scholarly journals Long read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits

2019 ◽  
Author(s):  
Doruk Beyter ◽  
Helga Ingimundardottir ◽  
Asmundur Oddsson ◽  
Hannes P. Eggertsson ◽  
Eythor Bjornsson ◽  
...  
Keyword(s):  
Sequence Data ◽  
P Value ◽  
Repeat Region ◽  
Structural Variants ◽  
Genome Wide ◽  
Population Average ◽  
Long Reads ◽  
Oxford Nanopore ◽  
A Genome ◽  
Long Read

Long-read sequencing (LRS) promises to improve characterization of structural variants (SVs), a major source of genetic diversity. We generated LRS data on 3,622 Icelanders using Oxford Nanopore Technologies, and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions), spanning a median of 10 Mb per haploid genome. We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association with a rare (AF = 0.037%) deletion of the first exon of PCSK9. Carriers of this deletion have 0.93 mmol/L (1.31 SD) lower LDL cholesterol levels than the population average (p-value = 7.0·10−20). We also discovered an association with a multi-allelic SV inside a large repeat region, contained within single long reads, in an exon of ACAN. Within this repeat region we found 11 alleles that differ in the number of a 57 bp-motif repeat, and observed a linear relationship (0.016 SD per motif inserted, p = 6.2·10−18) between the number of repeats carried and height. These results show that SVs can be accurately characterized at population scale using long read sequence data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.

scholarly journals Population genomic evidence of selection on structural variants in a natural hybrid zone

2022 ◽  
Author(s):  
Linyi Zhang ◽  
Samridhi Chaturvedi ◽  
Chris Nice ◽  
Lauren Lucas ◽  
Zachariah Gompert
Keyword(s):  
Reproductive Isolation ◽  
Hybrid Zone ◽  
Structural Variants ◽  
Hybrid Fitness ◽  
Genome Wide ◽  
Oxford Nanopore ◽  
Jackson Hole ◽  
Long Read ◽  
Genomic Regions

Structural variants (SVs) can promote speciation by directly causing reproductive isolation or by suppressing recombination across large genomic regions. Whereas examples of each mechanism have been documented, systematic tests of the role of SVs in speciation are lacking. Here, we take advantage of long-read (Oxford nanopore) whole-genome sequencing and a hybrid zone between two Lycaeides butterfly taxa (L. melissa and Jackson Hole Lycaeides) to comprehensively evaluate genome-wide patterns of introgression for SVs and relate these patterns to hypotheses about speciation. We found >100,000 SVs segregating within or between the two hybridizing species. SVs and SNPs exhibited similar levels of genetic differentiation between species, with the exception of inversions, which were more differentiated. We detected credible variation in patterns of introgression among SV loci in the hybrid zone, with 562 of 1419 ancestry-informative SVs exhibiting genomic clines that deviating from null expectations based on genome-average ancestry. Overall, hybrids exhibited a directional shift towards Jackson Hole Lycaeides ancestry at SV loci, consistent with the hypothesis that these loci experienced more selection on average then SNP loci. Surprisingly, we found that deletions, rather than inversions, showed the highest skew towards excess introgression from Jackson Hole Lycaeides. Excess Jackson Hole Lycaeides ancestry in hybrids was also especially pronounced for Z-linked SVs and inversions containing many genes. In conclusion, our results show that SVs are ubiquitous and suggest that SVs in general, but especially deletions, might contribute disproportionately to hybrid fitness and thus (partial) reproductive isolation.

scholarly journals BleTIES: Annotation of natural genome editing in ciliates using long read sequencing

2021 ◽  
Author(s):  
Brandon K. B. Seah ◽  
Estienne C. Swart
Keyword(s):  
Dna Sequences ◽  
Sequence Data ◽  
Low Complexity ◽  
Supplementary Information ◽  
Neighboring Element ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Element Elimination

Ciliates are single-celled eukaryotes that eliminate specific, interspersed DNA sequences (internally eliminated sequences, IESs) from their genomes during development. These are challenging to annotate and assemble because IES-containing sequences are much less abundant in the cell than those without, and IES sequences themselves often contain repetitive and low-complexity sequences. Long read sequencing technologies from Pacific Biosciences and Oxford Nanopore have the potential to reconstruct longer IESs than has been possible with short reads, and also the ability to detect correlations of neighboring element elimination. Here we present BleTIES, a software toolkit for detecting, assembling, and analyzing IESs using mapped long reads. Availability and implementation: BleTIES is implemented in Python 3. Source code is available at https://github.com/Swart-lab/bleties (MIT license), and also distributed via Bioconda. Contact: [email protected] Supplementary information: Benchmarking of BleTIES with published sequence data.

scholarly journals Telomere-to-telomere gapless chromosomes of banana using nanopore sequencing

