many antibody engineering high-throughput screening efforts. Although very useful, the commonly used Illumina NGS platform cannot handle the entire sequence of scFv or Fab in a single read, usually focusing on specific CDRs or resorting to sequencing VH and VL variable domains separately, thus limiting its utility in comprehensive monitoring of selection dynamics. Here we present a simple and robust method for deep sequencing repertoires of full length scFv, Fab and Fv antibody sequences. This process utilizes standard molecular procedures and unique molecular identifiers (UMI) to pair separately sequenced VH and VL. We show that UMI assisted VH-VL matching allows for a comprehensive and highly accurate mapping of full length Fv clonal dynamics in large highly homologous antibody libraries, as well as identification of rare variants. In addition to its utility in synthetic antibody discovery processes, our method can be instrumental in generating large datasets for machine learning (ML) applications, which in the field of antibody engineering has been hampered by conspicuous paucity of large scale full length Fv data.

Technological and computational approaches to detect somatic mosaicism in epilepsy

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

Direct Nanopore Sequencing of Human Cytomegalovirus Genomes from High-Viral-Load Clinical Samples

Nanopore sequencing is becoming increasingly commonplace in clinical settings, particularly for diagnostic assessments and outbreak investigations, due to its portability, low cost, and ability to operate in near real-time. Although high sequencing error rates initially hampered the wider implementation of this technology, improvements have been made continually with each iteration of the sequencing hardware and base-calling software. Here, we assess the feasibility of using nanopore sequencing to determine the complete genomes of human cytomegalovirus (HCMV) in high-viral-load clinical samples without viral DNA enrichment, PCR amplification, or prior knowledge of the sequences. We utilised a hybrid bioinformatic approach that involved assembling the reads de novo, improving the consensus sequence by aligning reads to the best-matching genome from a collated set of published sequences, and polishing the improved consensus sequence. The final genomes from a urine sample and a lung sample, the former with an HCMV to human DNA load approximately 50 times greater than the latter, achieved 99.97 and 99.93% identity, respectively, to the benchmark genomes obtained independently by Illumina sequencing. Thus, we demonstrated that nanopore sequencing is capable of determining HCMV genomes directly from high-viral-load clinical samples with a high accuracy.

Linear time complexity de novo long read genome assembly with GoldRush

Current state-of-the-art de novo long read genome assemblers follow the Overlap-Layout-Consensus paradigm. While read-to-read overlap - its most costly step - was improved in modern long read genome assemblers, these tools still often require excessive RAM when assembling a typical human dataset. Our work departs from this paradigm, foregoing all-vs-all sequence alignments in favor of a dynamic data structure implemented in GoldRush, a de novo long read genome assembly algorithm with linear time complexity. We tested GoldRush on Oxford Nanopore Technologies long sequencing read datasets with different base error profiles sourced from three human cell lines, rice, and tomato. Here, we show that GoldRush achieves assembly scaffold NGA50 lengths of 18.3-22.2, 0.3 and 2.6 Mbp, for the genomes of human, rice, and tomato, respectively, and assembles each genome within a day, using at most 54.5 GB of random-access memory, demonstrating the scalability of our genome assembly paradigm and its implementation.

Navigating bottlenecks and trade-offs in genomic data analysis

Genome sequencing and analysis allow researchers to decode the functional information hidden in DNA sequences as well as to study cell to cell variation within a cell population. Traditionally, the primary bottleneck in genomic analysis pipelines has been the sequencing itself, which has been much more expensive than the computational analyses that follow. However, an important consequence of the continued drive to expand the throughput of sequencing platforms at lower cost is that often the analytical pipelines are struggling to keep up with the sheer amount of raw data produced. Computational cost and efficiency have thus become of ever increasing importance. Recent methodological advances, such as data sketching, accelerators and domain-specific libraries/languages, promise to address these modern computational challenges. However, despite being more efficient, these innovations come with a new set of trade-offs, both expected, such as accuracy versus memory and expense versus time, and more subtle, including the human expertise needed to use non-standard programming interfaces and set up complex infrastructure. In this Review, we discuss how to navigate these new methodological advances and their trade-offs.

