scholarly journals A haplotype-aware de novo assembly of related individuals using pedigree graph

2019 ◽  
Author(s):  
Shilpa Garg ◽  
John Aach ◽  
Heng Li ◽  
Richard Durbin ◽  
George Church
Keyword(s):  
De Novo ◽  
Diploid Species ◽  
Real Data ◽  
Genome Project ◽  
Personal Genome ◽  
Sequencing Data ◽  
High Quality ◽  
Illumina Data ◽  
Long Read ◽  
Related Individuals

AbstractMotivationReconstructing high-quality haplotype-resolved assemblies for related individuals of various species has important applications in understanding Mendelian diseases along with evolutionary and comparative genomics. Through major genomics sequencing efforts such as the Personal Genome Project, the Vertebrate Genome Project (VGP), the Earth Biogenome Project (EBP) and the Genome in a Bottle project (GIAB), a variety of sequencing datasets from mother-father-child trios of various diploid species are becoming available.Current trio assembly approaches are not designed to incorporate long-read sequencing data from parents in a trio, and therefore require relatively high coverages of costly long-read data to produce high-quality assemblies. Thus, building a trio-aware assembler capable of producing accurate and chromosomal-scale diploid genomes in a pedigree, while being cost-effective in terms of sequencing costs, is a pressing need of the genomics community.ResultsWe present a novel pedigree-graph-based approach to diploid assembly using accurate Illumina data and long-read Pacific Biosciences (PacBio) data from all related individuals, thereby generalizing our previous work on single individuals. We demonstrate the effectiveness of our pedigree approach on a simulated trio of pseudo-diploid yeast genomes with different heterozygosity rates, and real data from Arabidopsis Thaliana. We show that we require as little as 30× coverage Illumina data and 15× PacBio data from each individual in a trio to generate chromosomal-scale phased assemblies. Additionally, we show that we can detect and phase variants from generated phased assemblies.Availabilityhttps://github.com/shilpagarg/[email protected], [email protected]

scholarly journals A haplotype-aware de novo assembly of related individuals using pedigree sequence graph

2019 ◽  
Vol 36 (8) ◽  
pp. 2385-2392 ◽  
Author(s):  
Shilpa Garg ◽  
John Aach ◽  
Heng Li ◽  
Isaac Sebenius ◽  
Richard Durbin ◽  
...  
Keyword(s):  
Population Genomics ◽  
De Novo ◽  
Real Data ◽  
Genome Project ◽  
Personal Genome ◽  
High Quality ◽  
Illumina Data ◽  
Sequence Graph ◽  
Long Read ◽  
Related Individuals

Abstract Motivation Reconstructing high-quality haplotype-resolved assemblies for related individuals has important applications in Mendelian diseases and population genomics. Through major genomics sequencing efforts such as the Personal Genome Project, the Vertebrate Genome Project (VGP) and the Genome in a Bottle project (GIAB), a variety of sequencing datasets from trios of diploid genomes are becoming available. Current trio assembly approaches are not designed to incorporate long- and short-read data from mother–father–child trios, and therefore require relatively high coverages of costly long-read data to produce high-quality assemblies. Thus, building a trio-aware assembler capable of producing accurate and chromosomal-scale diploid genomes of all individuals in a pedigree, while being cost-effective in terms of sequencing costs, is a pressing need of the genomics community. Results We present a novel pedigree sequence graph based approach to diploid assembly using accurate Illumina data and long-read Pacific Biosciences (PacBio) data from all related individuals, thereby generalizing our previous work on single individuals. We demonstrate the effectiveness of our pedigree approach on a simulated trio of pseudo-diploid yeast genomes with different heterozygosity rates, and real data from human chromosome. We show that we require as little as 30× coverage Illumina data and 15× PacBio data from each individual in a trio to generate chromosomal-scale phased assemblies. Additionally, we show that we can detect and phase variants from generated phased assemblies. Availability and implementation https://github.com/shilpagarg/WHdenovo.

scholarly journals Extensive sequencing of seven human genomes to characterize benchmark reference materials

2015 ◽  
Author(s):  
Justin M Zook ◽  
David Catoe ◽  
Jennifer McDaniel ◽  
Lindsay Vang ◽  
Noah Spies ◽  
...  
Keyword(s):  
Human Genome ◽  
Reference Materials ◽  
De Novo ◽  
Variant Calling ◽  
Genome Project ◽  
Genome Comparison ◽  
Personal Genome ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Human Genomes

The Genome in a Bottle Consortium, hosted by the National Institute of Standards and Technology (NIST) is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Chinese ancestry. The data come from 12 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCodeTM WGS, and Illumina exome and WGS paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly.

scholarly journals An exploration of assembly strategies and quality metrics on the accuracy of the Knightia excelsa (rewarewa) genome.

