Assembly Pipeline Research Articles

Chromosome Structural Rearrangements in Invasive Haplodiploid Ambrosia Beetles Revealed by the Genomes of Euwallacea fornicatus (Eichhoff) and Euwallacea similis (Ferrari) (Coleoptera, Curculionidae, Scolytinae).

Bark and ambrosia beetles are among the most ecologically and economically damaging introduced plant pests worldwide. Life history traits including polyphagy, haplodiploidy, inbreeding polygyny, and symbiosis with fungi contribute to their dispersal and impact. Species vary in their interactions with host trees, with many attacking stressed or recently dead trees, such as the globally distributed Euwallacea similis (Ferrari). Other species, like the Polyphagous Shot Hole Borer Euwallacea fornicatus (Eichhoff), can attack over 680 host plants and is causing considerable economic damage in several countries. Despite their notoriety, publicly accessible genomic resources for Euwallacea Hopkins species are scarce, hampering our understanding of their invasive capabilities as well as modern control measures, surveillance, and management. Using a combination of long and short read sequencing platforms, we assembled and annotated high quality (BUSCO > 98% complete) pseudo-chromosome-level genomes for these species. Comparative macrosynteny analysis identified an increased number of pseudo-chromosome scaffolds in the haplodiploid inbreeding species of Euwallacea compared to diploid outbred species, due to fission events. This suggests that life history traits can impact chromosome structure. Further, the genome of E. fornicatus had a higher relative proportion of repetitive elements, up to 17% more, than E. similis. Metagenomic assembly pipelines identified microbiota associated with both species including Fusarium fungal symbionts and a novel Wolbachia strain. These novel genomes of haplodiploid inbreeding species will contribute to the understanding of how life history traits are related to their evolution and to the management of these invasive pests.

Snow alga Sanguina aurantia as revealed through de novo genome assembly and annotation.

To thrive on melting alpine and polar snow, some Chlorophytes produce an abundance of astaxanthin, causing red blooms, often dominated by genus Sanguina. The red cells have not been cultured, but we recently grew a green biciliate conspecific with Sanguina aurantia from a sample of watermelon snow. This culture provided source material for Oxford Nanopore Technology and Illumina sequencing. Our assembly pipeline exemplifies the value of a hybrid long- and short-read approach for the complexities of working with a culture grown from a field sample. Using bioinformatic tools, we separated assembled contigs into 2 genomic pools based on a difference in GC content (57.5 and 55.1%). We present the data as 2 assemblies of S. aurantia variants but explore other possibilities. High-throughput chromatin conformation capture analysis (Hi-C sequencing) was used to scaffold the assemblies into a 96-Mb genome designated as "A" and a 102-Mb genome designated as "B." Both assemblies are highly contiguous: genome A consists of 38 scaffolds with an N50 of 5.4 Mb, while genome B has 50 scaffolds with an N50 of 6.4 Mb. RNA sequencing was used to improve gene annotation.

A Novel Robotic Multiple Peg-in-Hole Assembly Pipeline: Modeling, Strategy, and Control

A Novel Robotic Multiple Peg-in-Hole Assembly Pipeline: Modeling, Strategy, and Control

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes.

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

Otb: an automated HiC/HiFi pipeline assembles the Prosapia bicincta Genome.

The implementation of a new genomic assembly pipeline named only the best (otb) has effectively addressed various challenges associated with data management during the development and storage of genome assemblies. otb, which incorporates a comprehensive pipeline involving a setup layer, quality checks, templating, and the integration of Nextflow and Singularity. The primary objective of otb is to streamline the process of creating a HiFi/HiC genome, aiming to minimize the manual intervention required in the genome assembly process. The 2-lined spittlebug, (Prosapia bicincta, Hemiptera: Cercopidae), a true bug insect herbivore, serves as a practical test case for evaluating otb. The 2-lined spittlebug is both a crucial agricultural pest and a genomically understudied insect belonging to the order Hemiptera. This insect is a significant threat to grasslands and pastures, leading to plant wilting and phytotoxemia when infested. Its presence in tropical and subtropical regions around the world poses a long-term threat to the composition of plant communities in grassland landscapes, impacting rangelands, and posing a substantial risk to cattle production.

Sequencing Strategy to Ensure Accurate Plasmid Assembly.