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Caroline Belser ◽  
Franc-Christophe Baurens ◽  
Benjamin Noel ◽  
Guillaume Martin ◽  
Corinne Cruaud ◽  
...  
Keyword(s):  
Musa Acuminata ◽  
Genetic Maps ◽  
Nanopore Sequencing ◽  
Genome Coverage ◽  
Long Reads ◽  
Oxford Nanopore ◽  
A Genome ◽  
Long Read ◽  
Genome Assemblies ◽  
First Time

AbstractLong-read technologies hold the promise to obtain more complete genome assemblies and to make them easier. Coupled with long-range technologies, they can reveal the architecture of complex regions, like centromeres or rDNA clusters. These technologies also make it possible to know the complete organization of chromosomes, which remained complicated before even when using genetic maps. However, generating a gapless and telomere-to-telomere assembly is still not trivial, and requires a combination of several technologies and the choice of suitable software. Here, we report a chromosome-scale assembly of a banana genome (Musa acuminata) generated using Oxford Nanopore long-reads. We generated a genome coverage of 177X from a single PromethION flowcell with near 17X with reads longer than 75 kbp. From the 11 chromosomes, 5 were entirely reconstructed in a single contig from telomere to telomere, revealing for the first time the content of complex regions like centromeres or clusters of paralogous genes.

scholarly journals Telomere-to-telomere gapless chromosomes of banana using nanopore sequencing

2021 ◽  
Author(s):  
Caroline Belser ◽  
Franc-Christophe Baurens ◽  
Benjamin Noel ◽  
Guillaume Martin ◽  
Corinne Cruaud ◽  
...  
Keyword(s):  
Musa Acuminata ◽  
Genetic Maps ◽  
Nanopore Sequencing ◽  
Genome Coverage ◽  
Long Reads ◽  
Oxford Nanopore ◽  
A Genome ◽  
Long Read ◽  
Genome Assemblies ◽  
First Time

AbstractLong-read technologies hold the promise to obtain more complete genome assemblies and to make them easier. Coupled with long-range technologies, they can reveal the architecture of complex regions, like centromeres or rDNA clusters. These technologies also make it possible to know the complete organization of chromosomes, which remained complicated before even when using genetic maps. However, generating a gapless and telomere-to-telomere assembly is still not trivial, and requires a combination of several technologies and the choice of suitable software. Here, we report a chromosome-scale assembly of a banana genome (Musa acuminata) generated using Oxford Nanopore long-reads. We generated a genome coverage of 177X from a single PromethION flowcell with near 17X with reads longer than 75Kb. From the 11 chromosomes, 5 were entirely reconstructed in a single contig from telomere to telomere, revealing for the first time the content of complex regions like centromeres or clusters of paralogous genes.

scholarly journals Robust Benchmark Structural Variant Calls of An Asian Using the State-of-Art Long Fragment Sequencing Technologies

2020 ◽  
Author(s):  
Xiao Du ◽  
Lili Li ◽  
Fan Liang ◽  
Sanyang Liu ◽  
Wenxin Zhang ◽  
...  
Keyword(s):  
B Lymphocyte ◽  
De Novo ◽  
Structural Variants ◽  
High Confidence ◽  
False Negatives ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Circular Consensus Sequencing

AbstractThe importance of structural variants (SVs) on phenotypes and human diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of those approaches, our work established an Asian reference material comprising identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8,938 SVs in an EBV immortalized B lymphocyte line, by integrating four alignment-based SV callers [from 109× PacBio continuous long read (CLR), 22× PacBio circular consensus sequencing (CCS) reads, 104× Oxford Nanopore long reads, and 114× optical mapping platform (Bionano)] and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR and Sanger sequencing, proofing the robustness of our SV calls. Combining trio-binning based haplotype assemblies, we established an SV benchmark for identification of false negatives and false positives by constructing the continuous high confident regions (CHCRs), which cover 1.46Gb and 6,882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical diagnosis.

scholarly journals MoMI-G: modular multi-scale integrated genome graph browser

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Toshiyuki T. Yokoyama ◽  
Yoshitaka Sakamoto ◽  
Masahide Seki ◽  
Yutaka Suzuki ◽  
Masahiro Kasahara
Keyword(s):  
Human Cancer ◽  
Read Depth ◽  
Structural Variants ◽  
Structural Variations ◽  
Multi Scale ◽  
Long Reads ◽  
A Genome ◽  
Long Read ◽  
Complex Structural ◽  
Genome Graph

Abstract Background Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded. Results We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1. Conclusions Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. Software availability MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

scholarly journals De-novo chromosome level assembly of plant genomes from long read sequence data

