Training alignment parameters for arbitrary sequencers with LAST-TRAIN

Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing

Nanopore direct RNA sequencing (dRNA-seq) enables unique insights into RNA biology. However, applications are currently limited by the lack of accurate and cost-effective sample multiplexing. Here we introduce WarpDemuX, an ultra-fast and highly accurate adapter-barcoding and demultiplexing approach for dRNA-seq with SQK-RNA002 and SQK-RNA004 chemistries. WarpDemuX enhances speed and accuracy by fast processing of the raw nanopore signal, use of a light-weight machine-learning algorithm and design of optimized barcode sets. We demonstrate its utility by performing rapid phenotypic profiling of different SARS-CoV-2 viruses through multiplexed sequencing of longitudinal samples on a single flowcell, identifying systematic differences in transcript abundance and poly(A) tail lengths during infection. Additionally, integrating WarpDemuX into sequencing control software enables real-time enrichment of target molecules through barcode-specific adaptive sampling, which we demonstrate by enriching low abundance viral RNA. In summary, WarpDemuX represents a broadly applicable, high-performance, economical multiplexing solution for dRNA-seq, facilitating advanced (epi-) transcriptomic research.

Impact of Alignments on the Accuracy of Protein Subcellular Localization Predictions

Alignments in bioinformatics refer to the arrangement of sequences to identify regions of similarity that can indicate functional, structural, or evolutionary relationships. They are crucial for bioinformaticians as they enable accurate predictions and analyses in various applications, including protein subcellular localization. The predictive model used in this article is based on a deep - convolutional architecture. We tested configurations of Deep N-to-1 convolutional neural networks of various depths and widths during experimentation for the evaluation of better-performing values across a diverse set of eight classes. For without alignment assessment, sequences are encoded using one-hot encoding, converting each character into a numerical representation, which is straightforward for non-numerical data and useful for machine learning models. For with alignments assessment, multiple sequence alignments (MSAs) are created using PSI-BLAST, capturing evolutionary information by calculating frequencies of residues and gaps. The average difference in peak performance between models with alignments and without alignments is approximately 15.82%. The average difference in the highest accuracy achieved with alignments compared with without alignments is approximately 15.16%. Thus, extensive experimentation indicates that higher alignment accuracy implies a more reliable model and improved prediction accuracy, which can be trusted to deliver consistent performance across different layers and classes of subcellular localization predictions. This research provides valuable insights into prediction accuracies with and without alignments, offering bioinformaticians an effective tool for better understanding while potentially reducing the need for extensive experimental validations. The source code and datasets are available at http://distilldeep.ucd.ie/SCL8/.

Genetic linkage disequilibrium of deleterious mutations in threatened mammals

The impact of negative selection against deleterious mutations in endangered species remains underexplored. Recent studies have measured mutation load by comparing the accumulation of deleterious mutations, however, this method is most effective when comparing within and between populations of phylogenetically closely related species. Here, we introduced new statistics, LDcor, and its standardized form nLDcor, which allows us to detect and compare global linkage disequilibrium of deleterious mutations across species using unphased genotypes. These statistics measure averaged pairwise standardized covariance and standardize mutation differences based on the standard deviation of alleles to reflect selection intensity. We then examined selection strength in the genomes of seven mammals. Tigers exhibited an over-dispersion of deleterious mutations, while gorillas, giant pandas, and golden snub-nosed monkeys displayed negative linkage disequilibrium. Furthermore, the distribution of deleterious mutations in threatened mammals did not reveal consistent trends. Our results indicate that these newly developed statistics could help us understand the genetic burden of threatened species.

Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data

Third-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterize communities through the sequencing of long amplicons. While this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic for accurately identifying the community members present within a sample. Here, we present and validate CONCOMPRA, a tool that allows the detection of closely related strains within a community by drafting and mapping to consensus sequences. We show that CONCOMPRA outperforms several other tools for profiling bacterial communities using full-length 16S rRNA gene sequencing. Since CONCOMPRA does not rely on a sequence database for profiling communities, it is applicable to systems and amplicons for which little to no reference data exists. Our validation test shows that the amplification of long PCR products is likely to produce chimeric byproducts that inflate alpha diversity and skew community structure, stressing the importance of chimera detection. CONCOMPRA is available on GitHub (https://github.com/willem-stock/CONCOMPRA).

Targeted nanopore sequencing using the Flongle device to identify mitochondrial DNA variants

Variants in mitochondrial genomes (mtDNA) can cause various neurological and mitochondrial diseases such as mitochondrial myopathy, encephalopathy, lactic acidosis, stroke-like episodes (MELAS). Given the 16 kb length of mtDNA, continuous sequencing is feasible using long-read sequencing (LRS). Herein, we aimed to show a simple and accessible method for comprehensive mtDNA sequencing with potential diagnostic applications for mitochondrial diseases using the compact and affordable LRS flow cell "Flongle." Whole mtDNA amplification (WMA) was performed using genomic DNA samples derived from four patients with mitochondrial diseases, followed by LRS using Flongle. We compared these results to those obtained using Cas9 enrichment. Additionally, the accuracy of heteroplasmy rates was assessed by incorporating mtDNA variants at equimolar levels. Finally, mtDNA from 19 patients with Parkinson's disease (PD) was sequenced using Flongle to identify disease risk-associated variants. mtDNA variants were detected in all four patients with mitochondrial diseases, with results comparable to those obtained from Cas9 enrichment. Heteroplasmy levels were accurately detected (r2 > 0.99) via WMA using Flongle. A reported variant was identified in three patients with PD. In conclusion, Flongle can simplify the traditionally cumbersome and expensive mtDNA sequencing process, offering a streamlined and accessible approach to diagnosing mitochondrial diseases.

A simple method for finding related sequences by adding probabilities of alternative alignments

The main way of analyzing genetic sequences is by finding sequence regions that are related to each other. There are many methods to do that, usually based on this idea: Find an alignment of two sequence regions, which would be unlikely to exist between unrelated sequences. Unfortunately, it is hard to tell if an alignment is likely to exist by chance. Also, the precise alignment of related regions is uncertain. One alignment does not hold all evidence that they are related. We should consider alternative alignments too. This is rarely done, because we lack a simple and fast method that fits easily into practical sequence-search software. Described here is the simplest-conceivable change to standard sequence alignment, which sums probabilities of alternative alignments and makes it easier to tell if a similarity is likely to occur by chance. This approach is better than standard alignment at finding distant relationships, at least in a few tests. It can be used in practical sequence-search software, with minimal increase in implementation difficulty or run time. It generalizes to different kinds of alignment, for example, DNA-versus-protein with frameshifts. Thus, it can widely contribute to finding subtle relationships between sequences.

Utilizing a comparative approach to assess genome evolution during diploidization in Artemisia tridentata, a keystone species of western North America

PREMISE

Polyploidization is often followed by diploidization. Diploidization is generally studied using synthetic polyploid lines and/or crop plants, but rarely using extant diploids or nonmodel plants such as Artemisia tridentata. This threatened western North American keystone species has a large genome compared to congeneric Artemisia species; dominated by diploid and tetraploid cytotypes, with multiple origins of tetraploids with genome size reduction.

