NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy

Tandem repeats (TRs) play essential roles in a variety of biological functions, and their abnormal expansions are significantly implicated in phenotypic variation and cause >60 human diseases. However, long TR regions cannot be reliably detected using short-read sequencing, and long-read sequencing enables accurate genome-wide detection of TRs. In recent years, various computational tools have been developed to detect and genotype TRs from long-read data. In this survey, we systematically categorize and review 39 computational tools designed for TR detection, visualization and functional interpretation. We discuss their strengths and limitations for TR detection from long-read sequencing data, highlighting current challenges and future directions to advance long-read TR detection methodologies.

Somatic SVs significantly contribute to cancer development and progression. Characterizing these variations has traditionally been difficult due to the limitations of short-read sequencing technologies and the diverse types and lengths of SVs. The advent of long-read sequencing has enabled a more comprehensive analysis of germline SVs, highlighting its potential applications in cancer genomics. The melanoma cell line COLO829, along with its normal counterpart COLO829BL, is a standard reference for somatic SV detection. Valle-Inclan et al. recently validated 68 somatic SVs combining short-read, long-read, and linked-read sequencing data. However, the sensitivity may be compromised as only a limited number of alignment-based callers were employed, such as NanoSV, Sniffles (for Oxford Nanopore Technologies (ONT)), and pbsv for (PacBio HiFi). As more alignment-based SV callers are being developed, it is crucial to integrate a broader range of tools to construct a comprehensive call set of somatic SVs. Moreover, the performance of assembly-based methods in somatic SV detection within cancer remains largely unexplored. In this study, we aimed to establish a comprehensive spectrum of somatic SVs in the COLO829 melanoma cell line by employing both alignment-based and assembly-based methods with long-read whole-genome sequencing data from PacBio and ONT aligned with Minimap2, SVs were identified and integrated from 7 alignment-based callers: cuteSV, NanoVar, DeBreak, Sniffles2, Svision-Pro, NanoSV, and pbsv. In addition, genome assemblies were constructed via Hifiasm and Verkko, incorporating HiFi reads with Hi-C and ultra-long ONT integration, followed by SV detection using four assembly-based callers: Dipcall, PAV, SVIM-asm, and cuteSV. A dedicated pipeline was developed to identify and filter somatic SVs from germline events, which considers mapping quality, sequencing depth of SV regions and their flanking regions, and 50% reciprocal overlap. Compared to the truth set established by Valle-Inclan et al., we discovered 19 novel somatic SVs, including 10 deletions, 4 insertions, 3 duplications, and 2 inversions. As a comparison, assembly-based methods detected all the deletions, insertions and duplications found by the alignment-based methods. However, it missed 20 inversions and 6 translocations. Our findings highlight the superior sensitivity of alignment-based techniques in somatic SV detection and underscore the complementary nature of assembly-based approaches. This work enhances the benchmark for somatic SV characterization in cancer genomics and confirms the utility of integrated long-read sequencing analyses. Citation Format: Zishan Peng, Zechen Chong. Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5056.

SummaryDespite the continuous discovery of new transcript isoforms, fueled by the recent increase in accessibility and accuracy of long-read RNA sequencing data, functional differences between isoforms originating from the same gene often remain obscure. To address this issue and enable researchers to assess potential functional consequences of transcript isoform variation on the proteome, we developed IsoTV. IsoTV is a versatile pipeline to process, predict and visualize the functional features of translated transcript isoforms. Attributes such as gene and isoform expression, transcript composition and functional features are summarized in an easy-to-interpret visualization. IsoTV is able to analyze a variety of data types from all eukaryotic organisms, including short- and long-read RNA-seq data. Using Oxford Nanopore long read data, we demonstrate that IsoTV facilitates the understanding of potential protein isoform function in different cancer cell types.Availability and implementationIsoTV is available at https://github.molgen.mpg.de/MayerGroup/IsoTV, with the corresponding documentation at https://isotv.readthedocs.io/.Supplementary informationSupplementary data are available at Bioinformatics online.

Cellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, and co-infection of multiple pathogens. Detecting and phasing minor variants play an instrumental role in deciphering cellular genetic heterogeneity, but they are still difficult tasks because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, provide an opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrate that iGDA can accurately reconstruct haplotypes in closely related strains of the same species (divergence ≥0.011%) from long-read metagenomic data.