2021 ◽  
Author(s):  
Priyanka Sharma ◽  
Ardashir Kharabian Masouleh ◽  
Bruce Topp ◽  
Agnelo Furtado ◽  
Robert J. Henry
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Genetic Maps ◽  
Sequence Contigs ◽  
Plant Genomes ◽  
Proximity Analysis ◽  
Long Reads ◽  
A Genome ◽  
Long Read ◽  
Chromosome Level

SummaryRecent advances in the sequencing and assembly of plant genomes have allowed the generation of genomes with increasing contiguity and sequence accuracy. The chromosome level assembly of the contigs generated from long read sequencing has involved the use of proximity analysis (Hi-C) or traditional genetic maps to guide the placement of sequence contigs within chromosomes. The development of highly accurate long reads by repeated sequencing of circularized DNA (PacBio HiFi) has greatly increased the size of contigs. We now report the use of HiFiasm to assemble the genome of Macadamia jansenii. a genome that has been used as model to test sequencing and assembly. This achieved almost complete chromosome level assembly from the sequence data alone without the need for higher level chromosome map information. Eight of the 14 chromosomes were represented by a single large contig and the other 6 assembled into 2-4 main contigs. The small number of chromosome breaks appear to be due to highly repetitive regions of ribosomal genes that cannot be assembled by these approaches. De novo assembly of near complete chromosome level plant genomes now seems possible using these sequencing and assembly tools. Further targeted strategies might allow these remaining gaps to be closed.Significance statement (of up to two sentences)De novo assembly of near complete chromosome level plant genomes is now possible using current long read sequencing and assembly tools.

scholarly journals BleTIES: Annotation of natural genome editing in ciliates using long read sequencing

2021 ◽  
Author(s):  
Brandon K B Seah ◽  
Estienne C Swart
Keyword(s):  
Dna Sequences ◽  
Sequence Data ◽  
Low Complexity ◽  
Supplementary Information ◽  
Software Toolkit ◽  
Assembly Strategy ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read

Abstract Summary Ciliates are single-celled eukaryotes that eliminate specific, interspersed DNA sequences (internally eliminated sequences, IESs) from their genomes during development. These are challenging to annotate and assemble because IES-containing sequences are typically much less abundant in the cell than those without, and IES sequences themselves often contain repetitive and low-complexity sequences. Long read sequencing technologies from Pacific Biosciences and Oxford Nanopore have the potential to reconstruct longer IESs than has been possible with short reads, but require a different assembly strategy. Here we present BleTIES, a software toolkit for detecting, assembling, and analyzing IESs using mapped long reads. Availability and implementation BleTIES is implemented in Python 3. Source code is available at https://github.com/Swart-lab/bleties (MIT license), and also distributed via Bioconda. Supplementary information Benchmarking of BleTIES with published sequence data.

scholarly journals SVIM: Structural Variant Identification using Mapped Long Reads

2018 ◽  
Author(s):  
David Heller ◽  
Martin Vingron
Keyword(s):  
Single Molecule ◽  
Simulated Data ◽  
Structural Variants ◽  
Human Phenotype ◽  
Structural Variant ◽  
Small Indels ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read

AbstractMotivationStructural variants are defined as genomic variants larger than 50bp. They have been shown to affect more bases in any given genome than SNPs or small indels. Additionally, they have great impact on human phenotype and diversity and have been linked to numerous diseases. Due to their size and association with repeats, they are difficult to detect by shotgun sequencing, especially when based on short reads. Long read, single molecule sequencing technologies like those offered by Pacific Biosciences or Oxford Nanopore Technologies produce reads with a length of several thousand base pairs. Despite the higher error rate and sequencing cost, long read sequencing offers many advantages for the detection of structural variants. Yet, available software tools still do not fully exploit the possibilities.ResultsWe present SVIM, a tool for the sensitive detection and precise characterization of structural variants from long read data. SVIM consists of three components for the collection, clustering and combination of structural variant signatures from read alignments. It discriminates five different variant classes including similar types, such as tandem and interspersed duplications and novel element insertions. SVIM is unique in its capability of extracting both the genomic origin and destination of duplications. It compares favorably with existing tools in evaluations on simulated data and real datasets from PacBio and Nanopore sequencing machines.Availability and implementationThe source code and executables of SVIM are available on Github: github.com/eldariont/svim. SVIM has been implemented in Python 3 and published on bioconda and the Python Package [email protected]

scholarly journals Genomic prediction for growth using a low-density SNP panel in dromedary camels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Morteza Bitaraf Sani ◽  
Javad Zare Harofte ◽  
Mohammad Hossein Banabazi ◽  
Saeid Esmaeilkhanian ◽  
Ali Shafei Naderi ◽  
...  
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Sample Size ◽  
Genetic Improvement ◽  
Growth Traits ◽  
P Value ◽  
Dromedary Camels ◽  
Genome Wide ◽  
A Genome ◽  
Daily Gain

AbstractFor thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.

Sign in / Sign up

Export Citation Format

Share Document