METHODS

The genome of an A. tridentata sample was resequenced to study genome evolution and compared to that of A. annua, a diploid congener. Three diploid genomes of A. tridentata were compared to test for multiple diploidization events.

RESULTS

The A. tridentata genome had many chromosomal rearrangements relative to that of A. annua, while large-scale synteny of A. tridentata chromosome 3 and A. annua chromosome 4 was conserved. The three A. tridentata genomes had similar sizes (4.19-4.2 Gbp), heterozygosity (2.24-2.25%), and sequence (98.73-99.15% similarity) across scaffolds, and in k-mer analyses, similar patterns of diploid heterozygous k-mers (AB = 41%, 47%, and 47%), triploid heterozygous k-mers (AAB = 18-21%), and tetraploid k-mers (AABB = 13-17%). Biallelic SNPs were evenly distributed across scaffolds for all individuals. Comparisons of transposable element (TE) content revealed differential enrichment of TE clades.

CONCLUSIONS

Our findings suggest population-level TE differentiation after a shared polyploidization-to-diploidization event(s) and exemplify the complex processes of genome evolution. This research approached provides new resources for exploration of abiotic stress response, especially the roles of TEs in response pathways.

Comparative transcriptome and methylome of polar bears, giant and red pandas reveal diet-driven adaptive evolution

Epigenetic regulation plays an important role in the evolution of species adaptations, yet little information is available on the epigenetic mechanisms underlying the adaptive evolution of bamboo-eating in both giant pandas (Ailuropoda melanoleuca) and red pandas (Ailurus fulgens). To investigate the potential contribution of epigenetic to the adaptive evolution of bamboo-eating in giant and red pandas, we performed hepatic comparative transcriptome and methylome analyses between bamboo-eating pandas and carnivorous polar bears (Ursus maritimus). We found that genes involved in carbohydrate, lipid, amino acid, and protein metabolism showed significant differences in methylation and expression levels between the two panda species and polar bears. Clustering analysis of gene expression revealed that giant pandas did not form a sister group with the more closely related polar bears, suggesting that the expression pattern of genes in livers of giant pandas and red pandas have evolved convergently driven by their similar diets. Compared to polar bears, some key genes involved in carbohydrate metabolism and biological oxidation and cholesterol synthesis showed hypomethylation and higher expression in giant and red pandas, while genes involved in fat digestion and absorption, fatty acid metabolism, lysine degradation, resistance to lipid peroxidation and detoxification showed hypermethylation and low expression. Our study elucidates the special nutrient utilization mechanism of giant pandas and red pandas and provides some insights into the molecular mechanism of their adaptive evolution of bamboo feeding. This has important implications for the breeding and conservation of giant pandas and red pandas.

Isoform-specific RNA structure determination using Nano-DMS-MaP

RNA structure determination is essential to understand how RNA carries out its diverse biological functions. In cells, RNA isoforms are readily expressed with partial variations within their sequences due, for example, to alternative splicing, heterogeneity in the transcription start site, RNA processing or differential termination/polyadenylation. Nanopore dimethyl sulfate mutational profiling (Nano-DMS-MaP) is a method for in situ isoform-specific RNA structure determination. Unlike similar methods that rely on short sequencing reads, Nano-DMS-MaP employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules to reveal their previously hidden structural differences. This Protocol describes the development and applications of Nano-DMS-MaP and outlines the main considerations for designing and implementing a successful experiment: from bench to data analysis. In cell probing experiments can be carried out by an experienced molecular biologist in 3-4 d. Data analysis requires good knowledge of command line tools and Python scripts and requires a further 3-5 d.

Extreme genome scrambling in marine planktonic Oikopleura dioica cryptic species

Genome structural variations within species are rare. How selective constraints preserve gene order and chromosome structure is a central question in evolutionary biology that remains unsolved. Our sequencing of several genomes of the appendicularian tunicate Oikopleura dioica around the globe reveals extreme genome scrambling caused by thousands of chromosomal rearrangements, although showing no obvious morphological differences between these animals. The breakpoint accumulation rate is an order of magnitude higher than in ascidian tunicates, nematodes, Drosophila, or mammals. Chromosome arms and sex-specific regions appear to be the primary unit of macrosynteny conservation. At the microsyntenic level, scrambling did not preserve operon structures, suggesting an absence of selective pressure to maintain them. The uncoupling of the genome scrambling with morphological conservation in O. dioica suggests the presence of previously unnoticed cryptic species and provides a new biological system that challenges our previous vision of speciation in which similar animals always share similar genome structures.

ONTbarcoder 2.0: rapid species discovery and identification with real-time barcoding facilitated by Oxford Nanopore R10.4

Most arthropod species are undescribed and hidden in specimen-rich samples that are difficult to sort to species using morphological characters. For such samples, sorting to putative species with DNA barcodes is an attractive alternative, but needs cost-effective techniques that are suitable for use in many laboratories around the world. Barcoding using the portable and inexpensive MinION sequencer produced by Oxford Nanopore Technologies (ONT) could be useful for presorting specimen-rich samples with DNA barcodes because it requires little space and is inexpensive. However, similarly important is user-friendly and reliable software for analysis of the ONT data. It is here provided in the form of ONTbarcoder 2.0 that is suitable for all commonly used operating systems and includes a Graphical User Interface (GUI). Compared with an earlier version, ONTbarcoder 2.0 has three key improvements related to the higher read quality obtained with ONT's latest flow cells (R10.4), chemistry (V14 kits) and basecalling model (super-accuracy model). First, the improved read quality of ONT's latest flow cells (R10.4) allows for the use of primers with shorter indices than those previously needed (9 bp vs. 12-13 bp). This decreases the primer cost and can potentially improve PCR success rates. Second, ONTbarcoder now delivers real-time barcoding to complement ONT's real-time sequencing. This means that the first barcodes are obtained within minutes of starting a sequencing run; i.e. flow cell use can be optimized by terminating sequencing runs when most barcodes have already been obtained. The only input needed by ONTbarcoder 2.0 is a demultiplexing sheet and sequencing data (raw or basecalled) generated by either a Mk1B or a Mk1C. Thirdly, we demonstrate that the availability of R10.4 chemistry for the low-cost Flongle flow cell is an attractive option for users who require only 200-250 barcodes at a time.

Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq

BACKGROUND

Parent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression analysis (DEA) applied to the counts of RNA-seq read pairs aligned to parental references, but aligners do not always choose the correct parental reference.

RESULTS

We used public data for species that are known to hybridize. We measured our ability to assign RNA-seq read pairs to their proper transcriptome or genome references. We tested software packages that assign each read pair to a reference position and found that they often favored the incorrect species reference. To address this problem, we introduce a post process that extracts alignment features and trains a random forest classifier to choose the better alignment. On each simulated hybrid dataset tested, our machine-learning post-processor achieved higher accuracy than the aligner by itself at choosing the correct parent-of-origin per RNA-seq read pair.