Rapid Lineage Assignment of Severe Acute Respiratory Syndrome Coronavirus 2 Cases through Automated Library Preparation, Sequencing, and Bioinformatic Analysis

The coronavirus disease 2019 (COVID-19) pandemic has provided a stage to illustrate that there is considerable value in obtaining rapid, whole-genome-based information about pathogens. This article describes the utility of a commercially available, automated severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) library preparation, genome sequencing, and a bioinformatics analysis pipeline to provide rapid, near-real-time SARS-CoV-2 variant description. This study evaluated the turnaround time, accuracy, and other quality-related parameters obtained from commercially available automated sequencing instrumentation, from analysis of continuous clinical samples obtained from January 1, 2021, to October 6, 2021. This analysis included a base-by-base assessment of sequencing accuracy at every position in the SARS-CoV-2 chromosome using two commercially available methods. Mean turnaround time, from the receipt of a specimen for SARS-CoV-2 testing to the availability of the results, with lineage assignment, was <3 days. Accuracy of sequencing by one method was 100%, although certain sites on the genome were found repeatedly to have been sequenced with varying degrees of read error rate.

Deciphering integration loci of CHO manufacturing cell lines using long read nanopore sequencing

Despite advances in genetic characterization of Chinese hamster ovary (CHO) cell lines regarding identification of integration sites using next generation sequencing, e.g. targeted locus amplification sequencing (TLA-seq), the concatemer structure of the integrated vectors remains elusive. Here, the entire integration locus of two CHO manufacturing cell lines was reconstructed combining CRISPR/Cas9 target enrichment, nanopore sequencing and the Canu de novo assembly pipeline. An IgG producing CHO cell line integrated 3 vector copies, which were near full-length and contained all relevant vector elements such as transgenes and their promoters on each of the vector copies. In contrast, a second CHO cell line producing a bivalent bispecific antibody integrated 7 highly fragmented vector copies in different orientations leading to head-to-head and tail-to-tail fusions. The size of the vector fragments ranged from 3.0 to 11.4 kbp each carrying 1-3 transgenes. The breakpoints of the genome-vector and vector-vector junctions were validated using Sanger sequencing and Southern blotting. A comparison to TLA-seq data confirmed the genomic breakpoints, but most of the breakpoints of the vector-vector fusions were missed by TLA-seq. For the first time, the complete transgene locus of CHO manufacturing cell lines could be deciphered. Strikingly, the application of the nanopore long-read sequencing technology led to novel insights into the complexity of genomic transgene integrations of CHO manufacturing cell lines generated via random integration.

Evaluation of five commercial DNA extraction kits using Salmonella as a model for implementation of rapid Nanopore sequencing in routine diagnostic laboratories

Oxford Nanopore long-read sequencing offers advantages over Illumina short reads for the identification and characterization of bacterial pathogens for outbreak detection and surveillance activities within a diagnostic public health laboratory context. Compared to Illumina, Nanopore is more cost-effective for small batches, has a lower capital cost and has a faster turnaround time, in addition to the ability to assemble complete bacterial genomes. The quantity and quality of DNA required for Nanopore sequencing are greater than for Illumina, and the DNA extraction methods recommended for obtaining high-molecular-weight DNA are different from those typically used in diagnostic laboratories. Using a Salmonella isolate with a previously closed PacBio genome as a model Enterobacteriaceae organism, we evaluated the quantity, quality and fragmentation of five commercial DNA extraction kits. Nanopore sequencing performance was evaluated for the top three methods: Qiagen EZ1 DNA Tissue, Qiagen DNeasy Blood and Tissue, and a modified, in-house version of the MasterPure Complete DNA and RNA purification. To evaluate the effect of post-extraction DNA purification methods, we subjected extracted DNA from the three selected extraction methods to purification by AMPure beads or ethanol precipitation and compared these outputs with untreated DNA as a control. All methods are suitable for routine whole-genome sequencing (WGS), since all 60 replicates had very high genome recovery rates, with ≥98 % of the reference genome covered by mapped Nanopore reads. For 85 % of the replicates, assembly was able to produce a complete, circular chromosome using either Flye or Canu. In most cases, it is recommended to move directly from extraction to sequencing, as untreated DNA had the highest rates of genome closure regardless of extraction method. Using our evaluation criteria, the Qiagen DNeasy Blood and Tissue kit was found to be the best overall method due to its low cost, ability to scale from single tubes to 96-well plates, and high consistency in yield and sequencing performance.

