Long-read Sequencing Technologies Research Articles

Scalable telomere-to-telomere assembly for diploid and polyploid genomes with double graph.

Despite advances in long-read sequencing technologies, constructing a near telomere-to-telomere assembly is still computationally demanding. Here we present hifiasm (UL), an efficient de novo assembly algorithm combining multiple sequencing technologies to scale up population-wide near telomere-to-telomere assemblies. Applied to 22 human and two plant genomes, our algorithm produces better diploid assemblies at a cost of an order of magnitude lower than existing methods, and it also works with polyploid genomes.

Characterisation of the novel HLA-C*15:274 allele using short and long-read sequencing technologies.

The novel HLA-C*15:274 allele, first described in a potential bone marrow donor from Brazil.

Characterisation of the novel HLA-B*35:593 allele using short and long-read sequencing technologies.

The novel HLA-B*35:593 allele, first described in a potential bone marrow donor from Brazil.

Unveiling microbial diversity: harnessing long-read sequencing technology.

Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads. We provide insights into the advantages and disadvantages of long reads over short reads and their evolution from the early days of long-read sequencing to their recent impact on metagenomics and clinical diagnostics. We further point out remaining challenges for the field such as the integration of methylation signals in sub-strain analysis and the lack of benchmarks.

Nanopore and Illumina sequencing reveal different viral populations from human gut samples.

The advent of viral metagenomics, or viromics, has improved our knowledge and understanding of global viral diversity. High-throughput sequencing technologies enable explorations of the ecological roles, contributions to host metabolism, and the influence of viruses in various environments, including the human intestinal microbiome. However, bacterial metagenomic studies frequently have the advantage. The adoption of advanced technologies like long-read sequencing has the potential to be transformative in refining viromics and metagenomics. Here, we examined the effectiveness of long-read and hybrid sequencing by comparing Illumina short-read and Oxford Nanopore Technology (ONT) long-read sequencing technologies and different assembly strategies on recovering viral genomes from human faecal samples. Our findings showed that if a single sequencing technology is to be chosen for virome analysis, Illumina is preferable due to its superior ability to recover fully resolved viral genomes and minimise erroneous genomes. While ONT assemblies were effective in recovering viral diversity, the challenges related to input requirements and the necessity for amplification made it less ideal as a standalone solution. However, using a combined, hybrid approach enabled a more authentic representation of viral diversity to be obtained within samples.

Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data

Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.

Phased nanopore assembly with Shasta and modular graph phasing with GFAse.

Reference-free genome phasing is vital for understanding allele inheritance and the impact of single-molecule DNA variation on phenotypes. To achieve thorough phasing across homozygous or repetitive regions of the genome, long-read sequencing technologies are often used to perform phased de novo assembly. As a step toward reducing the cost and complexity of this type of analysis, we describe new methods for accurately phasing Oxford Nanopore Technologies (ONT) sequence data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of ONT PromethION sequencing, including those using proximity ligation, and show that newer, higher accuracy ONT reads substantially improve assembly quality.

MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes.

With the rapid increase in throughput of long-read sequencing technologies, recent studies have explored their potential for taxonomic classification by using alignment-based approaches to reduce the impact of higher sequencing error rates. While alignment-based methods are generally slower, k-mer-based taxonomic classifiers can overcome this limitation, potentially at the expense of lower sensitivity for strains and species that are not in the database. We present MetageNN, a memory-efficient long-read taxonomic classifier that is robust to sequencing errors and missing genomes. MetageNN is a neural network model that uses short k-mer profiles of sequences to reduce the impact of distribution shifts on error-prone long reads. Benchmarking MetageNN against other machine learning approaches for taxonomic classification (GeNet) showed substantial improvements with long-read data (20% improvement in F1 score). By utilizing nanopore sequencing data, MetageNN exhibits improved sensitivity in situations where the reference database is incomplete. It surpasses the alignment-based MetaMaps and MEGAN-LR, as well as the k-mer-based Kraken2 tools, with improvements of 100%, 36%, and 23% respectively at the read-level analysis. Notably, at the community level, MetageNN consistently demonstrated higher sensitivities than the previously mentioned tools. Furthermore, MetageNN requires < 1/4th of the database storage used by Kraken2, MEGAN-LR and MMseqs2 and is > 7× faster than MetaMaps and GeNet and > 2× faster than MEGAN-LR and MMseqs2. This proof of concept work demonstrates the utility of machine-learning-based methods for taxonomic classification using long reads. MetageNN can be used on sequences not classified by conventional methods and offers an alternative approach for memory-efficient classifiers that can be optimized further.