CONCLUSIONS

For the parent-of-origin classification of RNA-seq, machine learning can improve the accuracy of alignment-based methods. This approach could be useful for enhancing ASE detection in interspecies hybrids, though RNA-seq from real hybrids may present challenges not captured by our simulations. We believe this is the first application of machine learning to this problem domain.

Cost-Effective Cas9-Mediated Targeted Sequencing of Spinocerebellar Ataxia Repeat Expansions

Hereditary repeat diseases are caused by an abnormal expansion of short tandem repeats in the genome. Among them, spinocerebellar ataxia (SCA) is a heterogeneous disease, and currently, 16 responsible repeats are known. Genetic diagnosis is obtained by analyzing the number of repeats through separate testing of each repeat. Although simultaneous detection of candidate repeats using current massively parallel sequencing technologies has been developed to avoid complicated multiple experiments, these methods are generally expensive. This study developed a cost-effective SCA repeat panel [Flongle SCA repeat panel sequencing (FLO-SCAp)] using Cas9-mediated targeted long-read sequencing and the smallest long-read sequencing apparatus, Flongle. This panel enabled the detection of repeat copy number changes, internal repeat sequences, and DNA methylation in seven patients with different repeat expansion diseases. The median (interquartile range) values of coverage and on-target rate were 39.5 (12 to 72) and 11.6% (7.5% to 16.5%), respectively. This approach was validated by comparing repeat copy number changes measured by FLO-SCAp and short-read whole-genome sequencing. A high correlation was observed between FLO-SCAp and short-read whole-genome sequencing when the repeat length was ≤250 bp (r = 0.98; P < 0.001). Thus, FLO-SCAp represents the most cost-effective method for conducting multiplex testing of repeats and can serve as the first-line diagnostic tool for SCA.

Scalable, Cost-Effective, and Decentralized DNA Barcoding with Oxford Nanopore Sequencing

DNA barcodes are useful in biodiversity research, but sequencing barcodes with dye termination methods ("Sanger sequencing") has been so time-consuming and expensive that DNA barcodes are not as widely used as they should be. Fortunately, MinION sequencers from Oxford Nanopore Technologies have recently emerged as a cost-effective and efficient alternative for barcoding. MinION barcodes are now suitable for large-scale species discovery and enable specimen identification when the target species are represented in barcode databases. With a MinION, it is possible to obtain 10,000 barcodes from a single flow cell at a cost of less than 0.10 USD per specimen. Additionally, a Flongle flow cell can be used for small projects requiring up to 300 barcodes (0.50 USD per specimen). We here describe a cost-effective laboratory workflow for obtaining tagged amplicons, preparing ONT libraries, sequencing amplicon pools, and analyzing the MinION reads with the software ONTbarcoder. This workflow has been shown to yield highly accurate barcodes that are 99.99% identical to Sanger barcodes. Overall, we propose that the use of MinION for DNA barcoding is an attractive option for all researchers in need of a cost-effective and efficient solution for large-scale species discovery and specimen identification.

Genomic Signatures Associated with Transitions to Viviparity in Cyprinodontiformes

The transition from oviparity to viviparity has occurred independently over 150 times across vertebrates, presenting one of the most compelling cases of phenotypic convergence. However, whether the repeated, independent evolution of viviparity is driven by redeployment of similar genetic mechanisms and whether these leave a common signature in genomic divergence remains largely unknown. Although recent investigations into the evolution of viviparity have demonstrated striking similarity among the genes and molecular pathways involved across disparate vertebrate groups, quantitative tests for genome-wide convergent have provided ambivalent answers. Here, we investigate the potential role of molecular convergence during independent transitions to viviparity across an order of ray-finned freshwater fish (Cyprinodontiformes). We assembled de novo genomes and utilized publicly available genomes of viviparous and oviparous species to test for molecular convergence across both coding and noncoding regions. We found no evidence for an excess of molecular convergence in amino acid substitutions and in rates of sequence divergence, implying independent genetic changes are associated with these transitions. However, both statistical power and biological confounds could constrain our ability to detect significant correlated evolution. We therefore identified candidate genes with potential signatures of molecular convergence in viviparous Cyprinodontiformes lineages. Motif enrichment and gene ontology analyses suggest transcriptional changes associated with early morphogenesis, brain development, and immunity occurred alongside the evolution of viviparity. Overall, however, our findings indicate that independent transitions to viviparity in these fish are not strongly associated with an excess of molecular convergence, but a few genes show convincing evidence of convergent evolution.

Comparative Investigation of Coincident Single Nucleotide Polymorphisms Underlying Avian Influenza Viruses in Chickens and Ducks

Avian influenza is a severe viral infection that has the potential to cause human pandemics. In particular, chickens are susceptible to many highly pathogenic strains of the virus, resulting in significant losses. In contrast, ducks have been reported to exhibit rapid and effective innate immune responses to most avian influenza virus (AIV) infections. To explore the distinct genetic programs that potentially distinguish the susceptibility/resistance of both species to AIV, the investigation of coincident SNPs (coSNPs) and their differing causal effects on gene functions in both species is important to gain novel insight into the varying immune-related responses of chickens and ducks. By conducting a pairwise genome alignment between these species, we identified coSNPs and their respective effect on AIV-related differentially expressed genes (DEGs) in this study. The examination of these genes (e.g., CD74, RUBCN, and SHTN1 for chickens and ABCA3, MAP2K6, and VIPR2 for ducks) reveals their high relevance to AIV. Further analysis of these genes provides promising effector molecules (such as IκBα, STAT1/STAT3, GSK-3β, or p53) and related key signaling pathways (such as NF-κB, JAK/STAT, or Wnt) to elucidate the complex mechanisms of immune responses to AIV infections in both chickens and ducks.

Identification and characterization of novel ETV4 splice variants in prostate cancer

ETV4, one of ETS proteins overexpressed in prostate cancer, promotes migration, invasion, and proliferation in prostate cells. This study identifies a series of previously unknown ETV4 alternatively spliced transcripts in human prostate cell lines. Their expression has been validated using several unbiased techniques, including Nanopore sequencing. Most of these transcripts originate from an in-frame exon skipping and, thus, are expected to be translated into ETV4 protein isoforms. Functional analysis of the most abundant among these isoforms shows that they still bear an activity, namely a reduced ability to promote proliferation and a residual ability to regulate the transcription of ETV4 target genes. Alternatively spliced genes are common in cancer cells: an analysis of the TCGA dataset confirms the abundance of these novel ETV4 transcripts in prostate tumors, in contrast to peritumoral tissues. Since none of their translated isoforms have acquired a higher oncogenic potential, such abundance is likely to reflect the tumor deranged splicing machinery. However, it is also possible that their interaction with the canonical variants may contribute to the biology and the clinics of prostate cancer. Further investigations are needed to elucidate the biological role of these ETV4 transcripts and of their putative isoforms.

