scholarly journals Aquila_stLFR: assembly based variant calling package for stLFR and hybrid assembly for linked-reads

2019 ◽  
Author(s):  
Xin Zhou ◽  
Lu Zhang ◽  
Xiaodong Fang ◽  
Yichen Liu ◽  
David L. Dill ◽  
...  
Keyword(s):  
De Novo ◽  
Low Cost ◽  
Variant Calling ◽  
Hybrid Assembly ◽  
Structural Variants ◽  
Sequencing Data ◽  
Single Tube ◽  
Large Numbers ◽  
Key Characteristics ◽  
Hybrid Assemblies

AbstractHuman diploid genome assembly enables identifying maternal and paternal genetic variations. Algorithms based on 10x linked-read sequencing have been developed for de novo assembly, variant calling and haplotyping. Another linked-read technology, single tube long fragment read (stLFR), has recently provided a low-cost single tube solution that can enable long fragment data. However, no existing software is available for human diploid assembly and variant calls. We develop Aquila stLFR to adapt to the key characteristics of stLFR. Aquila stLFR assembles near perfect diploid assembled contigs, and the assembly-based variant calling shows that Aquila stLFR detects large numbers of structural variants which were not easily spanned by Illumina short-reads. Furthermore, the hybrid assembly mode Aquila hybrid allows a hybrid assembly based on both stLFR and 10x linked-reads libraries, demonstrating that these two technologies can always be complementary to each other for assembly to improve contiguity and the variants detection, regardless of assembly quality of the library itself from single sequencing technology. The overlapped structural variants (SVs) from two independent sequencing data of the same individual, and the SVs from hybrid assemblies provide us a high-confidence profile to study them.AvailabilitySource code and documentation are available on https://github.com/maiziex/Aquila_stLFR.

scholarly journals Efficient long single molecule sequencing for cost effective and accurate sequencing, haplotyping, and de novo assembly

2018 ◽  
Author(s):  
Ou Wang ◽  
Robert Chin ◽  
Xiaofang Cheng ◽  
Michelle Ka Wu ◽  
Qing Mao ◽  
...  
Keyword(s):  
Single Molecule ◽  
Genome Assembly ◽  
De Novo ◽  
Low Cost ◽  
Variant Calling ◽  
Cost Effective ◽  
High Quality ◽  
Single Molecule Sequencing ◽  
Single Tube ◽  
Complex Structural

Obtaining accurate sequences from long DNA molecules is very important for genome assembly and other applications. Here we describe single tube long fragment read (stLFR), a technology that enables this a low cost. It is based on adding the same barcode sequence to sub-fragments of the original long DNA molecule (DNA co-barcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process up to 3.6 billion unique barcode sequences were generated on beads, enabling practically non-redundant co-barcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique co-barcoding of over 8 million 20-300 kb genomic DNA fragments. Analysis of the genome of the human genome NA12878 with stLFR demonstrated high quality variant calling and phasing into contigs up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries and their construction did not significantly add to the time or cost of whole genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

scholarly journals CompStor Novos: a low cost yet fast assembly-based variant calling for personal genomes

2018 ◽  
Author(s):  
Travis Oenning ◽  
Taejeong Bae ◽  
Aravind Iyengar ◽  
Barrett Brickner ◽  
Madushanka Soysa ◽  
...  
Keyword(s):  
De Novo ◽  
Low Cost ◽  
Variant Calling ◽  
Computation Time ◽  
Next Generation Sequencing Data ◽  
Personal Genome ◽  
Sequencing Data ◽  
Commercial Off The Shelf ◽  
Genome Analyses ◽  
Assembly Algorithms

Application of assembly methods for personal genome analysis from next generation sequencing data has been limited by the requirement for an expensive supercomputer hardware or long computation times when using ordinary resources. We describe CompStor Novos, achieving supercomputer-class performance in de novo assembly computation time on standard server hardware, based on a tiered-memory algorithm. Run on commercial off-the-shelf servers, Novos assembly is more precise and 10-20 times faster than that of existing assembly algorithms. Furthermore, we integrated Novos into a variant calling pipeline and demonstrate that both compute times and precision of calling point variants and indels compare well with standard alignment-based pipelines. Additionally, assembly eliminates bias in the estimation of allele frequency for indels and naturally enables discovery of breakpoints for structural variants with base pair resolution. Thus, Novos bridges the gap between alignment-based and assembly-based genome analyses. Extension and adaption of its underlying algorithm will help quickly and fully harvest information in sequencing reads for personal genome reconstruction.

scholarly journals A unified haplotype-based method for accurate and comprehensive variant calling