A draft chromosome-scale genome assembly of a commercial sugarcane

Sugarcane accounts for a large portion of the worlds sugar production. Modern commercial cultivars are complex hybrids of S. officinarum, S. spontaneum, and several other Saccharum species, resulting in an auto-allopolyploid with 8-12 copies of each chromosome. The current genome assembly gold standard is to generate a long read assembly followed by chromatin conformation capture sequencing to scaffold. We used the PacBio RSII and chromatin conformation capture sequencing to sequence and assemble the genome of a South East Asian commercial sugarcane cultivar, known as Khon Kaen 3. The Khon Kaen 3 genome assembled into 104,477 contigs totalling 7 Gb, which scaffolded into 56 pseudochromosomes containing 5.2 Gb of sequence. Genome annotation produced 242,406 genes from 30,927 orthogroups. Aligning the Khon Kaen 3 genome sequence to S. officinarum and S. spontaneum revealed a high level of apparent recombination, indicating a chimeric assembly. This assembly error is explained by high nucleotide identity between S. officinarum and S. spontaneum, where 91.8% of S. spontaneum aligns to S. officinarum at 94% identity. Thus, the subgenomes of commercial sugarcane are so similar that using short reads to correct long PacBio reads produced chimeric long reads. Future attempts to sequence sugarcane must take this information into account.

Mapping-friendly sequence reductions: Going beyond homopolymer compression

Sequencing errors continue to pose algorithmic challenges to methods working with sequencing data. One of the simplest and most prevalent techniques for ameliorating the detrimental effects of homopolymer expansion/contraction errors present in long reads is homopolymer compression. It collapses runs of repeated nucleotides, to remove some sequencing errors and improve mapping sensitivity. Though our intuitive understanding justifies why homopolymer compression works, it in no way implies that it is the best transformation that can be done. In this paper, we explore if there are transformations that can be applied in the same pre-processing manner as homopolymer compression that would achieve better alignment sensitivity. We introduce a more general framework than homopolymer compression, called mapping-friendly sequence reductions. We transform the reference and the reads using these reductions and then apply an alignment algorithm. We demonstrate that some mapping-friendly sequence reductions lead to improved mapping accuracy, outperforming homopolymer compression.

•

Mapping-friendly sequence reductions (MSRs) are functions that transform DNA sequences

•

They are a generalization of the concept of homopolymer compression

•

We show that some well-chosen MSRs enable more accurate long-read mapping

Parameterized syncmer schemes improve long-read mapping

Motivation

Sequencing long reads presents novel challenges to mapping. One such challenge is low sequence similarity between the reads and the reference, due to high sequencing error and mutation rates. This occurs, e.g., in a cancer tumor, or due to differences between strains of viruses or bacteria. A key idea in mapping algorithms is to sketch sequences with their minimizers. Recently, syncmers were introduced as an alternative sketching method that is more robust to mutations and sequencing errors.

Results

We introduce parameterized syncmer schemes (PSS), a generalization of syncmers, and provide a theoretical analysis for multi-parameter schemes. By combining PSS with downsampling or minimizers we can achieve any desired compression and window guarantee. We implemented the use of PSS in the popular minimap2 and Winnowmap2 mappers. In tests on simulated and real long-read data from a variety of genomes, the PSS-based algorithms, with scheme parameters selected on the basis of our theoretical analysis, reduced unmapped reads by 20-60% at high compression while usually using less memory. The advantage was more pronounced at low sequence identity. At sequence identity of 75% and medium compression, PSS-minimap had only 37% as many unmapped reads, and 8% fewer of the reads that did map were incorrectly mapped. Even at lower compression and error rates, PSS-based mapping mapped more reads than the original minimizer-based mappers as well as mappers using the original syncmer schemes. We conclude that using PSS can improve mapping of long reads in a wide range of settings.

Popular long-read mappers use minimizers, the minimal hashed k-mers from overlapping windows, as alignment seeds. Recent work showed that syncmers, which select a fixed set of k-mers as seeds, are more likely to be conserved under errors or mutations than minimizers, making them potentially useful for mapping error-prone long reads. We introduce a framework for creating syncmers, that we call parameterized syncmer schemes, which generalize those introduced so far, and provide a theoretical analysis of their properties. We implemented parameterized syncmer schemes in the minimap2 and Winnowmap2 long-read mappers. Using parameters selected on the basis of our theoretical analysis we demonstrate improved mapping performance, with fewer unmapped and incorrectly mapped reads on a variety of simulated and real datasets. The improvements are consistent across a broad range of compression rates and sequence identities, with the most significant improvements for lower sequence identity (high error or mutation rates) and high compression.