Analysis of Tandem Repeat Expansions Using Long DNA Reads

Abnormal expansion or shortening of tandem repeats can cause a variety of genetic diseases. The use of long DNA reads has facilitated the analysis of disease-causing repeats in the human genome. Long read sequencers enable us to directly analyze repeat length and sequence content by covering whole repeats; they are therefore considered suitable for the analysis of long tandem repeats. Here, we describe an expanded repeat analysis using target sequencing data produced by the Oxford Nanopore Technologies (hereafter referred to as ONT) nanopore sequencer.

Finding Rearrangements in Nanopore DNA Reads with LAST and dnarrange

Long-read DNA sequencing techniques such as nanopore are especially useful for characterizing complex sequence rearrangements, which occur in some genetic diseases and also during evolution. Analyzing the sequence data to understand such rearrangements is not trivial, due to sequencing error, rearrangement intricacy, and abundance of repeated similar sequences in genomes.The LAST and dnarrange software packages can resolve complex relationships between DNA sequences and characterize changes such as gene conversion, processed pseudogene insertion, and chromosome shattering. They can filter out numerous rearrangements shared by controls, e.g., healthy humans versus a patient, to focus on rearrangements unique to the patient. One useful ingredient is last-train, which learns the rates (probabilities) of deletions, insertions, and each kind of base match and mismatch. These probabilities are then used to find the most likely sequence relationships/alignments, which is especially useful for DNA with unusual rates, such as DNA from Plasmodium falciparum (malaria) with ∼80% a+t. This is also useful for less-studied species that lack reference genomes, so the DNA reads are compared to a different species' genome. We also point out that a reference genome with ancestral alleles would be ideal.

Novel genome sequence of Chinese cavefish (Triplophysa rosa) reveals pervasive relaxation of natural selection in cavefish genomes

All cavefishes, living exclusively in caves across the globe, exhibit similar phenotypic traits, including the characteristic loss of eyes. To understand whether such phenotypic convergence shares similar genomic bases, here we investigated genome-wide evolutionary signatures of cavefish phenotypes by comparing whole-genome sequences of three pairs of cavefishes and their surface fish relatives. Notably, we newly sequenced and generated a whole-genome assembly of the Chinese cavefish Triplophysa rosa. Our comparative analyses revealed several shared features of cavefish genome evolution. Cavefishes had lower mutation rates than their surface fish relatives. In contrast, the ratio of nonsynonymous to synonymous substitutions (ω) was significantly elevated in cavefishes compared to in surface fishes, consistent with the relaxation of purifying selection. In addition, cavefish genomes had an increased mutational load, including mutations that alter protein hydrophobicity profiles, which were considered harmful. Interestingly, however, we found no overlap in positively selected genes among different cavefish lineages, indicating that the phenotypic convergence in cavefishes was not caused by positive selection of the same sets of genes. Analyses of previously identified candidate genes associated with cave phenotypes supported this conclusion. Genes belonging to the lipid metabolism functional ontology were under relaxed purifying selection in all cavefish genomes, which may be associated with the nutrient-poor habitat of cavefishes. Our work reveals previously uncharacterized patterns of cavefish genome evolution and provides comparative insights into the evolution of cave-associated phenotypic traits.

Non-coding RNA LEVER sequestration of PRC2 can mediate long range gene regulation

Polycomb Repressive Complex 2 (PRC2) is an epigenetic regulator required for gene silencing during development. Although PRC2 is a well-established RNA-binding complex, the biological function of PRC2-RNA interaction has been controversial. Here, we study the gene-regulatory role of the inhibitory PRC2-RNA interactions. We report a nuclear long non-coding RNA, LEVER, which mapped 236 kb upstream of the β-globin cluster as confirmed by Nanopore sequencing. LEVER RNA interacts with PRC2 in its nascent form, and this prevents the accumulation of the H3K27 repressive histone marks within LEVER locus. Interestingly, the accessible LEVER chromatin, in turn, suppresses the chromatin interactions between the ε-globin locus and β-globin locus control region (LCR), resulting in a repressive effect on ε-globin gene expression. Our findings validate that the nascent RNA-PRC2 interaction inhibits local PRC2 function in situ. More importantly, we demonstrate that such a local process can in turn regulate the expression of neighboring genes.

Identification of a long non-coding RNA LEVER, that inhibits the Polycomb Repressive Complex 2 (PRC2) and controls nearby embryonic form of beta-globin gene, provides additional evidence for PRC2-RNA functional interaction.

Assembly-free rapid differential gene expression analysis in non-model organisms using DNA-protein alignment

BACKGROUND

RNA-seq is being increasingly adopted for gene expression studies in a panoply of non-model organisms, with applications spanning the fields of agriculture, aquaculture, ecology, and environment. For organisms that lack a well-annotated reference genome or transcriptome, a conventional RNA-seq data analysis workflow requires constructing a de-novo transcriptome assembly and annotating it against a high-confidence protein database. The assembly serves as a reference for read mapping, and the annotation is necessary for functional analysis of genes found to be differentially expressed. However, assembly is computationally expensive. It is also prone to errors that impact expression analysis, especially since sequencing depth is typically much lower for expression studies than for transcript discovery.

RESULTS

We propose a shortcut, in which we obtain counts for differential expression analysis by directly aligning RNA-seq reads to the high-confidence proteome that would have been otherwise used for annotation. By avoiding assembly, we drastically cut down computational costs - the running time on a typical dataset improves from the order of tens of hours to under half an hour, and the memory requirement is reduced from the order of tens of Gbytes to tens of Mbytes. We show through experiments on simulated and real data that our pipeline not only reduces computational costs, but has higher sensitivity and precision than a typical assembly-based pipeline. A Snakemake implementation of our workflow is available at: https://bitbucket.org/project_samar/samar .

CONCLUSIONS

The flip side of RNA-seq becoming accessible to even modestly resourced labs has been that the time, labor, and infrastructure cost of bioinformatics analysis has become a bottleneck. Assembly is one such resource-hungry process, and we show here that it can be avoided for quick and easy, yet more sensitive and precise, differential gene expression analysis in non-model organisms.

RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning

Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface.

Long-read metagenomics of multiple displacement amplified DNA of low-biomass human gut phageomes by SACRA pre-processing chimeric reads

The human gut bacteriophage community (phageome) plays an important role in the host's health and disease; however, the entire structure is poorly understood, partly owing to the generation of many incomplete genomes in conventional short-read metagenomics. Here, we show long-read metagenomics of amplified DNA of low-biomass phageomes with multiple displacement amplification (MDA), involving the development of a novel bioinformatics tool, split amplified chimeric read algorithm (SACRA), that efficiently pre-processed numerous chimeric reads generated through MDA. Using five samples, SACRA markedly reduced the average chimera ratio from 72% to 1.5% in PacBio reads with an average length of 1.8 kb. De novo assembly of chimera-less PacBio long reads reconstructed contigs of ≥5 kb with an average proportion of 27%, which was 1% in contigs from MiSeq short reads, thereby dramatically improving contig length and genome completeness. Comparison of PacBio and MiSeq contigs found MiSeq contig fragmentations frequently near local repeats and hypervariable regions in the phage genomes, and those caused by multiple homologous phage genomes coexisting in the community. We also developed a reference-independent method to assess the completeness of the linear phage genomes. Overall, we established a SACRA-coupled long-read metagenomics robust to highly diverse gut phageomes, identifying high-quality circular and linear phage genomes with adequate sequence quantity.

