Detection of clinically relevant copy-number variants from short-read sequencing data for genomic diagnostics

2021 ◽  
Author(s):  
Ramakrishnan Rajagopalan
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing

scholarly journals High resolution copy number inference in cancer using short-molecule nanopore sequencing

2020 ◽  
Author(s):  
Timour Baslan ◽  
Sam Kovaka ◽  
Fritz J. Sedlazeck ◽  
Yanming Zhang ◽  
Robert Wappel ◽  
...  
Keyword(s):  
Copy Number ◽  
Cost Effective ◽  
Chromosome Analysis ◽  
Ease Of Use ◽  
Precision Oncology ◽  
Nanopore Sequencing ◽  
Dna Molecules ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing

ABSTRACTGenome copy number is an important source of genetic variation in health and disease. In cancer, clinically actionable Copy Number Alterations (CNAs) can be inferred from short-read sequencing data, enabling genomics-based precision oncology. Emerging Nanopore sequencing technologies offer the potential for broader clinical utility, for example in smaller hospitals, due to lower instrument cost, higher portability, and ease of use. Nonetheless, Nanopore sequencing devices are limited in terms of the number of retrievable sequencing reads/molecules compared to short-read sequencing platforms. This represents a challenge for applications that require high read counts such as CNA inference. To address this limitation, we targeted the sequencing of short-length DNA molecules loaded at optimized concentration in an effort to increase sequence read/molecule yield from a single nanopore run. We show that sequencing short DNA molecules reproducibly returns high read counts and allows high quality CNA inference. We demonstrate the clinical relevance of this approach by accurately inferring CNAs in acute myeloid leukemia samples. The data shows that, compared to traditional approaches such as chromosome analysis/cytogenetics, short molecule nanopore sequencing returns more sensitive, accurate copy number information in a cost effective and expeditious manner, including for multiplex samples. Our results provide a framework for the sequencing of relatively short DNA molecules on nanopore devices with applications in research and medicine, that include but are not limited to, CNAs.

scholarly journals High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING

2021 ◽  
Author(s):  
Wesley Marin ◽  
Ravi Dandekar ◽  
Danillo G. Augusto ◽  
Tasneem Yusufali ◽  
Bianca Heyn ◽  
...  
Keyword(s):  
High Resolution ◽  
High Throughput ◽  
Copy Number ◽  
Killer Cell ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing ◽  
Kir Genes

The killer-cell immunoglobulin-like receptor ( KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

scholarly journals Extensive gene duplication in Arabidopsis revealed by pseudo-heterozygosity

2021 ◽  
Author(s):  
Benjamin Jaegle ◽  
Luz Mayela Soto-Jimenez ◽  
Robin Burns ◽  
Fernando A. Rabanal ◽  
Magnus Nordborg
Keyword(s):  
Copy Number ◽  
Structural Variation ◽  
De Novo ◽  
Sequencing Data ◽  
Heterozygous Snps ◽  
Mendelian Segregation ◽  
Short Read ◽  
Short Read Sequencing ◽  
Snp Data ◽  
Number Variation

Background: It is becoming apparent that genomes harbor massive amounts of structural variation, and that this variation has largely gone undetected for technical reasons. In addition to being inherently interesting, structural variation can cause artifacts when short-read sequencing data are mapped to a reference genome. In particular, spurious SNPs (that do not show Mendelian segregation) may result from mapping of reads to duplicated regions. Recalling SNP using the raw reads of the 1001 Arabidopsis Genomes Project we identified 3.3 million heterozygous SNPs (44% of total). Given that Arabidopsis thaliana (A. thaliana) is highly selfing, we hypothesized that these SNPs reflected cryptic copy number variation, and investigated them further. Results: While genuine heterozygosity should occur in tracts within individuals, heterozygosity at a particular locus is instead shared across individuals in a manner that strongly suggests it reflects segregating duplications rather than actual heterozygosity. Focusing on pseudo-heterozygosity in annotated genes, we used GWAS to map the position of the duplicates, identifying 2500 putatively duplicated genes. The results were validated using de novo genome assemblies from six lines. Specific examples included an annotated gene and nearby transposon that, in fact, transpose together. Conclusions: Our study confirms that most heterozygous SNPs calls in A. thaliana are artifacts, and suggest that great caution is needed when analysing SNP data from short-read sequencing. The finding that 10% of annotated genes are copy-number variables, and the realization that neither gene- nor transposon-annotation necessarily tells us what is actually mobile in the genome suggest that future analyses based on independently assembled genomes will be very informative.

