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.
New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls =50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.
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.
A high-quality genome assembly from a single, field-collected spotted lanternfly (Lycorma delicatula) using the PacBio Sequel II system
Background A high-quality reference genome is an essential tool for applied and basic research on arthropods. Long-read sequencing technologies may be used to generate more complete and contiguous genome assemblies than alternate technologies; however, long-read methods have historically had greater input DNA requirements and higher costs than next-generation sequencing, which are barriers to their use on many samples. Here, we present a 2.3 Gb de novo genome assembly of a field-collected adult female spotted lanternfly (Lycorma delicatula) using a single Pacific Biosciences SMRT Cell. The spotted lanternfly is an invasive species recently discovered in the northeastern United States that threatens to damage economically important crop plants in the region. Results The DNA from 1 individual was used to make 1 standard, size-selected library with an average DNA fragment size of ~20 kb. The library was run on 1 Sequel II SMRT Cell 8M, generating a total of 132 Gb of long-read sequences, of which 82 Gb were from unique library molecules, representing ~36× coverage of the genome. The assembly had high contiguity (contig N50 length = 1.5 Mb), completeness, and sequence level accuracy as estimated by conserved gene set analysis (96.8% of conserved genes both complete and without frame shift errors). Furthermore, it was possible to segregate more than half of the diploid genome into the 2 separate haplotypes. The assembly also recovered 2 microbial symbiont genomes known to be associated with L. delicatula, each microbial genome being assembled into a single contig. Conclusions We demonstrate that field-collected arthropods can be used for the rapid generation of high-quality genome assemblies, an attractive approach for projects on emerging invasive species, disease vectors, or conservation efforts of endangered species.
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.
Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a ‘first of its kind’ resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.
Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.
The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5?kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15?megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.
Symbiosis is a major force of evolutionary change, influencing virtually all aspects of biology, from population ecology and evolution to genomics and molecular/biochemical mechanisms of development and reproduction. A remarkable example is Wolbachia endobacteria, present in some parasitic nematodes and many arthropod species. Acquisition of genomic data from diverse Wolbachia clades will aid in the elucidation of the different symbiotic mechanisms(s). However, challenges of de novo assembly of Wolbachia genomes include the presence in the sample of host DNA: nematode/vertebrate or insect. We designed biotinylated probes to capture large fragments of Wolbachia DNA for sequencing using PacBio technology (LEFT-SEQ: Large Enriched Fragment Targeted Sequencing). LEFT-SEQ was used to capture and sequence four Wolbachia genomes: the filarial nematode Brugia malayi, wBm, (21-fold enrichment), Drosophila mauritiana flies (2 isolates), wMau (11-fold enrichment), and Aedes albopictus mosquitoes, wAlbB (200-fold enrichment). LEFT-SEQ resulted in complete genomes for wBm and for wMau. For wBm, 18 single-nucleotide polymorphisms (SNPs), relative to the wBm reference, were identified and confirmed by PCR. A limit of LEFT-SEQ is illustrated by the wAlbB genome, characterized by a very high level of insertion sequences elements (ISs) and DNA repeats, for which only a 20-contig draft assembly was achieved.
The wide implementation of next-generation sequencing (NGS) technologies has revolutionized the field of medical genetics. However, the short read lengths of currently used sequencing approaches pose a limitation for identification of structural variants, sequencing repetitive regions, phasing alleles and distinguishing highly homologous genomic regions. These limitations may significantly contribute to the diagnostic gap in patients with genetic disorders who have undergone standard NGS, like whole exome or even genome sequencing. Now, the emerging long-read sequencing (LRS) technologies may offer improvements in the characterization of genetic variation and regions that are difficult to assess with the currently prevailing NGS approaches. LRS has so far mainly been used to investigate genetic disorders with previously known or strongly suspected disease loci. While these targeted approaches already show the potential of LRS, it remains to be seen whether LRS technologies can soon enable true whole genome sequencing routinely. Ultimately, this could allow the de novo assembly of individual whole genomes used as a generic test for genetic disorders. In this article, we summarize the current LRS-based research on human genetic disorders and discuss the potential of these technologies to facilitate the next major advancements in medical genetics.