LRScaf: improving draft genomes using long noisy reads

A number of next-generation sequencing (NGS) technologies such as Roche/454, Illumina and AB SOLiD have recently become available. These technologies are capable of generating hundreds of thousands or tens of millions of short DNA sequence reads at a relatively low cost. These NGS technologies, now referred as second-generation sequencing (SGS) technologies, are being utilized for de novo sequencing, genome re-sequencing, and whole genome and transcriptome analysis. Now, new generation of sequencers, based on the 'next-next' or third-generation sequencing (TGS) technologies like the Single-Molecule Real-Time (SMRT™) Sequencer, Heliscope™ Single Molecule Sequencer, and the Ion Personal Genome Machine™ are becoming available that are capable of generating longer sequence reads in a shorter time and at even lower costs per instrument run. Ever declining sequencing costs and increased data output and sample throughput for NGS and TGS sequencing technologies enable the plant genomics and breeding community to undertake genotyping-by-sequencing (GBS). Data analysis, storage and management of large-scale second or TGS projects, however, are essential. This article provides an overview of different sequencing technologies with an emphasis on forthcoming TGS technologies and bioinformatics tools required for the latest evolution of DNA sequencing platforms.

BackgroundThe RNA virosphere's extensive diversity and its role in emerging infectious diseases underscore the importance of non-targeted sequencing for identifying unknown or rare pathogens, including co-infections. However, enriching low-abundance viral sequences in RNA metaviromics, particularly in the preparation of cDNA libraries and their compatibility with next-generation sequencing (NGS) and third-generation sequencing (TGS), remains challenging. Therefore, our objective is to develop and systematically assess a practical RNA metavirome methodology specifically tailored for the enrichment of low-abundance viral sequences within samples.MethodsWe developed the SMART-RNA-Metavirome platform, integrating SMART-9n library preparation with NGS and TGS technologies. Total RNA was extracted from two field-collected wild Aedes albopictus pools, along with one laboratory-infected Ae. albopictus pool harboring dengue virus (DENV). This RNA was subjected to reverse transcription using both this optimized protocol and random primer-based methods, followed by high-throughput sequencing on Illumina, Oxford Nanopore, and QitanTech Nanopore technologies. Welch's t-test was employed for comparative analysis of the subsequent RNA metavirome data, specifically to evaluate differences in viral species composition and abundance of viral reads between experimental groups. Furthermore, the effectiveness of this platform was systematically validated via RT-qPCR and SMART-RNA-Metavirome-based Oxford Nanopore sequencing across multiple sample types, including mosquito specimens from DENV-infected Ae. albopictus, serum samples from dengue patients and viral isolates of Japanese encephalitis virus (JEV) and Zika virus (ZIKV).ResultsThe SMART-RNA-Metavirome platform has been systematically validated to excel in enriching the composition and diversity of the RNA virome (P = 0.04), providing sufficient coverage for the complete reconstruction of viral genomes. When employed in the detection of DENV-infected Ae. albopictus, clinical serum samples, and viral isolates of JEV and ZIKV, this technique exhibits a robust correlation with RT-qPCR (r2 > 0.95). Notably, it demonstrates exceptional sensitivity, ensuring sufficient coverage even in samples of DENV-infected Ae. albopictus with a Ct-value of 35.3, attaining an impressive 99.88% genome coverage. Furthermore, this platform possesses the capability to identify virus species and determine their serotypes.ConclusionsIn our study, the SMART-RNA-Metavirome platform outperforms traditional methods, enriching RNA virome composition and diversity, enabling practical compatibility with both NGS and TGS technologies. It demonstrates significant proficiency in detecting both known and unknown arboviruses, even in low-titer samples such as those from wild mosquitoes and clinical sera. This platform facilitates comprehensive monitoring, risk assessment, and early warning of RNA virus transmissions, enhancing our understanding of RNA virome diversity and ecological patterns.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s40249-025-01371-z.