Toward understanding the role of genomic repeat elements in neurodegenerative diseases

Abstract Neurodegenerative diseases cause great medical and economic burdens for both patients and society; however, the complex molecular mechanisms thereof are not yet well understood. With the development of high-coverage sequencing technology, researchers have started to notice that genomic repeat regions, previously neglected in search of disease culprits, are active contributors to multiple neurodegenerative diseases. In this review, we describe the association between repeat element variants and multiple degenerative diseases through genome-wide association studies and targeted sequencing. We discuss the identification of disease-relevant repeat element variants, further powered by the advancement of long-read sequencing technologies and their related tools, and summarize recent findings in the molecular mechanisms of repeat element variants in brain degeneration, such as those causing transcriptional silencing or RNA-mediated gain of toxic function. Furthermore, we describe how in silico predictions using innovative computational models, such as deep learning language models, could enhance and accelerate our understanding of the functional impact of repeat element variants. Finally, we discuss future directions to advance current findings for a better understanding of neurodegenerative diseases and the clinical applications of genomic repeat elements.

A de novo genome assembly of Solanum bulbocastanum Dun., a Mexican diploid species reproductively isolated from the A-genome species, including cultivated potatoes.

Potato and its wild relatives are distributed mainly in the Mexican highlands and central Andes of South America. The South American A-genome species, including cultivated potatoes, are reproductively isolated from Mexican diploid species. Whole-genome sequencing has disclosed genome structure and similarity, mostly in cultivated potatoes and their closely related species. In this study, we generated a chromosome-scale assembly of the genome of a Mexican diploid species, Solanum bulbocastanum Dun., using PacBio long-read sequencing, Optical mapping, and Hi-C scaffolding technologies. The final sequence assembly consisted of 737.9 Mb, among which 647.0 Mb were anchored to the 12 chromosomes. Compared with chromosome-scale assemblies of S. lycopersicum (tomato), S. etuberosum (non-tuber-bearing species with E genome), S. verrucosum, S. chacoense, S. multidissectum, and S. phureja (all four are A-genome species), the S. bulbocastnum genome was the shortest. It contained fewer transposable elements (56.2%) than A-genome species. A cluster analysis was performed based on pairwise ratios of syntenic regions among the seven chromosome-scale assemblies, showing that the A-genome species were first clustered as a distinct group. Then, this group was clustered with S. bulbocastanum. Sequence similarity in 1,624 single-copy orthologous gene groups among 36 Solanum species and clones separated S. bulbocastanum as a specific group, including other Mexican diploid species, from the A-genome species. Therefore, the S. bulbocastanum genome differs in genome structure and gene sequences from the A-genome species. These findings provide important insights into understanding and utilizing the genetic diversity of S. bulbocastanum and the other Mexican diploid species in potato breeding.

The chromosomal-scale genome sequencing and assembly of Athetis lepigone

Athetis lepigone is an emerging highly polyphagous insect pest reported to cause crop damage in several European and Asian countries. However, our understanding of its genetic adaptation mechanisms has been limited due to lack of high-quality genetic resources. In this study, we present a chromosomal-level genome of A. lepigone, representing the first species in the genus of Athetis. We employed PacBio long-read sequencing and Hi-C technologies to generate 612.49 Mb genome assembly which contains 42.43% repeat sequences with a scaffold N50 of 20.9 Mb. The contigs were successfully clustered into 31 chromosomal-size scaffolds with 37% GC content. BUSCO assessment revealed a genome completeness of 97.4% with 96.3 identified as core Arthropoda single copy orthologs. Among the 17,322 genes that were predicted, 15,965 genes were functionally annotated, representing a coverage of 92.17%. Furthermore, we revealed 106 P450, 37 GST, 27 UGT, and 74 COE gene families in the genome of A. lepigone. This genome provides a significant and invaluable genomic resource for further research across the entire genus of Athetis.

