High-accuracy long-read amplicon sequences using unique molecular identifiers with Nanopore or PacBio sequencing

Systematic evaluation of single-cell RNA-seq analyses performance based on long-read sequencing platforms

INTRODUCTION

The rapid development of next-generation sequencing (NGS)-based single-cell RNA sequencing (scRNA-seq) allows for detecting and quantifying gene expression in a high-throughput manner, providing a powerful tool for comprehensively understanding cellular function in various biological processes. However, the NGS-based scRNA-seq only quantifies gene expression and cannot reveal the exact transcript structures (isoforms) of each gene due to the limited read length. On the other hand, the long read length of third-generation sequencing (TGS) technologies, including Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), enable direct reading of intact cDNA molecules.

OBJECTIVES

Both ONT and PacBio have been used in conjunction with scRNA-seq, but their performance in single-cell analyses has not been systematically evaluated.

METHODS

To address this, we generated ONT and PacBio data from the same single-cell cDNA libraries containing different amount of cells.

RESULTS

Using NGS as a control, we assessed the performance of each platform in cell type identification. Additionally, the reliability in identifying novel isoforms and allele-specific gene/isoform expression by both platforms was verified, providing a systematic evaluation to design the sequencing strategies in single-cell transcriptome studies.

CONCLUSION

Beyond gene expression analysis, which the NGS-based scRNA-seq only affords, TGS-based scRNA-seq achieved gene splicing analyses, identifying novel isoforms. Attribute to higher sequencing quality of PacBio, it outperforms ONT in accuracy of novel transcripts identification and allele-specific gene/isoform expression.

Kastor: a reference-based comparative approach for assessment and correction of gene-fragmenting errors in long-read assemblies of small genomes

Long read sequencing technologies provide an efficient approach to generating highly contiguous and informative assemblies. However, higher relative error rates can introduce frameshifts and premature stop codons that pseudogenize genes, hindering downstream analyses. We developed a software tool that detects gene-fragmenting errors in draft assemblies of small genomes through comparison with a curated set of reference genome sequences and raw read information. In our presented example, detected errors represent less than 0.05% of the genome, but when corrected reduced the rate of pseudogenes from 23.3 to 5.6% in example long read assemblies, comparable to the rate of pseudogenes in short read assemblies. We demonstrate that this software can detect assembly errors in long read assemblies generated from small genomes and correct them to de-fragment genes.

Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling

Shallow genome-wide cell-free DNA sequencing holds great promise for noninvasive cancer monitoring by providing reliable copy number alteration (CNA) and fragmentomic profiles. Single-nucleotide variations (SNVs) are, however, much harder to identify with low sequencing depth due to sequencing errors. Here, we present Nanopore Rolling Circle Amplification (RCA)-enhanced Consensus Sequencing (NanoRCS), which leverages RCA and consensus calling based on genome-wide long-read nanopore sequencing to enable simultaneous multimodal tumor fraction (TF) estimation through SNVs, CNAs, and fragmentomics. The efficacy of NanoRCS is tested on 18 cancer patient samples and seven healthy controls, demonstrating its ability to reliably detect TFs as low as 0.24%. In vitro experiments confirm that SNV measurements are essential for detecting TFs below 3%. NanoRCS provides an opportunity for cost-effective and rapid sample processing, which aligns well with clinical needs, particularly in settings where quick and accurate cancer monitoring is essential for personalized treatment strategies.

A high-throughput and time-efficient Nanopore full-length 16S rRNA gene sequencing protocol for synthetic microbial communities

Next-generation sequencing (NGS) has transitioned from primarily research-focused applications to a mature technology. However, resolving microbial community composition on the species level based on the 16S rRNA gene is impeded by several critical bottlenecks that limit the efficiency and scalability of analyses. Specifically, standard MiSeq sequencing suffers from read-length limitation; library preparation requires multiple labour-intensive steps from DNA isolation to amplification and barcoding; and prolonged turnaround times delay results. These challenges underscore the need for improved methods, which our study aims to address. Recent advances in Oxford Nanopore long-read sequencing technology (ONT), including a smaller and cheaper benchtop instrument and support for diverse sample types, have enabled faster sequencing in-house with reduced costs. To address the need for standardized, reproducible workflows, we present an optimized and state-of-the-art protocol for full-length 16S rRNA gene sequencing using the ONT MinION sequencing device. Furthermore, we quantified the reproducibility and accuracy of our protocol and compared it with previous MiSeq results. The results showed that the accuracy of our sequencing pipeline for synthetic communities is significantly higher than for MiSeq pipeline. In summary, our protocol elucidates the composition of synthetic microbial communities in an easy, fast and accurate manner while ensuring reproducible results.

SuperDecode: An integrated toolkit for analyzing mutations induced by genome editing

Genome editing using CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein) or other systems has become a cornerstone of numerous biological and applied research fields. However, detecting the resulting mutations by analyzing sequencing data remains time consuming and inefficient. In response to this issue, we designed SuperDecode, an integrated software toolkit for analyzing editing outcomes using a range of sequencing strategies. SuperDecode comprises three modules, DSDecodeMS, HiDecode, and LaDecode, each designed to automatically decode mutations from Sanger, high-throughput short-read, and long-read sequencing data, respectively, from targeted PCR amplicons. By leveraging specific strategies for constructing sequencing libraries of pooled multiple amplicons, HiDecode and LaDecode facilitate large-scale identification of mutations induced by single or multiplex target-site editing in a cost-effective manner. We demonstrate the efficacy of SuperDecode by analyzing mutations produced using different genome editing tools (CRISPR/Cas, base editing, and prime editing) in different materials (diploid and tetraploid rice and protoplasts), underscoring its versatility in decoding genome editing outcomes across different applications. Furthermore, this toolkit can be used to analyze other genetic variations, as exemplified by its ability to estimate the C-to-U editing rate of the cellular RNA of a mitochondrial gene. SuperDecode offers both a standalone software package and a web-based version, ensuring its easy access and broad compatibility across diverse computer systems. Thus, SuperDecode provides a comprehensive platform for analyzing a wide array of mutations, advancing the utility of genome editing for scientific research and genetic engineering.

ConSeqUMI, an error-free nanopore sequencing pipeline to identify and extract individual nucleic acid molecules from heterogeneous samples

Nanopore sequencing has revolutionized genetic analysis by offering linkage information across megabase-scale genomes. However, the high intrinsic error rate of nanopore sequencing impedes the analysis of complex heterogeneous samples, such as viruses, bacteria, complex libraries, and edited cell lines. Achieving high accuracy in single-molecule sequence identification would significantly advance the study of diverse genomic populations, where clonal isolation is traditionally employed for complete genomic frequency analysis. Here, we introduce ConSeqUMI, an innovative experimental and analytical pipeline designed to address long-read sequencing error rates using unique molecular indices for precise consensus sequence determination. ConSeqUMI processes nanopore sequencing data without the need for reference sequences, enabling accurate assembly of individual molecular sequences from complex mixtures. We establish robust benchmarking criteria for this platform's performance and demonstrate its utility across diverse experimental contexts, including mixed plasmid pools, recombinant adeno-associated virus genome integrity, and CRISPR/Cas9-induced genomic alterations. Furthermore, ConSeqUMI enables detailed profiling of human pathogenic infections, as shown by our analysis of SARS-CoV-2 spike protein variants, revealing substantial intra-patient genetic heterogeneity. Lastly, we demonstrate how individual clonal isolates can be extracted directly from sequencing libraries at low cost, allowing for post-sequencing identification and validation of observed variants. Our findings highlight the robustness of ConSeqUMI in processing sequencing data from UMI-labeled molecules, offering a critical tool for advancing genomic research.

