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Asset Tag: Human population genetics

September 22, 2019  |  

Validation of Genomic Structural Variants Through Long Sequencing Technologies.

Although numerous algorithms have been developed to identify large chromosomal rearrangements (i.e., genomic structural variants, SVs), there remains a dearth of approaches to evaluate their results. This is significant, as the accurate identification of SVs is still an outstanding problem whereby no single algorithm has been shown to be able to achieve high sensitivity and specificity across different classes of SVs. The method introduced in this chapter, VaPoR, is specifically designed to evaluate the accuracy of SV predictions using third-generation long sequences. This method uses a recurrence approach and collects direct evidence from raw reads thus avoiding computationally costly whole genome assembly. This chapter would describe in detail as how to apply this tool onto different data types.

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September 22, 2019  |  

Human copy number variants are enriched in regions of low mappability.

Copy number variants (CNVs) are known to affect a large portion of the human genome and have been implicated in many diseases. Although whole-genome sequencing (WGS) can help identify CNVs, most analytical methods suffer from limited sensitivity and specificity, especially in regions of low mappability. To address this, we use PopSV, a CNV caller that relies on multiple samples to control for technical variation. We demonstrate that our calls are stable across different types of repeat-rich regions and validate the accuracy of our predictions using orthogonal approaches. Applying PopSV to 640 human genomes, we find that low-mappability regions are approximately 5 times more likely to harbor germline CNVs, in stark contrast to the nearly uniform distribution observed for somatic CNVs in 95 cancer genomes. In addition to known enrichments in segmental duplication and near centromeres and telomeres, we also report that CNVs are enriched in specific types of satellite and in some of the most recent families of transposable elements. Finally, using this comprehensive approach, we identify 3455 regions with recurrent CNVs that were missing from existing catalogs. In particular, we identify 347 genes with a novel exonic CNV in low-mappability regions, including 29 genes previously associated with disease.

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September 22, 2019  |  

A synthetic-diploid benchmark for accurate variant-calling evaluation.

Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.

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September 22, 2019  |  

Parliament2: Fast structural variant calling using optimized combinations of callers

Here we present Parliament2: a structural variant caller which combines multiple best-in-class structural variant callers to create a highly accurate callset. This captures more events than the individual callers achieve independently. Parliament2 uses a call-overlap-genotype approach that is highly extensible to new methods and presents users the choice to run some or all of Breakdancer, Breakseq, CNVnator, Delly, Lumpy, and Manta to run. Parliament2 applies an additional parallelization framework to speed certain callers and executes these in parallel, taking advantage of the different resource requirements to complete structural variant calling much faster than running the programs individually. Parliament2 is available as a Docker container, which pre-installs all required dependencies. This allows users to run any caller with easy installation and execution. This Docker container can easily be deployed in cloud or local environments and is available as an app on DNAnexus.

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September 22, 2019  |  

Variation graph toolkit improves read mapping by representing genetic variation in the reference.

Reference genomes guide our interpretation of DNA sequence data. However, conventional linear references represent only one version of each locus, ignoring variation in the population. Poor representation of an individual’s genome sequence impacts read mapping and introduces bias. Variation graphs are bidirected DNA sequence graphs that compactly represent genetic variation across a population, including large-scale structural variation such as inversions and duplications. Previous graph genome software implementations have been limited by scalability or topological constraints. Here we present vg, a toolkit of computational methods for creating, manipulating, and using these structures as references at the scale of the human genome. vg provides an efficient approach to mapping reads onto arbitrary variation graphs using generalized compressed suffix arrays, with improved accuracy over alignment to a linear reference, and effectively removing reference bias. These capabilities make using variation graphs as references for DNA sequencing practical at a gigabase scale, or at the topological complexity of de novo assemblies.

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September 22, 2019  |  

Targeted genotyping of variable number tandem repeats with adVNTR.

Whole-genome sequencing is increasingly used to identify Mendelian variants in clinical pipelines. These pipelines focus on single-nucleotide variants (SNVs) and also structural variants, while ignoring more complex repeat sequence variants. Here, we consider the problem of genotyping Variable Number Tandem Repeats (VNTRs), composed of inexact tandem duplications of short (6-100 bp) repeating units. VNTRs span 3% of the human genome, are frequently present in coding regions, and have been implicated in multiple Mendelian disorders. Although existing tools recognize VNTR carrying sequence, genotyping VNTRs (determining repeat unit count and sequence variation) from whole-genome sequencing reads remains challenging. We describe a method, adVNTR, that uses hidden Markov models to model each VNTR, count repeat units, and detect sequence variation. adVNTR models can be developed for short-read (Illumina) and single-molecule (Pacific Biosciences [PacBio]) whole-genome and whole-exome sequencing, and show good results on multiple simulated and real data sets.© 2018 Bakhtiari et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019  |  

TranSurVeyor: an improved database-free algorithm for finding non-reference transpositions in high-throughput sequencing data.