The Application of Metagenomics to Study Microbial Communities and Develop Desirable Traits in Fermented Foods

The microbial communities present within fermented foods are diverse and dynamic, producing a variety of metabolites responsible for the fermentation processes, imparting characteristic organoleptic qualities and health-promoting traits, and maintaining microbiological safety of fermented foods. In this context, it is crucial to study these microbial communities to characterise fermented foods and the production processes involved. High Throughput Sequencing (HTS)-based methods such as metagenomics enable microbial community studies through amplicon and shotgun sequencing approaches. As the field constantly develops, sequencing technologies are becoming more accessible, affordable and accurate with a further shift from short read to long read sequencing being observed. Metagenomics is enjoying wide-spread application in fermented food studies and in recent years is also being employed in concert with synthetic biology techniques to help tackle problems with the large amounts of waste generated in the food sector. This review presents an introduction to current sequencing technologies and the benefits of their application in fermented foods.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

The third international hackathon for applying insights into large-scale genomic composition to use cases in a wide range of organisms

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.

QuasiSeq: profiling viral quasispecies via self-tuning spectral clustering with PacBio long sequencing reads

MOTIVATION

The existence of quasispecies in the viral population causes difficulties for disease prevention and treatment. High-throughput sequencing provides opportunity to determine rare quasispecies and long sequencing reads covering full genomes reduce quasispecies determination to a clustering problem. The challenge is high similarity of quasispecies and high error rate of long sequencing reads.

RESULTS

We developed QuasiSeq using a novel signature-based self-tuning clustering method, SigClust, to profile viral mixtures with high accuracy and sensitivity. QuasiSeq can correctly identify quasispecies even using low-quality sequencing reads (accuracy <80%) and produce quasispecies sequences with high accuracy (≥99.55%). Using high-quality circular consensus sequencing reads, QuasiSeq can produce quasispecies sequences with 100% accuracy. QuasiSeq has higher sensitivity and specificity than similar published software. Moreover, the requirement of the computational resource can be controlled by the size of the signature, which makes it possible to handle big sequencing data for rare quasispecies discovery. Furthermore, parallel computation is implemented to process the clusters and further reduce the runtime. Finally, we developed a web interface for the QuasiSeq workflow with simple parameter settings based on the quality of sequencing data, making it easy to use for users without advanced data science skills.

AVAILABILITY AND IMPLEMENTATION

QuasiSeq is open source and freely available at https://github.com/LHRI-Bioinformatics/QuasiSeq. The current release (v1.0.0) is archived and available at https://zenodo.org/badge/latestdoi/340494542.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Strategies for sample labelling and library preparation in DNA metabarcoding studies

Metabarcoding of DNA extracted from environmental or bulk specimen samples is increasingly used to profile biota in basic and applied biodiversity research because of its targeted nature that allows sequencing of genetic markers from many samples in parallel. To achieve this, PCR amplification is carried out with primers designed to target a taxonomically informative marker within a taxonomic group, and sample-specific nucleotide identifiers are added to the amplicons prior to sequencing. The latter enables assignment of the sequences back to the samples they originated from. Nucleotide identifiers can be added during the metabarcoding PCR and during "library preparation", that is, when amplicons are prepared for sequencing. Different strategies to achieve this labelling exist. All have advantages, challenges and limitations, some of which can lead to misleading results, and in the worst case compromise the fidelity of the metabarcoding data. Given the range of questions addressed using metabarcoding, ensuring that data generation is robust and fit for the chosen purpose is critically important for practitioners seeking to employ metabarcoding for biodiversity assessments. Here, we present an overview of the three main workflows for sample-specific labelling and library preparation in metabarcoding studies on Illumina sequencing platforms; one-step PCR, two-step PCR, and tagged PCR. Further, we distill the key considerations for researchers seeking to select an appropriate metabarcoding strategy for their specific study. Ultimately, by gaining insights into the consequences of different metabarcoding workflows, we hope to further consolidate the power of metabarcoding as a tool to assess biodiversity across a range of applications.

