Menu

Auto Tag: NA12878

April 21, 2020  |  

rMETL: sensitive mobile element insertion detection with long read realignment.

Mobile element insertion (MEI) is a major category of structure variations (SVs). The rapid development of long read sequencing technologies provides the opportunity to detect MEIs sensitively. However, the signals of MEI implied by noisy long reads are highly complex due to the repetitiveness of mobile elements as well as the high sequencing error rates. Herein, we propose the Realignment-based Mobile Element insertion detection Tool for Long read (rMETL). Benchmarking results of simulated and real datasets demonstrate that rMETL enables to handle the complex signals to discover MEIs sensitively. It is suited to produce high-quality MEI callsets in many genomics studies.rMETL is available from https://github.com/hitbc/rMETL.Supplementary data are available at Bioinformatics online. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Read more
April 21, 2020  |  

TranscriptClean: variant-aware correction of indels, mismatches and splice junctions in long-read transcripts.

Long-read, single-molecule sequencing platforms hold great potential for isoform discovery and characterization of multi-exon transcripts. However, their high error rates are an obstacle to distinguishing novel transcript isoforms from sequencing artifacts. Therefore, we developed the package TranscriptClean to correct mismatches, microindels and noncanonical splice junctions in mapped transcripts using the reference genome while preserving known variants.Our method corrects nearly all mismatches and indels present in a publically available human PacBio Iso-seq dataset, and rescues 39% of noncanonical splice junctions.All Python and R scripts used in this paper are available at https://github.com/dewyman/TranscriptClean.

Read more
April 21, 2020  |  

Long-read sequencing identifies GGC repeat expansions in NOTCH2NLC associated with neuronal intranuclear inclusion disease.

Neuronal intranuclear inclusion disease (NIID) is a progressive neurodegenerative disease that is characterized by eosinophilic hyaline intranuclear inclusions in neuronal and somatic cells. The wide range of clinical manifestations in NIID makes ante-mortem diagnosis difficult1-8, but skin biopsy enables its ante-mortem diagnosis9-12. The average onset age is 59.7 years among approximately 140 NIID cases consisting of mostly sporadic and several familial cases. By linkage mapping of a large NIID family with several affected members (Family 1), we identified a 58.1 Mb linked region at 1p22.1-q21.3 with a maximum logarithm of the odds score of 4.21. By long-read sequencing, we identified a GGC repeat expansion in the 5′ region of NOTCH2NLC (Notch 2 N-terminal like C) in all affected family members. Furthermore, we found similar expansions in 8 unrelated families with NIID and 40 sporadic NIID cases. We observed abnormal anti-sense transcripts in fibroblasts specifically from patients but not unaffected individuals. This work shows that repeat expansion in human-specific NOTCH2NLC, a gene that evolved by segmental duplication, causes a human disease.

Read more
April 21, 2020  |  

Copy-number variants in clinical genome sequencing: deployment and interpretation for rare and undiagnosed disease.

Current diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, genome sequencing (GS) can detect all genomic pathogenic variant types on a single platform. Here we evaluate copy-number variant (CNV) calling as part of a clinically accredited GS test.We performed analytical validation of CNV calling on 17 reference samples, compared the sensitivity of GS-based variants with those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis of GS-based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.We found that CNV calls from GS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed, all of which were confirmed by an orthogonal approach. The pipeline also enabled discovery of a uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of select CNVs enabled breakpoint level resolution of genomic rearrangements and phasing of de novo CNVs.Robust identification of CNVs by GS is possible within a clinical testing environment.

Read more
April 21, 2020  |  

Evaluation of the performance of copy number variant prediction tools for the detection of deletions from whole genome sequencing data.

Whole genome sequencing (WGS) has increased in popularity and decreased in cost over the past decade, rendering this approach as a viable and sensitive method for variant detection. In addition to its utility for single nucleotide variant detection, WGS data has the potential to detect Copy Number Variants (CNV) to fine resolution. Many CNV detection software packages have been developed exploiting four main types of data: read pair, split read, read depth, and assembly based methods. The aim of this study was to evaluate the efficiency of each of these main approaches in detecting germline deletions.WGS data and high confidence deletion calls for the individual NA12878 from the Genome in a Bottle consortium were the benchmark dataset. The performance of BreakDancer, CNVnator, Delly, FermiKit, and Pindel was assessed by comparing the accuracy and sensitivity of each software package in detecting deletions exceeding 1?kb.There was considerable variability in the outputs of the different WGS CNV detection programs. The best performance was seen from BreakDancer and Delly, with 92.6% and 96.7% sensitivity, respectively and 34.5% and 68.5% false discovery rate (FDR), respectively. In comparison, Pindel, CNVnator, and FermiKit were less effective with sensitivities of 69.1%, 66.0%, and 15.8%, respectively and FDR of 91.3%, 69.0%, and 31.7%, respectively. Concordance across software packages was poor, with only 27 of the total 612 benchmark deletions identified by all five methodologies.The WGS based CNV detection tools evaluated show disparate performance in identifying deletions =1?kb, particularly those utilising different input data characteristics. Software that exploits read pair based data had the highest sensitivity, namely BreakDancer and Delly. BreakDancer also had the second lowest false discovery rate. Therefore, in this analysis read pair methods (BreakDancer in particular) were the best performing approaches for the identification of deletions =1?kb, balancing accuracy and sensitivity. There is potential for improvement in the detection algorithms, particularly for reducing FDR. This analysis has validated the utility of WGS based CNV detection software to reliably identify deletions, and these findings will be of use when choosing appropriate software for deletion detection, in both research and diagnostic medicine.Copyright © 2019 Elsevier Inc. All rights reserved.

