NanoR: A user-friendly R package to analyze and compare nanopore sequencing data

Haemoglobin Gene Repertoire in Teleost and Cichlid Fishes Shaped by Gene Duplications and Genome Rearrangements

Haemoglobin is a key molecule for oxygen transport in vertebrates. It exhibits remarkable gene diversity in teleost fishes, reflecting adaptation to various aquatic environments. In this study, we present the dynamic evolution of haemoglobin subunit genes based on a comparison of high-quality genome assemblies of 24 vertebrate species, including 17 teleosts (of which six are cichlids). Our findings indicate that teleost genomes contain a range of haemoglobin genes, from as few as five in fugu to as many as 43 in salmon, with the latter being the largest repertoire found in vertebrates. We find evidence that the teleost ancestor had at least four Hbα and three or four Hbβ subunit genes, and that the current gene diversity emerged during teleost radiation, driven primarily by (tandem) gene duplications, genome compaction, and rearrangement dynamics. We provide insights into the genomic organisation of haemoglobin clusters in different teleost species. We further show that the evolution of paralogous rhbdf1 genes flanking both teleost clusters (LA and MN) supports the hypothesis for the origin of the LA cluster by rearrangement within teleosts, rather than by the teleost specific whole-genome duplication. We specifically focus on cichlid fishes, where adaptation to low oxygen environment plays role in species diversification. Our analysis of six cichlid genomes, including Pungu maclareni from the Barombi Mbo crater lake, for which we sequenced a representative genome, reveals 18-32 copies of the Hb genes, and elevated rates of non-synonymous substitutions compared to other teleosts. Overall, this work facilitates a deeper understanding of how haemoglobin genes contribute to the adaptive potential of teleosts.

Effects of different straw breeding substrates on the growth of tomato seedlings and transcriptome analysis

Traditional substrate cultivation is now a routine practice in vegetable facility breeding. However, finding renewable substrates that can replace traditional substrates is urgent in today's production. In this study, we used the 'Pindstrup' substrate as control and two types of composite substrates made from fermented corn straw (i.e. 0-3 and 3-5 mm) to identify appropriate substrate conditions for tomato seedling growth under winter greenhouse conditions. Seedling growth potential related data and substrate water content related data were tested to carry out data-oriented support. Since the single physiological data cannot well explain the mechanism of tomato seedlings under winter greenhouse condition, transcriptomic analysis of tomato root and leaf tissues were conducted to provide theoretical basis. The physiological data of tomato seedlings and substrate showed that compared with 0-3 mm and Pindstrup substrate, tomato seedlings planted in 3-5 mm had stronger growth potential and stronger water retention, and were more suitable for planting tomato seedlings. Transcriptome analysis revealed a greater number of DEGs between the Pindstrup and the 3-5 mm. The genes in this group contribute to tomato growth as well as tomato stress response mechanisms, such as ABA-related genes, hormone-related genes and some TFs. The simulation network mechanism diagram adds evidence to the above conclusions. Overall, these results demonstrate the potential benefits of using the fermented corn straw of 3-5 mm for growing tomato seedlings and present a novel method of utilizing corn straw.

Can long-read sequencing tackle the barriers, which the next-generation could not? A review

The large-scale heterogeneity of genetic diseases necessitated the deeper examination of nucleotide sequence alterations enhancing the discovery of new targeted drug attack points. The appearance of new sequencing techniques was essential to get more interpretable genomic data. In contrast to the previous short-reads, longer lengths can provide a better insight into the potential health threatening genetic abnormalities. Long-reads offer more accurate variant identification and genome assembly methods, indicating advances in nucleotide deflect-related studies. In this review, we introduce the historical background of sequencing technologies and show their benefits and limits, as well. Furthermore, we highlight the differences between short- and long-read approaches, including their unique advances and difficulties in methodologies and evaluation. Additionally, we provide a detailed description of the corresponding bioinformatics and the current applications.

