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.
Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads.
The sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective standalone technology for de novo assembly of human genomes. © 2019 John Wiley & Sons Ltd/University College London.
Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases.
The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with ‘ready-to-use’ deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.
The recent advent of long-read sequencing technologies is expected to provide reasonable answers to genetic challenges unresolvable by short-read sequencing, primarily the inability to accurately study structural variations, copy number variations, and homologous repeats in complex parts of the genome. However, long-read sequencing comes along with higher rates of random short deletions and insertions, and single nucleotide errors. The relatively higher sequencing accuracy of short-read sequencing has kept it as the first choice of screening for single nucleotide variants and short deletions and insertions. Albeit, short-read sequencing still suffers from systematic errors that tend to occur at specific positions where a high depth of reads is not always capable to correct for these errors. In this study, we compared the genotyping of mitochondrial DNA variants in three samples using PacBio’s Sequel (Pacific Biosciences Inc., Menlo Park, CA, USA) long-read sequencing and illumina’s HiSeqX10 (illumine Inc., San Diego, CA, USA) short-read sequencing data. We concluded that, despite the differences in the type and frequency of errors in the long-reads sequencing, its accuracy is still comparable to that of short-reads for genotyping short nuclear variants; due to the randomness of errors in long reads, a lower coverage, around 37 reads, can be sufficient to correct for these random errors.
Development of high-throughput sequencing techniques have greatly benefited our understanding about microbial ecology; yet the methods producing short reads suffer from species-level resolution and uncertainty of identification. Here we optimize PacBio-based metabarcoding protocols covering the Internal Transcribed Spacer (ITS region) and partial Small Subunit (SSU) of the rRNA gene for species-level identification of all eukaryotes, with a specific focus on Fungi (including Glomeromycota) and Stramenopila (particularly Oomycota). Based on tests on composite soil samples and mock communities, we propose best suitable degenerate primers, ITS9munngs + ITS4ngsUni for eukaryotes and selected groups therein and discuss pros and cons of long read-based identification of eukaryotes. This article is protected by copyright. All rights reserved.
Long-read RNA sequencing (RNA-seq) is promising to transcriptomics studies, however, the alignment of the reads is still a fundamental but non-trivial task due to the sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass long RNA-seq read alignment approach, which constructs graph-based alignment skeletons to sensitively infer exons, and use them to generate spliced reference sequence to produce refined alignments. deSALT addresses several difficult issues, such as small exons, serious sequencing errors and consensus spliced alignment. Benchmarks demonstrate that this approach has a better ability to produce high-quality full-length alignments, which has enormous potentials to transcriptomics studies.
Motivation: Third-generation sequencing technologies can sequence long reads, which is advancing the frontiers of genomics research. However, their high error rates prohibit accurate and efficient downstream analysis. This difficulty has motivated the development of many long read error correction tools, which tackle this problem through sampling redundancy and/or leveraging accurate short reads of the same biological samples. Existing studies to asses these tools use simulated data sets, and are not sufficiently comprehensive in the range of software covered or diversity of evaluation measures used. Results: In this paper, we present a categorization and review of long read error correction methods, and provide a comprehensive evaluation of the corresponding long read error correction tools. Leveraging recent real sequencing data, we establish benchmark data sets and set up evaluation criteria for a comparative assessment which includes quality of error correction as well as run-time and memory usage. We study how trimming and long read sequencing depth affect error correction in terms of length distribution and genome coverage post-correction, and the impact of error correction performance on an important application of long reads, genome assembly. We provide guidelines for practitioners for choosing among the available error correction tools and identify directions for future research.
Existing long-read assemblers require tens of thousands of CPU hours to assemble a human genome and are being outpaced by sequencing technologies in terms of both throughput and cost. We developed a novel long-read assembler wtdbg2 that, for human data, is tens of times faster than published tools while achieving comparable contiguity and accuracy. It represents a significant algorithmic advance and paves the way for population-scale long-read assembly in future.
Relative Performance of MinION (Oxford Nanopore Technologies) versus Sequel (Pacific Biosciences) Third-Generation Sequencing Instruments in Identification of Agricultural and Forest Fungal Pathogens.