Read more
April 21, 2020  |  

Featherweight long read alignment using partitioned reference indexes.

The advent of Nanopore sequencing has realised portable genomic research and applications. However, state of the art long read aligners and large reference genomes are not compatible with most mobile computing devices due to their high memory requirements. We show how memory requirements can be reduced through parameter optimisation and reference genome partitioning, but highlight the associated limitations and caveats of these approaches. We then demonstrate how these issues can be overcome through an appropriate merging technique. We incorporated multi-index merging into the Minimap2 aligner and demonstrate that long read alignment to the human genome can be performed on a system with 2?GB RAM with negligible impact on accuracy.

Read more
April 21, 2020  |  

Platanus-allee is a de novo haplotype assembler enabling a comprehensive access to divergent heterozygous regions.

The ultimate goal for diploid genome determination is to completely decode homologous chromosomes independently, and several phasing programs from consensus sequences have been developed. These methods work well for lowly heterozygous genomes, but the manifold species have high heterozygosity. Additionally, there are highly divergent regions (HDRs), where the haplotype sequences differ considerably. Because HDRs are likely to direct various interesting biological phenomena, many genomic analysis targets fall within these regions. However, they cannot be accessed by existing phasing methods, and we have to adopt costly traditional methods. Here, we develop a de novo haplotype assembler, Platanus-allee ( http://platanus.bio.titech.ac.jp/platanus2 ), which initially constructs each haplotype sequence and then untangles the assembly graphs utilizing sequence links and synteny information. A comprehensive benchmark analysis reveals that Platanus-allee exhibits high recall and precision, particularly for HDRs. Using this approach, previously unknown HDRs are detected in the human genome, which may uncover novel aspects of genome variability.

Read more
April 21, 2020  |  

Deep convolutional neural networks for accurate somatic mutation detection.

Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different sequencing platforms, sequencing strategies, and tumor purities. NeuSomatic summarizes sequence alignments into small matrices and incorporates more than a hundred features to capture mutation signals effectively. It can be used universally as a stand-alone somatic mutation detection method or with an ensemble of existing methods to achieve the highest accuracy.

Read more
April 21, 2020  |  

Haplotype-aware diplotyping from noisy long reads.

Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.

Read more
April 21, 2020  |  

High-coverage, long-read sequencing of Han Chinese trio reference samples.

Single-molecule long-read sequencing datasets were generated for a son-father-mother trio of Han Chinese descent that is part of the Genome in a Bottle (GIAB) consortium portfolio. The dataset was generated using the Pacific Biosciences Sequel System. The son and each parent were sequenced to an average coverage of 60 and 30, respectively, with N50 subread lengths between 16 and 18?kb. Raw reads and reads aligned to both the GRCh37 and GRCh38 are available at the NCBI GIAB ftp site (ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/ChineseTrio/). The GRCh38 aligned read data are archived in NCBI SRA (SRX4739017, SRX4739121, and SRX4739122). This dataset is available for anyone to develop and evaluate long-read bioinformatics methods.

Read more
April 21, 2020  |  

Tandem-genotypes: robust detection of tandem repeat expansions from long DNA reads.

Tandemly repeated DNA is highly mutable and causes at least 31 diseases, but it is hard to detect pathogenic repeat expansions genome-wide. Here, we report robust detection of human repeat expansions from careful alignments of long but error-prone (PacBio and nanopore) reads to a reference genome. Our method is robust to systematic sequencing errors, inexact repeats with fuzzy boundaries, and low sequencing coverage. By comparing to healthy controls, we prioritize pathogenic expansions within the top 10 out of 700,000 tandem repeats in whole genome sequencing data. This may help to elucidate the many genetic diseases whose causes remain unknown.

Read more
April 21, 2020  |  

Construction of JRG (Japanese reference genome) with single-molecule real-time sequencing

In recent genome analyses, population-specific reference panels have indicated important. However, reference panels based on short-read sequencing data do not sufficiently cover long insertions. Therefore, the nature of long insertions has not been well documented. Here, we assembled a Japanese genome using single-molecule real-time sequencing data and characterized insertions found in the assembled genome. We identified 3691 insertions ranging from 100?bps to ~10,000?bps in the assembled genome relative to the international reference sequence (GRCh38). To validate and characterize these insertions, we mapped short-reads from 1070 Japanese individuals and 728 individuals from eight other populations to insertions integrated into GRCh38. With this result, we constructed JRGv1 (Japanese Reference Genome version 1) by integrating the 903 verified insertions, totaling 1,086,173 bases, shared by at least two Japanese individuals into GRCh38. We also constructed decoyJRGv1 by concatenating 3559 verified insertions, totaling 2,536,870 bases, shared by at least two Japanese individuals or by six other assemblies. This assembly improved the alignment ratio by 0.4% on average. These results demonstrate the importance of refining the reference assembly and creating a population-specific reference genome. JRGv1 and decoyJRGv1 are available at the JRG website.

Read more

Subscribe for blog updates:

Talk with an expert

If you have a question, need to check the status of an order, or are interested in purchasing an instrument, we're here to help.