ONTbarcoder and MinION barcodes aid biodiversity discovery and identification by everyone, for everyone

BACKGROUND

DNA barcodes are a useful tool for discovering, understanding, and monitoring biodiversity which are critical tasks at a time of rapid biodiversity loss. However, widespread adoption of barcodes requires cost-effective and simple barcoding methods. We here present a workflow that satisfies these conditions. It was developed via "innovation through subtraction" and thus requires minimal lab equipment, can be learned within days, reduces the barcode sequencing cost to < 10 cents, and allows fast turnaround from specimen to sequence by using the portable MinION sequencer.

RESULTS

We describe how tagged amplicons can be obtained and sequenced with the real-time MinION sequencer in many settings (field stations, biodiversity labs, citizen science labs, schools). We also provide amplicon coverage recommendations that are based on several runs of the latest generation of MinION flow cells ("R10.3") which suggest that each run can generate barcodes for > 10,000 specimens. Next, we present a novel software, ONTbarcoder, which overcomes the bioinformatics challenges posed by MinION reads. The software is compatible with Windows 10, Macintosh, and Linux, has a graphical user interface (GUI), and can generate thousands of barcodes on a standard laptop within hours based on only two input files (FASTQ, demultiplexing file). We document that MinION barcodes are virtually identical to Sanger and Illumina barcodes for the same specimens (> 99.99%) and provide evidence that MinION flow cells and reads have improved rapidly since 2018.

CONCLUSIONS

We propose that barcoding with MinION is the way forward for government agencies, universities, museums, and schools because it combines low consumable and capital cost with scalability. Small projects can use the flow cell dongle ("Flongle") while large projects can rely on MinION flow cells that can be stopped and re-used after collecting sufficient data for a given project.

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The number of pan-genes in these diverse genomes exceeds 103,000, with approximately a third found across all genotypes. The results demonstrate that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres revealed additional variation in major cytological landmarks. We show that combining structural variation with single-nucleotide polymorphisms can improve the power of quantitative mapping studies. We also document variation at the level of DNA methylation and demonstrate that unmethylated regions are enriched for cis-regulatory elements that contribute to phenotypic variation.

PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores

Motivation

Recent advances in high-throughput long-read sequencers, such as PacBio and Oxford Nanopore sequencers, produce longer reads with more errors than short-read sequencers. In addition to the high error rates of reads, non-uniformity of errors leads to difficulties in various downstream analyses using long reads. Many useful simulators, which characterize long-read error patterns and simulate them, have been developed. However, there is still room for improvement in the simulation of the non-uniformity of errors.

Results

To capture characteristics of errors in reads for long-read sequencers, here, we introduce a generative model for quality scores, in which a hidden Markov Model with a latest model selection method, called factorized information criteria, is utilized. We evaluated our developed simulator from various points, indicating that our simulator successfully simulates reads that are consistent with real reads.

Availability and implementation

The source codes of PBSIM2 are freely available from https://github.com/yukiteruono/pbsim2.

Supplementary information

Supplementary data are available at Bioinformatics online.

The molecular signatures of compatible and incompatible pollination in Arabidopsis

Background

Fertilization in flowering plants depends on the early contact and acceptance of pollen grains by the receptive papilla cells of the stigma. Deciphering the specific transcriptomic response of both pollen and stigmatic cells during their interaction constitutes an important challenge to better our understanding of this cell recognition event.

Results

Here we describe a transcriptomic analysis based on single nucleotide polymorphisms (SNPs) present in two Arabidopsis thaliana accessions, one used as female and the other as male. This strategy allowed us to distinguish 80% of transcripts according to their parental origins. We also developed a tool which predicts male/female specific expression for genes without SNP. We report an unanticipated transcriptional activity triggered in stigma upon incompatible pollination and show that following compatible interaction, components of the pattern-triggered immunity (PTI) pathway are induced on the female side.

Conclusions

Our work unveils the molecular signatures of compatible and incompatible pollinations both at the male and female side. We provide invaluable resource and tools to identify potential new molecular players involved in pollen-stigma interaction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07503-7.

Telomere-to-telomere assembly of the genome of an individual Oikopleura dioica from Okinawa using Nanopore-based sequencing

Background

The larvacean Oikopleura dioica is an abundant tunicate plankton with the smallest (65–70 Mbp) non-parasitic, non-extremophile animal genome identified to date. Currently, there are two genomes available for the Bergen (OdB3) and Osaka (OSKA2016) O. dioica laboratory strains. Both assemblies have full genome coverage and high sequence accuracy. However, a chromosome-scale assembly has not yet been achieved.

Results

Here, we present a chromosome-scale genome assembly (OKI2018_I69) of the Okinawan O. dioica produced using long-read Nanopore and short-read Illumina sequencing data from a single male, combined with Hi-C chromosomal conformation capture data for scaffolding. The OKI2018_I69 assembly has a total length of 64.3 Mbp distributed among 19 scaffolds. 99% of the assembly is contained within five megabase-scale scaffolds. We found telomeres on both ends of the two largest scaffolds, which represent assemblies of two fully contiguous autosomal chromosomes. Each of the other three large scaffolds have telomeres at one end only and we propose that they correspond to sex chromosomes split into a pseudo-autosomal region and X-specific or Y-specific regions. Indeed, these five scaffolds mostly correspond to equivalent linkage groups in OdB3, suggesting overall agreement in chromosomal organization between the two populations. At a more detailed level, the OKI2018_I69 assembly possesses similar genomic features in gene content and repetitive elements reported for OdB3. The Hi-C map suggests few reciprocal interactions between chromosome arms. At the sequence level, multiple genomic features such as GC content and repetitive elements are distributed differently along the short and long arms of the same chromosome.

Conclusions

We show that a hybrid approach of integrating multiple sequencing technologies with chromosome conformation information results in an accurate de novo chromosome-scale assembly of O. dioica’s highly polymorphic genome. This genome assembly opens up the possibility of cross-genome comparison between O. dioica populations, as well as of studies of chromosomal evolution in this lineage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07512-6.