2021 ◽  
Author(s):  
Ann McCartney ◽  
Elena Hilario ◽  
Seung-Sub Choi ◽  
Joseph Guhlin ◽  
Jessie Prebble ◽  
...  
Keyword(s):  
New Zealand ◽  
De Novo ◽  
Quality Metrics ◽  
Read Length ◽  
Model Organisms ◽  
Sequencing Data ◽  
Contig Assembly ◽  
High Quality ◽  
Aotearoa New Zealand ◽  
Long Read

We used long read sequencing data generated from Knightia excelsaI R.Br, a nectar producing Proteaceae tree endemic to Aotearoa New Zealand, to explore how sequencing data type, volume and workflows can impact final assembly accuracy and chromosome construction. Establishing a high-quality genome for this species has specific cultural importance to Māori, the indigenous people, as well as commercial importance to honey producers in Aotearoa New Zealand. Assemblies were produced by five long read assemblers using data subsampled based on read lengths, two polishing strategies, and two Hi-C mapping methods. Our results from subsampling the data by read length showed that each assembler tested performed differently depending on the coverage and the read length of the data. Assemblies that used longer read lengths (>30 kb) and lower coverage were the most contiguous, kmer and gene complete. The final genome assembly was constructed into pseudo-chromosomes using all available data assembled with FLYE, polished using Racon/Medaka/Pilon combined, scaffolded using SALSA2 and AllHiC, curated using Juicebox, and validated by synteny with Macadamia. We highlighted the importance of developing assembly workflows based on the volume and type of sequencing data and establishing a set of robust quality metrics for generating high quality assemblies. Scaffolding analyses highlighted that problems found in the initial assemblies could not be resolved accurately by utilizing Hi-C data and that scaffolded assemblies were more accurate when the underlying contig assembly was of higher accuracy. These findings provide insight into what is required for future high-quality de-novo assemblies of non-model organisms.

scholarly journals WENGAN: Efficient and high quality hybrid de novo assembly of human genomes

2019 ◽  
Author(s):  
Alex Di Genova ◽  
Elena Buena-Atienza ◽  
Stephan Ossowski ◽  
Marie-France Sagot
Keyword(s):  
De Novo ◽  
Computational Cost ◽  
Sequence Information ◽  
Sequencing Data ◽  
High Quality ◽  
Sequencing Technologies ◽  
Human Genomes ◽  
Long Reads ◽  
Long Read ◽  
Genome Assemblies

The continuous improvement of long-read sequencing technologies along with the development of ad-doc algorithms has launched a new de novo assembly era that promises high-quality genomes. However, it has proven difficult to use only long reads to generate accurate genome assemblies of large, repeat-rich human genomes. To date, most of the human genomes assembled from long error-prone reads add accurate short reads to further polish the consensus quality. Here, we report the development of a novel algorithm for hybrid assembly, WENGAN, and the de novo assembly of four human genomes using a combination of sequencing data generated on ONT PromethION, PacBio Sequel, Illumina and MGI technology. WENGAN implements efficient algorithms that exploit the sequence information of short and long reads to tackle assembly contiguity as well as consensus quality. The resulting genome assemblies have high contiguity (contig NG50:16.67-62.06 Mb), few assembly errors (contig NGA50:10.9-45.91 Mb), good consensus quality (QV:27.79-33.61), and high gene completeness (BUSCO complete: 94.6-95.1%), while consuming low computational resources (CPU hours:153-1027). In particular, the WENGAN assembly of the haploid CHM13 sample achieved a contig NG50 of 62.06 Mb (NGA50:45.91 Mb), which surpasses the contiguity of the current human reference genome (GRCh38 contig NG50:57.88 Mb). Providing highest quality at low computational cost, WENGAN is an important step towards the democratization of the de novo assembly of human genomes. The WENGAN assembler is available at https://github.com/adigenova/wengan

scholarly journals A robust benchmark for germline structural variant detection

2019 ◽  
Author(s):  
Justin M. Zook ◽  
Nancy F. Hansen ◽  
Nathan D. Olson ◽  
Lesley M. Chapman ◽  
James C. Mullikin ◽  
...  
Keyword(s):  
New Technologies ◽  
De Novo ◽  
Sequence Data ◽  
False Negative ◽  
Strong Support ◽  
False Positives ◽  
Genome Project ◽  
Personal Genome ◽  
Tier 1 ◽  
Long Read

AbstractNew 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.

scholarly journals An exploration of assembly strategies and quality metrics on the accuracy of the Knightia excelsa (rewarewa) genome

2020 ◽  
Author(s):  
Ann McCartney ◽  
Elena Hilario ◽  
Seung-Sub Choi ◽  
Joseph Guhlin ◽  
Jessica M. Prebble ◽  
...  
Keyword(s):  
New Zealand ◽  
De Novo ◽  
Quality Metrics ◽  
Read Length ◽  
Model Organisms ◽  
Sequencing Data ◽  
Contig Assembly ◽  
High Quality ◽  
Aotearoa New Zealand ◽  
Long Read