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

RI2AP: Robust and Interpretable 2D Anomaly Prediction in Assembly Pipelines.

Predicting anomalies in manufacturing assembly lines is crucial for reducing time and labor costs and improving processes. For instance, in rocket assembly, premature part failures can lead to significant financial losses and labor inefficiencies. With the abundance of sensor data in the Industry 4.0 era, machine learning (ML) offers potential for early anomaly detection. However, current ML methods for anomaly prediction have limitations, with F1 measure scores of only 50% and 66% for prediction and detection, respectively. This is due to challenges like the rarity of anomalous events, scarcity of high-fidelity simulation data (actual data are expensive), and the complex relationships between anomalies not easily captured using traditional ML approaches. Specifically, these challenges relate to two dimensions of anomaly prediction: predicting when anomalies will occur and understanding the dependencies between them. This paper introduces a new method called Robust and Interpretable 2D Anomaly Prediction (RI2AP) designed to address both dimensions effectively. RI2AP is demonstrated on a rocket assembly simulation, showing up to a 30-point improvement in F1 measure compared to current ML methods. This highlights its potential to enhance automated anomaly prediction in manufacturing. Additionally, RI2AP includes a novel interpretation mechanism inspired by a causal-influence framework, providing domain experts with valuable insights into sensor readings and their impact on predictions. Finally, the RI2AP model was deployed in a real manufacturing setting for assembling rocket parts. Results and insights from this deployment demonstrate the promise of RI2AP for anomaly prediction in manufacturing assembly pipelines.

PlasCAT: Plasmid Cloud Assembly Tool.

PlasCAT (Plasmid Cloud Assembly Tool) is an easy-to-use cloud-based bioinformatics tool that enables de novo plasmid sequence assembly from raw sequencing data. Nontechnical users can now assemble sequences from long reads and short reads without ever touching a line of code. PlasCAT uses high-performance computing servers to reduce run times on assemblies and deliver results faster. PlasCAT is freely available on the web at https://sequencing.genofab.com. The assembly pipeline source code and server code are available for download at https://bitbucket.org/genofabinc/workspace/projects/PLASCAT. Click the Cancel button to access the source code without authenticating. Web servers implemented in React.js and Python, with all major browsers supported.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BackgroundImplementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.ResultsThe routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a “generic” build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.ConclusionsThe accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Abstract 2337: Accelerated optical genome mapping analysis with Stratys Compute and Guided Assembly

Abstract Background Optical genome maps (OGM) from Bionano enable the detection of genomic structural and copy number variants that cannot be detected by next-generation sequencing (NGS) technologies and are often missed by conventional cytogenetic techniques. Bionano has developed bioinformatics pipelines for calling structural and copy number variants including the Bionano Solve de novo assembly pipeline for constitutional analysis and the Rare Variant Analysis (RVA) pipeline for low-allele-fraction cancer applications. Both pipelines are computationally intensive and currently take 5-10 hours on the latest generation of the Bionano Saphyr® Compute which is deployed as a four-node compute cluster and requires significant IT resources. Methods To increase throughput and simplify the deployment of the compute resources needed to support the Stratys™ optical genome mapping instrument, Bionano has developed Stratys™ Compute. Stratys Compute improves both compute and analytical performance by adapting compute-intensive stages in the Solve pipeline to run on GPUs and by developing the Guided Assembly pipeline. Stratys Compute is powered by state-of-the-art NVIDIA RTX 6000 Ada generation cards and CUDA-optimized refinement, alignment, and structural variation detection kernels to accelerate OGM analysis. Stratys Compute is a standalone workstation placed adjacent to Stratys instrument. This will minimize the IT footprint and bypass the integration with the customer site’s data center. We have incorporated these optimizations into the new Guided Assembly pipeline, which aims to combine the low-allele fraction detection capability of the RVA pipeline with the whole genome coverage and ability to detect smaller structural variants enabled by the de novo assembly pipeline. The Guided Assembly pipeline uses the reference genome as an initial seed followed by extension, refinement, and structural variant calling. This new analysis method has been evaluated through comparison to previous results from both existing pipelines and standard benchmarking datasets used to estimate structural variant calling performance and is deployed on Stratys Compute for both constitutional and low allele-fraction applications. Results Guided Assembly has been adapted to run on GPU hardware in a simplified compute tower that can be deployed to a lab along with the Stratys instrument without the need for a dedicated server room. We found concordance between the guided assembly results and our previous de novo and RVA pipeline results. We also found increased sensitivity at low allele fractions for detecting insertion variants smaller than 5 kb and larger than 200 kb while finding equivalent performance for other variant types with the updated methods. The accelerated Guided Assembly for constitutional and low-allele-fraction applications will be available to early access customers in Q4 2023 with full commercial release in Q2 2024. Citation Format: Damla Senol Cali, Thomas Anantharaman, Martin Muggli, Samer Al-Saffar, Charles Schoonover, Neil Miller. Accelerated optical genome mapping analysis with Stratys Compute and Guided Assembly [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2337.