GRAPHICAL ABSTRACT

BASELINE: A CRISPR Base Editing Platform for Mammalian-Scale Single-Cell Lineage Tracing

A cells fate is shaped by its inherited state, or lineage, and the ever-shifting context of its environment. CRISPR-based recording technologies are a promising solution to map the lineage of a developing system, yet challenges remain regarding single-cell recovery, engineering complexity, and scale. Here, we introduce BASELINE, which uses base editing to generate high-resolution lineage trees in conjunction with single-cell profiling. BASELINE uses the Cas12a adenine base editor to irreversibly edit nucleotides within 50 synthetic target sites, which are integrated multiple times into a cells genome. We show that BASELINE accumulates lineage-specific marks over a wide range of biologically relevant intervals, recording more than 4300 bits of information in a model of pancreatic cancer, a 50X increase over existing technologies. Single-cell sequencing reveals high-fidelity capture of these recorders, recovering lineage reconstructions up to 40 cell divisions deep, within the estimated range of mammalian development. We expect BASELINE to apply to a wide range of lineage-tracing projects in development and disease, especially in which cellular engineering makes small, more distributed systems challenging.

Development of a Clinically Applicable High-Resolution Assay for Sperm Mosaicism

Sperm mosaicism, the presence of a pathogenic variant in a subset of sperm, is an important cause of heritable genetic disease. However, clinical testing for sperm mosaicism outside research has been limited by the lack of Clinical Laboratory Improvement Amendments (CLIA)-validated results deliverable to patients. We developed the Sensitive Assay for Mosaicism (SAM), a two-phase method for sperm mosaicism detection. In phase 1, sperm DNA undergoes deep sequencing using next-generation sequencing or nanopore-based sequencing with unique molecular identifiers (UMIs) to improve accuracy. In phase 2, PCR primers specific to UMI sequences generate amplicons for CLIA-validated Sanger sequencing, providing patient-ready results. SAM's performance was characterized and tested on semen samples from 14 participants, each with a prior offspring with a de novo pathogenic variant. SAM demonstrated a detection limit of approximately 0.005%. The UMI strategy improved sequencing accuracy on next-generation sequencing and nanopore platforms from 99.9% to >99.999%, and from 93% to >99.99%, respectively. Sperm mosaicism was identified in two tested cases: FAM111A (5.51%) and FGFR3 (0.0129%), with FGFR3 exhibiting selfish mutation validated in unrelated individuals showing varying mosaicism levels. SAM provides sensitive detection of low-level sperm mosaicism with CLIA-validated results for patients, enabling recurrence risk assessment and guiding risk mitigation strategies such as in vitro fertilization with preimplantation genetic testing for monogenic disease, sperm donation, and prenatal diagnosis.

A Barcoded ITS Primer-Based Nanopore Sequencing Protocol for Detection of Alternaria Species and Other Fungal Pathogens in Diverse Plant Hosts

Alternaria is a genus that contains several important plant pathogens affecting nearly 400 plant species worldwide, including economically important crops such as grapes, citrus, and ornamental plants. Rapid, scalable, and efficient methods of pathogen detection are crucial for managing plant diseases and ensuring agricultural productivity. Current amplicon sequencing protocols for Alternaria detection often require the enzymatic barcoding of amplicons, increasing hands-on time, cost, and contamination risk. We present a proof-of-concept study using custom barcoded primers, combining universal primers targeting ITS1 and ITS2 regions (600 bp) coupled with Oxford Nanopore Technologies (ONT) barcode sequences. Sequencing was performed on infected grapevine, mandarin orange, thuja, and maple tree samples. In total, we analyzed 38 samples using qPCR; 8 tested positive for Alternaria, which were sequenced using a newly developed protocol. As a result, we could identify Alternaria in every positive sample, and besides the pathogen of interest, we could identify the associated mycobiome. This protocol reduces hands-on time and cost, making a significant advancement over current sequencing methods. Future work will focus on optimizing our approach for high-throughput sequencing of up to 96 samples and determining the method's applicability for large-scale mycobiome analysis.

The murine lung microbiome is disbalanced by the human-pathogenic fungus Aspergillus fumigatus resulting in enrichment of anaerobic bacteria

Here, we report significant changes in the composition of the lung microbiome and metabolome of mice under immune suppression, infection of immunosuppressed mice with virulent and avirulent strains of the clinically important human-pathogenic fungus Aspergillus fumigatus, and treatment with the clinically used antifungal drug voriconazole. Our data also indicate the important role of the gut microbiome for lung homeostasis mediated by the plasma metabolome. In the lung microbiome, DNA sequencing indicates that infection by A. fumigatus leads to a significant increase of anaerobic bacteria, most prominently of Ligilactobacillus murinus; the latter has been confirmed by qPCR analyses. We also isolated live bacteria, including L. murinus, from the murine lower respiratory tract. Co-cultivation of L. murinus and A. fumigatus leads to a reduction in oxygen concentration accompanied by an increase of L. murinus cells, suggesting that A. fumigatus establishes a microaerophilic niche, thereby promoting growth of anaerobic bacteria.

AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow

MOTIVATION

The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA sequencing (scRNAseq) assays enables the detailed exploration of transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, including the lack of advanced simulation tools that can effectively mimic the unique complexities of scRNAseq long-read datasets. Such tools are essential for the evaluation and optimization of isoform detection methods dedicated to single-cell long-read studies.

RESULTS

We developed AsaruSim, a workflow that simulates synthetic single-cell long-read Nanopore datasets, closely mimicking real experimental data. AsaruSim employs a multi-step process that includes the creation of a synthetic count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting. Applied to a dataset of human peripheral blood mononuclear cells, AsaruSim accurately reproduced experimental read characteristics.

AVAILABILITY AND IMPLEMENTATION

The source code and full documentation are available at https://github.com/GenomiqueENS/AsaruSim.

Investigation into the genotyping performance of a unique molecular identifier based microhaplotypes MPS panel in complex DNA mixture

In forensic science, genotyping mixed DNA is a critical and complex task. Sequencing errors and allele sharing complicate the analysis, particularly in cases involving unbalanced mixtures, multiple contributors, and kinship relationships. Massively parallel sequencing (MPS) panels comprising highly polymorphic microhaplotypes (MHs) offer a promising approach for detecting unique alleles in mixtures with a mixture ratio greater than 10:1, involving more than two contributors or contributors with kinship. However, sequencing errors such as base substitution and InDels on the MPS platform remain a significant challenge in genotyping complex mixed DNA. The barcoding approach has been introduced to MPS to distinguish true alleles from sequencing errors. This method employs unique molecular identifiers (UMIs) to tag individual DNA molecules, allowing for the identification and correction of random sequencing errors. By generating consensus sequences from read replicates associated with the same UMI, this approach enhances the accuracy of allele detection. In this study, UMIs were incorporated into developing a highly polymorphic panel consisting of 105 MHs, with an average effective number of alleles (Ae) of 6.9. Various types of mixed DNA samples were prepared, including unbalanced mixtures with ratios ranging from 1:1-160:1, multi-contributor mixtures with 2-6 contributors, and kinship-involved mixtures with parent-offspring to fourth-degree relatives contributors. Unique alleles were quantified, and mixture proportions (Mx) were calculated separately using sequencing reads and the number of UMI families with more than 10 members. The results demonstrated that UMI played a critical role in identifying sequencing errors and enhancing the accuracy of allele genotyping in unbalanced mixtures. A strong correlation (R² = 0.96) between UMI count and DNA template amount demonstrated that DNA template amount could be inferred from UMI count. Mx values derived from the number of UMIs were consistent across loci and showed a high correlation with mixture ratios (R2 = 0.85). Additionally, the panel efficiently detected unique alleles across all three types of complex DNA mixtures. Overall, this study underscores the importance of UMIs in mitigating PCR and sequencing biases, thereby improving the performance of the MH-MPS panel for genotyping complex DNA mixtures. UMIs represent a valuable tool for mixed DNA genotyping and hold potential for boarder applications in probabilistic genotyping.