Culture-based molecular identification methods have revolutionized detection of pathogens, yet these methods are slow and may yield inconclusive results from environmental materials. The second-generation sequencing tools have much-improved precision and sensitivity of detection, but these analyses are costly and may take several days to months. Of the third-generation sequencing techniques, the portable MinION device (Oxford Nanopore Technologies) has received much attention because of its small size and possibility of rapid analysis at reasonable cost. Here, we compare the relative performances of two third-generation sequencing instruments, MinION and Sequel (Pacific Biosciences), in identification and diagnostics of fungal and oomycete pathogens from conifer (Pinaceae) needles and potato (Solanum tuberosum) leaves and tubers. We demonstrate that the Sequel instrument is efficient for metabarcoding of complex samples, whereas MinION is not suited for this purpose due to a high error rate and multiple biases. However, we find that MinION can be utilized for rapid and accurate identification of dominant pathogenic organisms and other associated organisms from plant tissues following both amplicon-based and PCR-free metagenomics approaches. Using the metagenomics approach with shortened DNA extraction and incubation times, we performed the entire MinION workflow, from sample preparation through DNA extraction, sequencing, bioinformatics, and interpretation, in 2.5 h. We advocate the use of MinION for rapid diagnostics of pathogens and potentially other organisms, but care needs to be taken to control or account for multiple potential technical biases.IMPORTANCE Microbial pathogens cause enormous losses to agriculture and forestry, but current combined culturing- and molecular identification-based detection methods are too slow for rapid identification and application of countermeasures. Here, we develop new and rapid protocols for Oxford Nanopore MinION-based third-generation diagnostics of plant pathogens that greatly improve the speed of diagnostics. However, due to high error rate and technical biases in MinION, the Pacific BioSciences Sequel platform is more useful for in-depth amplicon-based biodiversity monitoring (metabarcoding) from complex environmental samples.Copyright © 2019 American Society for Microbiology.
Whole Genome Sequencing and Analysis of Chlorimuron-Ethyl Degrading Bacteria Klebsiella pneumoniae 2N3.
Klebsiella pneumoniae 2N3 is a strain of gram-negative bacteria that can degrade chlorimuron-ethyl and grow with chlorimuron-ethyl as the sole nitrogen source. The complete genome of Klebsiella pneumoniae 2N3 was sequenced using third generation high-throughput DNA sequencing technology. The genomic size of strain 2N3 was 5.32 Mb with a GC content of 57.33% and a total of 5156 coding genes and 112 non-coding RNAs predicted. Two hydrolases expressed by open reading frames (ORFs) 0934 and 0492 were predicted and experimentally confirmed by gene knockout to be involved in the degradation of chlorimuron-ethyl. Strains of ?ORF 0934, ?ORF 0492, and wild type (WT) reached their highest growth rates after 8-10 hours in incubation. The degradation rates of chlorimuron-ethyl by both ?ORF 0934 and ?ORF 0492 decreased in comparison to the WT during the first 8 hours in culture by 25.60% and 24.74%, respectively, while strains ?ORF 0934, ?ORF 0492, and the WT reached the highest degradation rates of chlorimuron-ethyl in 36 hours of 74.56%, 90.53%, and 95.06%, respectively. This study provides scientific evidence to support the application of Klebsiella pneumoniae 2N3 in bioremediation to control environmental pollution.
Long-read sequencing has substantial advantages for structural variant discovery and phasing of vari- ants compared to short-read technologies, but the required and optimal read length has not been as- sessed. In this work, we used long reads simulated from human genomes and evaluated structural vari- ant discovery and variant phasing using current best practicebioinformaticsmethods.Wedeterminedthatoptimal discovery of structural variants from human genomes can be obtained with reads of minimally 20 kb. Haplotyping variants across genes only reaches its optimum from reads of 100 kb. These findings are important for the design of future long-read sequenc- ing projects.