Constructing telomere-to-telomere diploid genome by polishing haploid nanopore-based assembly.

Draft genomes generated from Oxford Nanopore Technologies (ONT) long reads are known to have a higher error rate. Although existing genome polishers can enhance their quality, the error rate (including mismatches, indels and switching errors between paternal and maternal haplotypes) can be significant. Here, we develop two polishers, hypo-short and hypo-hybrid to address this issue. Hypo-short utilizes Illumina short reads to polish an ONT-based draft assembly, resulting in a high-quality assembly with low error rates and switching errors. Expanding on this, hypo-hybrid incorporates ONT long reads to further refine the assembly into a diploid representation. Leveraging on hypo-hybrid, we have created a diploid genome assembly pipeline called hypo-assembler. Hypo-assembler automates the generation of highly accurate, contiguous and nearly complete diploid assemblies using ONT long reads, Illumina short reads and optionally Hi-C reads. Notably, our solution even allows for the production of telomere-to-telomere diploid genomes with additional manual steps. As a proof of concept, we successfully assembled a fully phased telomere-to-telomere diploid genome of HG00733, achieving a quality value exceeding 50.

ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

BackgroundTranscriptome assembly from RNA-sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate ability to reconstruct transcript isoforms. We address this issue by constructing an assembly pipeline whose main purpose is to produce a comprehensive set of transcript isoforms.ResultsWe present the de novo transcript isoform assembler ClusTrast, which takes short read RNA-seq data as input, assembles a primary assembly, clusters a set of guiding contigs, aligns the short reads to the guiding contigs, assembles each clustered set of short reads individually, and merges the primary and clusterwise assemblies into the final assembly. We tested ClusTrast on real datasets from six eukaryotic species, and showed that ClusTrast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. For recall, ClusTrast was on top in the lower end of expression levels (<15% percentile) for all tested datasets, and over the entire range for almost all datasets. Reference transcripts were often (35–69% for the six datasets) reconstructed to at least 95% of their length by ClusTrast, and more than half of reference transcripts (58–81%) were reconstructed with contigs that exhibited polymorphism, measuring on a subset of reliably predicted contigs. ClusTrast recall increased when using a union of assembled transcripts from more than one assembly tool as primary assembly.ConclusionWe suggest that ClusTrast can be a useful tool for studying isoforms in species without a reliable reference genome, in particular when the goal is to produce a comprehensive transcriptome set with polymorphic variants.

Shaping immunity against infectious diseases with multivalent DNA vaccines.

Immunization has dramatically transformed human and animal health. Since its earliest days, vaccination has served as a fundamental strategy for infectious disease prevention, providing population-level coverage for childhood diseases and seasonal infections, and serving as a rapid response to pandemic pathogens. Yet, there is continued circulation of endemic, emerging, and reemerging pathogens for which there are no licensed prophylactic measures. The successes of nucleic acid technologies during the COVID-19 pandemic, exemplified in the first two licensed mRNA vaccines [1] and the first DNA vaccine receiving emergency use authorization for human use [2], are reinvigorating vaccine development to tackle this urgent unmet need. The inherent stability of DNA offers advantageous features such as thermostability and extended shelf life. These characteristics are pivotal for transport and storage in resource-constrained environments, like low and middle-income countries. Furthermore, the ability to encode large transgenes and well-established modular assembly pipelines are key attributes of DNA-based platforms. This versatility extends to combination strategies of individual DNA vaccines as a multivalent drug product. Multivalent synthetic DNA vaccines are therefore emerging as part of the exciting nucleic acid-based vaccine landscape as a strategy to induce robust and durable immunity in diverse global populations.

MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

BackgroundThe possibility of recovering metagenome-assembled genomes (MAGs) from sequence reads allows for further insights into microbial communities and their members, possibly even analyzing such sequences with tools designed for single-isolate genomes. As result quality depends on sequence quality, performance of tools for single-isolate genomes on MAGs should be tested beforehand. Bioinformatics can be leveraged to quickly create varied synthetic test sets with known composition for this purpose.ResultsWe present MAGICIAN, a flexible, user-friendly pipeline for the simulation of MAGs. MAGICIAN combines a synthetic metagenome simulator with a metagenomic assembly and binning pipeline to simulate MAGs based on user-supplied input genomes, allowing users to test performance of tools on MAGs while having a ground truth to compare results to. Using MAGICIAN, we found that even very slight (1%) changes in depth of coverage can drastically affect whether a genome can be recovered. We also demonstrate the use of simulated MAGs by evaluating the suitability of such genomes obtained with MAGICIAN’s current default pipeline for analysis with the antimicrobial resistance gene identification tool ResFinder.ConclusionsUsing MAGICIAN, it is possible to simulate MAGs which, while generally high in quality, reflect issues encountered with real-world data, thus providing realistic best-case data. Evaluating the results of ResFinder analysis of these genomes revealed a risk for plausible-looking false positives, which underlines the need for pipeline validation so that researchers are aware of the potential issues when interpreting real-world data. Furthermore, the effects of fluctuations in depth of coverage on genome recovery in our simulated “random sequencing” warrant further investigation and indicate random subsampling of reads may affect discovery of more genomes.

Artifactual Orthologs and the Need for Diligent Data Exploration in Complex Phylogenomic Datasets: A Museomic Case Study from the Andean Flora.

The Andes mountains of western South America are a globally important biodiversity hotspot, yet there is a paucity of resolved phylogenies for plant clades from this region. Filling an important gap in our understanding of the World's richest flora, we present the first phylogeny of Freziera (Pentaphylacaceae), an Andean-centered, cloud forest radiation. Our dataset was obtained via hybrid-enriched target sequence capture of Angiosperms353 universal loci for 50 of the ca. 75 spp., obtained almost entirely from herbarium specimens. We identify high phylogenomic complexity in Freziera, including the presence of data artifacts. Via by-eye observation of gene trees, detailed examination of warnings from recently improved assembly pipelines, and gene tree filtering, we identified that artifactual orthologs (i.e., the presence of only one copy of a multicopy gene due to differential assembly) were an important source of gene tree heterogeneity that had a negative impact on phylogenetic inference and support. These artifactual orthologs may be common in plant phylogenomic datasets, where multiple instances of genome duplication are common. After accounting for artifactual orthologs as source of gene tree error, we identified a significant, but nonspecific signal of introgression using Patterson's D and f4 statistics. Despite phylogenomic complexity, we were able to resolve Freziera into 9 well-supported subclades whose evolution has been shaped by multiple evolutionary processes, including incomplete lineage sorting, historical gene flow, and gene duplication. Our results highlight the complexities of plant phylogenomics, which are heightened in Andean radiations, and show the impact of filtering data processing artifacts and standard filtering approaches on phylogenetic inference.

Chromosome-level genome assembly of the glass catfish ( Kryptopterus vitreolus) reveals molecular clues to its transparent phenotype.

Glass catfish ( Kryptopterus vitreolus) are notable in the aquarium trade for their highly transparent body pattern. This transparency is due to the loss of most reflective iridophores and light-absorbing melanophores in the main body, although certain black and silver pigments remain in the face and head. To date, however, the molecular mechanisms underlying this transparent phenotype remain largely unknown. To explore the genetic basis of this transparency, we constructed a chromosome-level haplotypic genome assembly for the glass catfish, encompassing 32 chromosomes and 23 344 protein-coding genes, using PacBio and Hi-C sequencing technologies and standard assembly and annotation pipelines. Analysis revealed a premature stop codon in the putative albinism-related tyrp1b gene, encoding tyrosinase-related protein 1, rendering it a nonfunctional pseudogene. Notably, a synteny comparison with over 30 other fish species identified the loss of the endothelin-3 ( edn3b) gene in the glass catfish genome. To investigate the role of edn3b, we generated edn3b -/- mutant zebrafish, which exhibited a remarkable reduction in black pigments in body surface stripes compared to wild-type zebrafish. These findings indicate that edn3b loss contributes to the transparent phenotype of the glass catfish. Our high-quality chromosome-scale genome assembly and identification of key genes provide important molecular insights into the transparent phenotype of glass catfish. These findings not only enhance our understanding of the molecular mechanisms underlying transparency in glass catfish, but also offer a valuable genetic resource for further research on pigmentation in various animal species.