Molecular Monitoring of Fungicide Resistance in Crop Phytopathogens

The fight against crop pathogens relies mainly on host genetics and chemistry; however, both areas are compromised by the evolution of resistance in the pathogen population. Fungicide resistance is an ongoing challenge to global food security, as it threatens these important crop protection chemistries. One critical component of resistance management is an effective detection and monitoring program, which needs to be agile, scalable, sensitive, accurate, and cost effective. A rapidly evolving suite of molecular tools are being developed for the detection of fungicide resistance mutations in phytopathogen populations, including high-throughput PCR-based quantitative assays and cutting-edge third-generation DNA sequencing. A single "silver bullet" detection technology that will satisfy all study objectives does not exist; thus, every tool has a niche in an integrated detection and monitoring program. This review presents an overview of the rapidly changing landscape of fungicide resistance detection, illustrates how molecular techniques are being exploited to combat fungicide resistance in cereal crop phytopathogens, and highlights challenges and future research directions to aid in the design of effective monitoring systems that aim to apply fungicides strategically and minimize the cost of resistance. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

An unignorable human health risk posed by antibiotic resistome and microbiome in urban rivers: Insights from Beijing, China

Urban rivers are the main water bodies humans frequently come into contact with, so the risks posed are closely monitored. Antibiotic resistance genes (ARGs) residues in reclaimed water pose serious risks to human health. There are urgent needs to improve the understanding of distribution of and risks posed by ARGs in urban rivers. In this study, shotgun metagenomic approach was used to characterize ARGs, mobile genetic elements (MGEs), and virulence factors (VFs) in water and sediment from Xinfeng River in Beijing and to identify microbes, potential antibiotic resistant bacteria, and human pathogens (HPs). MGE, microbial community, VF, and ARG co-occurrences were used to assess the environmental risks posed by ARGs. The results indicated that quinolone was the most abundant ARG type and that tufA and fusA were the two dominant ARG subtypes. Wetland effluent increased ARG abundance in the river, and the effect was detected even 50 m downstream. ARG abundances and distribution in the river had difference in different seasons. The dominant bacteria in the river were Proteobacteria, Bacteroidetes, and Actinobacteria, and 59 HPs were detected. In total, 69 MGEs and 19 VFs were found. Co-occurrence networks indicated that potential antibiotic resistant bacteria, MGEs, VFs, and ARGs in the river significantly correlated, indicating the potential risks posed by ARGs. The results improve our understanding of ARG distribution and environmental risks in urban river water. More attention should be paid to controlling environmental risks posed by ARGs in urban river and reclaimed water.

Harnessing Non-standard Nucleic Acids for Highly Sensitive Icosaplex (20-Plex) Detection of Microbial Threats for Environmental Surveillance

Environmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. Using parallelized multitarget TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay on wastewater, soil, and human stool samples, we found 90% agreement on positive calls and 89% agreement on negative calls. Additionally, we show how long-read and short-read sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish subspecies. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.

In vivo expansion of gene-targeted hepatocytes through transient inhibition of an essential gene

Homology-directed repair (HDR)-based genome editing is an approach that could permanently correct a broad range of genetic diseases. However, its utility is limited by inefficient and imprecise DNA repair mechanisms in terminally differentiated tissues. Here, we tested Repair Drive, a platform technology for selectively expanding HDR-corrected hepatocytes in adult mice in vivo. Repair Drive involves transient conditioning of the liver by knocking down an essential gene, fumarylacetoacetate hydrolase (Fah), and delivering an untargetable version of the essential gene in cis with a therapeutic transgene. We show that Repair Drive increased the percentage of correctly targeted hepatocytes in healthy wild-type mice up to 25%, which resulted in a fivefold increased expression of a therapeutic transgene, human factor IX (FIX). Repair Drive was well tolerated and did not induce toxicity or tumorigenesis during a 1-year follow-up. This approach may broaden the range of liver diseases that can be treated with somatic genome editing.

Full-Length Immune Repertoire Reconstruction and Profiling at the Transcriptome Level Using Long-Read Sequencing

BACKGROUND

Due to the diversity of the immune repertoire (IR), reconstructing full-length IR using traditional short-read sequencing has proven challenging.

METHODS

A full-length IR sequencing (FLIRseq) work flow was developed with linear rolling circle amplification and nanopore sequencing. Its accuracy and quantification ability were verified by plasmid mixtures and commercial B-cell receptor/T-cell receptor sequencing (BCR/TCR-seq) based on short reads. IRs in tissues and the peripheral blood from 8 patients with acute lymphoblastic leukemia, 3 patients with allergic diseases, 4 patients with psoriasis, and 5 patients with prostate cancer were analyzed using FLIRseq.

RESULTS

FLIRseq reads had lower mismatch rates and gap rates, and higher identify rates than nanopore reads (all P < 2.2 × -16). The relative quantification of components by FLIRseq was consistent with the actual quantification (P > 0.05). FLIRseq had superiority over BCR/TCR-seq, providing the long complementarity-determining region 3, B-cell isotype, and the rarely used V gene sequence. FLIRseq observed an increase in clonotype diversity (P < 0.05) and a decrease in the percentage of abnormal BCRs/TCRs in patients with leukemia in remission. For patients with allergic diseases or psoriasis, FLIRseq provided direct insights into V(D)J recombination and specific immunoglobulin classes. Compared with that in prostate cancer tissues, the full-length V segment of the biased T-cell receptor β chain from lymphocytes in psoriatic tissues showed a more consistent AlphaFold2-predicted protein structure (P < 0.05).

CONCLUSIONS

FLIRseq enables unbiased and comprehensive analyses of direct V(D)J recombination and immunoglobulin classes, thereby contributing to characterizing pathogenic mechanisms, monitoring minimal residual disease, and customizing adoptive cell therapy.

Strategies and Protocols for Optimized Genome Editing in Potato

The potato family includes a highly diverse cultivar repertoire and has a high potential for nutritional yield improvement and refinement but must in line with other crops be adapted to biotic and abiotic stresses, for example, accelerated by climate change and environmental demands. The combination of pluripotency, high ploidy, and relative ease of protoplast isolation, transformation, and regeneration together with clonal propagation through tubers makes potato highly suitable for precise genetic engineering. Most potato varieties are tetraploid having a very high prevalence of length polymorphisms and small nucleotide polymorphisms between alleles, often complicating CRISPR-Cas editing designs and strategies. CRISPR-Cas editing in potato can be divided into (i) characterization of target area and in silico-aided editing design, (ii) isolation and editing of protoplast cells, and (iii) the subsequent explant regeneration from single protoplast cells. Implementation of efficient CRISPR-Cas editing relies on efficient editing at the protoplast (cell pool) level and on robust high-throughput editing scoring methods at the cell pool and explant level. Gene and chromatin structure are additional features to optionally consider. Strategies and solutions for addressing key steps in genome editing of potato, including light conditions and schemes for reduced exposure to hormones during explant regeneration, which is often linked to somaclonal variation, are highlighted.