Transpositions transfer DNA segments between different loci within a genome; in particular, when a transposition is found in a sample but not in a reference genome, it is called a non-reference transposition. They are important structural variations that have clinical impact. Transpositions can be called by analyzing second generation high-throughput sequencing datasets. Current methods follow either a database-based or a database-free approach. Database-based methods require a database of transposable elements. Some of them have good specificity; however this approach cannot detect novel transpositions, and it requires a good database of transposable elements, which is not yet available for many species. Database-free methods perform de novo calling of transpositions, but their accuracy is low. We observe that this is due to the misalignment of the reads; since reads are short and the human genome has many repeats, false alignments create false positive predictions while missing alignments reduce the true positive rate. This paper proposes new techniques to improve database-free non-reference transposition calling: first, we propose a realignment strategy called one-end remapping that corrects the alignments of reads in interspersed repeats; second, we propose a SNV-aware filter that removes some incorrectly aligned reads. By combining these two techniques and other techniques like clustering and positive-to-negative ratio filter, our proposed transposition caller TranSurVeyor shows at least 3.1-fold improvement in terms of F1-score over existing database-free methods. More importantly, even though TranSurVeyor does not use databases of prior information, its performance is at least as good as existing database-based methods such as MELT, Mobster and Retroseq. We also illustrate that TranSurVeyor can discover transpositions that are not known in the current database.

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September 22, 2019  |  

Noise-Cancelling Repeat Finder: Uncovering tandem repeats in error-prone long-read sequencing data

Tandem DNA repeats can be sequenced with long-read technologies, but cannot be accurately deciphered due to the lack of computational tools taking high error rates of these technologies into account. Here we introduce Noise-Cancelling Repeat Finder (NCRF) to uncover putative tandem repeats of specified motifs in noisy long reads produced by Pacific Biosciences and Oxford Nanopore sequencers. Using simulations, we validated the use of NCRF to locate tandem repeats with motifs of various lengths and demonstrated its superior performance as compared to two alternative tools. Using real human whole-genome sequencing data, NCRF identified long arrays of the (AATGG)n repeat involved in heat shock stress response.

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September 22, 2019  |  

Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools.

We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel computational tools for the analysis of human genome sequence variation for the dominant Illumina sequencing technology can test and hone their algorithms by making variant calls from these Venter/HuRef datasets and then immediately confirm the detected variants in the Sanger assembly, freeing them of the need for further experimental validation. This process also applies to implementing and benchmarking existing genome analysis pipelines. We prepared and sequenced 200?bp and 350?bp short-insert whole-genome sequencing libraries (sequenced to 100x and 40x genomic coverages respectively) as well as 2?kb, 5?kb, and 12?kb mate-pair libraries (49x, 122x, and 145x physical coverages respectively). Lastly, we produced a linked-read library (128x physical coverage) from which we also performed haplotype phasing.

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September 22, 2019  |  

Integrative haplotype estimation with sub-linear complexity

The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here, we present a new method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear scaling with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPET4 in an open source format on https://odelaneau.github.io/shapeit4/ and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.

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July 19, 2019  |  

High-quality assembly of an individual of Yoruban descent

De novo assembly of human genomes is now a tractable effort due in part to advances in sequencing and mapping technologies. We use PacBio single-molecule, real-time (SMRT) sequencing and BioNano genomic maps to construct the first de novo assembly of NA19240, a Yoruban individual from Africa. This chromosome-scaffolded assembly of 3.08 Gb with a contig N50 of 7.25 Mb and a scaffold N50 of 78.6 Mb represents one of the most contiguous high-quality human genomes. We utilize a BAC library derived from NA19240 DNA and novel haplotype-resolving sequencing technologies and algorithms to characterize regions of complex genomic architecture that are normally lost due to compression to a linear haploid assembly. Our results demonstrate that multiple technologies are still necessary for complete genomic representation, particularly in regions of highly identical segmental duplications. Additionally, we show that diploid assembly has utility in improving the quality of de novo human genome assemblies.