2018 ◽  
Author(s):  
Daniel P Cooke ◽  
David C Wedge ◽  
Gerton Lunter
Keyword(s):  
De Novo ◽  
Variant Calling ◽  
Normal Sample ◽  
Sequencing Data ◽  
Somatic Variation ◽  
Data Set ◽  
Small Complex ◽  
Physical Linkage ◽  
Germline Variation ◽  
Almost All

Haplotype-based variant callers, which consider physical linkage between variant sites, are currently among the best tools for germline variation discovery and genotyping from short-read sequencing data. However, almost all such tools were designed specifically for detecting common germline variation in diploid populations, and give sub-optimal results in other scenarios. Here we present Octopus, a versatile haplotype-based variant caller that uses a polymorphic Bayesian genotyping model capable of modeling sequencing data from a range of experimental designs within a unified haplotype-aware framework. We show that Octopus accurately calls de novo mutations in parent-offspring trios and germline variants in individuals, including SNVs, indels, and small complex replacements such as microinversions. In addition, using a carefully designed synthetic-tumour data set derived from clean sequencing data from a sample with known germline haplotypes, and observed mutations in large cohort of tumour samples, we show that Octopus accurately characterizes germline and somatic variation in tumours, both with and without a paired normal sample. Sequencing reads and prior information are combined to phase called genotypes of arbitrary ploidy, including those with somatic mutations. Octopus also outputs realigned evidence BAMs to aid validation and interpretation.

scholarly journals Trio deep-sequencing does not reveal unexpected off-target and on-target mutations in Cas9-edited rhesus monkeys

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Xin Luo ◽  
Yaoxi He ◽  
Chao Zhang ◽  
Xiechao He ◽  
Lanzhen Yan ◽  
...  
Keyword(s):  
Rhesus Monkeys ◽  
De Novo ◽  
Preclinical Model ◽  
Structural Variants ◽  
Sequencing Data ◽  
De Novo Mutations ◽  
Target Region ◽  
Long Read ◽  
Target Effect

AbstractCRISPR-Cas9 is a widely-used genome editing tool, but its off-target effect and on-target complex mutations remain a concern, especially in view of future clinical applications. Non-human primates (NHPs) share close genetic and physiological similarities with humans, making them an ideal preclinical model for developing Cas9-based therapies. However, to our knowledge no comprehensive in vivo off-target and on-target assessment has been conducted in NHPs. Here, we perform whole genome trio sequencing of Cas9-treated rhesus monkeys. We only find a small number of de novo mutations that can be explained by expected spontaneous mutations, and no unexpected off-target mutations (OTMs) were detected. Furthermore, the long-read sequencing data does not detect large structural variants in the target region.

scholarly journals SvABA: Genome-wide detection of structural variants and indels by local assembly

2017 ◽  
Author(s):  
Jeremiah Wala ◽  
Pratiti Bandopadhayay ◽  
Noah Greenwald ◽  
Ryan O’Rourke ◽  
Ted Sharpe ◽  
...  
Keyword(s):  
Variant Calling ◽  
Accurate Method ◽  
Structural Variants ◽  
Sequencing Data ◽  
Cancer Driver ◽  
Insertion And Deletion ◽  
Genome Wide ◽  
Cancer Genomes ◽  
Local Assembly ◽  
Genomic Regions

AbstractStructural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at-scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA’s performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs, and substantially improved detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (< 1,000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types, and found that templated-sequence insertions occur in ~4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized SVs.

scholarly journals Rapid low-cost assembly of the Drosophila melanogaster reference genome using low-coverage, long-read sequencing

2018 ◽  
Author(s):  
Edwin A. Solares ◽  
Mahul Chakraborty ◽  
Danny E. Miller ◽  
Shannon Kalsow ◽  
Kate Hall ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Genetic Variation ◽  
Large Scale ◽  
Reference Genome ◽  
De Novo ◽  
Low Cost ◽  
Nucleotide Polymorphisms ◽  
Structural Variants ◽  
High Coverage ◽  
Reference Assembly