Resolving complex structural variants via nanopore sequencing

The recent development of high-throughput sequencing platforms provided impressive insights into the field of human genetics and contributed to considering structural variants (SVs) as the hallmark of genome instability, leading to the establishment of several pathologic conditions, including neoplasia and neurodegenerative and cognitive disorders. While SV detection is addressed by next-generation sequencing (NGS) technologies, the introduction of more recent long-read sequencing technologies have already been proven to be invaluable in overcoming the inaccuracy and limitations of NGS technologies when applied to resolve wide and structurally complex SVs due to the short length (100-500 bp) of the sequencing read utilized. Among the long-read sequencing technologies, Oxford Nanopore Technologies developed a sequencing platform based on a protein nanopore that allows the sequencing of "native" long DNA molecules of virtually unlimited length (typical range 1-100 Kb). In this review, we focus on the bioinformatics methods that improve the identification and genotyping of known and novel SVs to investigate human pathological conditions, discussing the possibility of introducing nanopore sequencing technology into routine diagnostics.

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias

Aberrant DNA methylation at CpG dinucleotides is a cancer hallmark that is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole-genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Analyses of available datasets confirmed TF binding to their target genes and conservation of the same gene-regulatory networks in large patient cohorts. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.

Sequoia: A Framework for Visual Analysis of RNA Modifications from Direct RNA Sequencing Data

Oxford Nanopore-based long-read direct RNA sequencing protocols are being increasingly used to study the dynamics of RNA metabolic processes due to improvements in read lengths, increased throughput, decreasing cost, ease of library preparation, and convenience. Long-read sequencing enables single-molecule-based detection of posttranscriptional changes, promising novel insights into the functional roles of RNA. However, fulfilling this potential will necessitate the development of new tools for analyzing and exploring this type of data. Although there are tools that allow users to analyze signal information, such as comparing raw signal traces to a nucleotide sequence, they don't facilitate studying each individual signal instance in each read or perform analysis of signal clusters based on signal similarity. Therefore, we present Sequoia, a visual analytics application that allows users to interactively analyze signals originating from nanopore sequencers and can readily be extended to both RNA and DNA sequencing datasets. Sequoia combines a Python-based backend with a multi-view graphical interface that allows users to ingest raw nanopore sequencing data in Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to find attributes of interest. In this tutorial, we illustrate each individual step involved in running Sequoia and in the process dissect input data characteristics. We show how to generate Nanopore sequencing-based visualizations by leveraging dimensionality reduction and parameter tuning to separate modified RNA sequences from their unmodified counterparts. Sequoia's interactive features enhance nanopore-based computational methodologies. Sequoia enables users to construct rationales and hypotheses and develop insights about the dynamic nature of RNA from the visual analysis. Sequoia is available at https://github.com/dnonatar/Sequoia .

Hemorrhagic fever with renal syndrome caused by destruction of residential area of rodent in a construction site: epidemiological investigation

BACKGROUND

An outbreak of hemorrhagic fever with renal syndrome (HFRS), caused by a Hantavirus, affected nine adult males in the southwest area of Xi'an in November 2020 was analyzed in this study.

METHODS

Clinical and epidemiological data of HFRS patients in this outbreak were retrospectively analyzed. The whole genome of a hantavirus named 201120HV03xa (hv03xa for short) isolated from Apodemus agrarius captured in the construction site was sequenced and analyzed. In addition, nine HFRS patients were monitored for the IgG antibody against the HV N protein at 6 and 12 months, respectively.

RESULTS

In this study, inhalation of aerosolized excreta and contaminated food may be the main source of infection. Genome analysis and phylogenetic analysis showed that hv03xa is a reassortment strain of HTNV, having an S segment related to A16 of HTN 4, an M segment related to Q37 and Q10 of HTN 4, and an L segment related to prototype strain 76-118 of HTN 7. Potential recombination was detected in the S segment of hv03xa strain. The anti-HV-IgG level of all the patients persist for at least one year after infection.

CONCLUSIONS

This report documented an HFRS outbreak in Xi'an, China, which provided the basic data for epidemiological surveillance of endemic HTNV infection and facilitated to predict disease risk and implement prevention measures.