First Steps towards Efficient Genome Assembly on ARM-Based HPC

Exponential advances in computational power have fueled advances in many disciplines, and biology is no exception. High-Performance Computing (HPC) is gaining traction as one of the essential tools in scientific research. Further advances to exascale capabilities will necessitate more energy-efficient hardware. In this article, we present our efforts to improve the efficiency of genome assembly on ARM-based HPC systems. We use vectorization to optimize the popular genome assembly pipeline of minimap2, miniasm, and Racon. We compare different implementations using the Scalable Vector Extension (SVE) instruction set architecture and evaluate their performance in different aspects. Additionally, we compare the performance of autovectorization to hand-tuned code with intrinsics. Lastly, we present the design of a CPU dispatcher included in the Racon consensus module that enables the automatic selection of the fastest instruction set supported by the utilized CPU. Our findings provide a promising direction for further optimization of genome assembly on ARM-based HPC systems.

Metagenomic Analyses of Viruses in the Orchid Mycorrhizal Interaction Using Improved Assemble Tools.

In nature, mycorrhizal association with soil-borne fungi is indispensable for orchid species. Compatible mycorrhizal fungi form endo-mycorrhizal structures in orchid cells, and the fungal structures are digested in orchid cells to be supplied to orchids as nutrition. Because orchid seeds lack the reserves for germination, they keep receiving nutrition through mycorrhizal formation from seed germination until nonphotosynthetic young seedlings develop leaves and become photoautotrophic. Seeds of all orchids germinate with the help of their own fungal partners, and therefore, specific partnership has been acquired in a long evolutionary history between orchids and fungi. Assuming that horizontal transmission of viruses may occur in such a close relationship, we are focusing on viruses that infect orchids and their mycorrhizal fungi. We prepared aseptically germinated orchid plants (i.e., fungi-free plants) together with pure-cultured fungal isolates and conducted transcriptome analyses (RNA-seq) by next-generation sequencing (NGS) approach. To reconstruct virus-related sequences that would have been present in the RNA sample of interest, de novo assembly process is required using short read sequences obtained from RNA-seq. In the previous version of our protocol (see Viral Metagenomics, first edition 2018), virus searches were conducted using contig sets constructed by a single assembler, but this time we devised a method to construct more reliable contigs using multiple assemblers and again reinvestigated that viruses could be detected. Because the virus detection efficiency and number of detected virus species clearly differed depending on the assembly pipeline and the number of the input data, multiple methods should be used to identify viral infection, if possible.

Chromosome-level genome assembly of chub mackerel (Scomber japonicus) from the Indo-Pacific Ocean

Chub mackerels (Scomber japonicus) are a migratory marine fish widely distributed in the Indo-Pacific Ocean. They are globally consumed for their high Omega-3 content, but their population is declining due to global warming. Here, we generated the first chromosome-level genome assembly of chub mackerel (fScoJap1) using the Vertebrate Genomes Project assembly pipeline with PacBio HiFi genomic sequencing and Arima Hi-C chromosome contact data. The final assembly is 828.68 Mb with 24 chromosomes, nearly all containing telomeric repeats at their ends. We annotated 31,656 genes and discovered that approximately 2.19% of the genome contained DNA transposon elements repressed within duplicated genes. Analyzing 5-methylcytosine (5mC) modifications using HiFi reads, we observed open/close chromatin patterns at gene promoters, including the FADS2 gene involved in Omega-3 production. This chromosome-level reference genome provides unprecedented opportunities for advancing our knowledge of chub mackerels in biology, industry, and conservation.