Nanopore direct RNA sequencing detects DUX4-activated repeats and isoforms in human muscle cells

Facioscapulohumeral muscular dystrophy (FSHD) is an inherited muscle disease caused by misexpression of the DUX4 gene in skeletal muscle. DUX4 is a transcription factor, which is normally expressed in the cleavage-stage embryo and regulates gene expression involved in early embryonic development. Recent studies revealed that DUX4 also activates the transcription of repetitive elements such as endogenous retroviruses (ERVs), mammalian apparent long terminal repeat (LTR)-retrotransposons and pericentromeric satellite repeats (Human Satellite II). DUX4-bound ERV sequences also create alternative promoters for genes or long non-coding RNAs, producing fusion transcripts. To further understand transcriptional regulation by DUX4, we performed nanopore long-read direct RNA sequencing (dRNA-seq) of human muscle cells induced by DUX4, because long reads show whole isoforms with greater confidence. We successfully detected differential expression of known DUX4-induced genes and discovered 61 differentially expressed repeat loci, which are near DUX4–ChIP peaks. We also identified 247 gene–ERV fusion transcripts, of which 216 were not reported previously. In addition, long-read dRNA-seq clearly shows that RNA splicing is a common event in DUX4-activated ERV transcripts. Long-read analysis showed non-LTR transposons including Alu elements are also transcribed from LTRs. Our findings revealed further complexity of DUX4-induced ERV transcripts. This catalogue of DUX4-activated repetitive elements may provide useful information to elucidate the pathology of FSHD. Also, our results indicate that nanopore dRNA-seq has complementary strengths to conventional short-read complementary DNA sequencing.

lncEvo: automated identification and conservation study of long noncoding RNAs

BACKGROUND

Long noncoding RNAs represent a large class of transcripts with two common features: they exceed an arbitrary length threshold of 200 nt and are assumed to not encode proteins. Although a growing body of evidence indicates that the vast majority of lncRNAs are potentially nonfunctional, hundreds of them have already been revealed to perform essential gene regulatory functions or to be linked to a number of cellular processes, including those associated with the etiology of human diseases. To better understand the biology of lncRNAs, it is essential to perform a more in-depth study of their evolution. In contrast to protein-encoding transcripts, however, they do not show the strong sequence conservation that usually results from purifying selection; therefore, software that is typically used to resolve the evolutionary relationships of protein-encoding genes and transcripts is not applicable to the study of lncRNAs.

RESULTS

To tackle this issue, we developed lncEvo, a computational pipeline that consists of three modules: (1) transcriptome assembly from RNA-Seq data, (2) prediction of lncRNAs, and (3) conservation study-a genome-wide comparison of lncRNA transcriptomes between two species of interest, including search for orthologs. Importantly, one can choose to apply lncEvo solely for transcriptome assembly or lncRNA prediction, without calling the conservation-related part.

CONCLUSIONS

lncEvo is an all-in-one tool built with the Nextflow framework, utilizing state-of-the-art software and algorithms with customizable trade-offs between speed and sensitivity, ease of use and built-in reporting functionalities. The source code of the pipeline is freely available for academic and nonacademic use under the MIT license at https://gitlab.com/spirit678/lncrna_conservation_nf .

Investigating the mitochondrial genomic landscape of Arabidopsis thaliana by long-read sequencing

Plant mitochondrial genomes have distinctive features compared to those of animals; namely, they are large and divergent, with sizes ranging from hundreds of thousands of to a few million bases. Recombination among repetitive regions is thought to produce similar structures that differ slightly, known as "multipartite structures," which contribute to different phenotypes. Although many reference plant mitochondrial genomes represent almost all the genes in mitochondria, the full spectrum of their structures remains largely unknown. The emergence of long-read sequencing technology is expected to yield this landscape; however, many studies aimed to assemble only one representative circular genome, because properly understanding multipartite structures using existing assemblers is not feasible. To elucidate multipartite structures, we leveraged the information in existing reference genomes and classified long reads according to their corresponding structures. We developed a method that exploits two classic algorithms, partial order alignment (POA) and the hidden Markov model (HMM) to construct a sensitive read classifier. This method enables us to represent a set of reads as a POA graph and analyze it using the HMM. We can then calculate the likelihood of a read occurring in a given cluster, resulting in an iterative clustering algorithm. For synthetic data, our proposed method reliably detected one variation site out of 9,000-bp synthetic long reads with a 15% sequencing-error rate and produced accurate clustering. It was also capable of clustering long reads from six very similar sequences containing only slight differences. For real data, we assembled putative multipartite structures of mitochondrial genomes of Arabidopsis thaliana from nine accessions sequenced using PacBio Sequel. The results indicated that there are recurrent and strain-specific structures in A. thaliana mitochondrial genomes.

lamassemble: Multiple Alignment and Consensus Sequence of Long Reads

Long DNA and RNA reads from nanopore and PacBio technologies have many applications, but the raw reads have a substantial error rate. More accurate sequences can be obtained by merging multiple reads from overlapping parts of the same sequence. lamassemble aligns up to ∼1000 reads to each other, and makes a consensus sequence, which is often much more accurate than the raw reads. It is useful for studying a region of interest such as an expanded tandem repeat or other disease-causing mutation.

Regional sequence expansion or collapse in heterozygous genome assemblies

High levels of heterozygosity present a unique genome assembly challenge and can adversely impact downstream analyses, yet is common in sequencing datasets obtained from non-model organisms. Here we show that by re-assembling a heterozygous dataset with variant parameters and different assembly algorithms, we are able to generate assemblies whose protein annotations are statistically enriched for specific gene ontology categories. While total assembly length was not significantly affected by assembly methodologies tested, the assemblies generated varied widely in fragmentation level and we show local assembly collapse or expansion underlying the enrichment or depletion of specific protein functional groups. We show that these statistically significant deviations in gene ontology groups can occur in seemingly high-quality assemblies, and result from difficult-to-detect local sequence expansion or contractions. Given the unpredictable interplay between assembly algorithm, parameter, and biological sequence data heterozygosity, we highlight the need for better measures of assembly quality than N50 value, including methods for assessing local expansion and collapse.

In the genomic era, genomes must be reconstructed from fragments using computational methods, or assemblers. How do we know that a new genome assembly is correct? This is important because errors in assembly can lead to downstream problems in gene predictions and these inaccurate results can contaminate databases, affecting later comparative studies. A particular challenge occurs when a diploid organism inherits two highly divergent genome copies from its parents. While it is widely appreciated that this type of data is difficult for assemblers to handle properly, here we show that the process is prone to more errors than previously appreciated. Specifically, we document examples of regional expansion and collapse, affecting downstream gene prediction accuracy, but without changing the overall genome assembly size or other metrics of accuracy. Our results suggest that assembly evaluation methods should be altered to identify whether regional expansions and collapses are present in the genome assembly.

A pipeline for complete characterization of complex germline rearrangements from long DNA reads

BACKGROUND

Many genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. It is important to fully understand the order and orientation of rearranged fragments, with precise breakpoints, to know the pathogenicity of the rearrangements.

METHODS

We performed whole-genome-coverage nanopore sequencing of long DNA reads from four patients with chromosomal translocations. We identified rearrangements relative to a reference human genome, subtracted rearrangements shared by any of 33 control individuals, and determined the order and orientation of rearranged fragments, with our newly developed analysis pipeline.