Tandem repeat (TR) expansions have been implicated in dozens of genetic diseases, including Huntington’s Disease, Fragile X Syndrome, and hereditary ataxias. Furthermore, TRs have recently been implicated in a range of complex traits, including gene expression and cancer risk. While the human genome harbors hundreds of thousands of TRs, analysis of TR expansions has been mainly limited to known pathogenic loci. A major challenge is that expanded repeats are beyond the read length of most next-generation sequencing (NGS) datasets and are not profiled by existing genome-wide tools. We present GangSTR, a novel algorithm for genome-wide genotyping of both short and expanded TRs. GangSTR extracts information from paired-end reads into a unified model to estimate maximum likelihood TR lengths. We validate GangSTR on real and simulated data and show that GangSTR outperforms alternative methods in both accuracy and speed. We apply GangSTR to a deeply sequenced trio to profile the landscape of TR expansions in a healthy family and validate novel expansions using orthogonal technologies. Our analysis reveals that healthy individuals harbor dozens of long TR alleles not captured by current genome-wide methods. GangSTR will likely enable discovery of novel disease-associated variants not currently accessible from NGS. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
Rapid antigen diversification through mitotic recombination in the human malaria parasite Plasmodium falciparum.
Malaria parasites possess the remarkable ability to maintain chronic infections that fail to elicit a protective immune response, characteristics that have stymied vaccine development and cause people living in endemic regions to remain at risk of malaria despite previous exposure to the disease. These traits stem from the tremendous antigenic diversity displayed by parasites circulating in the field. For Plasmodium falciparum, the most virulent of the human malaria parasites, this diversity is exemplified by the variant gene family called var, which encodes the major surface antigen displayed on infected red blood cells (RBCs). This gene family exhibits virtually limitless diversity when var gene repertoires from different parasite isolates are compared. Previous studies indicated that this remarkable genome plasticity results from extensive ectopic recombination between var genes during mitotic replication; however, the molecular mechanisms that direct this process to antigen-encoding loci while the rest of the genome remains relatively stable were not determined. Using targeted DNA double-strand breaks (DSBs) and long-read whole-genome sequencing, we show that a single break within an antigen-encoding region of the genome can result in a cascade of recombination events leading to the generation of multiple chimeric var genes, a process that can greatly accelerate the generation of diversity within this family. We also found that recombinations did not occur randomly, but rather high-probability, specific recombination products were observed repeatedly. These results provide a molecular basis for previously described structured rearrangements that drive diversification of this highly polymorphic gene family.
Information about variations in multiple copies of bacterial 16S rRNA genes may aid in species identification.
Variable region analysis of 16S rRNA gene sequences is the most common tool in bacterial taxonomic studies. Although used for distinguishing bacterial species, its use remains limited due to the presence of variable copy numbers with sequence variation in the genomes. In this study, 16S rRNA gene sequences, obtained from completely assembled whole genome and Sanger electrophoresis sequencing of cloned PCR products from Serratia fonticola GS2, were compared. Sanger sequencing produced a combination of sequences from multiple copies of 16S rRNA genes. To determine whether the variant copies of 16S rRNA genes affected Sanger sequencing, two ratios (5:5 and 8:2) with different concentrations of cloned 16S rRNA genes were used; it was observed that the greater the number of copies with similar sequences the higher its chance of amplification. Effect of multiple copies for taxonomic classification of 16S rRNA gene sequences was investigated using the strain GS2 as a model. 16S rRNA copies with the maximum variation had 99.42% minimum pairwise similarity and this did not have an effect on species identification. Thus, PCR products from genomes containing variable 16S rRNA gene copies can provide sufficient information for species identification except from species which have high similarity of sequences in their 16S rRNA gene copies like the case of Bacillus thuringiensis and Bacillus cereus. In silico analysis of 1,616 bacterial genomes from long-read sequencing was also done. The average minimum pairwise similarity for each phylum was reported with their average genome size and average “unique copies” of 16S rRNA genes and we found that the phyla Proteobacteria and Firmicutes showed the highest amount of variation in their copies of their 16S rRNA genes. Overall, our results shed light on how the variations in the multiple copies of the 16S rRNA genes of bacteria can aid in appropriate species identification.