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Auto Tag: Genome in a Bottle

April 21, 2020  |  

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.

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April 21, 2020  |  

A robust benchmark for germline structural variant detection

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.

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April 21, 2020  |  

High satellite repeat turnover in great apes studied with short- and long-read technologies.

Satellite repeats are a structural component of centromeres and telomeres, and in some instances their divergence is known to drive speciation. Due to their highly repetitive nature, satellite sequences have been understudied and underrepresented in genome assemblies. To investigate their turnover in great apes, we studied satellite repeats of unit sizes up to 50?bp in human, chimpanzee, bonobo, gorilla, and Sumatran and Bornean orangutans, using unassembled short and long sequencing reads. The density of satellite repeats, as identified from accurate short reads (Illumina), varied greatly among great ape genomes. These were dominated by a handful of abundant repeated motifs, frequently shared among species, which formed two groups: (1) the (AATGG)n repeat (critical for heat shock response) and its derivatives; and (2) subtelomeric 32-mers involved in telomeric metabolism. Using the densities of abundant repeats, individuals could be classified into species. However clustering did not reproduce the accepted species phylogeny, suggesting rapid repeat evolution. Several abundant repeats were enriched in males vs. females; using Y chromosome assemblies or FIuorescent In Situ Hybridization, we validated their location on the Y. Finally, applying a novel computational tool, we identified many satellite repeats completely embedded within long Oxford Nanopore and Pacific Biosciences reads. Such repeats were up to 59?kb in length and consisted of perfect repeats interspersed with other similar sequences. Our results based on sequencing reads generated with three different technologies provide the first detailed characterization of great ape satellite repeats, and open new avenues for exploring their functions. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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April 21, 2020  |  

Profiling the genome-wide landscape of tandem repeat expansions.

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.

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April 21, 2020  |  

An open resource for accurately benchmarking small variant and reference calls.

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.

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April 21, 2020  |  

Fast and accurate genomic analyses using genome graphs.

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions (indels). The pipeline processes one whole-genome sequencing sample in 6.5?h using a system with 36?CPU cores. We show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is an important advance toward fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.

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April 21, 2020  |  

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.

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April 21, 2020  |  

Evaluation of the performance of copy number variant prediction tools for the detection of deletions from whole genome sequencing data.

Whole genome sequencing (WGS) has increased in popularity and decreased in cost over the past decade, rendering this approach as a viable and sensitive method for variant detection. In addition to its utility for single nucleotide variant detection, WGS data has the potential to detect Copy Number Variants (CNV) to fine resolution. Many CNV detection software packages have been developed exploiting four main types of data: read pair, split read, read depth, and assembly based methods. The aim of this study was to evaluate the efficiency of each of these main approaches in detecting germline deletions.WGS data and high confidence deletion calls for the individual NA12878 from the Genome in a Bottle consortium were the benchmark dataset. The performance of BreakDancer, CNVnator, Delly, FermiKit, and Pindel was assessed by comparing the accuracy and sensitivity of each software package in detecting deletions exceeding 1?kb.There was considerable variability in the outputs of the different WGS CNV detection programs. The best performance was seen from BreakDancer and Delly, with 92.6% and 96.7% sensitivity, respectively and 34.5% and 68.5% false discovery rate (FDR), respectively. In comparison, Pindel, CNVnator, and FermiKit were less effective with sensitivities of 69.1%, 66.0%, and 15.8%, respectively and FDR of 91.3%, 69.0%, and 31.7%, respectively. Concordance across software packages was poor, with only 27 of the total 612 benchmark deletions identified by all five methodologies.The WGS based CNV detection tools evaluated show disparate performance in identifying deletions =1?kb, particularly those utilising different input data characteristics. Software that exploits read pair based data had the highest sensitivity, namely BreakDancer and Delly. BreakDancer also had the second lowest false discovery rate. Therefore, in this analysis read pair methods (BreakDancer in particular) were the best performing approaches for the identification of deletions =1?kb, balancing accuracy and sensitivity. There is potential for improvement in the detection algorithms, particularly for reducing FDR. This analysis has validated the utility of WGS based CNV detection software to reliably identify deletions, and these findings will be of use when choosing appropriate software for deletion detection, in both research and diagnostic medicine.Copyright © 2019 Elsevier Inc. All rights reserved.

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April 21, 2020  |  

Deep convolutional neural networks for accurate somatic mutation detection.

Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different sequencing platforms, sequencing strategies, and tumor purities. NeuSomatic summarizes sequence alignments into small matrices and incorporates more than a hundred features to capture mutation signals effectively. It can be used universally as a stand-alone somatic mutation detection method or with an ensemble of existing methods to achieve the highest accuracy.

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April 21, 2020  |  

Haplotype-aware diplotyping from noisy long reads.

Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.

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April 21, 2020  |  

High-coverage, long-read sequencing of Han Chinese trio reference samples.

Single-molecule long-read sequencing datasets were generated for a son-father-mother trio of Han Chinese descent that is part of the Genome in a Bottle (GIAB) consortium portfolio. The dataset was generated using the Pacific Biosciences Sequel System. The son and each parent were sequenced to an average coverage of 60 and 30, respectively, with N50 subread lengths between 16 and 18?kb. Raw reads and reads aligned to both the GRCh37 and GRCh38 are available at the NCBI GIAB ftp site (ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/ChineseTrio/). The GRCh38 aligned read data are archived in NCBI SRA (SRX4739017, SRX4739121, and SRX4739122). This dataset is available for anyone to develop and evaluate long-read bioinformatics methods.

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September 22, 2019  |  

Advantages of genome sequencing by long-read sequencer using SMRT technology in medical area.

PacBio RS II is the first commercialized third-generation DNA sequencer able to sequence a single molecule DNA in real-time without amplification. PacBio RS II’s sequencing technology is novel and unique, enabling the direct observation of DNA synthesis by DNA polymerase. PacBio RS II confers four major advantages compared to other sequencing technologies: long read lengths, high consensus accuracy, a low degree of bias, and simultaneous capability of epigenetic characterization. These advantages surmount the obstacle of sequencing genomic regions such as high/low G+C, tandem repeat, and interspersed repeat regions. Moreover, PacBio RS II is ideal for whole genome sequencing, targeted sequencing, complex population analysis, RNA sequencing, and epigenetics characterization. With PacBio RS II, we have sequenced and analyzed the genomes of many species, from viruses to humans. Herein, we summarize and review some of our key genome sequencing projects, including full-length viral sequencing, complete bacterial genome and almost-complete plant genome assemblies, and long amplicon sequencing of a disease-associated gene region. We believe that PacBio RS II is not only an effective tool for use in the basic biological sciences but also in the medical/clinical setting.

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September 22, 2019  |  

SuperTranscripts: a data driven reference for analysis and visualisation of transcriptomes.

Numerous methods have been developed to analyse RNA sequencing (RNA-seq) data, but most rely on the availability of a reference genome, making them unsuitable for non-model organisms. Here we present superTranscripts, a substitute for a reference genome, where each gene with multiple transcripts is represented by a single sequence. The Lace software is provided to construct superTranscripts from any set of transcripts, including de novo assemblies. We demonstrate how superTranscripts enable visualisation, variant detection and differential isoform detection in non-model organisms. We further use Lace to combine reference and assembled transcriptomes for chicken and recover hundreds of gaps in the reference genome.

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September 22, 2019  |  

Long reads: their purpose and place.

In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.

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September 22, 2019  |  

MUMmer4: A fast and versatile genome alignment system.

The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.

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