The complete sequence of a human genome

Nurk, Sergey; Koren, Sergey; Rhie, Arang; Rautiainen, Mikko; Av, Bzikadze; Mikheenko, Alla; Mr, Vollger; Altemose, Nicolas; Uralsky, L. I.; Gershman, Ariel; Aganezov, Sergey; Sj, Hoyt; Diekhans, Mark; Logsdon, Glennis A.; Alonge, Michael; Antonarakis, Stylianos E.; Borchers, Matthew; Gg, Bouffard; Sy, Brooks; Gv, Caldas; Cheng, Haoyu; Chin, Chen-Shan; Chow, William; Lima, de; Pc, Dishuck; Durbin, Richard; Dvorkina, Tatiana; It, Fiddes; Formenti, Giulio; Rs, Fulton; Fungtammasan, Arkarachai; Garrison, Erik; Pg, Grady; Ta, Graves-Lindsay; Im, Hall; Nf, Hansen; Hartley, Gabrielle A.; Haukness, Marina; Howe, Kerstin; Mw, Hunkapiller; Jain, Chirag; Jain, Miten; Ed, Jarvis; Kerpedjiev, Peter; Kirsche, Melanie; Kolmogorov, Mikhail; Korlach, Jonas; Kremitzki, Milinn; H, Li; Vv, Maduro; Marschall, Tobias; Cartney, Ann Mc; McDaniel, Jennifer; De, Miller; Jc, Mullikin; Ew, Myers; Nd, Olson; Paten, Benedict; Peluso, Paul; Pa, Pevzner; Porubský, David; Potapova, Tamara; Ei, Rogaev; Ja, Rosenfeld; Salzberg, Steven L.; Va, Schneider; Sedlazeck, Fritz J.; Shafin, Kishwar; Cj, Shew; Shumate, Alaina; Sims, Ying; Afa, Smit; Dc, Soto; Sović, Ivan; Jm, Storer; Streets, Aaron; Ba, Sullivan; Thibaud‐Nissen, Françoise; Torrance, James; Wagner, Justin; Bp, Walenz; Wenger, Aaron M.; Jmd, Wood; Xiao, Chunlin; Shu, Yan; Ac, Young; Zarate, Samantha; Surti, Urvashi; McCoy, Rajiv C.; My, Dennis; Ia, Alexandrov; Jl, Gerton; Rj, O’Neill; Timp, Winston; Jm, Zook; Mc, Schatz; Ee, Eichler; Kh, Miga; Am, Phillippy

doi:10.1101/2021.05.26.445798

Cited by 138 publications

(173 citation statements)

References 88 publications

(65 reference statements)

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“…In addition, there were systematic anomalies in the SV calls in highly repetitive regions such as the centromere and satellite repeats and an overall excess of variants that are found in all samples. There has recently been work to improve the reference genome to more accurately reflect these regions (Nurk et al 2021) , and as tools for aligning to and calling variants in these regions continue to mature, we expect the accuracy of these calls to even further improve. Finally, while we have detected a large number of SVs in the 31 samples we studied, there is still much to be discovered.…”

Section: Discussionmentioning

confidence: 99%

Jasmine: Population-scale structural variant comparison and analysis

Kirsche

Prabhu

Sherman

et al. 2021

Preprint

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The increasing availability of long-reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine (https://github.com/mkirsche/Jasmine), a fast and accurate method for SV refinement, comparison, and population analysis. Using an SV proximity graph, Jasmine outperforms five widely-used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than five-fold, and reveals a set of high confidence de novo SVs confirmed by multiple long-read technologies. We also present a harmonized callset of 205,192 SVs from 31 samples of diverse ancestry sequenced with long reads. We genotype these SVs in 444 short read samples from the 1000 Genomes Project with both DNA and RNA sequencing data and assess their widespread impact on gene expression, including within several medically relevant genes.