Deconstructing Difflugia: The tangled evolution of lobose testate amoebae shells (Amoebozoa: Arcellinida) illustrates the importance of convergent evolution in protist phylogeny

Protists, the micro-eukaryotes that are neither plants, animals nor fungi build up the greatest part of eukaryotic diversity on Earth. Yet, their evolutionary histories and patterns are still mostly ignored, and their complexity overlooked. Protists are often assumed to keep stable morphologies for long periods of time (morphological stasis). In this work, we test this paradigm taking Arcellinida testate amoebae as a model. We build a taxon-rich phylogeny based on two mitochondrial (COI and NADH) and one nuclear (SSU) gene, and reconstruct morphological evolution among clades. In addition, we prove the existence of mitochondrial mRNA editing for the COI gene. The trees show a lack of conservatism of shell outlines within the main clades, as well as a widespread occurrence of morphological convergences between far-related taxa. Our results refute, therefore, a widespread morphological stasis, which may be an artefact resulting from low taxon coverage. As a corollary, we also revise the groups systematics, notably by emending the large and highly polyphyletic genus Difflugia. These results lead, amongst others, to the erection of a new infraorder Cylindrothecina, as well as two new genera Cylindrifflugia and Golemanskia.

Clinical Performance of Nanopore Targeted Sequencing for Diagnosing Infectious Diseases

The gold standard for confirming bacterial infections is culture-positive, which has a long sample-to-result turnaround time and poor sensitivity for unculturable and fastidious pathogens; therefore, it is hard to guide early, targeted antimicrobial therapy and reduce overuse of broad-spectrum antibiotics. Nanopore targeted sequencing (NTS) is reported to be advantageous in detection speed and range over culture in prior published reports. However, investigation of the clinical performance of NTS is deficient at present. Thus, we assessed the feasibility of NTS for the first time with cohort and systematic comparisons with traditional culture assays and PCR followed by Sanger sequencing. This retrospective study was performed on 472 samples, including 6 specimen types from 436 patients, to evaluate the clinical performance of NTS designed for identifying the microbial composition of various infections. Of these samples, 86.7% were found to be NTS positive, which was significantly higher than culture-positive (26.7%). A total of 425 significant human opportunistic bacteria and fungi detected by NTS were selected to go through validation with PCR followed by Sanger sequencing. The average accuracy rate was 85.2% (maximum 100% created by Cryptococcus neoformans, the last one 66.7% provided by both Staphylococcus haemolyticus and Moraxella osloensis, minimum 0% produced by Burkholderia cepacia). The accuracy rate also varied with sample type; the highest accuracy rate was found in pleural and ascites fluid (95.8%) followed by bronchoalveolar lavage fluid (88.7%), urine (86.8%), and wound secretions (85.0%), while the lowest was present in cerebrospinal fluid (58.8%). NTS had a diagnostic sensitivity of 94.5% and specificity of 31.8%. The positive and negative predictive values of NTS were 79.9% and 66.7%, respectively. For diagnosis of infectious diseases, the sensitivity was greatly increased by 56.7% in NTS compared with culture (94.5% vs 37.8%). Therefore, NTS can accurately detect the causative pathogens in infectious samples, particularly in pleural and ascites fluid, bronchoalveolar lavage fluid, urine, and wound secretions, with a short turnaround time of 8-14 h, and might innovatively contribute to personalizing antibiotic treatments for individuals with standardized protocols in clinical practices. IMPORTANCE Nanopore targeted sequencing (NTS) is reported to be advantageous in detection speed and range over culture in prior published reports. Investigation of the clinical performance of NTS is deficient at present. In our study, cohort and systematic comparisons among three assays (culture, NTS, and Sanger sequencing) were analyzed retrospectively for the first time. We found that NTS undoubtedly has incomparable advantages in accurately detecting the causative pathogens in infectious samples, particularly in pleural and ascites fluid, bronchoalveolar lavage fluid, urine, and wound secretions, with a short turnaround time of 8-14 h. For sterile specimens like blood and cerebrospinal fluid (CSF), the NTS outcomes should be validated using other nucleic acid based detection technology. Overall, NTS might innovatively contribute to guiding early, targeted antimicrobial therapy with lower cost and reduce overuse of broad-spectrum antibiotics.