Remarkably High Repeat Content in the Genomes of Sparrows: The Importance of Genome Assembly Completeness for Transposable Element Discovery.

Transposable elements (TE) play critical roles in shaping genome evolution. Highly repetitive TE sequences are also a major source of assembly gaps making it difficult to fully understand the impact of these elements on host genomes. The increased capacity of long-read sequencing technologies to span highly repetitive regions promises to provide new insights into patterns of TE activity across diverse taxa. Here we report the generation of highly contiguous reference genomes using PacBio long-read and Omni-C technologies for three species of Passerellidae sparrow. We compared these assemblies to three chromosome-level sparrow assemblies and nine other sparrow assemblies generated using a variety of short- and long-read technologies. All long-read based assemblies were longer (range: 1.12 to 1.41 Gb) than short-read assemblies (0.91 to 1.08 Gb) and assembly length was strongly correlated with the amount of repeat content. Repeat content for Bell's sparrow (31.2% of genome) was the highest level ever reported within the order Passeriformes, which comprises over half of avian diversity. The highest levels of repeat content (79.2% to 93.7%) were found on the W chromosome relative to other regions of the genome. Finally, we show that proliferation of different TE classes varied even among species with similar levels of repeat content. These patterns support a dynamic model of TE expansion and contraction even in a clade where TEs were once thought to be fairly depauperate and static. Our work highlights how the resolution of difficult-to-assemble regions of the genome with new sequencing technologies promises to transform our understanding of avian genome evolution.

Profiling genome-wide methylation in two maples: Fine-scale approaches to detection with nanopore technology.

DNA methylation is critical to the regulation of transposable elements and gene expression and can play an important role in the adaptation of stress response mechanisms in plants. Traditional methods of methylation quantification rely on bisulfite conversion that can compromise accuracy. Recent advances in long-read sequencing technologies allow for methylation detection in real time. The associated algorithms that interpret these modifications have evolved from strictly statistical approaches to Hidden Markov Models and, recently, deep learning approaches. Much of the existing software focuses on methylation in the CG context, but methylation in other contexts is important to quantify, as it is extensively leveraged in plants. Here, we present methylation profiles for two maple species across the full range of 5mC sequence contexts using Oxford Nanopore Technologies (ONT) long-reads. Hybrid and reference-guided assemblies were generated for two new Acer accessions: Acer negundo (box elder; 65x ONT and 111X Illumina) and Acer saccharum (sugar maple; 93x ONT and 148X Illumina). The ONT reads generated for these assemblies were re-basecalled, and methylation detection was conducted in a custom pipeline with the published Acer references (PacBio assemblies) and hybrid assemblies reported herein to generate four epigenomes. Examination of the transposable element landscape revealed the dominance of LTR Copia elements and patterns of methylation associated with different classes of TEs. Methylation distributions were examined at high resolution across gene and repeat density and described within the broader angiosperm context, and more narrowly in the context of gene family dynamics and candidate nutrient stress genes.

Pacybara: accurate long-read sequencing for barcoded mutagenized allelic libraries.

Long-read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library. Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or nonunique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues. Pacybara, freely available at https://github.com/rothlab/pacybara, is implemented using R, Python, and bash for Linux. It runs on GNU/Linux HPC clusters via Slurm, PBS, or GridEngine schedulers. A single-machine simplex version is also available.

A chromosome-level genome assembly of East Asia endemic minnow Zacco platypus

Zacco platypus is an endemic colorful freshwater minnow that is intensively distributed in East Asia. In this study, two adult female individuals collected from Haihe River basin were used for karyotypic study and genome sequencing, respectively. The karyotype formula of Z. platypus is 2N = 48 = 18 M + 24SM/ST + 6 T. We used PacBio long-read sequencing and Hi-C technology to assemble a chromosome-level genome of Z. platypus. As a result, an 814.87 Mb genome was assembled with the PacBio long reads. Subsequently, 98.64% assembled sequences were anchored into 24 chromosomes based on the Hi-C data. The chromosome-level assembly contained 54 scaffolds with a N50 length of 32.32 Mb. Repeat elements accounted for 52.35% in genome, and 24,779 protein-coding genes were predicted, with 92.11% were functionally annotated with the public databases. BUSCO analysis yielded a completeness score of 96.5%. This high-quality genome assembly provides valuable resources for future functional genomic research, comparative genomics, and evolutionary studies of genus Zacco.