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July 19, 2019  |  

De novo assembly and phasing of a Korean human genome.

Advances in genome assembly and phasing provide an opportunity to investigate the diploid architecture of the human genome and reveal the full range of structural variation across population groups. Here we report the de novo assembly and haplotype phasing of the Korean individual AK1 (ref. 1) using single-molecule real-time sequencing, next-generation mapping, microfluidics-based linked reads, and bacterial artificial chromosome (BAC) sequencing approaches. Single-molecule sequencing coupled with next-generation mapping generated a highly contiguous assembly, with a contig N50 size of 17.9?Mb and a scaffold N50 size of 44.8?Mb, resolving 8 chromosomal arms into single scaffolds. The de novo assembly, along with local assemblies and spanning long reads, closes 105 and extends into 72 out of 190 euchromatic gaps in the reference genome, adding 1.03?Mb of previously intractable sequence. High concordance between the assembly and paired-end sequences from 62,758 BAC clones provides strong support for the robustness of the assembly. We identify 18,210 structural variants by direct comparison of the assembly with the human reference, identifying thousands of breakpoints that, to our knowledge, have not been reported before. Many of the insertions are reflected in the transcriptome and are shared across the Asian population. We performed haplotype phasing of the assembly with short reads, long reads and linked reads from whole-genome sequencing and with short reads from 31,719 BAC clones, thereby achieving phased blocks with an N50 size of 11.6?Mb. Haplotigs assembled from single-molecule real-time reads assigned to haplotypes on phased blocks covered 89% of genes. The haplotigs accurately characterized the hypervariable major histocompatability complex region as well as demonstrating allele configuration in clinically relevant genes such as CYP2D6. This work presents the most contiguous diploid human genome assembly so far, with extensive investigation of unreported and Asian-specific structural variants, and high-quality haplotyping of clinically relevant alleles for precision medicine.

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July 19, 2019  |  

Cytogenomic identification and long-read single molecule real-time (SMRT) sequencing of a Bardet-Biedl Syndrome 9 (BBS9) deletion.

Bardet-Biedl syndrome (BBS) is a recessive disorder characterized by heterogeneous clinical manifestations, including truncal obesity, rod-cone dystrophy, renal anomalies, postaxial polydactyly, and variable developmental delays. At least 20 genes have been implicated in BBS, and all are involved in primary cilia function. We report a 1-year-old male child from Guyana with obesity, postaxial polydactyly on his right foot, hypotonia, ophthalmologic abnormalities, and developmental delay, which together indicated a clinical diagnosis of BBS. Clinical chromosomal microarray (CMA) testing and high-throughput BBS gene panel sequencing detected a homozygous 7p14.3 deletion of exons 1-4 of BBS9 that was encompassed by a 17.5?Mb region of homozygosity at chromosome 7p14.2-p21.1. The precise breakpoints of the deletion were delineated to a 72.8?kb region in the proband and carrier parents by third-generation long-read single molecule real-time (SMRT) sequencing (Pacific Biosciences), which suggested non-homologous end joining as a likely mechanism of formation. Long-read SMRT sequencing of the deletion breakpoints also determined that the aberration included the neighboring RP9 gene implicated in retinitis pigmentosa; however, the clinical significance of this was considered uncertain given the paucity of reported cases with unambiguous RP9 mutations. Taken together, our study characterized a BBS9 deletion, and the identification of this shared haplotype in the parents suggests that this pathogenic aberration may be a BBS founder mutation in the Guyanese population. Importantly, this informative case also highlights the utility of long-read SMRT sequencing to map nucleotide breakpoints of clinically relevant structural variants.

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July 19, 2019  |  

Piercing the dark matter: bioinformatics of long-range sequencing and mapping.

Several new genomics technologies have become available that offer long-read sequencing or long-range mapping with higher throughput and higher resolution analysis than ever before. These long-range technologies are rapidly advancing the field with improved reference genomes, more comprehensive variant identification and more complete views of transcriptomes and epigenomes. However, they also require new bioinformatics approaches to take full advantage of their unique characteristics while overcoming their complex errors and modalities. Here, we discuss several of the most important applications of the new technologies, focusing on both the currently available bioinformatics tools and opportunities for future research.

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July 19, 2019  |  

Accurate detection of complex structural variations using single-molecule sequencing.

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr ) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles ) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

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