Human Alphacoronavirus Universal Primers for Genome Amplification and Sequencing

Rapid and accurate sequencing covering the entire genome is essential to identify genetic variations of viral pathogens. However, due to the low viral titers in clinical samples, certain amplification steps are required for viral genome sequencing. At present, there are no universal primers available for alphacoronaviruses and that, since these viruses have diverse strains, new primers specific to the target strain must be continuously developed for sequencing. Thus, in this study, we aimed to develop a universal primer set valid for all human alphacoronaviruses and applicable to samples containing trace amounts of the virus. To this aim, we designed overlapping primer pairs capable of amplifying the entire genome of all known human alphacoronaviruses. The selected primers, named the AC primer set, were composed of 10 primer pairs stretching over the entire genome of alphacoronaviruses, and produced PCR products of the expected size (3-5 kb) from both the HCoV-229E and HCoV-NL63 strains. After genome amplification, an evaluation using various sequencing platforms was carried out. The amplicon library sequencing data were assembled into complete genome sequences in all sequencing strategies examined in this study. The sequencing accuracy varied depending on the sequencing technology, but all sequencing methods showed a sequencing error of less than 0.01%. In the mock clinical specimen, the detection limit was 10^-3 PFU/ml (10² copies/ml). The AC primer set and experimental procedure optimized in this study may enable the fast diagnosis of mutant alphacoronaviruses in future epidemics.

The evolution of bacterial genome assemblies - where do we need to go next?

Genome sequencing has fundamentally changed our ability to decipher and understand the genetic blueprint of life and how it changes over time in response to environmental and evolutionary pressures. The pace of sequencing is still increasing in response to advances in technologies, paving the way from sequenced genes to genomes to metagenomes to metagenome-assembled genomes (MAGs). Our ability to interrogate increasingly complex microbial communities through metagenomes and MAGs is opening up a tantalizing future where we may be able to delve deeper into the mechanisms and genetic responses emerging over time. In the near future, we will be able to detect MAG assembly variations within strains originating from diverging sub-populations, and one of the emerging challenges will be to capture these variations in a biologically relevant way. Here, we present a brief overview of sequencing technologies and the current state of metagenome assemblies to suggest the need to develop new data formats that can capture the genetic variations within strains and communities, which previously remained invisible due to sequencing technology limitations.

A comprehensive preclinical study supporting clinical trial of oncolytic chimeric poxvirus CF33-hNIS-anti-PD-L1 to treat breast cancer

CF33-hNIS-anti-PD-L1 is an oncolytic chimeric poxvirus encoding two transgenes: human sodium iodide symporter and a single-chain variable fragment against PD-L1. Comprehensive preclinical pharmacology studies encompassing primary and secondary pharmacodynamics and biodistribution and safety studies were performed to support the clinical development of CF33-hNIS-anti-PD-L1. Most of the studies were performed in triple-negative breast cancer (TNBC) models, as the phase I trial is planned for patients with TNBC. Biological functions of virus-encoded transgenes were confirmed, and the virus demonstrated anti-tumor efficacy against TNBC models in mice. In a good laboratory practice (GLP) toxicology study, the virus did not produce any observable adverse effects in mice, suggesting that the doses proposed for the clinical trial should be well tolerated in patients. Furthermore, no neurotoxic effects in mice were seen following intracranial injection of the virus. Also, the risk for horizontal transmission of CF33-hNIS-anti-PD-L1 was assessed in mice, and our results suggest that the virus is unlikely to transmit from infected patients to healthy individuals. Finally, the in-use stability and compatibility of CF33-hNIS-anti-PD-L1 tested under different conditions mimicking the clinical scenarios confirmed the suitability of the virus in clinical settings. The results of these preclinical studies support the use of CF33-hNIS-anti-PD-L1 in a first-in-human trial in patients with TNBC.