RESULTS

We describe the full characterization of complex chromosomal rearrangements, by filtering out genomic rearrangements seen in controls without the same disease, reducing the number of loci per patient from a few thousand to a few dozen. Breakpoint detection was very accurate; we usually see ~ 0 ± 1 base difference from Sanger sequencing-confirmed breakpoints. For one patient with two reciprocal chromosomal translocations, we find that the translocation points have complex rearrangements of multiple DNA fragments involving 5 chromosomes, which we could order and orient by an automatic algorithm, thereby fully reconstructing the rearrangement. A rearrangement is more than the sum of its parts: some properties, such as sequence loss, can be inferred only after reconstructing the whole rearrangement. In this patient, the rearrangements were evidently caused by shattering of the chromosomes into multiple fragments, which rejoined in a different order and orientation with loss of some fragments.

CONCLUSIONS

We developed an effective analytic pipeline to find chromosomal aberration in congenital diseases by filtering benign changes, only from long read sequencing. Our algorithm for reconstruction of complex rearrangements is useful to interpret rearrangements with many breakpoints, e.g., chromothripsis. Our approach promises to fully characterize many congenital germline rearrangements, provided they do not involve poorly understood loci such as centromeric repeats.

Benchmarking hybrid assemblies of Giardia and prediction of widespread intra-isolate structural variation

Background

Currently available short read genome assemblies of the tetraploid protozoan parasite Giardia intestinalis are highly fragmented, highlighting the need for improved genome assemblies at a reasonable cost. Long nanopore reads are well suited to resolve repetitive genomic regions resulting in better quality assemblies of eukaryotic genomes. Subsequent addition of highly accurate short reads to long-read assemblies further improves assembly quality. Using this hybrid approach, we assembled genomes for three Giardia isolates, two with published assemblies and one novel, to evaluate the improvement in genome quality gained from long reads. We then used the long reads to predict structural variants to examine this previously unexplored source of genetic variation in Giardia.

Methods

With MinION reads for each isolate, we assembled genomes using several assemblers specializing in long reads. Assembly metrics, gene finding, and whole genome alignments to the reference genomes enabled direct comparison to evaluate the performance of the nanopore reads. Further improvements from adding Illumina reads to the long-read assemblies were evaluated using gene finding. Structural variants were predicted from alignments of the long reads to the best hybrid genome for each isolate and enrichment of key genes was analyzed using random genome sampling and calculation of percentiles to find thresholds of significance.

Results

Our hybrid assembly method generated reference quality genomes for each isolate. Consistent with previous findings based on SNPs, examination of heterozygosity using the structural variants found that Giardia BGS was considerably more heterozygous than the other isolates that are from Assemblage A. Further, each isolate was shown to contain structural variant regions enriched for variant-specific surface proteins, a key class of virulence factor in Giardia.

Conclusions

The ability to generate reference quality genomes from a single MinION run and a multiplexed MiSeq run enables future large-scale comparative genomic studies within the genus Giardia. Further, prediction of structural variants from long reads allows for more in-depth analyses of major sources of genetic variation within and between Giardia isolates that could have effects on both pathogenicity and host range.

Long-read sequencing for rare human genetic diseases

During the past decade, the search for pathogenic mutations in rare human genetic diseases has involved huge efforts to sequence coding regions, or the entire genome, using massively parallel short-read sequencers. However, the approximate current diagnostic rate is <50% using these approaches, and there remain many rare genetic diseases with unknown cause. There may be many reasons for this, but one plausible explanation is that the responsible mutations are in regions of the genome that are difficult to sequence using conventional technologies (e.g., tandem-repeat expansion or complex chromosomal structural aberrations). Despite the drawbacks of high cost and a shortage of standard analytical methods, several studies have analyzed pathogenic changes in the genome using long-read sequencers. The results of these studies provide hope that further application of long-read sequencers to identify the causative mutations in unsolved genetic diseases may expand our understanding of the human genome and diseases. Such approaches may also be applied to molecular diagnosis and therapeutic strategies for patients with genetic diseases in the future.

Rate variation in the evolution of non-coding DNA associated with social evolution in bees

The evolutionary origins of eusociality represent increases in complexity from individual to caste-based, group reproduction. These behavioural transitions have been hypothesized to go hand in hand with an increased ability to regulate when and where genes are expressed. Bees have convergently evolved eusociality up to five times, providing a framework to test this hypothesis. To examine potential links between putative gene regulatory elements and social evolution, we compare alignable, non-coding sequences in 11 diverse bee species, encompassing three independent origins of reproductive division of labour and two elaborations of eusocial complexity. We find that rates of evolution in a number of non-coding sequences correlate with key social transitions in bees. Interestingly, while we find little evidence for convergent rate changes associated with independent origins of social behaviour, a number of molecular pathways exhibit convergent rate changes in conjunction with subsequent elaborations of social organization. We also present evidence that many novel non-coding regions may have been recruited alongside the origin of sociality in corbiculate bees; these loci could represent gene regulatory elements associated with division of labour within this group. Thus, our findings are consistent with the hypothesis that gene regulatory innovations are associated with the evolution of eusociality and illustrate how a thorough examination of both coding and non-coding sequence can provide a more complete understanding of the molecular mechanisms underlying behavioural evolution. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

A survey of localized sequence rearrangements in human DNA

Genomes mutate and evolve in ways simple (substitution or deletion of bases) and complex (e.g. chromosome shattering). We do not fully understand what types of complex mutation occur, and we cannot routinely characterize arbitrarily-complex mutations in a high-throughput, genome-wide manner. Long-read DNA sequencing methods (e.g. PacBio, nanopore) are promising for this task, because one read may encompass a whole complex mutation. We describe an analysis pipeline to characterize arbitrarily-complex 'local' mutations, i.e. intrachromosomal mutations encompassed by one DNA read. We apply it to nanopore and PacBio reads from one human cell line (NA12878), and survey sequence rearrangements, both real and artifactual. Almost all the real rearrangements belong to recurring patterns or motifs: the most common is tandem multiplication (e.g. heptuplication), but there are also complex patterns such as localized shattering, which resembles DNA damage by radiation. Gene conversions are identified, including one between hemoglobin gamma genes. This study demonstrates a way to find intricate rearrangements with any number of duplications, deletions, and repositionings. It demonstrates a probability-based method to resolve ambiguous rearrangements involving highly similar sequences, as occurs in gene conversion. We present a catalog of local rearrangements in one human cell line, and show which rearrangement patterns occur.

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genome

We sequenced the genome of the Yoruban reference individual NA19240 on the long-read sequencing platform Oxford Nanopore PromethION for evaluation and benchmarking of recently published aligners and germline structural variant calling tools, as well as a comparison with the performance of structural variant calling from short-read sequencing data. The structural variant caller Sniffles after NGMLR or minimap2 alignment provides the most accurate results, but additional confidence or sensitivity can be obtained by a combination of multiple variant callers. Sensitive and fast results can be obtained by minimap2 for alignment and a combination of Sniffles and SVIM for variant identification. We describe a scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long-read genome sequencing of an individual or population. By discussing the results of this well-characterized reference individual, we provide an approximation of what can be expected in future long-read sequencing studies aiming for structural variant identification.

