Characterizing the Major Structural Variant Alleles of the Human Genome

Audano, Peter A.; Sulovari, Arvis; Graves-Lindsay, Tina A.; Cantsilieris, Stuart; Sorensen, Melanie; Welch, AnneMarie E.; Dougherty, Max L.; Nelson, Bradley J.; Shah, Ankeeta; Dutcher, Susan K.; Warren, Wesley C.; Magrini, Vincent; McGrath, Sean; Li, Yang; Wilson, Richard K.; Eichler, Evan E.

doi:10.1016/j.cell.2018.12.019

Cited by 435 publications

(706 citation statements)

References 75 publications

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“…Over half of the insertions also occur at a low AF, but there is a sizeable number of insertions with very high AF or even becomes fixated (AF=1) in the population. As been reported previously 12 , these high AF insertions are likely to represent defects and/or rare alleles in the reference human genome.…”

Section: Genotyping In Tandem Repeatssupporting

confidence: 71%

“…This is chiefly because, compared to short reads, long (10-50kbp) reads can be more reliably mapped to such regions and are more likely to span entire SVs [8][9][10] . These technologies combined with data generated by population studies using multiple sequencing platforms, are leading to a rapid and ongoing expansion of the reference SV databases in a variety of species [11][12][13] .…”

mentioning

confidence: 99%

“…Most targeted methods for genotyping are integrated with particular discovery algorithms and require the input SVs to be originally discovered by the designated SV caller [15][16][17] , require a complete genome-wide realignment 18,19 or need to be optimized on a set of training samples 12,20 .…”

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confidence: 99%

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Paragraph: A graph-based structural variant genotyper for short-read sequence data

Chen

Krusche

Dolzhenko

et al. 2019

Preprint

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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, an accurate genotyper that models SVs using sequence graphs and SV annotations. We demonstrate the accuracy of Paragraph on whole-genome sequence data from three samples using long read SV calls as the truth set, and then apply Paragraph at scale to a cohort of 100 short-read sequenced samples of diverse ancestry. Our analysis shows that Paragraph has better accuracy than other existing genotypers and can be applied to population-scale studies.

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Section: Genotyping In Tandem Repeatssupporting

confidence: 71%

mentioning

confidence: 99%

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Paragraph: A graph-based structural variant genotyper for short-read sequence data

Chen

Krusche

Dolzhenko

et al. 2019

Preprint

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“…Given the reduced sensitivity of short-read WGS in repetitive and low-complexity sequences, gnomAD-SV certainly underestimates the true mutation rates and distributions of SVs, which are likely to be refined by population-scale applications of long-read genome assembly methods. 33,34 Nevertheless, these analyses clearly implicate multiple aspects of chromosomal context and SV class in driving SV mutation rates throughout the genome.…”

Section: Figure 1 | Properties Of Svs Across Human Populationsmentioning

confidence: 99%

An open resource of structural variation for medical and population genetics

Team¹

2019

Preprint

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Structural variants (SVs) rearrange large segments of the genome and can have profound consequences for evolution and human diseases. As national biobanks, disease association studies, and clinical genetic testing grow increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral for interpreting genetic variation.To date, no large-scale reference maps of SVs exist from high-coverage sequencing comparable to those available for point mutations in protein-coding genes. Here, we constructed a reference atlas of SVs across 14,891 genomes from diverse global populations (54% non-European) as a component of gnomAD. We discovered a rich landscape of 433,371 distinct SVs, including 5,295 multi-breakpoint complex SVs across 11 mutational subclasses, and examples of localized chromosome shattering, as in chromothripsis. The average individual harbored 7,439 SVs, which accounted for 25-29% of all rare protein-truncating events per genome. We found strong correlations between constraint against damaging point mutations and rare SVs that both disrupt and duplicate protein-coding sequence, suggesting intolerance to reciprocal dosage alterations for a subset of tightly regulated genes. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than any effect on noncoding SVs. Finally, we benchmarked carrier rates for medically relevant SVs, finding very large (≥1Mb) rare SVs in 3.8% of genomes (~1:26 individuals) and clinically reportable incidental SVs in 0.18% of genomes (~1:556 individuals). These data have been integrated directly into the gnomAD browser (https://gnomad.broadinstitute. org) and will have broad utility for population genetics, disease association, and diagnostic screening.

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“…During the last years a substantial amount of information has accumulated about different types of genomic changes, ranging from single nucleotide polymorphisms (SNPs) to more complex structural variants (SVs) (The 1000 Genomes Project Consortium 2015; Sudmant et al 2015;Handsaker et al 2015;Audano et al 2019). However, inversions remain as one of the most difficult classes of variation to identify and characterize.…”

Section: Introductionmentioning

confidence: 99%

Determining the impact of uncharacterized inversions in the human genome by droplet digital PCR

Puig

Lerga-Jaso

Giner-Delgado

et al. 2019

Preprint

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Despite the interest in characterizing all genomic variation, the presence of large repeats at the breakpoints of many structural variants hinders their analysis. This is especially problematic in the case of inversions, since they are balanced changes without gain or loss of DNA. Here we tested novel linkage-based droplet digital PCR (ddPCR) assays on 20 inversions ranging from 3.1 to 742 kb and flanked by long inverted repeats (IRs) of up to 134 kb. Among these, we validated 13 inversions predicted by different genome-wide techniques. In addition, we have generated new experimental human population information across 95 African, European and East-Asian individuals for 16 of them, including four already known inversions for which there were no high-throughput methods to determine directly the orientation, like the well-characterized 17q21 inversion. Through comparison with previous data, independent replicates and both inversion breakpoints, we have demonstrated that the technique is highly accurate and reproducible. Most of the studied inversions are frequent and widespread across continents, showing a negative correlation with genetic length. Moreover, all except two show clear signs of being recurrent, and the new data allowed us to define more clearly the factors affecting recurrence levels and estimate the inversion rate across the genome. Finally, thanks to the generated genotypes, we have been able to check inversion functional effects in multiple tissues, validating gene expression differences reported before for two inversions and finding new candidate associations. Our work therefore provides a tool to screen these and other complex genomic variants quickly in a large number of samples for the first time, highlighting the importance of direct genotyping to assess their potential consequences and clinical implications.

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Characterizing the Major Structural Variant Alleles of the Human Genome

Cited by 435 publications

References 75 publications

Paragraph: A graph-based structural variant genotyper for short-read sequence data

Paragraph: A graph-based structural variant genotyper for short-read sequence data

An open resource of structural variation for medical and population genetics

Determining the impact of uncharacterized inversions in the human genome by droplet digital PCR

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