Control of subunit stoichiometry in single-chain MspA nanopores

Transmembrane protein channels enable fast and highly sensitive detection of single molecules. Nanopore sequencing of DNA was achieved using an engineered Mycobacterium smegmatis porin A (MspA) in combination with a motor enzyme. Due to its favorable channel geometry, the octameric MspA pore exhibits the highest current level compared with other pore proteins. To date, MspA is the only protein nanopore with a published record of DNA sequencing. While widely used in commercial devices, nanopore sequencing of DNA suffers from significant base-calling errors due to stochastic events of the complex DNA-motor-pore combination and the contribution of up to five nucleotides to the signal at each position. Different mutations in specific subunits of a pore protein offer an enormous potential to improve nucleotide resolution and sequencing accuracy. However, individual subunits of MspA and other oligomeric protein pores are randomly assembled in vivo and in vitro, preventing the efficient production of designed pores with different subunit mutations. In this study, we converted octameric MspA into a single-chain pore by connecting eight subunits using peptide linkers. Lipid bilayer experiments demonstrated that single-chain MspA formed membrane-spanning channels and discriminated all four nucleotides identical to MspA produced from monomers in DNA hairpin experiments. Single-chain constructs comprising three, five, six, and seven connected subunits assembled to functional channels, demonstrating a remarkable plasticity of MspA to different subunit stoichiometries. Thus, single-chain MspA constitutes a new milestone in the optimization of MspA as a biosensor for DNA sequencing and many other applications by enabling the production of pores with distinct subunit mutations and pore diameters.

Estimating individual mtDNA haplotypes in mixed DNA samples by combining MinION and MiSeq

We tried to estimate individual mtDNA haplotypes in mixed DNA samples by combining MinION and MiSeq. The BAM files produced by MiSeq were viewed using Integrative Genomics Viewer (IGV) to verify mixed bases. By sorting the reads according to base type for each mixed base, partial haplotypes were determined. Then, the BAM files produced by MinKNOW were viewed using IGV. To determine haplotypes with IGV, only mixed bases determined by MiSeq were used as target bases. By sorting the reads according to base type for each target base, each contributor's haplotype was estimated. In mixed samples from two contributors, even a haplotype with a minor contribution of 5% could be distinguished from the haplotype of the major contributor. In mixed samples of three contributors (mixture ratios of 1:1:1 and 4:2:1), each haplotype could also be distinguished. Sequences of C-stretches were determined very inaccurately in the MinION analysis. Although the analysis method was simple, each haplotype was correctly detected in all mixed samples with two or three contributors in various mixture ratios by combining MinION and MiSeq. This should be useful for identifying contributors to mixed samples.

Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

In this study, we addressed different aspects regarding the implementation of quasimetagenomic sequencing as a hybrid surveillance method in combination with enrichment for early detection of Listeria monocytogenes in the food industry. Different experimental enrichment cultures were used, comprising seven L. monocytogenes strains of different sequence types (STs), with and without a background microbiota community. To assess whether the proportions of the different STs changed over time during enrichment, the growth and population dynamics were assessed using dapE colony sequencing and dapE and 16S rRNA amplicon sequencing. There was a tendency of some STs to have a higher relative abundance during the late stage of enrichment when L. monocytogenes was enriched without background microbiota. When coenriched with background microbiota, the population dynamics of the different STs was more consistent over time. To evaluate the earliest possible time point during enrichment that allows the detection of L. monocytogenes and at the same time the generation of genetic information that enables an estimation regarding the strain diversity in a sample, quasimetagenomic sequencing was performed early during enrichment in the presence of the background microbiota using Oxford Nanopore Technologies Flongle and Illumina MiSeq sequencing. The application of multiple displacement amplification (MDA) enabled detection of L. monocytogenes (and the background microbiota) after only 4 h of enrichment using both applied sequencing approaches. The MiSeq sequencing data additionally enabled the prediction of cooccurring L. monocytogenes strains in the samples.

IMPORTANCE We showed that a combination of a short primary enrichment combined with MDA and Nanopore sequencing can accelerate the traditional process of cultivation and identification of L. monocytogenes. The use of Illumina MiSeq sequencing additionally allowed us to predict the presence of cooccurring L. monocytogenes strains. Our results suggest quasimetagenomic sequencing is a valuable and promising hybrid surveillance tool for the food industry that enables faster identification of L. monocytogenes during early enrichment. Routine application of this approach could lead to more efficient and proactive actions in the food industry that prevent contamination and subsequent product recalls and food destruction, economic and reputational losses, and human listeriosis cases.

Theory of local k-mer selection with applications to long-read alignment

Motivation

Selecting a subset of k-mers in a string in a local manner is a common task in bioinformatics tools for speeding up computation. Arguably the most well-known and common method is the minimizer technique, which selects the ‘lowest-ordered’ k-mer in a sliding window. Recently, it has been shown that minimizers may be a sub-optimal method for selecting subsets of k-mers when mutations are present. There is, however, a lack of understanding behind the theory of why certain methods perform well.