ABSTRACTAccurate and comprehensive characterization of genetic variation is essential for deciphering the genetic basis of diseases and other phenotypes. A vast amount of genetic variation stems from large-scale sequence changes arising from the duplication, deletion, inversion, and translocation of sequences. In the past 10 years, high-throughput short reads have greatly expanded our ability to assay sequence variation due to single nucleotide polymorphisms. However, a recent de novo assembly of a second Drosophila melanogaster reference genome has revealed that short read genotyping methods miss hundreds of structural variants, including those affecting phenotypes. While genomes assembled using high-coverage long reads can achieve high levels of contiguity and completeness, concerns about cost, errors, and low yield have limited widespread adoption of such sequencing approaches. Here we resequenced the reference strain of D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for 24 hours. Using only reads longer than 1 kb or with at least 30x coverage, we assembled a highly contiguous de novo genome. The addition of inexpensive paired reads and subsequent scaffolding using an optical map technology achieved an assembly with completeness and contiguity comparable to the D. melanogaster reference assembly. Comparison of our assembly to the reference assembly of ISO1 uncovered a number of structural variants (SVs), including novel LTR transposable element insertions and duplications affecting genes with developmental, behavioral, and metabolic functions. Collectively, these SVs provide a snapshot of the dynamics of genome evolution. Furthermore, our assembly and comparison to the D. melanogaster reference genome demonstrates that high-quality de novo assembly of reference genomes and comprehensive variant discovery using such assemblies are now possible by a single lab for under $1,000 (USD).

scholarly journals DeNovoCNN: A deep learning approach to de novo variant calling in next generation sequencing data

2021 ◽  
Author(s):  
Gelana Khazeeva ◽  
Karolis Sablauskas ◽  
Bart van der Sanden ◽  
Wouter Steyaert ◽  
Michael Kwint ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
De Novo ◽  
Genetic Disorders ◽  
Variant Calling ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Accurate Identification ◽  
Whole Exome ◽  
De Novo Variant ◽  
Generation Sequencing

De novo mutations (DNMs) are an important cause of genetic disorders. The accurate identification of DNMs from sequencing data is therefore fundamental to rare disease research and diagnostics. Unfortunately, identifying reliable DNMs remains a major challenge due to sequence errors, uneven coverage, and mapping artifacts. Here, we developed a deep convolutional neural network (CNN) DNM caller (DeNovoCNN), that encodes alignment of sequence reads for a trio as 160×164 resolution images. DeNovoCNN was trained on DNMs of whole exome sequencing (WES) of 2003 trios achieving on average 99.2% recall and 93.8% precision. We find that DeNovoCNN has increased recall/sensitivity and precision compared to existing de novo calling approaches (GATK, DeNovoGear, Samtools) based on the Genome in a Bottle reference dataset. Sanger validations of DNMs called in both exome and genome datasets confirm that DeNovoCNN outperforms existing methods. Most importantly, we show that DeNovoCNN is robust against different exome sequencing and analyses approaches, thereby allowing it to be applied on other datasets. DeNovoCNN is freely available and can be run on existing alignment (BAM/CRAM) and variant calling (VCF) files from WES and WGS without a need for variant recalling.

scholarly journals Ultra-low input single tube linked-read library method enables short-read NGS systems to generate highly accurate and economical long-range sequencing information for de novo genome assembly and haplotype phasing

2019 ◽  
Author(s):  
Zhoutao Chen ◽  
Long Pham ◽  
Tsai-Chin Wu ◽  
Guoya Mo ◽  
Yu Xia ◽  
...  
Keyword(s):  
Long Range ◽  
De Novo ◽  
Low Cost ◽  
Cost Effective ◽  
De Novo Genome Assembly ◽  
Short Read ◽  
Single Tube ◽  
Haplotype Phasing ◽  
A Genome ◽  
Long Read

AbstractLong-range sequencing information is required for haplotype phasing, de novo assembly and structural variation detection. Current long-read sequencing technologies can provide valuable long-range information but at a high cost with low accuracy and high DNA input requirement. We have developed a single-tube Transposase Enzyme Linked Long-read Sequencing (TELL-Seq™) technology, which enables a low-cost, high-accuracy and high-throughput short-read next generation sequencer to routinely generate over 100 Kb long-range sequencing information with as little as 0.1 ng input material. In a PCR tube, millions of clonally barcoded beads are used to uniquely barcode long DNA molecules in an open bulk reaction without dilution and compartmentation. The barcode linked reads are used to successfully assemble genomes ranging from microbes to human. These linked-reads also generate mega-base-long phased blocks and provide a cost-effective tool for detecting structural variants in a genome, which are important to identify compound heterozygosity in recessive Mendelian diseases and discover genetic drivers and diagnostic biomarkers in cancers.

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 Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
D. N. U. Naranpanawa ◽  
C. H. W. M. R. B. Chandrasekara ◽  
P. C. G. Bandaranayake ◽  
A. U. Bandaranayake
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Transcriptome Assembly ◽  
Low Cost ◽  
Santalum Album ◽  
Sequencing Data ◽  
Illumina Hiseq ◽  
Tissue Samples ◽  
Downstream Analysis ◽  
Bioinformatics Workflow

Abstract Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.

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