scholarly journals De Novo Assembly of Two Swedish Genomes Reveals Missing Segments from the Human GRCh38 Reference and Improves Variant Calling of Population-Scale Sequencing Data

Genes ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 486 ◽  
Author(s):  
Adam Ameur ◽  
Huiwen Che ◽  
Marcel Martin ◽  
Ignas Bunikis ◽  
Johan Dahlberg ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
De Novo Assembly ◽  
De Novo ◽  
Variant Calling ◽  
Whole Genome Sequencing Data ◽  
Personal Genome ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Population Scale

The current human reference sequence (GRCh38) is a foundation for large-scale sequencing projects. However, recent studies have suggested that GRCh38 may be incomplete and give a suboptimal representation of specific population groups. Here, we performed a de novo assembly of two Swedish genomes that revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have an elevated GC-content, and are primarily located in centromeric or telomeric regions. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are also missing from GRCh38 at chromosomes 14, 17, and 21. Inclusion of NS into the GRCh38 reference radically improves the alignment and variant calling from short-read whole-genome sequencing data at several genomic loci. A re-analysis of a Swedish population-scale sequencing project yields > 75,000 putative novel single nucleotide variants (SNVs) and removes > 10,000 false positive SNV calls per individual, some of which are located in protein coding regions. Our results highlight that the GRCh38 reference is not yet complete and demonstrate that personal genome assemblies from local populations can improve the analysis of short-read whole-genome sequencing data.

scholarly journals GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jian-Jun Jin ◽  
Wen-Bin Yu ◽  
Jun-Bo Yang ◽  
Yu Song ◽  
Claude W. dePamphilis ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
De Novo Assembly ◽  
De Novo ◽  
State Of The Art ◽  
Whole Genome Sequencing Data ◽  
Mitochondrial Genomes ◽  
Whole Genome ◽  
Sequencing Data ◽  
Organelle Genomes ◽  
Complete Mitochondrial Genomes

Abstract GetOrganelle is a state-of-the-art toolkit to accurately assemble organelle genomes from whole genome sequencing data. It recruits organelle-associated reads using a modified “baiting and iterative mapping” approach, conducts de novo assembly, filters and disentangles the assembly graph, and produces all possible configurations of circular organelle genomes. For 50 published plant datasets, we are able to reassemble the circular plastomes from 47 datasets using GetOrganelle. GetOrganelle assemblies are more accurate than published and/or NOVOPlasty-reassembled plastomes as assessed by mapping. We also assemble complete mitochondrial genomes using GetOrganelle. GetOrganelle is freely released under a GPL-3 license (https://github.com/Kinggerm/GetOrganelle).

scholarly journals De novo assembly of two Swedish genomes reveals missing segments from the human GRCh38 reference and improves variant calling of population-scale sequencing data

2018 ◽  
Author(s):  
Adam Ameur ◽  
Huiwen Che ◽  
Marcel Martin ◽  
Ignas Bunikis ◽  
Johan Dahlberg ◽  
...  
Keyword(s):  
De Novo ◽  
Gc Content ◽  
Variant Calling ◽  
Whole Genome Sequencing Data ◽  
Personal Genome ◽  
Sequencing Data ◽  
Swedish Population ◽  
Protein Coding ◽  
Sequencing Project ◽  
Population Scale

AbstractWe have performed de novo assembly of two Swedish genomes using long-read sequencing and optical mapping, resulting in total assembly sizes of nearly 3 Gb and hybrid scaffold N50 values of over 45 Mb. A further analysis revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have elevated GC-content and are primarily located in centromeric or telomeric regions. A BLAST search showed that 31% of the NS are different from any sequences deposited in nucleotide databases. The remaining NS correspond to human (62%) or primate (6%) nucleotide entries, while 1% of hits show the highest similarity to other species, including mouse and a few different classes of parasitic worms. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are missing from GRCh38 also at chromosomes 14, 17 and 21. Inclusion of these novel sequences into the GRCh38 reference radically improves the alignment and variant calling of whole-genome sequencing data at several genomic loci. Through a re-analysis of 200 samples from a Swedish population-scale sequencing project, we obtained over 75,000 putative novel SNVs per individual when using a custom version of GRCh38 extended with 17.3 Mb of NS. In addition, about 10,000 false positive SNV calls per individual were removed from the GRCh38 autosomes and sex chromosomes in the re-analysis, with some of them located in protein coding regions.

scholarly journals Rapid Diagnosis of Spinocerebellar Ataxia 36 in a Three‐Generation Family Using Short‐Read Whole‐Genome Sequencing Data

