Long-read Sequencing Technologies Research Articles

The nuclear and mitochondrial genome assemblies of Tetragonisca angustula (Apidae: Meliponini), a tiny yet remarkable pollinator in the Neotropics

BackgroundThe field of bee genomics has considerably advanced in recent years, however, the most diverse group of honey producers on the planet, the stingless bees, are still largely neglected. In fact, only eleven of the ~ 600 described stingless bee species have been sequenced, and only three using a long-read (LR) sequencing technology. Here, we sequenced the nuclear and mitochondrial genomes of the most common, widespread and broadly reared stingless bee in Brazil and other neotropical countries—Tetragonisca angustula (popularly known in Brazil as jataí).ResultsA total of 48.01 Gb of DNA data were generated, including 2.31 Gb of Pacific Bioscience HiFi reads and 45.70 Gb of Illumina short reads (SRs). Our preferred assembly comprised 683 contigs encompassing 284.49 Mb, 62.84 Mb of which (22.09%) corresponded to 445,793 repetitive elements. N50, L50 and complete BUSCOs reached 1.02 Mb, 91 contigs and 97.1%, respectively. We predicted that the genome of T. angustula comprises 17,459 protein-coding genes and 4,108 non-coding RNAs. The mitogenome consisted of 17,410 bp, and all 37 genes were found to be on the positive strand, an unusual feature among bees. A phylogenomic analysis of 26 hymenopteran species revealed that six odorant receptor orthogroups of T. angustula were found to be experiencing rapid evolution, four of them undergoing significant contractions.ConclusionsHere, we provided the first nuclear and mitochondrial genome assemblies for the ecologically and economically important T. angustula, the fourth stingless bee species to be sequenced with LR technology thus far. We demonstrated that even relatively small amounts of LR data in combination with sufficient SR data can yield high-quality genome assemblies for bees.

Characterisation of the novel HLA-DRB1*03:215 allele using short- and long-read sequencing technologies.

The novel HLA-DRB1*03:215 allele, first described in a potential bone marrow donor from Brazil.

Characterisation of the novel HLA-B*18:243 allele using short- and long-read sequencing technologies.

The novel HLA-B*18:243 allele, first described in a potential bone marrow donor from Brazil.

GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences.

Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.

A chromosome-scale genome assembly of the nipa palm hispid beetle Octodonta nipae

Nipa palm hispid beetle (Octodonta nipae) is an insect species that is native to Malaysia but has spread to southern China and beyond, seriously threatening palm production. A lack of high-quality genome resources has hindered understanding of the insect’s invasive characteristics and ecological adaptations. Here, we combined Illumina short read, PacBio long-read, and high-throughput chromosome conformation capture (Hi-C) sequencing technologies to generate a high-quality, chromosome-scale genome assembly of nipa palm hispid beetle. The genome assembly was 1.31 Gb in size, consisting of nine chromosomes. The contig and scaffold N50 values were 1.022 Mb and 148.6 Mb, respectively. The genome assembly completeness was estimated at 99.1%. Annotation revealed 16,305 protein-coding genes and 62.16% repeat sequences. This high-quality genome assembly is a valuable resource that will contribute to understanding of the genetic factors underlying the invasive characteristics of nipa palm hispid beetle, ultimately promoting development of efficient control policies.

Phenomics and genomic features of Enterococcus avium IRMC1622a isolated from a clinical sample of hospitalized patient