Cost-Effective Detection of SNPs and Structural Variations in Full-Length Genes of Wheat and Sunflower Using Multiplex PCR and Rapid Nanopore Kit

The rapid identification of allele variants in target genes is crucial for accelerating marker-assisted selection (MAS) in plant breeding. Although current high-throughput genotyping methods are efficient in detecting known polymorphisms, they are limited when multiple variant sites are scattered along the gene. This study presents a target amplicon sequencing approach using Oxford Nanopore Technologies (ONT-TAS) to rapidly sequence full-length genes and identify allele variants in sunflower and wheat collections. This procedure combines multiplex PCR and a rapid sequencing kit, significantly reducing the time and cost compared to previous methods. The efficiency of the approach was demonstrated by sequencing four genes (Ahasl1, Ahasl2, Ahasl3, and FAD2) in 40 sunflower genotypes and three genes (Ppo, Wx, and Lox) in 30 wheat genotypes. The ONT-TAS revealed a complete picture of SNPs and InDels distributed over the individual alleles, enabling rapid (4.5 h for PCR and sequencing) characterization of the genetic diversity of the target genes in the germplasm collections. The results showed a significant diversity of the Ahasl1/Ahasl3 and Wx-A/Lox-B genes in the sunflower and wheat collections, respectively. This method offers a high-throughput, cost-effective (USD 3.4 per gene) solution for genotyping and identifying novel allele variants in plant breeding programs.

Evaluating the efficiency of 16S-ITS-23S operon sequencing for species level resolution in microbial communities

Rapid advancements in long-read sequencing have facilitated species-level microbial profiling through full-length 16S rRNA sequencing (~ 1500 bp), and more notably, by the newer 16S-ITS-23S ribosomal RNA operon (RRN) sequencing (~ 4500 bp). RRN sequencing is emerging as a superior method for species resolution, exceeding the capabilities of short-read and full-length 16S rRNA sequencing. However, being in its early stages of development, RRN sequencing has several underexplored or understudied elements, highlighting the need for a critical and thorough examination of its methodologies. Key areas that require detailed analysis include understanding how primer pairs, sequencing platforms, and classifiers and databases affect the accuracy of species resolution achieved through RRN sequencing. Our study addresses these gaps by evaluating the effect of primer pairs using four RRN primer combinations, and that of sequencing platforms by employing PacBio and Oxford Nanopore Technologies (ONT) systems. Furthermore, two classification methods (Minimap2 and OTU clustering), in combination with four RRN reference databases (MIrROR, rrnDB, and two versions of GROND) were compared to identify consistent and accurate classification methods with RRN sequencing. Here we demonstrate that RRN primer pair choice and sequencing platform do not substantially bias taxonomic profiles for most of the tested mock communities, while classification methods significantly impact the accuracy of species-level assignments. Of the classification methods tested, Minimap2 classifier in combination with the GROND database most consistently provided accurate species-level classification across the communities tested, irrespective of sequencing platform.

Labor- and cost-effective long-read amplicon sequencing using a plasmid analysis service: application to transposon-containing alleles in Japanese morning glory

The sequencing of PCR fragments amplified from specific regions of genomes is a fundamental technique in molecular genetics. Sanger sequencing is commonly used for this analysis; however, amplicon sequencing utilizing next-generation sequencing has become widespread. In addition, long-read amplicon sequencing, using Nanopore or PacBio sequencers to analyze long PCR fragments, has emerged, although it is often more expensive than Sanger sequencing. Recently, low-cost commercial services for full-length plasmid DNA sequencing using Nanopore sequencers have been launched in several countries, including Japan. This study explored the potential of these services to sequence long PCR fragments without the need for cloning into plasmid DNA, as cloning long PCR fragments or blunt-end PCR fragments into plasmids is often challenging. PCR fragments of 4-11 kb, amplified from the DFR-B gene involved in the biosynthesis of anthocyanin, with or without Tpn1 transposons in Japanese morning glory (Ipomoea nil), were circularized using T4 DNA ligase and analyzed as templates. Although some inaccuracies in the length of homopolymer stretches were observed, the remaining sequences were obtained without significant errors. This method could potentially reduce the labor and costs associated with cloning, primer synthesis and sequence assembly, thus making it a viable option for the analysis of long PCR fragment sequences. Moreover, this study reconfirmed that Tpn1 transposons are major mutagens in I. nil and demonstrated their transposition in the Violet line, a long-used standard in plant physiology.

Navigating triplet repeats sequencing: concepts, methodological challenges and perspective for Huntington's disease

The accurate characterization of triplet repeats, especially the overrepresented CAG repeats, is increasingly relevant for several reasons. First, germline expansion of CAG repeats above a gene-specific threshold causes multiple neurodegenerative disorders; for instance, Huntington's disease (HD) is triggered by >36 CAG repeats in the huntingtin (HTT) gene. Second, extreme expansions up to 800 CAG repeats have been found in specific cell types affected by the disease. Third, synonymous single nucleotide variants within the CAG repeat stretch influence the age of disease onset. Thus, new sequencing-based protocols that profile both the length and the exact nucleotide sequence of triplet repeats are crucial. Various strategies to enrich the target gene over the background, along with sequencing platforms and bioinformatic pipelines, are under development. This review discusses the concepts, challenges, and methodological opportunities for analyzing triplet repeats, using HD as a case study. Starting with traditional approaches, we will explore how sequencing-based methods have evolved to meet increasing scientific demands. We will also highlight experimental and bioinformatic challenges, aiming to provide a guide for accurate triplet repeat characterization for diagnostic and therapeutic purposes.

An accurate haplotyping method using multiplex pyrosequencing with AS-PCR to detect ABCB1 haplotypes associated with rivaroxaban-derived hemorrhagic events

In clinical practice, owing to the comprehensive genetic insights they offer, haplotypes have attracted greater attention than individual single nucleotide polymorphisms (SNPs). Due to the long distances across SNP locations, detecting the haplotype using genomic DNA is challenging. Current haplotyping methods are either expensive and labor-intensive (high-throughput DNA sequencing), or haplotyping a single clinical sample (computational approach) is impossible. Herein, we propose using mRNA as a haplotyping target to minimize the distance among SNPs and employing allele-specific PCR (AS-PCR) to pick up a desired haplotype, followed by multiplex pyrosequencing to type the alleles at the SNP location of interest. AS-PCR was improved by combining an additional 3'-phosphorylated modified probe to achieve the specific separation of two closely similar templates. Only the sample with more than two heterozygotes needs to be haplotyped; therefore, we propose a stratification strategy to screen the samples for further haplotyping. This method was evaluated by associating ABCB1 haplotypes with the rivaroxaban-derived side effect in a cohort of 505 patients with nephrotic syndrome, focusing on the SNPs of ABCB1: rs1236C > T, rs2677G > T/A, and rs3435C > T. We successfully identified five bleeding-related haplotypes: rs1236T-rs2677T-rs3435T, rs1236C-rs2677G-rs3435T, rs1236T-rs2677G-rs3435C, rs1236C-rs2677G-rs3435C, and rs1236T-rs2677T-rs3435C. We compared the results with those from the conventional computational algorithm PHASE and observed that PHASE results dismissed the impact of rs1236C-rs2677G-rs3435C and rs1236C-rs2677G-rs3435T on bleeding risk and erroneously suggested a false positive association of rs1236C-rs2677A-rs3435T with increased bleeding risk.

Recent Advances in Antimicrobial Resistance: Insights from Escherichia coli as a Model Organism

Antimicrobial resistance (AMR) represents a critical global health threat, and a thorough understanding of resistance mechanisms in Escherichia coli is needed to guide effective treatment interventions. This review explores recent advances for investigating AMR in E. coli, including machine learning for resistance pattern analysis, laboratory evolution to generate resistant mutants, mutant library construction, and genome sequencing for in-depth characterization. Key resistance mechanisms are discussed, including drug inactivation, target modification, altered transport, and metabolic adaptation. Additionally, we highlight strategies to mitigate the spread of AMR, such as dynamic resistance monitoring, innovative therapies like phage therapy and CRISPR-Cas technology, and tighter regulation of antibiotic use in animal production systems. This review provides actionable insights into E. coli resistance mechanisms and identifies promising directions for future antibiotic development and AMR management.