2020 ◽  
Vol 35 (9) ◽  
pp. 1675-1679
Author(s):  
Haloom Rafehi ◽  
David J. Szmulewicz ◽  
Kate Pope ◽  
Mathew Wallis ◽  
John Christodoulou ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Spinocerebellar Ataxia ◽  
Genome Sequencing ◽  
Rapid Diagnosis ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Generation Family

scholarly journals De novo indels within introns contribute to ASD incidence

2017 ◽  
Author(s):  
Adriana Munoz ◽  
Boris Yamrom ◽  
Yoon-ha Lee ◽  
Peter Andrews ◽  
Steven Marks ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Target Genes ◽  
De Novo ◽  
Whole Genome Sequencing Data ◽  
P Value ◽  
Whole Genome ◽  
Sequencing Data ◽  
Control Sets ◽  
The Difference

AbstractCopy number profiling and whole-exome sequencing has allowed us to make remarkable progress in our understanding of the genetics of autism over the past ten years, but there are major aspects of the genetics that are unresolved. Through whole-genome sequencing, additional types of genetic variants can be observed. These variants are abundant and to know which are functional is challenging. We have analyzed whole-genome sequencing data from 510 of the Simons Simplex Collections quad families and focused our attention on intronic variants. Within the introns of 546 high-quality autism target genes, we identified 63 de novo indels in the affected and only 37 in the unaffected siblings. The difference of 26 events is significantly larger than expected (p-val = 0.01) and using reasonable extrapolation shows that de novo intronic indels can contribute to at least 10% of simplex autism. The significance increases if we restrict to the half of the autism targets that are intolerant to damaging variants in the normal human population, which half we expect to be even more enriched for autism genes. For these 273 targets we observe 43 and 20 events in affected and unaffected siblings, respectively (p-value of 0.005). There was no significant signal in the number of de novo intronic indels in any of the control sets of genes analyzed. We see no signal from de novo substitutions in the introns of target genes.

scholarly journals TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

2018 ◽  
Author(s):  
Anna E Sheppard ◽  
Nicole Stoesser ◽  
Ian German-Mesner ◽  
Kasi Vegesana ◽  
A Sarah Walker ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Transposable Elements ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Whole Genome Sequencing Data ◽  
Sequence Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatic Pipeline ◽  
Short Read

ABSTRACTMuch of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

scholarly journals Short-Read Whole-Genome Sequencing for Laboratory-Based Surveillance of Bordetella pertussis

2017 ◽  
Vol 55 (5) ◽  
pp. 1446-1453 ◽  
Author(s):  
Alex Marchand-Austin ◽  
Raymond S. W. Tsang ◽  
Jennifer L. Guthrie ◽  
Jennifer H. Ma ◽  
Gillian H. Lim ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Bordetella Pertussis ◽  
Vaccine Effectiveness ◽  
Vaccine Antigen ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Content Type

ABSTRACTBordetella pertussisis a Gram-negative bacterium that causes respiratory infections in humans. Ongoing molecular surveillance ofB. pertussisacellular vaccine (aP) antigens is critical for understanding the interaction between evolutionary pressures, disease pathogenesis, and vaccine effectiveness. Methods currently used to characterize aP components are relatively labor-intensive and low throughput. To address this challenge, we sought to derive aP antigen genotypes from minimally processed short-read whole-genome sequencing data generated from 40 clinicalB. pertussisisolates and analyzed using the SRST2 bioinformatic package. SRST2 was able to identify aP antigen genotypes for all antigens with the exception of pertactin, possibly due to low read coverage in GC-rich low-complexity regions of variation. Two main genotypes were observed in addition to a singular third genotype that contained an 84-bp deletion that was identified by SRST2 despite the issues in allele calling. This method has the potential to generate large pools ofB. pertussismolecular data that can be linked to clinical and epidemiological information to facilitate research of vaccine effectiveness and disease severity in the context of emerging vaccine antigen-deficient strains.

scholarly journals Determining Streptococcus suis serotype from short-read whole-genome sequencing data

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Taryn B. T. Athey ◽  
Sarah Teatero ◽  
Sonia Lacouture ◽  
Daisuke Takamatsu ◽  
Marcelo Gottschalk ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Streptococcus Suis ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Suis Serotype

scholarly journals read_haps: using read haplotypes to detect same species contamination in DNA sequences

2020 ◽  
Author(s):  
Hannes P. Eggertsson ◽  
Bjarni V. Halldorsson
Keyword(s):  
Data Analysis ◽  
Genome Sequencing ◽  
Dna Sequences ◽  
Diploid Species ◽  
Reliable Data ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Polymorphic Snps

AbstractMotivationData analysis is requisite on reliable data. In genetics this includes verifying that the sample is not contaminated with another, a problem ubiquitous in biology.ResultsIn human, and other diploid species, DNA contamination from the same species can be found by the presence of three haplotypes between polymorphic SNPs. read_haps is a tool that detects sample contamination from short read whole genome sequencing data.Availabilitygithub.com/DecodeGenetics/[email protected]

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