Motivationde novo variants (DNVs) are variants that are present in offspring but not in their parents. DNVs are both important for examining mutation rates as well as in the identification of disease-related variation. While efforts have been made to call DNVs, calling of DNVs is still challenging from parent–child sequenced trio data. We developed Hare And Tortoise (HAT) as an automated DNV detection workflow for highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genomics and HAT addresses this need.ResultsHAT is a computational workflow that begins with aligned read data (i.e. CRAM or BAM) from a parent–child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from Illumina short-read whole-exome sequencing, Illumina short-read whole-genome sequencing, and highly accurate PacBio HiFi long-read whole-genome sequencing data. The quality of these DNVs is high based on a series of quality metrics including number of DNVs per individual, percent of DNVs at CpG sites, and percent of DNVs phased to the paternal chromosome of origin.Availability and implementationhttps://github.com/TNTurnerLab/HAT

BackgroundAs a domesticated species vital to humans, horses are raised worldwide as a source of mechanical energy for sports, leisure, food production, and transportation. The gut microbiota plays an important role in the health, diseases, athletic performance, and behaviour of horses.ResultsHere, using approximately 2.2 Tb of metagenomic sequencing data from gut samples from 242 horses, including 110 samples from the caecum and 132 samples from the rectum (faeces), we assembled 4142 microbial metagenome-assembled genomes (MAG), 4015 (96.93%) of which appear to correspond to new species. From long-read data, we successfully assembled 13 circular whole-chromosome bacterial genomes representing novel species. The MAG contained over 313,568 predicted carbohydrate-active enzymes (CAZy), over 59.77% of which had low similarity match in CAZy public databases. High abundance and diversity of antibiotic resistance genes (ARG) were identified in the MAG, likely showing the wide use of antibiotics in the management of horse. The abundances of at least 36 MAG (e.g. MAG belonging to Lachnospiraceae, Oscillospiraceae, and Ruminococcus) were higher in racehorses than in nonracehorses. These MAG enriched in racehorses contained every gene in a major pathway for producing acetate and butyrate by fibre fermentation, presenting potential for greater amount of short-chain fatty acids available to fuel athletic performance.ConclusionOverall, we assembled 4142 MAG from short- and long-read sequence data in the horse gut. Our dataset represents an exhaustive microbial genome catalogue for the horse gut microbiome and provides a valuable resource for discovery of performance-enhancing microbes and studies of horse gut microbiome.5Q4GzktoVGndspuVBLwUREVideo

Long-read sequencing data is useful for detecting large and complex structural variations; however, technical artifacts can lead to false structural variant calls. In our analyses, we became aware of a foldback artifact in long-read data. Therefore, we developed the open-source Breakinator tool to flag putative foldback artifact reads, as well as previously known chimeric artifacts. Through an alignment-based approach, Breakinator can detect artifacts missed by existing quality control tools. We profiled the occurrences of foldbacks and chimeric reads in both Oxford Nanopore and PacBio sequences across a range of specimens, library types, sequencing chemistries, sequencing machines, and base-calling software.

The root systems of most plant species are aided by the soil-foraging capacities of symbiotic arbuscular mycorrhizal (AM) fungi of the Glomeromycotina subphylum. Despite recent advances in our knowledge of the ecology and molecular biology of this mutualistic symbiosis, our understanding of the AM fungi genome biology is just emerging. Presented here is a close to T2T genome assembly of the model AM fungus Rhizophagus irregularis DAOM197198, achieved through Nanopore long-read DNA sequencing and Hi-C data. This haploid genome assembly of R. irregularis, alongside short- and long-read RNA-Sequencing data, was used to produce a comprehensive annotation catalog of gene models, repetitive elements, small RNA loci, and DNA cytosine methylome. A phylostratigraphic gene age inference framework revealed that the birth of genes associated with nutrient transporter activity and transmembrane ion transport systems predates the emergence of Glomeromycotina. While nutrient cycling in AM fungi relies on genes that existed in ancestor lineages, a burst of Glomeromycotina-restricted genetic innovation is also detected. Analysis of the chromosomal distribution of genetic and epigenetic features highlights evolutionarily young genomic regions that produce abundant small RNAs, suggesting active RNA-based monitoring of genetic sequences surrounding recently evolved genes. This chromosome-scale view of the genome of an AM fungus genome reveals previously unexplored sources of genomic novelty in an organism evolving under an obligate symbiotic life cycle.

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology through the comprehensive identification and quantification of full-length mRNA isoforms. Despite great promise, challenges remain in the widespread implementation of LRS technologies for RNA-based applications, including concerns about low coverage, high sequencing error, and robust computational pipelines. Although much focus has been placed on defining mRNA exon composition and structure with LRS data, less careful characterization has been done of the ability to assess the terminal ends of isoforms, specifically, transcription start and end sites. Such characterization is crucial for completely delineating full mRNA molecules and regulatory consequences. However, there are substantial inconsistencies in both start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. Here, we describe the specific challenges of identifying and quantifying mRNA terminal ends with LRS technologies and how these issues influence biological interpretations of LRS data. We then review recent experimental and computational advances designed to alleviate these problems, with ideal use cases for each approach. Finally, we outline anticipated developments and necessary improvements for the characterization of terminal ends from LRS data.