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Section: Discussionmentioning

confidence: 99%

Jasmine: Population-scale structural variant comparison and analysis

Kirsche

Prabhu

Sherman

et al. 2021

Preprint

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“…To test DiMeLo-seq's ability to measure protein occupancy in heterochromatic, repetitive regions of the genome we targeted H3K9me3, which is abundant in pericentric heterochromatin. We chose to target H3K9me3 in HG002 cells because the chromosome X centromere has been completely assembled for this male-derived lymphoblast line (Nurk et al 2021), and many different sequencing data types are available for it (Gershman et al 2021). To validate the specificity of targeted methylation, we calculated the fraction of adenines methylated within HG002 CUT&RUN H3K9me3 peaks (Altemose et al 2021) compared to the fraction of adenines methylated outside of broadly defined peaks (Methods).…”

Section: Mapping Histone Modifications In Heterochromatin With Dimelo-seqmentioning

confidence: 99%

DiMeLo-seq: a long-read, single-molecule method for mapping protein-DNA interactions genome-wide

Altemose

Maslan

Smith

et al. 2021

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Molecular studies of genome regulation often rely on the ability to map where specific proteins interact with genomic DNA. Existing techniques for mapping protein-DNA interactions genome-wide rely on DNA amplification methods followed by sequencing with short reads, which dissociates joint binding information at neighboring sites, removes endogenous DNA methylation information, and precludes the ability to reliably map interactions in repetitive regions of the genome. To address these limitations, we created a new protein-DNA mapping method, called Directed Methylation with Long-read sequencing (DiMeLo-seq), which methylates DNA near each target protein's DNA binding site in situ, then leverages the ability to distinguish methylated and unmethylated bases on long, native DNA molecules using long-read, single-molecule sequencing technologies. We demonstrate the optimization and utility of this method by mapping the interaction sites of a variety of different proteins and histone modifications across the human genome, achieving a single-molecule binding site resolution of less than 200 bp. Furthermore, we mapped the positions of the centromeric histone H3 variant CENP-A in repetitive regions that are unmappable with short reads, while simultaneously analyzing endogenous CpG methylation and joint binding events on single molecules. DiMeLo-seq is a versatile method that can provide multimodal and truly genome-wide information for investigating protein-DNA interactions.

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“…Modern draft eukaryotic genome assembly graphs are typically built from a subset of four Whole Genome Shotgun (WGS) sequencing data types: Illumina short reads 7,8 , Oxford Nanopore Technologies (ONT) long reads 9 , PacBio Continuous Long Reads (CLR), and PacBio High-Fidelity (HiFi) long reads 9,10 , all of which have been extensively described [7][8][9][10] . However, we note that even the high-accuracy technologies produce sequencing data with some noise caused by platform-specific technical biases that require careful validation and polishing 11,12,1,10,13 .…”

Section: Introductionmentioning

confidence: 98%

“…Genome assembly is a foundational practice of quantitative biological research with increasing utility. By representing the genomic sequence of a sample of interest, genome assemblies enable researchers to annotate important features, quantify functional data, and discover/genotype genetic variants in a population [1][2][3][4][5][6] . Modern draft eukaryotic genome assembly graphs are typically built from a subset of four Whole Genome Shotgun (WGS) sequencing data types: Illumina short reads 7,8 , Oxford Nanopore Technologies (ONT) long reads 9 , PacBio Continuous Long Reads (CLR), and PacBio High-Fidelity (HiFi) long reads 9,10 , all of which have been extensively described [7][8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

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Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies

Cartney

Shafin

Alonge

et al. 2021

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Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first Telomere-to-Telomere (T2T) human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Though derived from highly accurate sequencing, evaluation revealed that the initial T2T draft assembly had evidence of small errors and structural misassemblies. To correct these errors, we designed a novel repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly QV to 73.9. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both PacBio HiFi and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies.

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The complete sequence of a human genome

Cited by 138 publications

References 88 publications

Jasmine: Population-scale structural variant comparison and analysis

Jasmine: Population-scale structural variant comparison and analysis

DiMeLo-seq: a long-read, single-molecule method for mapping protein-DNA interactions genome-wide

Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies

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