Marine cone snail venoms represent a vast library of bioactive peptides with proven potential as research tools, drug leads, and therapeutics. In this study, a transcriptome library of four different organs, namely radular sheath, venom duct, venom gland, and salivary gland, from piscivorous Conus striatus was constructed and sequenced using both Illumina next-generation sequencing (NGS) and PacBio third-generation sequencing (TGS) technologies. A total of 428 conotoxin precursor peptides were retrieved from these transcriptome data, of which 413 conotoxin sequences assigned to 13 gene superfamilies, and 15 conotoxin sequences were classified as unassigned families. It is worth noting that there were significant differences in the diversity of conotoxins identified from the NGS and TGS data: 82 conotoxins were identified from the NGS datasets while 366 conotoxins from the TGS datasets. Interestingly, we found point mutations in the signal peptide sequences of some conotoxins with the same mature sequence. Therefore, TGS broke the traditional view of the conservation of conotoxin signal peptides and the variability of mature peptides obtained by NGS technology. These results shed light on the integrated NGS and TGS technologies to mine diverse conotoxins in Conus species, which will greatly contribute to the discovery of novel conotoxins and the development of new marine drugs.

BackgroundWhile next-generation sequencing technologies have made sequencing genomes faster and more affordable, deciphering the complete genome sequence of an organism remains a significant bioinformatics challenge, especially for large genomes. Low sequence coverage, repetitive elements and short read length make de novo genome assembly difficult, often resulting in sequence and/or fragment “gaps” – uncharacterized nucleotide (N) stretches of unknown or estimated lengths. Some of these gaps can be closed by re-processing latent information in the raw reads. Even though there are several tools for closing gaps, they do not easily scale up to processing billion base pair genomes.ResultsHere we describe Sealer, a tool designed to close gaps within assembly scaffolds by navigating de Bruijn graphs represented by space-efficient Bloom filter data structures. We demonstrate how it scales to successfully close 50.8 % and 13.8 % of gaps in human (3 Gbp) and white spruce (20 Gbp) draft assemblies in under 30 and 27 h, respectively – a feat that is not possible with other leading tools with the breadth of data used in our study.ConclusionSealer is an automated finishing application that uses the succinct Bloom filter representation of a de Bruijn graph to close gaps in draft assemblies, including that of very large genomes. We expect Sealer to have broad utility for finishing genomes across the tree of life, from bacterial genomes to large plant genomes and beyond. Sealer is available for download at https://github.com/bcgsc/abyss/tree/sealer-release.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0663-4) contains supplementary material, which is available to authorized users.

Genome assembly of short reads from large plant genomes remains a challenge in computational biology despite major developments in next generation sequencing. Of late several draft assemblies have been reported in sequenced plant genomes. The reported draft genome assemblies of Cajanus cajan have different levels of genome completeness, a large number of repeats, gaps, and segmental duplications. Draft assemblies with portions of genome missing are shorter than the referenced original genome. These assemblies come with low map accuracy affecting further functional annotation and the prediction of gene components as desired by crop researchers. Genome coverage, i.e., the number of sequenced raw reads mapped onto a certain location of the genome is an important quality indicator of completeness and assembly quality in draft assemblies. The present work aimed to improve the coverage in reported de novo sequenced draft genomes (GCA_000340665.1 and GCA_000230855.2) of pigeonpea, a legume widely cultivated in India. The two recently sequenced assemblies, A1 and A2 comprised 72% and 75% of the estimated coverage of the genome, respectively. We employed an assembly reconciliation approach to compare the draft assemblies and merge them, filling the gaps by employing an algorithm size sorting mate-pair library to generate a high quality and near complete assembly with enhanced contiguity. The majority of gaps present within scaffolds were filled with right-sized mate-pair reads. The improved assembly reduced the number of gaps than those reported in draft assemblies resulting in an improved genome coverage of 82.4%. Map accuracy of the improved assembly was evaluated using various quality metrics and for the presence of specific trait-related functional genes. Employed pair-end and mate-pair local libraries helped us to reduce gaps, repeats, and other sequence errors resulting in lengthier scaffolds compared to the two draft assemblies. We reported the prediction of putative host resistance genes against Fusarium wilt disease by their performance and evaluated them both in wet laboratory and field phenotypic conditions.

BackgroundBacterial whole-genome sequencing based on short-read technologies often results in a draft assembly formed by contiguous sequences. The introduction of long-read sequencing technologies permits those contiguous sequences to be unambiguously bridged into complete genomes. However, the elevated costs associated with long-read sequencing frequently limit the number of bacterial isolates that can be long-read sequenced. Here we evaluated the recently released 96 barcoding kit from Oxford Nanopore Technologies (ONT) to generate complete genomes on a high-throughput basis. In addition, we propose an isolate selection strategy that optimizes a representative selection of isolates for long-read sequencing considering as input large-scale bacterial collections.ResultsDespite an uneven distribution of long reads per barcode, near-complete chromosomal sequences (assembly contiguity = 0.89) were generated for 96 Escherichia coli isolates with associated short-read sequencing data. The assembly contiguity of the plasmid replicons was even higher (0.98), which indicated the suitability of the multiplexing strategy for studies focused on resolving plasmid sequences. We benchmarked hybrid and ONT-only assemblies and showed that the combination of ONT sequencing data with short-read sequencing data is still highly desirable (i) to perform an unbiased selection of isolates for long-read sequencing, (ii) to achieve an optimal genome accuracy and completeness, and (iii) to include small plasmids underrepresented in the ONT library.ConclusionsThe proposed long-read isolate selection ensures the completion of bacterial genomes that span the genome diversity inherent in large collections of bacterial isolates. We show the potential of using this multiplexing approach to close bacterial genomes on a high-throughput basis.

Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject's genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of base pairs in these long reads is incorrectly identified. These errors propagate to the assembly and affect the accuracy of genome analysis. Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e. read-to-assembly alignment information). However, current assembly polishing algorithms can only polish an assembly using reads from either a certain sequencing technology or a small assembly. Such technology-dependency and assembly-size dependency require researchers to (i) run multiple polishing algorithms and (ii) use small chunks of a large genome to use all available readsets and polish large genomes, respectively. We introduce Apollo, a universal assembly polishing algorithm that scales well to polish an assembly of any size (i.e. both large and small genomes) using reads from all sequencing technologies (i.e. second- and third-generation). Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to improve the accuracy of assembly polishing and that can polish large genomes. Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly alignment to train the pHMM with the Forward-Backward algorithm and (iii) decodes the trained model with the Viterbi algorithm to produce a polished assembly. Our experiments with real readsets demonstrate that Apollo is the only algorithm that (i) uses reads from any sequencing technology within a single run and (ii) scales well to polish large assemblies without splitting the assembly into multiple parts. Source code is available at https://github.com/CMU-SAFARI/Apollo. Supplementary data are available at Bioinformatics online.

Background: The recent introduction of clinical Next Generation Sequencing (NGS) technologies has transformed the ability of health care providers to provide personalized hereditary breast cancer risk assessments to patients and their family members. However, along with the plethora of data derived from NGS technologies come challenges regarding how to interpret this data in a clinically meaning way to guide medical management decisions. Methods: A retrospective analysis was performed on a population of 242 patients with a personal or family history of breast and/or ovarian cancer and completed NGS genetic testing between March 2012 and May 2014 at Ambry Genetics. Data points included age, gender, primary diagnosis, type of NGS genetic test and result. Patients with prior genetic testing were not excluded from the analysis. Results: Of the 242 patients who completed NGS genetic testing 199 (82%) had a personal history of cancer and 43 (18%) had a family history of cancer. Ten (5%) clinically significant deleterious mutations were found in the affected population; 3 MUTYH mutations were consider not clinically significant and excluded from the analysis. Four (40%) were CHEK2 mutations, 2(20%) BRCA1 mutations, 1(10%) NBN mutation, 1(10%) ATM mutation, 1(10%) MSH6 mutation and 1(10%) PTEN mutation. One patient with a history of ovarian cancer had two deleterious mutations in the BRCA1 and NBN genes, and three affected patients had a deleterious mutation in addition to a variant of uncertain significance (VUS); a patient with synchronous breast and ovarian cancers had a MSH6 mutation and a BRCA2 VUS, a patient with breast cancer had a CHEK2 mutation and a CHEK2 VUS, and a patient with breast cancer had a CHEK2 mutation and a MSH6 VUS. A total of 37 (19%) VUS were found in the affected population, including one patient with a history of breast cancer and a VUS in both ATM and MRE11A. A single (2%) clinically significant BRCA1 deleterious mutation and 6(14%) VUS were detected in the unaffected population. Conclusions: NGS technologies allow for health care providers to complete more comprehensive hereditary breast cancer risk assessments for patients and their families. However, the high VUS rate (14-19%) and the possibility for multiple mutations and/or variants in a single patient create unique challenges when interpreting NGS genetic test results. Furthermore, the paucity of prospective studies and consensus guidelines limits the ability of the health care provider to interpret NGS genetic test results in a clinically meaningful way to guide patient management. This is highlighted by the case example above regarding the patient with synchronous breast and ovarian cancers who was found to have a MSH6 mutation and a BRCA2 VUS. Given that the patient does not meet Amsterdam criteria, the MSH6 mutations would have been missed had it not been for the NGS technology utilized for this patient. However, challenges still exist about how to interpret this data for both the patient and her family in a clinically meaningful way given that the family does not look like a classic Lynch Syndrome family. Citation Format: Barbara Hamlington, Scot Sedlacek, Lucy Langer, Brittney Goetsch, Katie Lemas, Sami Diab. Utilizing next generation sequencing technologies for hereditary breast cancer risk assessments in a private oncology practice [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-12-08.