Results

We first theoretically investigate the conservation metric for k-mer selection methods. We derive an exact expression for calculating the conservation of a k-mer selection method. This turns out to be tractable enough for us to prove closed-form expressions for a variety of methods, including (open and closed) syncmers, (a, b, n)-words, and an upper bound for minimizers. As a demonstration of our results, we modified the minimap2 read aligner to use a more conserved k-mer selection method and demonstrate that there is up to an 8.2% relative increase in number of mapped reads. However, we found that the k-mers selected by more conserved methods are also more repetitive, leading to a runtime increase during alignment. We give new insight into how one might use new k-mer selection methods as a reparameterization to optimize for speed and alignment quality.

Availability and implementation

Simulations and supplementary methods are available at https://github.com/bluenote-1577/local-kmer-selection-results. os-minimap2 is a modified version of minimap2 and available at https://github.com/bluenote-1577/os-minimap2.

Supplementary information

Supplementary data are available at Bioinformatics online.

Functional meta-omics provide critical insights into long- and short-read assemblies

Real-world evaluations of metagenomic reconstructions are challenged by distinguishing reconstruction artifacts from genes and proteins present in situ. Here, we evaluate short-read-only, long-read-only and hybrid assembly approaches on four different metagenomic samples of varying complexity. We demonstrate how different assembly approaches affect gene and protein inference, which is particularly relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic and metaproteomic data to assess the metagenomic data-based protein predictions. Our findings pave the way for critical assessments of metagenomic reconstructions. We propose a reference-independent solution, which exploits the synergistic effects of multi-omic data integration for the in situ study of microbiomes using long-read sequencing data.

BlockPolish: accurate polishing of long-read assembly via block divide-and-conquer

Long-read sequencing technology enables significant progress in de novo genome assembly. However, the high error rate and the wide error distribution of raw reads result in a large number of errors in the assembly. Polishing is a procedure to fix errors in the draft assembly and improve the reliability of genomic analysis. However, existing methods treat all the regions of the assembly equally while there are fundamental differences between the error distributions of these regions. How to achieve very high accuracy in genome assembly is still a challenging problem. Motivated by the uneven errors in different regions of the assembly, we propose a novel polishing workflow named BlockPolish. In this method, we divide contigs into blocks with low complexity and high complexity according to statistics of aligned nucleotide bases. Multiple sequence alignment is applied to realign raw reads in complex blocks and optimize the alignment result. Due to the different distributions of error rates in trivial and complex blocks, two multitask bidirectional Long short-term memory (LSTM) networks are proposed to predict the consensus sequences. In the whole-genome assemblies of NA12878 assembled by Wtdbg2 and Flye using Nanopore data, BlockPolish has a higher polishing accuracy than other state-of-the-arts including Racon, Medaka and MarginPolish & HELEN. In all assemblies, errors are predominantly indels and BlockPolish has a good performance in correcting them. In addition to the Nanopore assemblies, we further demonstrate that BlockPolish can also reduce the errors in the PacBio assemblies. The source code of BlockPolish is freely available on Github (https://github.com/huangnengCSU/BlockPolish).

Sequencing DNA with nanopores: Troubles and biases

Oxford Nanopore Technologies' (ONT) long read sequencers offer access to longer DNA fragments than previous sequencer generations, at the cost of a higher error rate. While many papers have studied read correction methods, few have addressed the detailed characterization of observed errors, a task complicated by frequent changes in chemistry and software in ONT technology. The MinION sequencer is now more stable and this paper proposes an up-to-date view of its error landscape, using the most mature flowcell and basecaller. We studied Nanopore sequencing error biases on both bacterial and human DNA reads. We found that, although Nanopore sequencing is expected not to suffer from GC bias, it is a crucial parameter with respect to errors. In particular, low-GC reads have fewer errors than high-GC reads (about 6% and 8% respectively). The error profile for homopolymeric regions or regions with short repeats, the source of about half of all sequencing errors, also depends on the GC rate and mainly shows deletions, although there are some reads with long insertions. Another interesting finding is that the quality measure, although over-estimated, offers valuable information to predict the error rate as well as the abundance of reads. We supplemented this study with an analysis of a rapeseed RNA read set and shown a higher level of errors with a higher level of deletion in these data. Finally, we have implemented an open source pipeline for long-term monitoring of the error profile, which enables users to easily compute various analysis presented in this work, including for future developments of the sequencing device. Overall, we hope this work will provide a basis for the design of better error-correction methods.