PRONAME: a user-friendly pipeline to process long-read nanopore metabarcoding data by generating high-quality consensus sequences

Background

The study of sample taxonomic composition has evolved from direct observations and labor-intensive morphological studies to different DNA sequencing methodologies. Most of these studies leverage the metabarcoding approach, which involves the amplification of a small taxonomically-informative portion of the genome and its subsequent high-throughput sequencing. Recent advances in sequencing technology brought by Oxford Nanopore Technologies have revolutionized the field, enabling portability, affordable cost and long-read sequencing, therefore leading to a significant increase in taxonomic resolution. However, Nanopore sequencing data exhibit a particular profile, with a higher error rate compared with Illumina sequencing, and existing bioinformatics pipelines for the analysis of such data are scarce and often insufficient, requiring specialized tools to accurately process long-read sequences.

Results

We present PRONAME (PROcessing NAnopore MEtabarcoding data), an open-source, user-friendly pipeline optimized for processing raw Nanopore sequencing data. PRONAME includes precompiled databases for complete 16S sequences (Silva138 and Greengenes2) and a newly developed and curated database dedicated to bacterial 16S-ITS-23S operon sequences. The user can also provide a custom database if desired, therefore enabling the analysis of metabarcoding data for any domain of life. The pipeline significantly improves sequence accuracy, implementing innovative error-correction strategies and taking advantage of the new sequencing chemistry to produce high-quality duplex reads. Evaluations using a mock community have shown that PRONAME delivers consensus sequences demonstrating at least 99.5% accuracy with standard settings (and up to 99.7%), making it a robust tool for genomic analysis of complex multi-species communities.

Conclusion

PRONAME meets the challenges of long-read Nanopore data processing, offering greater accuracy and versatility than existing pipelines. By integrating Nanopore-specific quality filtering, clustering and error correction, PRONAME produces high-precision consensus sequences. This brings the accuracy of Nanopore sequencing close to that of Illumina sequencing, while taking advantage of the benefits of long-read technologies.

Application of third-generation sequencing technology in the genetic testing of thalassemia

Thalassemia is an autosomal recessive genetic disorder and a common form of Hemoglobinopathy. It is classified into α-thalassemia and β-thalassemia. This disease is mainly prevalent in tropical and subtropical regions, including southern China. Severe α-thalassemia and intermediate α-thalassemia are among the most common birth defects in southern China. Intermediate α-thalassemia, also known as Hb H disease, is characterized by moderate anemia. Severe α-thalassemia, also known as Hb Bart's Hydrops fetalis syndrome, is a fatal condition. Infants with severe β-thalassemia do not show symptoms at birth but develop severe anemia later, requiring expensive treatment. Most untreated patients with severe β-thalassemia die in early childhood. Screening for thalassemia carriers and genetic diagnosis in high-prevalence areas significantly reduce the incidence of severe thalassemia. This review aims to summarize the genetic diagnostic approaches for thalassemia. Conventional genetic testing methods can identify 95-98% of thalassemia carriers but may miss rare thalassemia genotypes. Third-Generation Sequencing offers significant advantages in complementing other genetic diagnostic approaches, providing a basis for genetic counseling and prenatal diagnosis.

scIALM: A method for sparse scRNA-seq expression matrix imputation using the Inexact Augmented Lagrange Multiplier with low error

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of specific cell populations at the single-cell level, providing a foundation for studying cellular heterogeneity and patient pathological characteristics. It is effective for developmental, fertility, and disease studies. However, the cell-gene expression matrix of single-cell sequencing data is often sparse and contains numerous zero values. Some of the zero values derive from noise, where dropout noise has a large impact on downstream analysis. In this paper, we propose a method named scIALM for imputation recovery of sparse single-cell RNA data expression matrices, which employs the Inexact Augmented Lagrange Multiplier method to use sparse but clean (accurate) data to recover unknown entries in the matrix. We perform experimental analysis on four datasets, calling the expression matrix after Quality Control (QC) as the original matrix, and comparing the performance of scIALM with six other methods using mean squared error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC), and cosine similarity (CS). Our results demonstrate that scIALM accurately recovers the original data of the matrix with an error of 10e-4, and the mean value of the four metrics reaches 4.5072 (MSE), 0.765 (MAE), 0.8701 (PCC), 0.8896 (CS). In addition, at 10%-50% random masking noise, scIALM is the least sensitive to the masking ratio. For downstream analysis, this study uses adjusted rand index (ARI) and normalized mutual information (NMI) to evaluate the clustering effect, and the results are improved on three datasets containing real cluster labels.

Reprogramming human B cells with custom heavy-chain antibodies

The immunoglobulin locus of B cells can be reprogrammed by genome editing to produce custom or non-natural antibodies that are not induced by immunization. However, current strategies for antibody reprogramming require complex expression cassettes and do not allow for customization of the constant region of the antibody. Here we show that human B cells can be edited at the immunoglobulin heavy-chain locus to express heavy-chain-only antibodies that support alterations to both the fragment crystallizable domain and the antigen-binding domain, which can be based on both antibody and non-antibody components. Using the envelope protein (Env) from the human immunodeficiency virus as a model antigen, we show that B cells edited to express heavy-chain antibodies to Env support the regulated expression of B cell receptors and antibodies through alternative splicing and that the cells respond to the Env antigen in a tonsil organoid model of immunization. This strategy allows for the reprogramming of human B cells to retain the potential for in vivo amplification while producing molecules with flexibility of composition beyond that of standard antibodies.

Giraffe: A tool for comprehensive processing and visualization of multiple long-read sequencing data

Third-generation sequencing techniques have become increasingly popular due to their capacity to produce long, high-quality reads. Effective comparative analysis across various samples and sequencing platforms is essential for understanding biological mechanisms and establishing benchmark baselines. However, existing tools for long-read sequencing predominantly focus on quality control (QC) and processing for individual samples, complicating the comparison of multiple datasets. The lack of comprehensive tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. To address this gap, we present Giraffe (https://github.com/lrslab/Giraffe_View), a Python3-based command-line tool designed for comparative analysis and visualization across diverse samples and platforms. Giraffe facilitates the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its effectiveness has been demonstrated in various scenarios, including comparisons of sequencing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology, ONT vs. Pacific Biosciences, PacBio), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows).

Nanopore sequencing: flourishing in its teenage years

Over the past decade, nanopore sequencing has experienced significant advancements and changes, transitioning from an initially emerging technology to a significant instrument in the field of genomic sequencing. However, as advancements in next-generation sequencing technology persist, nanopore sequencing also improves. This paper reviews the developments, applications, and outlook on nanopore sequencing technology. Currently, nanopore sequencing supports both DNA and RNA sequencing, making it widely applicable in areas such as telomere-to-telomere (T2T) genome assembly, direct RNA sequencing (DRS), and metagenomics. The openness and versatility of nanopore sequencing have established it as a preferred option for an increasing number of research teams, signaling a transformative influence on life science research. As the nanopore sequencing technology advances, it provides a faster, more cost-effective approach with extended read lengths, demonstrating the significant potential for complex genome assembly, pathogen detection, environmental monitoring, and human disease research, offering a fresh perspective in sequencing technologies.