Mitochondria are essential organelles that provide energy for plants. They are semi-autonomous, maternally inherited, and closely linked to cytoplasmic male sterility (CMS) in plants. Lonicera macranthoides, a widely used medicinal plant from the Caprifoliaceae family, is rich in chlorogenic acid (CGA) and its analogues, which are known for their antiviral and anticancer properties. However, studies on the mitogenome of L. macranthoides still remain limited. The mitochondrial DNA contained in the whole genome DNA was extracted from a male sterile cultivar of L. macranthoides, named 'Yulei 1'. Next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies were combined to obtain the mitogenome. RNA editing events were identified by integrating the mitogenome data with RNA sequencing data from leaf, stem, and flower tissues. The potential causes of male sterility in 'Yulei 1' were analyzed based on the loss of functional genes, mitogenome rearrangements, RNA editing events, and open reading frames (ORFs). The complete mitogenome of L. macranthoides 'Yulei 1' was obtained for the first time, with a length of 1,002,202 bp. It contains 48 protein-coding genes (PCGs), 26 tRNA genes, and 3 rRNA genes. Additionally, 79 simple sequence repeats (SSRs), 39 tandem repeats, and 99 dispersed repeats were identified. Among these, two direct repeats (RP1a/1b, RP2a/2b) and two inverse repeats (RP3a/b, RP4a/b) may facilitate mitogenome recombination. Gene transfer analysis revealed that 4.36% and 21.98% of mitogenomic sequences mapped to the chloroplast and nuclear genomes, respectively. Phylogenetic analysis indicated that L. macranthoides is closest to L. japonica at the mitogenome level. Notably, RNA editing events varied across different plant tissues, with 357 editing sites in 30 PCGs in leaves, 138 sites in 24 PCGs in flowers, and 68 sites in 13 PCGs in stems. Finally, all indications of CMS in the mitogenome were screened, including the detection of ORFs, and the findings showed no mutations in the mitogenome that would explain the sterility of 'Yulei 1'. Overall, our study provides a complete mitogenome of L. macranthoides, which will aid in its genetic marker exploration, evolutionary relationship analysis, and breeding programs.

Alternative splicing is an essential mechanism for generating protein diversity by producing distinct isoforms from a single gene. Dysregulation of splicing that affects pancreatic function and immune tolerance has been linked to both types 1 and 2 diabetes. Next-generation sequencing technologies, with their short read lengths, are limited in their ability to accurately detect splice variants. Long-read sequencing technologies offer the potential to overcome these limitations by providing full-length transcript information; however, their application in single-cell RNA sequencing has been hindered by technical challenges, including insufficient read lengths and higher error rates. Furthermore, cell types that produce high levels of a single transcript, such as islet endocrine cells, can obscure identification of lower-abundance transcripts. In this study, we optimized a protocol for single-cell long-read sequencing in pancreatic islets to improve read length and transcript detection. Our findings demonstrate that 5′ library preparation protocols outperform 3′ protocols, resulting in better transcript identification. Furthermore, we show that targeted depletion of insulin transcripts enhances the detection of informative reads, highlighting the utility of transcript-depletion strategies. This optimized protocol enables isoform-specific gene expression analysis and reveals differential transcript usage across the various cell types in pancreatic islets. By leveraging this approach, we gain deeper insights into the transcriptomic complexity and cellular heterogeneity within pancreatic islets.Article HighlightsThis study addresses the limitations of current single-cell long-read RNA sequencing technologies in detecting full-length transcripts and isoform diversity, particularly in pancreatic islets.We demonstrate that optimizing single-cell library preparation protocols reproducibly enhances read length and transcript identification in pancreatic islets.Combined with targeted insulin depletion and extended reverse transcription, 5′ capture methods significantly improved read length and isoform detection compared with standard protocols, while maximizing the number of informative reads.These improvements yield longer reads in single-cell experiments, substantially enhancing transcript identification and enabling more accurate analysis of isoform diversity.