scholarly journals Hecaton: reliably detecting copy number variation in plant genomes using short read sequencing data

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Raúl Y. Wijfjes ◽  
Sandra Smit ◽  
Dick de Ridder
Keyword(s):  
Copy Number Variation ◽  
Plant Species ◽  
Copy Number ◽  
State Of The Art ◽  
Sequencing Data ◽  
Short Read ◽  
Plant Genomes ◽  
Short Read Sequencing ◽  
Number Variation ◽  
Multiple State

Abstract Background Copy number variation (CNV) is thought to actively contribute to adaptive evolution of plant species. While many computational algorithms are available to detect copy number variation from whole genome sequencing datasets, the typical complexity of plant data likely introduces false positive calls. Results To enable reliable and comprehensive detection of CNV in plant genomes, we developed Hecaton, a novel computational workflow tailored to plants, that integrates calls from multiple state-of-the-art algorithms through a machine-learning approach. In this paper, we demonstrate that Hecaton outperforms current methods when applied to short read sequencing data of Arabidopsis thaliana, rice, maize, and tomato. Moreover, it correctly detects dispersed duplications, a type of CNV commonly found in plant species, in contrast to several state-of-the-art tools that erroneously represent this type of CNV as overlapping deletions and tandem duplications. Finally, Hecaton scales well in terms of memory usage and running time when applied to short read datasets of domesticated and wild tomato accessions. Conclusions Hecaton provides a robust method to detect CNV in plants. We expect it to be of immediate interest to both applied and fundamental research on the relationship between genotype and phenotype in plants.

scholarly journals Hecaton: reliably detecting copy number variation in plant genomes using short read sequencing data

2019 ◽  
Author(s):  
Raúl Wijfjes ◽  
Sandra Smit ◽  
Dick de Ridder
Keyword(s):  
Copy Number Variation ◽  
Plant Species ◽  
Copy Number ◽  
State Of The Art ◽  
Sequencing Data ◽  
Short Read ◽  
Plant Genomes ◽  
Short Read Sequencing ◽  
Number Variation ◽  
Multiple State

AbstractCopy number variation (CNV) is thought to actively contribute to adaptive evolution of plant species. While many computational algorithms are available to detect copy number variation from whole genome sequencing datasets, the typical complexity of plant data likely introduces false positive calls.To enable reliable and comprehensive detection of CNV in plant genomes, we developed Hecaton, a novel computational workflow tailored to plants, that integrates calls from multiple state-of-the-art algorithms through a machine-learning approach. In this paper, we demonstrate that Hecaton outperforms current methods when applied to short read sequencing data of A. thaliana, rice, maize, and tomato. Moreover, it correctly detects dispersed duplications, a type of CNV commonly found in plant species, in contrast to several state-of-the-art tools that erroneously represent this type of CNV as overlapping deletions and tandem duplications. Finally, Hecaton scales well in terms of memory usage and running time when applied to short read datasets of domesticated and wild tomato accessions. Hecaton provides a robust method to detect CNV in plants. We expect it to be of immediate interest to both applied and fundamental research on the relationship between genotype and phenotype in plants.