Tandem-genotypes: robust detection of tandem repeat expansions from long DNA reads

Tandemly repeated DNA is highly mutable and causes at least 31 diseases, but it is hard to detect pathogenic repeat expansions genome-wide. Here, we report robust detection of human repeat expansions from careful alignments of long but error-prone (PacBio and nanopore) reads to a reference genome. Our method is robust to systematic sequencing errors, inexact repeats with fuzzy boundaries, and low sequencing coverage. By comparing to healthy controls, we prioritize pathogenic expansions within the top 10 out of 700,000 tandem repeats in whole genome sequencing data. This may help to elucidate the many genetic diseases whose causes remain unknown.

Evaluation and application of RNA-Seq by MinION

The current RNA-Seq method analyses fragments of mRNAs, from which it is occasionally difficult to reconstruct the entire transcript structure. Here, we performed and evaluated the recent procedure for full-length cDNA sequencing using the Nanopore sequencer MinION. We applied MinION RNA-Seq for various applications, which would not always be easy using the usual RNA-Seq by Illumina. First, we examined and found that even though the sequencing accuracy was still limited to 92.3%, practically useful RNA-Seq analysis is possible. Particularly, taking advantage of the long-read nature of MinION, we demonstrate the identification of splicing patterns and their combinations as a form of full-length cDNAs without losing precise information concerning their expression levels. Transcripts of fusion genes in cancer cells can also be identified and characterized. Furthermore, the full-length cDNA information can be used for phasing of the SNPs detected by WES on the transcripts, providing essential information to identify allele-specific transcriptional events. We constructed a catalogue of full-length cDNAs in seven major organs for two particular individuals and identified allele-specific transcription and splicing. Finally, we demonstrate that single-cell sequencing is also possible. RNA-Seq on the MinION platform should provide a novel approach that is complementary to the current RNA-Seq.

NanoPipe-a web server for nanopore MinION sequencing data analysis

BACKGROUND

The fast-moving progress of the third-generation long-read sequencing technologies will soon bring the biological and medical sciences to a new era of research. Altogether, the technique and experimental procedures are becoming more straightforward and available to biologists from diverse fields, even without any profound experience in DNA sequencing. Thus, the introduction of the MinION device by Oxford Nanopore Technologies promises to "bring sequencing technology to the masses" and also allows quick and operative analysis in field studies. However, the convenience of this sequencing technology dramatically contrasts with the available analysis tools, which may significantly reduce enthusiasm of a "regular" user. To really bring the sequencing technology to every biologist, we need a set of user-friendly tools that can perform a powerful analysis in an automatic manner.

FINDINGS

NanoPipe was developed in consideration of the specifics of the MinION sequencing technologies, providing accordingly adjusted alignment parameters. The range of the target species/sequences for the alignment is not limited, and the descriptive usage page of NanoPipe helps a user to succeed with NanoPipe analysis. The results contain alignment statistics, consensus sequence, polymorphisms data, and visualization of the alignment. Several test cases are used to demonstrate the efficiency of the tool.

CONCLUSIONS

Freely available NanoPipe software allows effortless and reliable analysis of MinION sequencing data for experienced bioinformaticians, as well for wet-lab biologists with minimum bioinformatics knowledge. Moreover, for the latter group, we describe the basic algorithm necessary for MinION sequencing analysis from the first to last step.

Sequencing and phasing cancer mutations in lung cancers using a long-read portable sequencer

Here, we employed cDNA amplicon sequencing using a long-read portable sequencer, MinION, to characterize various types of mutations in cancer-related genes, namely, EGFR, KRAS, NRAS and NF1. For homozygous SNVs, the precision and recall rates were 87.5% and 91.3%, respectively. For previously reported hotspot mutations, the precision and recall rates reached 100%. The precise junctions of EML4-ALK, CCDC6-RET and five other gene fusions were also detected. Taking advantages of long-read sequencing, we conducted phasing of EGFR mutations and elucidated the mutational allelic backgrounds of anti-tumor drug-sensitive and resistant mutations, which could provide useful information for selecting therapeutic approaches. In the H1975 cells, 72% of the reads harbored both L858R and T790M mutations, and 22% of the reads harbored neither mutation. To ensure that the clinical requirements can be met in potentially low cancer cell populations, we further conducted a serial dilution analysis of the template for EGFR mutations. Several percent of the mutant alleles could be detected depending on the yield and quality of the sequencing data. Finally, we characterized the mutation genotypes in eight clinical samples. This method could be a convenient long-read sequencing-based analytical approach and thus may change the current approaches used for cancer genome sequencing.

Beyond similarity assessment: selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm

Motivation

Pair Hidden Markov Models (PHMMs) are probabilistic models used for pairwise sequence alignment, a quintessential problem in bioinformatics. PHMMs include three types of hidden states: match, insertion and deletion. Most previous studies have used one or two hidden states for each PHMM state type. However, few studies have examined the number of states suitable for representing sequence data or improving alignment accuracy.

Results

We developed a novel method to select superior models (including the number of hidden states) for PHMM. Our method selects models with the highest posterior probability using Factorized Information Criterion, which is widely utilized in model selection for probabilistic models with hidden variables. Our simulations indicated that this method has excellent model selection capabilities with slightly improved alignment accuracy. We applied our method to DNA datasets from 5 and 28 species, ultimately selecting more complex models than those used in previous studies.

Availability and implementation

The software is available at https://github.com/bigsea-t/fab-phmm.

Supplementary information

Supplementary data are available at Bioinformatics online.

Nanopore-based single molecule sequencing of the D4Z4 array responsible for facioscapulohumeral muscular dystrophy

Subtelomeric macrosatellite repeats are difficult to sequence using conventional sequencing methods owing to the high similarity among repeat units and high GC content. Sequencing these repetitive regions is challenging, even with recent improvements in sequencing technologies. Among these repeats, a haplotype carrying a particular sequence and shortening of the D4Z4 array on human chromosome 4q35 causes one of the most prevalent forms of muscular dystrophy with autosomal-dominant inheritance, facioscapulohumeral muscular dystrophy (FSHD). Here, we applied a nanopore-based ultra-long read sequencer to sequence a BAC clone containing 13 D4Z4 repeats and flanking regions. We successfully obtained the whole D4Z4 repeat sequence, including the pathogenic gene DUX4 in the last D4Z4 repeat. The estimated sequence accuracy of the total repeat region was 99.8% based on a comparison with the reference sequence. Errors were typically observed between purine or between pyrimidine bases. Further, we analyzed the D4Z4 sequence from publicly available ultra-long whole human genome sequencing data obtained by nanopore sequencing. This technology may be a new tool for studying D4Z4 repeats and pathomechanism of FSHD in the future and has the potential to widen our understanding of subtelomeric regions.