Towards standardization of the description and publication of next‐generation sequencing datasets of fungal communities

Background: The structural annotation of genes serves as an important resource in the genomics era. Next-generation sequencing (NGS)-based RNA-seq has been used to reconstruct transcriptomes by assembling short reads; however, coupled alternative RNA processing events occurring over long distances cannot be captured. Although the more recently developed third-generation sequencing (TGS) technologies can generate longer reads, challenges exist in full-length transcriptome (FLT) reconstruction due to their higher sequencing error rate and relatively lower throughput. Results: Here, to address the above-stated technical challenges and provide practical FLT annotation in rat, we developed a hybrid-sequencing workflow for reconstructing FLT and applied it to rat hippocampus. Our workflow combines high sequencing accuracy from NGS and long read length from TGS, and has two main features: (1) cDNA normalization and size fractionation to facilitate the profiling of diverse transcripts at an affordable throughput; and (2) a computational approach to correct TGS sequencing errors using NGS reads. The error correction substantially improved the read accuracy with respect to gene expression levels. To determine high-confidence FLT, we used independent 5´ and 3´-end profiling data to validate and filter for a final FLT set in rat hippocampus, which contains 28,268 transcripts derived from 6,380 RefSeq gene loci and 849 unannotated loci. Comparing our FLT to RefSeq annotation, we found that our FLT displayed a higher diversity and more than 90% of our FLT isoforms were not annotated in RefSeq. Moreover, we discovered significant co-occurrence of alternative RNA processing events between transcript 5´-ends and 3´-ends, alternative 5´ and 3´ splice sites, and multiple retained intron. Integrating with polysome profiling and ribosome footprinting data, we predicted active or inactive translational status of transcript isoforms, and reconstructed an open reading frame (ORF)-eome in rat hippocampus, which was largely supported by mass spectrometry-based proteomics datasets. Compared to RefSeq-annotated ORFs, only less than one-third of our ORFome were annotated in RefSeq, whereas the majority were ORF variants, and about one-tenth were novel ORFs. Finally, we identify isoforms with specific subcellular localization patterns in neurons. Conclusions: Altogether, our data expand the current rat gene annotation and provide a rich resource for future functional studies. The developed hybrid-sequencing workflow and downstream analysis can be easily adapted to uncover the complex transcriptome/ORFeome landscapes expressed in other tissues from other organisms. Full article: PMID: 31676752 PMCID: PMC6825209 DOI: 10.1038/s41467-019-13037-0

Collection and storage of HLA NGS genotyping data for the 17th International HLA and Immunogenetics Workshop

BackgroundThe female genital tract microbiome has become a particular area of interest in improving assisted reproductive technology (ART) outcomes with the emergence of next-generation sequencing (NGS) technology. However, NGS assessment of microbiomes currently lacks uniformity and poses significant challenges for accurate and precise bacterial population representation.ObjectiveAs multiple NGS platforms and assays have been developed in recent years for microbiome investigation—including the advent of long-read sequencing technologies—this work aimed to identify current trends and practices undertaken in female genital tract microbiome investigations.ResultsAreas like sample collection and transport, DNA extraction, 16S amplification vs. metagenomics, NGS library preparation, and bioinformatic analysis demonstrated a detrimental lack of uniformity. The lack of uniformity present is a significant limitation characterised by gap discrepancies in generation and interpretation of results. Minimal consistency was observed in primer design, DNA extraction techniques, sample transport, and bioinformatic analyses.ConclusionWith third-generation sequencing technology highlighted as a promising tool in microbiota-based research via full-length 16S rRNA sequencing, there is a desperate need for future studies to investigate and optimise methodological approaches of the genital tract microbiome to ensure better uniformity of methods and results interpretation to improve clinical impact.Graphical

The first generation sequencing technology based on the dideoxynucleotide (ddNTP) chain termination method proposed by Sanger was gradually eliminated due to its high cost, low sequencing read length and cumbersome process. The second generation of sequencing technology, called High-throughput sequencing (HTS), which was then developed, still has the problem of fixed read length. In recent years, the third generation sequencing technology represented by SMRT technology and Nanopore sequencing technology has gradually become popular. Compared with the previous two generations of sequencing technology, the most significant advantage of the third generation sequencing technology is its ability to carry out single molecule sequencing. In this process, the infinite length of nucleic acid sequence can be determined theoretically without the help of PCR amplification. This paper first introduces the basic principles, advantages and disadvantages of third-generation sequencing, and introduces in detail the CRISPR/Cas family-mediated SMRT technology and Nanopore sequencing technology in the third-generation sequencing technology. Finally, the research progress and prospects of the combination of the third generation sequencing technology and gene editing technology in the future are analyzed.