scholarly journals High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING

2021 ◽  
Vol 17 (8) ◽  
pp. e1008904
Author(s):  
Wesley M. Marin ◽  
Ravi Dandekar ◽  
Danillo G. Augusto ◽  
Tasneem Yusufali ◽  
Bianca Heyn ◽  
...  
Keyword(s):  
High Resolution ◽  
High Throughput ◽  
Copy Number ◽  
Killer Cell ◽  
Gene Copy Number ◽  
Synthetic Dataset ◽  
Gene Copy ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

scholarly journals High resolution copy number inference in cancer using short-molecule nanopore sequencing

2021 ◽  
Author(s):  
Timour Baslan ◽  
Sam Kovaka ◽  
Fritz J Sedlazeck ◽  
Yanming Zhang ◽  
Robert Wappel ◽  
...  
Keyword(s):  
Copy Number ◽  
Cost Effective ◽  
Chromosome Analysis ◽  
Ease Of Use ◽  
Precision Oncology ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing ◽  
Sequencing Platforms

Abstract Genome copy number is an important source of genetic variation in health and disease. In cancer, Copy Number Alterations (CNAs) can be inferred from short-read sequencing data, enabling genomics-based precision oncology. Emerging Nanopore sequencing technologies offer the potential for broader clinical utility, for example in smaller hospitals, due to lower instrument cost, higher portability, and ease of use. Nonetheless, Nanopore sequencing devices are limited in the number of retrievable sequencing reads/molecules compared to short-read sequencing platforms, limiting CNA inference accuracy. To address this limitation, we targeted the sequencing of short-length DNA molecules loaded at optimized concentration in an effort to increase sequence read/molecule yield from a single nanopore run. We show that short-molecule nanopore sequencing reproducibly returns high read counts and allows high quality CNA inference. We demonstrate the clinical relevance of this approach by accurately inferring CNAs in acute myeloid leukemia samples. The data shows that, compared to traditional approaches such as chromosome analysis/cytogenetics, short molecule nanopore sequencing returns more sensitive, accurate copy number information in a cost effective and expeditious manner, including for multiplex samples. Our results provide a framework for short-molecule nanopore sequencing with applications in research and medicine, which includes but is not limited to, CNAs.

scholarly journals REscan: inferring repeat expansions and structural variation in paired-end short read sequencing data

2020 ◽  
Author(s):  
Russell Lewis McLaughlin
Keyword(s):  
Structural Variation ◽  
Sequence Data ◽  
Neurological Diseases ◽  
Repeat Expansion ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing ◽  
Repeat Expansions ◽  
Paired End Sequencing

Abstract Motivation Repeat expansions are an important class of genetic variation in neurological diseases. However, the identification of novel repeat expansions using conventional sequencing methods is a challenge due to their typical lengths relative to short sequence reads and difficulty in producing accurate and unique alignments for repetitive sequence. However, this latter property can be harnessed in paired-end sequencing data to infer the possible locations of repeat expansions and other structural variation. Results This article presents REscan, a command-line utility that infers repeat expansion loci from paired-end short read sequencing data by reporting the proportion of reads orientated towards a locus that do not have an adequately mapped mate. A high REscan statistic relative to a population of data suggests a repeat expansion locus for experimental follow-up. This approach is validated using genome sequence data for 259 cases of amyotrophic lateral sclerosis, of which 24 are positive for a large repeat expansion in C9orf72, showing that REscan statistics readily discriminate repeat expansion carriers from non-carriers. Availabilityand implementation C source code at https://github.com/rlmcl/rescan (GNU General Public Licence v3).

scholarly journals Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

2020 ◽  
Author(s):  
Andrew J. Page ◽  
Nabil-Fareed Alikhan ◽  
Michael Strinden ◽  
Thanh Le Viet ◽  
Timofey Skvortsov
Keyword(s):  
Mycobacterium Tuberculosis ◽  
State Of The Art ◽  
Sequence Data ◽  
Human Pathogen ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing ◽  
Long Reads ◽  
Long Read

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.

Sign in / Sign up

Export Citation Format

Share Document