Long-Read Sequencing Revealing the Effectiveness of Captive Breeding Strategy for Improving the Gut Microbiota of Spotted Seal (Phoca largha)

The spotted seal (Phoca largha) is the sole pinniped species that can reproduce in China and has been classified as the First-Grade State Protection animal. The conventional method for the protection and maintenance of the spotted seal population is the captive maintenance of the species in artificially controlled environments. Nevertheless, the efficacy of the captive strategy remains uncertain, with the potential to impact the health of spotted seals through alterations in gut microbiota. In this study, PacBio sequencing based on the full-length of the bacterial 16S rRNA gene was applied to faeces from captive and wild spotted seals, thereby providing a first reference for the gut microbiota profile of spotted seals at the species scale. The gut microbiota of captive spotted seals was found to be more diverse than that of the wild population. The gut microbiota of spotted seals exhibited notable variation due to captive breeding, with an enrichment of Firmicutes and a reduction in Proteobacteria. The results of the co-occurrence network analysis indicated that the gut microbiota of captive spotted seals exhibited a greater degree of complexity and stability in comparison to that observed in their wild counterparts. The analysis of community assembly mechanisms revealed an increased determinism for the gut microbiota of captive individuals, with a concomitant decrease in the contribution of drift. Furthermore, the results of the predicted functions indicated a reduction in stress responses and an enhanced ability to metabolise sugars in the gut microbiota of captive spotted seals. In conclusion, the results of this study provide evidence that the current captive breeding strategy is an effective approach for improving the gut microbiota of spotted seals. Furthermore, this study demonstrates the potential of monitoring the gut microbiota to assess the health of marine mammals and inform conservation strategies for endangered species.

Humic substances increase tomato tolerance to osmotic stress while modulating vertically transmitted endophytic bacterial communities

While humic substances (HS) are recognized for their role in enhancing plant growth under abiotic stress by modulating hormonal and redox metabolisms, a key question remains: how do HS influence the microbiota associated with plants? This study hypothesizes that the effects of HS extend beyond plant physiology, impacting the plant-associated bacterial community. To explore this, we investigated the combined and individual impacts of HS and osmotic stress on tomato plant physiology and root endophytic communities. Tomatoes were grown within a sterile hydroponic system, which allowed the experiment to focus on seed-transmitted endophytic bacteria. Moreover, sequencing the 16S-ITS-23S region of the rrn operon (~4,500 bp) in a metabarcoding assay using the PNA-chr11 clamp nearly eliminated the reads assigned to Solanum lycopersicum and allowed the species-level identification of these communities. Our findings revealed that HS, osmotic stress, and their combined application induce changes in bacterial endophytic communities. Osmotic stress led to reduced plant growth and a decrease in Bradyrhizobium sp., while the application of HS under osmotic stress resulted in increased tomato growth, accompanied by an increase in Frigoribacterium sp., Roseateles sp., and Hymenobacter sp., along with a decrease in Sphingomonas sp. Finally, HS application under non-stress conditions did not affect plant growth but did alter the endophytic community, increasing Hymenobacter sp. and decreasing Sphingomonas sp. This study enhances the understanding of plant-endophyte interactions under stress and HS application, highlighting the significance of the vertically transmitted core microbiome in tomato roots and suggesting new insights into the mode of action of HS that was used as a biostimulant.

Continuous evolution of user-defined genes at 1 million times the genomic mutation rate

When nature evolves a gene over eons at scale, it produces a diversity of homologous sequences with patterns of conservation and change that contain rich structural, functional, and historical information about the gene. However, natural gene diversity accumulates slowly and likely excludes large regions of functional sequence space, limiting the information that is encoded and extractable. We introduce upgraded orthogonal DNA replication (OrthoRep) systems that radically accelerate the evolution of chosen genes under selection in yeast. When applied to a maladapted biosynthetic enzyme, we obtained collections of extensively diverged sequences with patterns that revealed structural and environmental constraints shaping the enzyme's activity. Our upgraded OrthoRep systems should support the discovery of factors influencing gene evolution, uncover previously unknown regions of fitness landscapes, and find broad applications in biomolecular engineering.

Progress in malaria genomic surveillance using long-read sequencing

Recent studies by Girgis et al. and de Cesare et al. promise to advance malaria genomic surveillance using inexpensive and portable long-read amplicon-sequencing technologies. These technologies allow rapid characterization of drug-resistance markers, antigenic diversity, and diagnostic target loci from dried blood spots, providing new tools for surveillance in endemic regions and informing interventions to combat malaria more effectively.

Enhancing testing efficacy of high-density SNP microarrays to distinguish pedigrees belonging to the same kinship class

Kinship testing, which involves genotyping genetic markers and comparing their profiles between individuals, holds significant applications in forensic science. However, the prevalent use of independent markers often lacks the discriminatory power to distinguish pedigrees belong to the same kinship class. While numerous studies have attempted to address this challenge through diverse approaches, the testing efficacy of high-density SNP microarrays in combination with the likelihood approach remains unclear. In this study, we further explored the utilization of linked autosomal SNPs derived from microarrays with the likelihood approach. Several SNP panels with differing numbers of loci were developed and putative pedigrees were constructed to evaluated to test their efficacy in distinguishing second-degree relationships, including grandparent-grandchild, half-siblings, and avuncular. Our findings indicate that the use of high-density SNP microarrays is theoretically feasible for discriminating second-degree relationships, with balanced classification rates ranging from 0.444 to 0.853. Moreover, to optimize the practical effectiveness of discriminating pedigrees belonging to the same kinship class, several other aspects such as adding additional SNPs or an additional relative and examining the effects of genotype errors and population selection were discussed. Our results revealed that the employment of denser marker sets with more accurate genotyping methods may be beneficial. Additionally, the inclusion of additional relatives and the selection of an appropriate reference population also appear to be crucial factors for enhancing the accuracy of kinship testing. In conclusion, our study provides insights into the potential of high-density SNPs in kinship testing and highlights the need for further optimization and examination into various factors that may contribute to enhancing testing efficacy.

Microbial community assembly patterns at the species level in different parts of the medium temperature Daqu during fermentation

Medium-temperature Daqu (MT-Daqu) serves as a crucial saccharifying and fermentation agent in the production of strong-flavor Baijiu. Due to the spatial heterogeneity of solid fermentation, significant differences occurred in the fermentation state and appearance features in different parts of Daqu during fermentation. Currently, the understanding of the underlying mechanism behind this phenomenon remains limited. Here, we analyzed the microbial succession and assembly models and driving factors in different parts of MT-Daqu at the species level based on the PacBio single-molecule real-time sequencing technology. The results showed significantly different bacterial and fungal community compositions, successions, and interaction patterns in different parts of MT-Daqu. The bacterial community composition and succession model in the middle layer were similar to those in the core layer, whereas the fungal community composition and succession model in the surface layer were similar to those in the middle layer. The co-occurrence network analysis showed that microbial interaction is stronger in the middle and core layers than in the surface layer. Analyses based on both niche theory and neutral theory models indicated that deterministic processes predominantly governed the microbial community assembly and these processes played an increasingly important role from the surface to the core layer. Random forest analysis revealed that temperature was the primary endogenous factor driving the bacterial and fungal community assembly. The results of this study contribute to a better understanding of the microbial community in MT-Daqu and are helpful for the quality control of MT-Daqu fermentation.

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.

Nanopore sequencing with unique molecular identifiers enables accurate mutation analysis and haplotyping in the complex lipoprotein(a) KIV-2 VNTR

BACKGROUND

Repetitive genome regions, such as variable number of tandem repeats (VNTR) or short tandem repeats (STR), are major constituents of the uncharted dark genome and evade conventional sequencing approaches. The protein-coding LPA kringle IV type-2 (KIV-2) VNTR (5.6 kb per unit, 1-40 units per allele) is a medically highly relevant example with a particularly intricate structure, multiple haplotypes, intragenic homologies, and an intra-VNTR STR. It is the primary regulator of plasma lipoprotein(a) [Lp(a)] concentrations, an important cardiovascular risk factor. Lp(a) concentrations vary widely between individuals and ancestries. Multiple variants and functional haplotypes in the LPA gene and especially in the KIV-2 VNTR strongly contribute to this variance.