Multiple displacement amplification (MDA) has become the most commonly used method of whole genome amplification, generating a vast amount of DNA with higher molecular weight and greater genome coverage. Coupling with long-read sequencing, it is possible to sequence the amplicons of over 20kb in length. However, the formation of chimeric sequences (chimeras, expressed as structural errors in sequencing data) in MDA seriously interferes with the bioinformatics analysis but its influence on long-read sequencing data is unknown. We sequenced the phi29 DNA polymerase-mediated MDA amplicons on the PacBio platform and analyzed chimeras within the generated data. The 3rd-ChimeraMiner has been constructed as a pipeline for recognizing and restoring chimeras into the original structures in long-read sequencing data, improving the efficiency of using TGS data. Five long-read datasets and one high-fidelity long-read dataset with various amplification folds were analyzed. The result reveals that the mis-priming events in amplification are more frequently occurring than widely perceived, and the propor tion gradually accumulates from 42% to over 78% as the amplification continues. In total, 99.92% of recognized chimeric sequences were demonstrated to be artifacts, whose structures were wrongly formed in MDA instead of existing in original genomes. By restoring chimeras to their original structures, the vast majority of supplementary alignments that introduce false-positive structural variants are recycled, removing 97% of inversions on average and contributing to the analysis of structural variation in MDA-amplified samples. The impact of chimeras in long-read sequencing data analysis should be emphasized, and the 3rd-ChimeraMiner can help to quantify and reduce the influence of chimeras. The 3rd-ChimeraMiner is available on GitHub, https://github.com/dulunar/3rdChimeraMiner.

Objective:The aim of this project was to implement long-read sequencing for BCR-ABL1 TKI resistance mutation screening in a clinical setting for patients undergoing treatment for chronic myeloid leukemia.Materials and Methods:Processes were established for registering and transferring samples from the clinic to an academic sequencing facility for long-read sequencing. An automated analysis pipeline for detecting mutations was established, and an information system was implemented comprising features for data management, analysis and visualization. Clinical validation was performed by identifying BCR-ABL1 TKI resistance mutations by Sanger and long-read sequencing in parallel. The developed software is available as open source via GitHub at https://github.com/pharmbio/clampResults:The information system enabled traceable transfer of samples from the clinic to the sequencing facility, robust and automated analysis of the long-read sequence data, and communication of results from sequence analysis in a reporting format that could be easily interpreted and acted upon by clinical experts. In a validation study, all 17 resistance mutations found by Sanger sequencing were also detected by long-read sequencing. An additional 16 mutations were found only by long-read sequencing, all of them with frequencies below the limit of detection for Sanger sequencing. The clonal distributions of co-existing mutations were automatically resolved through the long-read data analysis. After the implementation and validation, the clinical laboratory switched their routine protocol from using Sanger to long-read sequencing for this application.Conclusions:Long-read sequencing delivers results with higher sensitivity compared to Sanger sequencing and enables earlier detection of emerging TKI resistance mutations. The developed processes, analysis workflow, and software components lower barriers for adoption and could be extended to other applications.

BackgroundGenomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the strain or population at time zero is required to compare with the genomes derived later. However, there is no fully automated computational approach in experimental evolution studies to establish the chromosome-level genome assembly using unique features of sequencing data.Methods and resultsIn this study, we developed a new software pipeline, the integrative meta-assembly pipeline (IMAP), to build chromosome-level genome sequence assemblies by generating and combining multiple initial assemblies using three de novo assemblers from short-read sequencing data. We significantly improved the continuity and accuracy of the genome assembly using a large collection of sequencing data and hybrid assembly approaches. We validated our pipeline by generating chromosome-level assemblies of yeast strains W303 and SK1, and compared our results with assemblies built using long-read sequencing and various assembly evaluation metrics. We also constructed chromosome-level sequence assemblies of S. cerevisiae strain Sigma1278b, and three commonly used fungal strains: Aspergillus nidulans A713, Neurospora crassa 73, and Thielavia terrestris CBS 492.74, for which long-read sequencing data are not yet available. Finally, we examined the effect of IMAP parameters, such as reference and resolution, on the quality of the final assembly of the yeast strains W303 and SK1.ConclusionsWe developed a cost-effective pipeline to generate chromosome-level sequence assemblies using only short-read sequencing data. Our pipeline combines the strengths of reference-guided and meta-assembly approaches. Our pipeline is available online at http://github.com/jkimlab/IMAP including a Docker image, as well as a Perl script, to help users install the IMAP package, including several prerequisite programs. Users can use IMAP to easily build the chromosome-level assembly for the genome of their interest.

