February 5, 2021
Podcast: Why the diversity of genomic data matters
The lack of diversity in genomic data has been an issue of growing concern. It threatens to limit the benefits from the massive investment that has been made to date…
Asset Tag: Human population genetics
February 5, 2021
Webinar: Size Matters: Accurate detection and phasing of structural variations
In this presentation Fritz Sedlazeck describes his latest work to obtain comprehensive genomes leveraging long-read sequencing and linked reads.
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.
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.
April 21, 2020
Telomere-to-telomere assembly of a complete human X chromosome
After nearly two decades of improvements, the current human reference genome (GRCh38) is the most accurate and complete vertebrate genome ever produced. However, no one chromosome has been finished end to end, and hundreds of unresolved gaps persist. The remaining gaps include ribosomal rDNA arrays, large near-identical segmental duplications, and satellite DNA arrays. These regions harbor largely unexplored variation of unknown consequence, and their absence from the current reference genome can lead to experimental artifacts and hide true variants when re-sequencing additional human genomes. Here we present a de novo human genome assembly that surpasses the continuity of GRCh38, along with the first gapless, telomere-to-telomere assembly of a human chromosome. This was enabled by high-coverage, ultra-long-read nanopore sequencing of the complete hydatidiform mole CHM13 genome, combined with complementary technologies for quality improvement and validation. Focusing our efforts on the human X chromosome 3, we reconstructed the ~2.8 megabase centromeric satellite DNA array and closed all 29 remaining gaps in the current reference, including new sequence from the human pseudoautosomal regions and cancer-testis ampliconic gene families (CT-X and GAGE). This complete chromosome X, combined with the ultra-long nanopore data, also allowed us to map methylation patterns across complex tandem repeats and satellite arrays for the first time. These results demonstrate that finishing the human genome is now within reach and will enable ongoing efforts to complete the remaining human chromosomes.
April 21, 2020
Paragraph: A graph-based structural variant genotyper for short-read sequence data
Accurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, a fast and accurate genotyper that models SVs using sequence graphs and SV annotations produced by a range of methods and technologies. We demonstrate the accuracy of Paragraph on whole genome sequence data from a control sample with both short and long read sequencing data available, and then apply it at scale to a cohort of 100 samples of diverse ancestry sequenced with short-reads. Comparative analyses indicate that Paragraph has better accuracy than other existing genotypers. The Paragraph software is open-source and available at ?https://github.com/Illumina/paragraph
April 21, 2020
Characterization of LINE-1 transposons in a human genome at allelic resolution
The activity of the retrotransposon LINE-1 has created a substantial portion of the human genome. Most of this sequence comprises fractured and debilitated LINE-1s. An accurate approximation of the number, location, and sequence of the LINE-1 elements present in any single genome has proven elusive due to the difficulty of assembling and phasing the repetitive and polymorphic regions of the human genome. Through an in-depth analysis of publicly-available, deep, long-read assemblies of nearly homozygous human genomes, we defined the location and sequence of all intact LINE-1s in these assemblies. We found 148 and 142 intact LINE-1s in two nearly homozygous assemblies. A combination of these assemblies suggests a diploid human genome contains at least 50% more intact LINE-1s than previous estimates textendash in this case, 290 intact LINE-1s at 194 loci. We think this is the best approximation, to date, of the number of intact LINE-1s in a single diploid human genome. In addition to counting intact LINE-1 elements, we resolved the sequence of each element, including some LINE-1 elements in unassembled, presumably centromeric regions of the genome. A comparison of the intact LINE-1s in each assembly shows the specific pattern of variation between these genomes, including LINE-1s that remain intact in only one genome, allelic variation in shared intact LINE-1s, and LINE-1s that are unique (presumably young) insertions in only one genome. We found that many old elements (> 6 million years old) remain intact, and comparison of the young and intact LINE-1s across assemblies reinforces the notion that only a small portion of all LINE-1 sequences that may be intact in the genomes of the human population has been uncovered. This dataset provides the first nearly comprehensive estimate of LINE-1 diversity within an individual, an important dataset in the quest to understand the functional consequences of sequence variation in LINE-1 and the complete set of LINE-1s in the human population.