METHODS

We evaluated the performance of amplicon-based nanopore sequencing with unique molecular identifiers (UMI-ONT-Seq) for SNP detection, haplotype mapping, VNTR unit consensus sequence generation, and copy number estimation via coverage-corrected haplotypes quantification in the KIV-2 VNTR. We used 15 human samples and low-level mixtures (0.5 to 5%) of KIV-2 plasmids as a validation set. We then applied UMI-ONT-Seq to extract KIV-2 VNTR haplotypes in 48 multi-ancestry 1000 Genome samples and analyzed at scale a poorly characterized STR within the KIV-2 VNTR.

RESULTS

UMI-ONT-Seq detected KIV-2 SNPs down to 1% variant level with high sensitivity, specificity, and precision (0.977 ± 0.018; 1.000 ± 0.0005; 0.993 ± 0.02) and accurately retrieved the full-length haplotype of each VNTR unit. Human variant levels were highly correlated with next-generation sequencing (R2 = 0.983) without bias across the whole variant level range. Six reads per UMI produced sequences of each KIV-2 unit with Q40 quality. The KIV-2 repeat number determined by coverage-corrected unique haplotype counting was in close agreement with droplet digital PCR (ddPCR), with 70% of the samples falling even within the narrow confidence interval of ddPCR. We then analyzed 62,679 intra-KIV-2 STR sequences and explored KIV-2 SNP haplotype patterns across five ancestries.

CONCLUSIONS

UMI-ONT-Seq accurately retrieves the SNP haplotype and precisely quantifies the VNTR copy number of each repeat unit of the complex KIV-2 VNTR region across multiple ancestries. This study utilizes the KIV-2 VNTR, presenting a novel and potent tool for comprehensive characterization of medically relevant complex genome regions at scale.

Species-level understanding of the bacterial community in Daqu based on full-length 16S rRNA gene sequences

Daqu is used as the fermentation starter of Baijiu and contributes diversified functional microbes for saccharifying grains and converting sugars into ethanol and aroma components in Baijiu products. Daqu is mainly classified into three types, namely low (LTD), medium (MTD) and high (HTD) temperature Daqu, according to the highest temperatures reached in their fermentation processes. In this study, we used the PacBio small-molecule real-time (SMRT) sequencing technology to determine the full-length 16 S rRNA gene sequences from the metagenomes of 296 samples of different types of Daqu collected from ten provinces in China, and revealed the bacterial diversity at the species level in the Daqu samples. We totally identified 310 bacteria species, including 78 highly abundant species (with a relative abundance >0.1% each) which accounted for 91.90% of the reads from all the Daqu samples. We also recognized the differentially enriched bacterial species in different types of Daqu, and in the Daqu samples with the same type but from different provinces. Specifically, Lactobacillales, Enterobacterales and Bacillaceae were significantly enriched in the LTD, MTD and HTD groups, respectively. The potential co-existence and exclusion relationships among the bacteria species involved in all the Daqu samples and in the LTD, MTD and HTD samples from a specific region were also identified. These results provide a better understanding of the bacterial diversity in different types of Daqu at the species level.

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.

Mitochondrial sequence variants: testing imputation accuracy and their association with dairy cattle milk traits

BACKGROUND

Mitochondrial genomes differ from the nuclear genome and in humans it is known that mitochondrial variants contribute to genetic disorders. Prior to genomics, some livestock studies assessed the role of the mitochondrial genome but these were limited and inconclusive. Modern genome sequencing provides an opportunity to re-evaluate the potential impact of mitochondrial variation on livestock traits. This study first evaluated the empirical accuracy of mitochondrial sequence imputation and then used real and imputed mitochondrial sequence genotypes to study the role of mitochondrial variants on milk production traits of dairy cattle.

RESULTS

The empirical accuracy of imputation from Single Nucleotide Polymorphism (SNP) panels to mitochondrial sequence genotypes was assessed in 516 test animals of Holstein, Jersey and Red breeds using Beagle software and a sequence reference of 1883 animals. The overall accuracy estimated as the Pearson's correlation squared (R2) between all imputed and real genotypes across all animals was 0.454. The low accuracy was attributed partly to the majority of variants having low minor allele frequency (MAF < 0.005) but also due to variants in the hypervariable D-loop region showing poor imputation accuracy. Beagle software provides an internal estimate of imputation accuracy (DR2), and 10 percent of the total 1927 imputed positions showed DR2 greater than 0.9 (N = 201). There were 151 sites with empirical R2 > 0.9 (of 954 variants segregating in the test animals) and 138 of these overlapped the sites with DR2 > 0.9. This suggests that the DR2 statistic is a reasonable proxy to select sites that are imputed with higher accuracy for downstream analyses. Accordingly, in the second part of the study mitochondrial sequence variants were imputed from real mitochondrial SNP panel genotypes of 9515 Australian Holstein, Jersey and Red dairy cattle. Then, using only sites with DR2 > 0.900 and real genotypes, we undertook a genome-wide association study (GWAS) for milk, fat and protein yields. The GWAS mitochondrial SNP effects were not significant.

CONCLUSION

The accuracy of imputation of mitochondrial genotypes from the SNP panel to sequence was generally low. The Beagle DR2 statistic enabled selection of sites imputed with higher empirical accuracy. We recommend building larger reference populations with mitochondrial sequence to improve the accuracy of imputing less common variants and ensuring that SNP panels include common variants in the D-loop region.

Harnessing non-standard nucleic acids for highly sensitive icosaplex (20-plex) detection of microbial threats

Environmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. We benchmarked this assay using a low-cost, portable sequencing platform (Oxford Nanopore) on wastewater, soil, and human stool samples. Using parallelized multi-target TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay, there was 74% agreement on positive calls and 97% agreement on negative calls. Additionally, we show how sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish sub-species. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.

Nanopore sequencing provides snapshots of the genetic variation within salmonid alphavirus-3 (SAV3) during an ongoing infection in Atlantic salmon (Salmo salar) and brown trout (Salmo trutta)

Frequent RNA virus mutations raise concerns about evolving virulent variants. The purpose of this study was to investigate genetic variation in salmonid alphavirus-3 (SAV3) over the course of an experimental infection in Atlantic salmon and brown trout. Atlantic salmon and brown trout parr were infected using a cohabitation challenge, and heart samples were collected for analysis of the SAV3 genome at 2-, 4- and 8-weeks post-challenge. PCR was used to amplify eight overlapping amplicons covering 98.8% of the SAV3 genome. The amplicons were subsequently sequenced using the Nanopore platform. Nanopore sequencing identified a multitude of single nucleotide variants (SNVs) and deletions. The variation was widespread across the SAV3 genome in samples from both species. Mostly, specific SNVs were observed in single fish at some sampling time points, but two relatively frequent (i.e., major) SNVs were observed in two out of four fish within the same experimental group. Two other, less frequent (i.e., minor) SNVs only showed an increase in frequency in brown trout. Nanopore reads were de novo clustered using a 99% sequence identity threshold. For each amplicon, a number of variant clusters were observed that were defined by relatively large deletions. Nonmetric multidimensional scaling analysis integrating the cluster data for eight amplicons indicated that late in infection, SAV3 genomes isolated from brown trout had greater variation than those from Atlantic salmon. The sequencing methods and bioinformatics pipeline presented in this study provide an approach to investigate the composition of genetic diversity during viral infections.