FLAME: long-read bioinformatics tool for comprehensive spliceome characterization

Comprehensive characterization of differentially spliced RNA transcripts with nanopore sequencing is limited by bioinformatics tools that are reliant on existing annotations. We have developed FLAME, a bioinformatics pipeline for alternative splicing analysis of gene-specific or transcriptome-wide long-read sequencing data. FLAME is a Python-based tool aimed at providing comprehensible quantification of full-length splice variants, reliable de novo recognition of splice sites and exons, and representation of consecutive exon connectivity in the form of a weighted adjacency matrix. Notably, this workflow circumvents issues related to inadequate reference annotations and allows for incorporation of short-read sequencing data to improve the confidence of nanopore sequencing reads. In this study, the Epstein-Barr virus long noncoding RNA RPMS1 was used to demonstrate the utility of the pipeline. RPMS1 is ubiquitously expressed in Epstein-Barr virus associated cancer and known to undergo ample differential splicing. To fully resolve the RPMS1 spliceome, we combined gene-specific nanopore sequencing reads from a primary gastric adenocarcinoma and a nasopharyngeal carcinoma cell line with matched publicly available short-read sequencing data sets. All previously reported splice variants, including putative ORFs, were detected using FLAME. In addition, 32 novel exons, including two intron retentions and a cassette exon, were discovered within the RPMS1 gene.

A Journey on the Skin Microbiome: Pitfalls and Opportunities

The human skin microbiota is essential for maintaining homeostasis and ensuring barrier functions. Over the years, the characterization of its composition and taxonomic diversity has reached outstanding goals, with more than 10 million bacterial genes collected and cataloged. Nevertheless, the study of the skin microbiota presents specific challenges that need to be addressed in study design. Benchmarking procedures and reproducible and robust analysis workflows for increasing comparability among studies are required. For various reasons and because of specific technical problems, these issues have been investigated in gut microbiota studies, but they have been largely overlooked for skin microbiota. After a short description of the skin microbiota, the review tackles methodological aspects and their pitfalls, covering NGS approaches and high throughput culture-based techniques. Recent insights into the "core" and "transient" types of skin microbiota and how the manipulation of these communities can prevent or combat skin diseases are also covered. Finally, this review includes an overview of the main dermatological diseases, the changes in the microbiota composition associated with them, and the recommended skin sampling procedures. The last section focuses on topical and oral probiotics to improve and maintain skin health, considering their possible applications for skin diseases.

Insertions in SARS-CoV-2 genome caused by template switch and duplications give rise to new variants that merit monitoring

The appearance of multiple new SARS-CoV-2 variants during the winter of 2020-2021 is a matter of grave concern. Some of these new variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the COVID-19 pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on point nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the spike protein is thought to be a determinant of SARS-CoV-2 virulence and other inserts might have contributed to coronavirus pathogenicity as well. Here, we investigate insertions in SARS-CoV-2 genomes and identify 347 unique inserts of different lengths. We present evidence that these inserts reflect actual virus variance rather than sequencing errors. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. We show that inserts in the Spike glycoprotein can affect its antigenic properties and thus merit monitoring. At least, three inserts in the N-terminal domain of the Spike (ins245IME, ins246DSWG, and ins248SSLT) that were first detected in 2021 are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity.

Expanding the conservation genomics toolbox: Incorporating structural variants to enhance genomic studies for species of conservation concern

Structural variants (SVs) are large rearrangements (>50 bp) within the genome that impact gene function and the content and structure of chromosomes. As a result, SVs are a significant source of functional genomic variation, that is, variation at genomic regions underpinning phenotype differences, that can have large effects on individual and population fitness. While there are increasing opportunities to investigate functional genomic variation in threatened species via single nucleotide polymorphism (SNP) data sets, SVs remain understudied despite their potential influence on fitness traits of conservation interest. In this future-focused Opinion, we contend that characterizing SVs offers the conservation genomics community an exciting opportunity to complement SNP-based approaches to enhance species recovery. We also leverage the existing literature-predominantly in human health, agriculture and ecoevolutionary biology-to identify approaches for readily characterizing SVs and consider how integrating these into the conservation genomics toolbox may transform the way we manage some of the world's most threatened species.