Comprehensive transcriptome analysis reveals altered mRNA splicing and post-transcriptional changes in the aged mouse brain.

A comprehensive understanding of molecular changes during brain aging is essential to mitigate cognitive decline and delay neurodegenerative diseases. The interpretation of mRNA alterations during brain aging is influenced by the health and age of the animal cohorts studied. Here, we carefully consider these factors and provide an in-depth investigation of mRNA splicing and dynamics in the aging mouse brain, combining short- and long-read sequencing technologies with extensive bioinformatic analyses. Our findings encompass a spectrum of age-related changes, including differences in isoform usage, decreased mRNA dynamics and a module showing increased expression of neuronal genes. Notably, our results indicate a reduced abundance of mRNA isoforms leading to nonsense-mediated RNA decay and suggest a regulatory role for RNA-binding proteins, indicating that their regulation may be altered leading to the reshaping of the aged brain transcriptome. Collectively, our study highlights the importance of studying mRNA splicing events during brain aging.

Genome Sequence of Fusarium oxysporum f. sp. malus HS2 Causing Apple Replant Disease

Apple replant disease (ARD) has been observed to cause 50% mortality in fields where apples are replanted, which has seriously limited the sustainable development of China's apple industry. Our previous study revealed that Fusarium oxysporum is one of the causal agents of ARD; however, its pathogenic mechanism is still unclear. In this study, we obtained the draft genome of Fusarium oxysporum f. sp. malus HS2 using a combination of long-read single-molecule real-time sequencing technology (Pacific Biosciences [PacBio]) and MGISEQ sequencing. The total length of the assembled was 56,825,273 bp, and the GC content was 47.72%. The genome provides a valuable resource for facilitating our understanding the response of F. oxysporum to apple. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

UrsaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data.

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.

Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection

BackgroundThe timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood.MethodsBlood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol—SepsiPURE.ResultsAfter first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50–100 colony forming units (CFU)/mL to 1–5 CFU/mL.ConclusionIn this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Microbiome diversity and zoonotic bacterial pathogen prevalence in Peromyscus mice from agricultural landscapes and synanthropic habitat.

Rodents are key reservoirs of zoonotic pathogens and play an important role in disease transmission to humans. Importantly, anthropogenic land-use change has been found to increase the abundance of rodents that thrive in human-built environments (synanthropic rodents), particularly rodent reservoirs of zoonotic disease. Anthropogenic environments also affect the microbiome of synanthropic wildlife, influencing wildlife health and potentially introducing novel pathogens. Our objective was to examine the effect of agricultural development and synanthropic habitat on microbiome diversity and the prevalence of zoonotic bacterial pathogens in wild Peromyscus mice to better understand the role of these rodents in pathogen maintenance and transmission. We conducted 16S amplicon sequencing on faecal samples using long-read nanopore sequencing technology to characterize the rodent microbiome. We compared microbiome diversity and composition between forest and synanthropic habitats in agricultural and undeveloped landscapes and screened for putative pathogenic bacteria. Microbiome richness, diversity, and evenness were higher in the agricultural landscape and synanthropic habitat compared to undeveloped-forest habitat. Microbiome composition also differed significantly between agricultural and undeveloped landscapes and forest and synanthropic habitats. We detected overall low diversity and abundance of putative pathogenic bacteria, though putative pathogens were more likely to be found in mice from the agricultural landscape. Our findings show that landscape- and habitat-level anthropogenic factors affect Peromyscus microbiomes and suggest that landscape-level agricultural development may be important to predict zoonotic pathogen prevalence. Ultimately, understanding how anthropogenic land-use change and synanthropy affect rodent microbiomes and pathogen prevalence is important to managing transmission of rodent-borne zoonotic diseases to humans.