NERD-seq: a novel approach of Nanopore direct RNA sequencing that expands representation of non-coding RNAs

Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Species-level characterization of gut microbiota and their metabolic role in kidney stone formation using full-length 16S rRNA sequencing

The critical role of the human gut microbiota in kidney stone formation remains largely unknown, due to the low taxonomic resolution of previous sequencing technologies. Therefore, this study aimed to explore the gut microbiota using high-throughput sequencing to provide valuable insights and identify potential bacterial species and metabolite roles involved in kidney stone formation. The overall gut bacterial community and its potential functions in healthy participants and patients were examined using PacBio sequencing targeting the full-length 16S rRNA gene, coupled with stone and statistical analyses. Most kidney stones comprised calcium oxalate and calcium phosphate (75%), pure calcium oxalate (20%), and calcium phosphate and magnesium phosphate (5%), with higher content of Ca (130,510.5 ± 108,362.7 ppm) followed by P (18,746.4 ± 23,341.2 ppm). The microbial community structure was found to be weaker in patients' kidney stone samples, followed by patients' stool samples, than in healthy participants' stool samples. The most abundant bacterial species in kidney stone samples was uncultured Morganella, whereas that in patient and healthy participant stool samples was Bacteroides vulgatus. Similarly, Akkermansia muciniphila was significantly enriched in patient stool samples at the species level, whereas Bacteroides plebeius was significantly enriched in kidney stone samples than that in healthy participant stool samples. Three microbial metabolic pathways, TCA cycle, fatty acid oxidation, and urea cycle, were significantly enriched in kidney stone patients compared to healthy participants. Inferring bacteria at the species level revealed key players in kidney stone formation, enhancing the clinical relevance of gut microbiota.

Approach for Phased Sequence-Based Genotyping of the Critical Pharmacogene Dihydropyrimidine Dehydrogenase (DPYD)

Pre-treatment genotyping of four well-characterized toxicity risk-variants in the dihydropyrimidine dehydrogenase gene (DPYD) has been widely implemented in Europe to prevent serious adverse effects in cancer patients treated with fluoropyrimidines. Current genotyping practices are largely limited to selected commonly studied variants and are unable to determine phasing when more than one variant allele is detected. Recent evidence indicates that common DPYD variants modulate the functional impact of deleterious variants in a phase-dependent manner, where a cis- or a trans-configuration translates into different toxicity risks and dosing recommendations. DPYD is a large gene with 23 exons spanning nearly a mega-base of DNA, making it a challenging candidate for full-gene sequencing in the diagnostic setting. Herein, we present a time- and cost-efficient long-read sequencing approach for capturing the complete coding region of DPYD. We demonstrate that this method can reliably produce phased genotypes, overcoming a major limitation with current methods. This method was validated using 21 subjects, including two cancer patients, each of whom carried multiple DPYD variants. Genotype assignments showed complete concordance with conventional approaches. Furthermore, we demonstrate that the method is robust to technical challenges inherent in long-range sequencing of PCR products, including reference alignment bias and PCR chimerism.

Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs

Next-generation sequencing (NGS), represented by Illumina platforms, has been an essential cornerstone of basic and applied research. However, the sequencing error rate of 1 per 1000 bp (10-3) represents a serious hurdle for research areas focusing on rare mutations, such as somatic mosaicism or microbe heterogeneity. By examining the high-fidelity sequencing methods developed in the past decade, we summarized three major factors underlying errors and the corresponding 12 strategies mitigating these errors. We then proposed a novel framework to classify 11 preexisting representative methods according to the corresponding combinatory strategies and identified three trends that emerged during methodological developments. We further extended this analysis to eight long-read sequencing methods, emphasizing error reduction strategies. Finally, we suggest two promising future directions that could achieve comparable or even higher accuracy with lower costs in both NGS and long-read sequencing.

Influenza A defective viral genomes and non-infectious particles are increased by host PI3K inhibition via anti-cancer drug alpelisib

RNA viruses produce abundant defective viral genomes during replication, setting the stage for interactions between viral genomes that alter the course of pathogenesis. Harnessing these interactions to develop antivirals has become a recent goal of intense research focus. Despite decades of research, the mechanisms that regulate the production and interactions of Influenza A defective viral genomes are still unclear. The role of the host is essentially unexplored; specifically, it remains unknown whether host metabolism can influence the formation of defective viral genomes and the particles that house them. To address this question, we manipulated host cell anabolic signaling activity and monitored the production of defective viral genomes and particles by A/H1N1 and A/H3N2 strains, using a combination of single-cell immunofluorescence quantification, third-generation long-read sequencing, and the cluster-forming assay, a method we developed to titer defective and fully-infectious particles simultaneously. Here we show that alpelisib (Piqray), a highly selective inhibitor of mammalian Class 1a phosphoinositide-3 kinase (PI3K) receptors, significantly changed the proportion of defective particles and viral genomes (specifically deletion-containing viral genomes) in a strain-specific manner, under conditions that minimize multiple cycles of replication. Alpelisib pre-treatment of cells led to an increase in defective particles in the A/H3N2 strain, while the A/H1N1 strain showed a decrease in total viral particles. In the same infections, we found that defective viral genomes of polymerase and antigenic segments increased in the A/H1N1 strain, while the total particles decreased suggesting defective interference. We also found that the average deletion size in polymerase complex viral genomes increased in both the A/H3N2 and A/H1N1 strains. The A/H1N1 strain, additionally showed a dose-dependent increase in total number of defective viral genomes. In sum, we provide evidence that host cell metabolism can increase the production of defective viral genomes and particles at an early stage of infection, shifting the makeup of the infection and potential interactions among virions. Given that Influenza A defective viral genomes can inhibit pathogenesis, our study presents a new line of investigation into metabolic states associated with less severe flu infection and the potential induction of these states with metabolic drugs.

The impact of next-generation sequencing for diagnosis and disease understanding of myeloid malignancies

INTRODUCTION

Defining the chromosomal and molecular changes associated with myeloid neoplasms (MNs) optimizes clinical care through improved diagnosis, prognosis, treatment planning, and patient monitoring. This review will concisely describe the techniques used to profile MNs clinically today, with descriptions of challenges and emerging approaches that may soon become standard-of-care.

AREAS COVERED

In this review, the authors discuss molecular assessment of MNs using non-sequencing techniques, including conventional cytogenetic analysis, fluorescence in situ hybridization, chromosomal genomic microarray testing; as well as DNA- or RNA-based next-generation sequencing (NGS) assays; and sequential monitoring via digital PCR or measurable residual disease assays. The authors explain why distinguishing somatic from germline alleles is critical for optimal management. Finally, they introduce emerging technologies, such as long-read, whole exome/genome, and single-cell sequencing, which are reserved for research purposes currently but will become clinical tests soon.

EXPERT OPINION

The authors describe challenges to the adoption of comprehensive genomic tests for those in resource-constrained environments and for inclusion into clinical trials. In the future, all aspects of patient care will likely be influenced by the adaptation of artificial intelligence and mathematical modeling, fueled by rapid advances in telecommunications.

MiDAS 5: Global diversity of bacteria and archaea in anaerobic digesters

Anaerobic digestion of organic waste into methane and carbon dioxide (biogas) is carried out by complex microbial communities. Here, we use full-length 16S rRNA gene sequencing of 285 full-scale anaerobic digesters (ADs) to expand our knowledge about diversity and function of the bacteria and archaea in ADs worldwide. The sequences are processed into full-length 16S rRNA amplicon sequence variants (FL-ASVs) and are used to expand the MiDAS 4 database for bacteria and archaea in wastewater treatment systems, creating MiDAS 5. The expansion of the MiDAS database increases the coverage for bacteria and archaea in ADs worldwide, leading to improved genus- and species-level classification. Using MiDAS 5, we carry out an amplicon-based, global-scale microbial community profiling of the sampled ADs using three common sets of primers targeting different regions of the 16S rRNA gene in bacteria and/or archaea. We reveal how environmental conditions and biogeography shape the AD microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 692 genera and 1013 species. These represent 84-99% and 18-61% of the accumulated read abundance, respectively, across samples depending on the amplicon primers used. Finally, we examine the global diversity of functional groups with known importance for the anaerobic digestion process.