A blood drop through the pore: nanopore sequencing in hematology

The development of new sequencing platforms, technologies, and bioinformatics tools in the past decade fostered key discoveries in human genomics. Among the most recent sequencing technologies, nanopore sequencing (NS) has caught the interest of researchers for its intriguing potential and flexibility. This up-to-date review highlights the recent application of NS in the hematology field, focusing on progress and challenges of the technological approaches employed for the identification of pathologic alterations. The molecular and analytic pipelines developed for the analysis of the whole-genome, target regions, and transcriptomics provide a proof of evidence of the unparalleled amount of information that could be retrieved by an innovative approach based on long-read sequencing.

Nanopore sequencing technology, bioinformatics and applications

Rapid advances in nanopore technologies for sequencing single long DNA and RNA molecules have led to substantial improvements in accuracy, read length and throughput. These breakthroughs have required extensive development of experimental and bioinformatics methods to fully exploit nanopore long reads for investigations of genomes, transcriptomes, epigenomes and epitranscriptomes. Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance. Many opportunities remain for improving data quality and analytical approaches through the development of new nanopores, base-calling methods and experimental protocols tailored to particular applications.

Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

Background

Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data.

Result

Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization.

Conclusions

Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07791-z.

Chromosome-level genome assembly of the bean bug Riptortus pedestris

The bean bug (Riptortus pedestris) causes great economic losses of soybeans by piercing and sucking pods and seeds. Although R. pedestris has become the focus of numerous studies associated with insect-microbe interactions, plant-insect interactions, and pesticide resistance, a lack of genomic resources has limited deeper insights. Here, we report the first R. pedestris genome at the chromosomal level using PacBio, Illumina, and Hi-C technologies. The assembled genome was 1.080 Gb in size with a contig N50 of 2.882 Mb. More than 96.3% of the total genome bases were successfully anchored to six unique chromosomes. Genome resequencing of male and female individuals and chromosomic staining demonstrated that the sex chromosome system of R. pedestris is XO, and the shortest chromosome is the X chromosome. In total, 19,026 protein-coding genes were predicted, 18,745 of which were validated as being expressed. Temporospatial expression of R. pedestris genes in six tissues and 37 development stages revealed 4,657 and 7,793 genes mainly expressed in gonads and egg periods, respectively. Evolutionary analysis demonstrated that R. pedestris and Oncopeltus fasciatus formed a sister group and split ∼80 million years ago (Mya). Additionally, a 5.04 Mb complete genome of symbiotic Serratia marcescens Rip1 was assembled, and the virulence factors that account for successful colonization in the host midgut were identified. The high-quality R. pedestris genome provides a valuable resource for further research, as well as for the pest management of bug pests.

TRiCoLOR: tandem repeat profiling using whole-genome long-read sequencing data

BACKGROUND

Tandem repeat sequences are widespread in the human genome, and their expansions cause multiple repeat-mediated disorders. Genome-wide discovery approaches are needed to fully elucidate their roles in health and disease, but resolving tandem repeat variation accurately remains a challenging task. While traditional mapping-based approaches using short-read data have severe limitations in the size and type of tandem repeats they can resolve, recent third-generation sequencing technologies exhibit substantially higher sequencing error rates, which complicates repeat resolution.

RESULTS

We developed TRiCoLOR, a freely available tool for tandem repeat profiling using error-prone long reads from third-generation sequencing technologies. The method can identify repetitive regions in sequencing data without a prior knowledge of their motifs or locations and resolve repeat multiplicity and period size in a haplotype-specific manner. The tool includes methods to interactively visualize the identified repeats and to trace their Mendelian consistency in pedigrees.

CONCLUSIONS

TRiCoLOR demonstrates excellent performance and improved sensitivity and specificity compared with alternative tools on synthetic data. For real human whole-genome sequencing data, TRiCoLOR achieves high validation rates, suggesting its suitability to identify tandem repeat variation in personal genomes.

Versatile Quality Control Methods for Nanopore Sequencing

Third-generation sequencing using nanopores as biosensors has recently emerged as a strategy capable to overcome next-generation sequencing drawbacks and pitfalls. Assessing the quality of the data produced by nanopore sequencing platforms is essential to decide how useful these may be in making biological discoveries. Here, we briefly contextualized NanoR, a quality control method for nanopore sequencing data we developed, in the scenario of preexistent similar tools. We also illustrated 2 quality control pipelines, readily applicable to nanopore sequencing data, respectively, based on NanoR and PyPore, a second quality control method published by our group.