BackgroundEnterococcus avium (E. avium) is a Gram-positive nosocomial pathogen that is commonly isolated from the alimentary tract. The objective of this functional genomics study was to identify the resistant genes by analyzing the genome of E. avium IRMC1622a, a type of bacteria found in feces collected from a patient at a Saudi Arabian tertiary hospital. MethodsThe bacterial strain IRMC1622a was identified by 16 S rRNA sequencing as Enterococcus sp. The resistance phenomics were performed using VITEK® 2, and morphological analysis was achieved using a scanning electron microscope (SEM). Finally, the whole bacterial genome of the bacterial strain IRMC1622a was subjected to sequencing during October 2023 using Oxford Nanopore long-read sequencing technology, and mining for resistant genes. ResultsThe results of antimicrobial resistant phenomics indicated that the IRMC1622a strain was sensitive to all tested antimicrobial agents except for erythromycin, and the same result was confirmed by genomic analysis in addition to other classes of antibiotics. SEM showed E. avium IRMC1622a is ovoid shape, in single cells (L 1.2797 ± 0.1490 µm), in pairs (L 1.7333 ± 0.1054 µm), and in chains (L 2.44033 ± 0.1978 µm). The E. avium IRMC1622a genome has 14 (in CARD) antimicrobial resistance genes that were identified with several mechanisms of antimicrobial resistance, such as the efflux pump and conferring antibiotic resistance. The present study revealed that the E. avium IRMC1622a genome contains a high number of genes associated with virulence factors, and 14 matched pathogenic protein families and predicted as human pathogen (probability score 0.855). We report two (ISEnfa4 and ISEfa5) mobile genetic elements for the first time in the E. avium genome. ConclusionsThe study concludes that E. avium IRMC1622a is susceptible to all tested antibacterials except erythromycin. The IRMC1622a has 14 genes encoding antimicrobial resistance mechanisms, including the efflux pump and conferring antibiotic resistance. This could indicate a potential rise in E. avium resistance in healthcare facilities. These observations may raise concerns regarding E. avium resistance in healthcare. We need more research to understand the pathophysiology of E. avium, which leads to hospital-acquired infections.

ACMGA: a reference-free multiple-genome alignment pipeline for plant species

BackgroundThe short-read whole-genome sequencing (WGS) approach has been widely applied to investigate the genomic variation in the natural populations of many plant species. With the rapid advancements in long-read sequencing and genome assembly technologies, high-quality genome sequences are available for a group of varieties for many plant species. These genome sequences are expected to help researchers comprehensively investigate any type of genomic variants that are missed by the WGS technology. However, multiple genome alignment (MGA) tools designed by the human genome research community might be unsuitable for plant genomes.ResultsTo fill this gap, we developed the AnchorWave-Cactus Multiple Genome Alignment (ACMGA) pipeline, which improved the alignment of repeat elements and could identify long (> 50 bp) deletions or insertions (INDELs). We conducted MGA using ACMGA and Cactus for 8 Arabidopsis (Arabidopsis thaliana) and 26 Maize (Zea mays) de novo assembled genome sequences and compared them with the previously published short-read variant calling results. MGA identified more single nucleotide variants (SNVs) and long INDELs than did previously published WGS variant callings. Additionally, ACMGA detected significantly more SNVs and long INDELs in repetitive regions and the whole genome than did Cactus. Compared with the results of Cactus, the results of ACMGA were more similar to the previously published variants called using short-read. These two MGA pipelines identified numerous multi-allelic variants that were missed by the WGS variant calling pipeline.ConclusionsAligning denovo assembled genome sequences could identify more SNVs and INDELs than mapping short-read. ACMGA combines the advantages of AnchorWave and Cactus and offers a practical solution for plant MGA by integrating global alignment, a 2-piece-affine-gap cost strategy, and the progressive MGA algorithm.

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.

Chromosomal-level genome assembly of the long-spined sea urchin Diadema setosum (Leske,1778).

The long-spined sea urchin Diadema setosum is an algal and coral feeder widely distributed in the Indo-Pacific that can cause severe bioerosion on the reef community. However, the lack of genomic information has hindered the study of its ecology and evolution. Here, we report the chromosomal-level genome (885.8Mb) of the long-spined sea urchin D. setosum using a combination of PacBio long-read sequencing and Omni-C scaffolding technology. The assembled genome contains a scaffold N50 length of 38.3Mb, 98.1% of complete BUSCO (Geno, metazoa_odb10) genes (the single copy score is 97.8% and the duplication score is 0.3%), and 98.6% of the sequences are anchored to 22 pseudo-molecules/chromosomes. A total of 27,478 gene models have were annotated, reaching a total of 28,414 transcripts, including 5,384 tRNA and 23,030 protein-coding genes. The high-quality genome of D. setosum presented here is a valuable resource for the ecological and evolutionary studies of this coral reef-associated sea urchin.

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.

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.

Advances in single-cell long-read sequencing technologies.

With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenomeand epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.