Obtaining complete and accurate bacterial genomes is vital for studying the characteristics of uncultured bacteria. Single-cell genomics is a promising approach for the culture-independent recovery of bacterial genomes from individual cells. However, single-amplified genomes (SAGs) often have fragmented and incomplete sequences due to chimeric and biased sequences introduced during the genome amplification process. To address this, we developed a single-cell amplified genome long-read assembly (scALA) workflow to construct complete circular SAGs (cSAGs) from long-read single-cell sequencing data of uncultured bacteria. We used the SAG-gel platform, which is both cost-effective and high-throughput, to obtain hundreds of short-read and long-read sequencing data for specific bacterial strains. The scALA workflow generated cSAGs by repeated in silico processing for sequence bias reduction and contig assembly. From 12 human fecal samples, including two cohabitant groups, scALA generated 16 cSAGs of three specifically targeted bacterial species: Anaerostipes hadrus, Agathobacter rectalis, and Ruminococcus gnavus. We discovered strain-specific structural variations shared among cohabiting hosts, while all cSAGs of the same species showed high homology in aligned genomic regions. A. hadrus cSAGs exhibited 10 kbp-long phage insertions, various saccharide metabolic capabilities, and different CRISPR-Cas systems in each strain. The sequence similarity of A. hadrus genomes did not necessarily correspond with orthologous functional genes, while host geographical regionality seemed to be highly related to gene possession. scALA allowed us to obtain closed circular genomes of specifically targeted bacteria from human microbiota samples, leading to an understanding of within-species diversities, including structural variations and linking mobile genetic elements, such as phages, to hosts. These analyses provide insight into microbial evolution, the adaptation of the community to environmental changes, and interactions with hosts. cSAGs constructed using this method can expand bacterial genome databases and our understanding of within-species diversities in uncultured bacteria.

Transposable elements, such as Long INterspersed Elements (LINEs), are DNA sequences that can replicate within genomes. LINEs replicate using an RNA intermediate followed by reverse transcription and are typically a few kilobases in length. LINE activity creates genomic structural variants in human populations and leads to somatic alterations in cancer genomes. Long-read RNA sequencing technologies, including Oxford Nanopore and PacBio, can directly sequence relatively long transcripts, thus providing the opportunity to examine full-length LINE transcripts. This study focuses on the development of a new bioinformatics pipeline for the identification and quantification of active, full-length LINE transcripts in diverse human tissues and cell lines. In our pipeline, we utilized RepeatMasker to identify LINE-1 (L1) transcripts from long-read transcriptome data and incorporated several criteria, such as transcript start position, divergence, and length, to remove likely false positives. Comparisons between cancerous and normal cell lines, as well as human tissue samples, revealed elevated expression levels of young LINEs in cancer, particularly at intact L1 loci. By employing bioinformatics methodologies on long-read transcriptome data, this study demonstrates the landscape of L1 expression in tissues and cell lines.

BackgroundThe barred knifejaw (Oplegnathus fasciatus), a member of the Oplegnathidae family of the Centrarchiformes, is a commercially important rocky reef fish native to East Asia. Oplegnathus fasciatus has become an important fishery resource for offshore cage aquaculture and fish stocking of marine ranching in China, Japan, and Korea. Recently, sexual dimorphism in growth with neo-sex chromosome and widespread biotic diseases in O. fasciatus have been increasing concern in the industry. However, adequate genome resources for gaining insight into sex-determining mechanisms and establishing genetically resistant breeding systems for O. fasciatus are lacking. Here, we analyzed the entire genome of a female O. fasciatus fish using long-read sequencing and Hi-C data to generate chromosome-length scaffolds and a highly contiguous genome assembly.FindingsWe assembled the O. fasciatus genome with a total of 245.0 Gb of raw reads that were generated using both Pacific Bioscience (PacBio) Sequel and Illumina HiSeq 2000 platforms. The final draft genome assembly was approximately 778.7 Mb, which reached a high level of continuity with a contig N50 of 2.1 Mb. The genome size was consistent with the estimated genome size (777.5 Mb) based on k-mer analysis. We combined Hi-C data with a draft genome assembly to generate chromosome-length scaffolds. Twenty-four scaffolds corresponding to the 24 chromosomes were assembled to a final size of 768.8 Mb with a contig N50 of 2.1 Mb and a scaffold N50 of 33.5 Mb using 1,372 contigs. The identified repeat sequences accounted for 33.9% of the entire genome, and 24 003 protein-coding genes with an average of 10.1 exons per gene were annotated using de novo methods, with RNA sequencing data and homologies to other teleosts. According to phylogenetic analysis using protein-coding genes, O. fasciatus is closely related to Larimichthys crocea, with O. fasciatus diverging from their common ancestor approximately 70.5–88.5 million years ago.ConclusionsWe generated a high-quality draft genome for O. fasciatus using long-read PacBio sequencing technology, which represents the first chromosome-level reference genome for Oplegnathidae species. Assembly of this genome assists research into fish sex-determining mechanisms and can serve as a resource for accelerating genome-assisted improvements in resistant breeding systems.