AbstractBackgroundWe used long read sequencing data generated from Knightia excelsaI R.Br, a nectar producing Proteaceae tree endemic to Aotearoa New Zealand, to explore how sequencing data type, volume and workflows can impact final assembly accuracy and chromosome construction. Establishing a high-quality genome for this species has specific cultural importance to Māori, the indigenous people, as well as commercial importance to honey producers in Aotearoa New Zealand.ResultsAssemblies were produced by five long read assemblers using data subsampled based on read lengths, two polishing strategies, and two Hi-C mapping methods. Our results from subsampling the data by read length showed that each assembler tested performed differently depending on the coverage and the read length of the data. Assemblies that used longer read lengths (>30 kb) and lower coverage were the most contiguous, kmer and gene complete. The final genome assembly was constructed into pseudochromosomes using all available data assembled with FLYE, polished using Racon/Medaka/Pilon combined, scaffolded using SALSA2 and AllHiC, curated using Juicebox, and validated by synteny with Macadamia.ConclusionsWe highlighted the importance of developing assembly workflows based on the volume and type of sequencing data and establishing a set of robust quality metrics for generating high quality assemblies. Scaffolding analyses highlighted that problems found in the initial assemblies could not be resolved accurately by utilizing Hi-C data and that scaffolded assemblies were more accurate when the underlying contig assembly was of higher accuracy. These findings provide insight into what is required for future high-quality de-novo assemblies of non-model organisms.

scholarly journals Comparison of long-read methods for sequencing and assembly of a plant genome

GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Valentine Murigneux ◽  
Subash Kumar Rai ◽  
Agnelo Furtado ◽  
Timothy J C Bruxner ◽  
Wei Tian ◽  
...  
Keyword(s):  
De Novo ◽  
Cost Effective ◽  
Genome Project ◽  
Plant Genome ◽  
Sequencing Data ◽  
Pacific Biosciences ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
The Cost

Abstract Background Sequencing technologies have advanced to the point where it is possible to generate high-accuracy, haplotype-resolved, chromosome-scale assemblies. Several long-read sequencing technologies are available, and a growing number of algorithms have been developed to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology, as well as the most appropriate software for assembly and polishing. It is thus important to benchmark different approaches applied to the same sample. Results Here, we report a comparison of 3 long-read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION), and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of Pacific Biosciences and Nanopore reads. Results obtained from combining long-read technologies or short-read and long-read technologies are also presented. The assemblies were compared for contiguity, base accuracy, and completeness, as well as sequencing costs and DNA material requirements. Conclusions The 3 long-read technologies produced highly contiguous and complete genome assemblies of M. jansenii. At the time of sequencing, the cost associated with each method was significantly different, but continuous improvements in technologies have resulted in greater accuracy, increased throughput, and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.

scholarly journals Comparison of long read methods for sequencing and assembly of a plant genome

2020 ◽  
Author(s):  
Valentine Murigneux ◽  
Subash Kumar Rai ◽  
Agnelo Furtado ◽  
Timothy J.C. Bruxner ◽  
Wei Tian ◽  
...  
Keyword(s):  
De Novo ◽  
Cost Effective ◽  
Genome Project ◽  
Plant Genome ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
The Cost ◽  
Genome Assemblies

AbstractSequencing technologies have advanced to the point where it is possible to generate high accuracy, haplotype resolved, chromosome scale assemblies. Several long read sequencing technologies are available on the market and a growing number of algorithms have been developed over the last years to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology as well as the most appropriate software for assembly and polishing. For this reason, it is important to benchmark different approaches applied to the same sample. Here, we report a comparison of three long read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION) and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of PacBio and Nanopore reads. Results obtained from combining long read technologies or short read and long read technologies are also presented. The assemblies were compared for contiguity, accuracy and completeness as well as sequencing costs and DNA material requirements. Overall, the three long read technologies produced highly contiguous and complete genome assemblies of Macadamia jansenii. At the time of sequencing, the cost associated with each method was significantly different but continuous improvements in technologies have resulted in greater accuracy, increased throughput and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.

scholarly journals Extended haplotype phasing of de novo genome assemblies with FALCON-Phase

2018 ◽  
Author(s):  
Zev N. Kronenberg ◽  
Arang Rhie ◽  
Sergey Koren ◽  
Gregory T. Concepcion ◽  
Paul Peluso ◽  
...  
Keyword(s):  
Zebra Finch ◽  
De Novo ◽  
Chromatin Interaction ◽  
Sequencing Data ◽  
High Quality ◽  
Extended Haplotype ◽  
Long Read ◽  
Contact Data ◽  
The Individual ◽  
Genome Assemblies

ABSTRACTHaplotype-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.

scholarly journals Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation

BMJ ◽  
2021 ◽  
pp. n214
Author(s):  
Weedon MN ◽  
Jackson L ◽  
Harrison JW ◽  
Ruth KS ◽  
Tyrrell J ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Population Based ◽  
Genome Project ◽  
Personal Genome ◽  
Uk Biobank ◽  
Sequencing Data ◽  
Snp Chip ◽  
Pathogenic Variants ◽  
The Uk

Abstract Objective To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population. Design Retrospective, population based diagnostic evaluation. Participants 49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project. Main outcome measures Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data. Results Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03). Conclusions SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

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