April 21, 2020
Extended haplotype phasing of de novo genome assemblies with FALCON-Phase
Haplotype-resolved genome assemblies are important for understanding how combinations of variants impact phenotypes. These assemblies can be created in various ways, such as use of tissues that contain single-haplotype (haploid) genomes, or by co-sequencing of parental genomes, but these approaches can be impractical in many situations. We present FALCON-Phase, which integrates long-read sequencing data and ultra-long-range Hi-C chromatin interaction data of a diploid individual to create high-quality, phased diploid genome assemblies. The method was evaluated by application to three datasets, including human, cattle, and zebra finch, for which high-quality, fully haplotype resolved assemblies were available for benchmarking. Phasing algorithm accuracy was affected by heterozygosity of the individual sequenced, with higher accuracy for cattle and zebra finch (>97%) compared to human (82%). In addition, scaffolding with the same Hi-C chromatin contact data resulted in phased chromosome-scale scaffolds.
April 21, 2020
Fast and accurate long-read assembly with wtdbg2
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.
April 21, 2020
Centromeric Satellite DNAs: Hidden Sequence Variation in the Human Population.
The central goal of medical genomics is to understand the inherited basis of sequence variation that underlies human physiology, evolution, and disease. Functional association studies currently ignore millions of bases that span each centromeric region and acrocentric short arm. These regions are enriched in long arrays of tandem repeats, or satellite DNAs, that are known to vary extensively in copy number and repeat structure in the human population. Satellite sequence variation in the human genome is often so large that it is detected cytogenetically, yet due to the lack of a reference assembly and informatics tools to measure this variability, contemporary high-resolution disease association studies are unable to detect causal variants in these regions. Nevertheless, recently uncovered associations between satellite DNA variation and human disease support that these regions present a substantial and biologically important fraction of human sequence variation. Therefore, there is a pressing and unmet need to detect and incorporate this uncharacterized sequence variation into broad studies of human evolution and medical genomics. Here I discuss the current knowledge of satellite DNA variation in the human genome, focusing on centromeric satellites and their potential implications for disease.
April 21, 2020
Critical length in long-read resequencing
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.
April 21, 2020
Long-read sequence and assembly of segmental duplications.
We have developed a computational method based on polyploid phasing of long sequence reads to resolve collapsed regions of segmental duplications within genome assemblies. Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA ) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs. We apply it to single-molecule, real-time sequence data from three human genomes and recover 33-79 megabase pairs (Mb) of duplications in which approximately half of the loci are diverged (<99.8%) compared to the reference genome. We show that the corresponding sequence is highly accurate (>99.9%) and that the diverged sequence corresponds to copy-number-variable paralogs that are absent from the human reference genome. Our method can be applied to other complex genomes to resolve the last gene-rich gaps, improve duplicate gene annotation, and better understand copy-number-variant genetic diversity at the base-pair level.
April 21, 2020
Characterizing the major structural variant alleles of the human genome.
In order to provide a comprehensive resource for human structural variants (SVs), we generated long-read sequence data and analyzed SVs for fifteen human genomes. We sequence resolved 99,604 insertions, deletions, and inversions including 2,238 (1.6 Mbp) that are shared among all discovery genomes with an additional 13,053 (6.9 Mbp) present in the majority, indicating minor alleles or errors in the reference. Genotyping in 440 additional genomes confirms the most common SVs in unique euchromatin are now sequence resolved. We report a ninefold SV bias toward the last 5 Mbp of human chromosomes with nearly 55% of all VNTRs (variable number of tandem repeats) mapping to this portion of the genome. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity. Copyright © 2018 Elsevier Inc. All rights reserved.
April 21, 2020
Genetic Variation, Comparative Genomics, and the Diagnosis of Disease.
The discovery of mutations associated with human genetic dis- ease is an exercise in comparative genomics (see Glossary). Although there are many different strategies and approaches, the central premise is that affected persons harbor a significant excess of pathogenic DNA variants as com- pared with a group of unaffected persons (controls) that is either clinically defined1 or established by surveying large swaths of the general population.2 The more exclu- sive the variant is to the disease, the greater its penetrance, the larger its effect size, and the more relevant it becomes to both disease diagnosis and future therapeutic investigation. The most popular approach used by researchers in human genetics is the case–control design, but there are others that can be used to track variants and disease in a family context or that consider the probability of different classes of mutations based on evolutionary patterns of divergence or de novo mutational change.3,4 Although the approaches may be straightforward, the discovery of patho- genic variation and its mechanism of action often is less trivial, and decades of research can be required in order to identify the variants underlying both mendelian and complex genetic traits.
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.