Oligomannose-Type Glycans in the Antigen Binding Site Identify Origin and Prognosis of Diffuse Large B Cell Lymphoma

The acquisition of N-glycosylation sites (AGS) in the complementarity-determining region (CDR) of the tumor immunoglobulin (Ig) is an early clonal requirement of classic follicular lymphoma (FL). In FL, the AGS are occupied by oligomannose-type glycans, which mediate lymphoma Ig interaction with the microenvironmental lectin dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN). This interaction induces a persistent low-level signal, favouring adhesion and ultimately survival and growth of the lymphoma cells in their protected environment . Oligomannose-type glycans can also occupy the CDR-located AGS of a subset of germinal-centre B cell-like (GCB) diffuse large B-cell lymphomas (DLBCL) but the consequences of AGS in DLBCL are less known. We determined the frequency, distribution, and composition of the glycan structures occupying the AGS in DLBCL using a discovery-validation approach with two large independent international public cohorts (BCC, dataset ID: EGAD00001003783; NCI accession phs001444.v1.p1), following our RNAseq Ig assembly pipeline (Ig-Seq-R) and high-resolution mass-spectrometry. Glycan types were compared to our FL cohort (12 samples) and correlated with DLBCL cell of origin (COO), genetic, clinical characteristics and outcome. The full IGHV-IGHD-IGHJ-IGHC transcript sequences were obtained from 251 DLBCL of the BCC, and 339 of the NCI cohort. Sample distribution by COO, clinical or molecular features, LymphGen subtype, progression-free survival (PFS) and overall survival (OS) were not different from the extended public cohorts. AGS were observed in 48-55% GCB-DLBCL, with 84-85% of them located in the CDR. Overall, frequency of CDR-located AGS contrasted dramatically between GCB-DLBCL (41-46%) and activated B-cell like (ABC)-DLBCL (7-10%). Also, within GCB-DLBCL, CDR-located AGS associated mostly with the EZB subtype (68-73%). However, only 66-61% EZB were AGS+ve, all of which were CDR+ve, while the remaining 34-39% had no AGS (AGS-ve EZB). The glycan structures of the synthetic F(ab)s from 35 AGS+ve DLBCL and 12 FL were analyzed by site-specific mass spectrometry. The DLBCL comprised 12 AGS+ve EZB and 23 AGS+ve non-EZB (14 CDR+ve, 9 located in the framework region). Glycan analysis revealed that all AGS+ve EZB and FL were invariably occupied by oligomannose-type glycans (Ig-Mann+ve DLBCL). In contrast, the other AGS+ve DLBCL were not occupied by oligomannose type glycans. They were either occupied by complex glycans (the remaining non-EZB GCB-DLBCL) or not occupied (preferentially the ABC-DLBCL), irrespective of AGS location. These data indicated that CDR+ve EZB Ig were universally and exclusively Ig-Mann+ve DLBCL, share the COO of FL, and have likely been influenced by an environmental driver distinct from the other GCB-DLBCL and ABC-DLBCL. We compared the clinical behavior of Ig-Mann+ve DLBCL versus other DLBCL subtypes including AGS-ve EZB and the other non-EZB GCB-DLBCL and ABC-DLBCL. In both the BCC and NCI cohorts, Ig-Mann+ve DLBCL status identified the subset with the worst PFS and OS of all GCB-DLBCL, not different from ABC-DLBCL (Figure 1A). This contrasted with the other GCB-DLBCL (AGS-ve/EZB and AGS+ve/non-EZB), which all shared an extremely good PFS and OS (Figure 1A). Univariate and multivariate analyses revealed that Ig-Mann+ve status was an independent prognostic factor for PFS and OS (Figure 1B). Gene expression profile analysis revealed that Ig-Mann+ve status associated with an enrichment of MYC, PI3K-Akt-mTORC1, pro-survival, and cell cycle pathways, while proinflammatory and apoptotic pathways were decreased in the Ig-Mann+ve DLBCL compared to AGS-ve/EZB and AGS+ve/non-EZB, independently of MYC translocations and double-hit signature. These data indicate identical COO of a EZB subset with FL cells, and point to a highly selective chronic environmental pressure on Ig-Mann+ve DLBCL negatively affecting patients survival. The combination of Ig gene analysis with the lymphGen classification can predict Ig glycan structure and provide a new fundamental approach to identifying the most aggressive GCB-DLBCL subtype, and the precise environmental tumour interaction (DC-SIGN:Ig-Mann) to intercept therapeutically early in the natural history of Ig-Mann+ve DLBCL.