scholarly journals Correcting bias from stochastic insert size in read pair data — applications to structural variation detection and genome assembly

2015 ◽  
Author(s):  
Kristoffer Sahlin ◽  
Mattias Frånberg ◽  
Lars Arvestad
Keyword(s):  
Size Distribution ◽  
Genome Assembly ◽  
Structural Variation ◽  
De Novo ◽  
State Of The Art ◽  
Size Distributions ◽  
Insert Size ◽  
Genome Assemblies ◽  
Paired Read ◽  
Insert Size Distribution

Insert size distributions from paired read protocols are used for inference in bioinformatic applications such as genome assembly and structural variation detection. However, many of the models that are being used are subject to bias. This bias arises when we assume that all insert sizes within a distribution are equally likely to be observed, when in fact, size matters. These systematic errors exist in popular software even when the assumptions made about data are true. We have previously shown that bias occurs for scaffolders in genome assembly. Here, we generalize the theory and demonstrate that it is applicable in other contexts. We provide examples of bias in state-of the-art software and improve them using our model. One key application of our theory is structural variation detection using read pairs. We show that an incorrect null-hypothesis is commonly used in popular tools and can be corrected using our theory. Furthermore, we approximate the smallest size of indels that are possible to discover given an insert size distribution. Two other applications are inference of insert size distribution on \emph{de novo} genome assemblies and error correction of genome assemblies using mated reads. Our theory is implemented in a tool called GetDistr (\url{https://github.com/ksahlin/GetDistr}).

scholarly journals A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome

2021 ◽  
Author(s):  
Seyoung Mun ◽  
Songmi Kim ◽  
Wooseok Lee ◽  
Keunsoo Kang ◽  
Thomas J. Meyer ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Genome Assembly ◽  
De Novo ◽  
Personal Genome ◽  
Human Populations ◽  
Whole Genome ◽  
Structural Variations ◽  
Insert Size ◽  
Human Genomes ◽  
Next Generation Sequencing Ngs

AbstractAdvances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE–TE recombination-mediated deletion. In this study, we carried out de novo whole-genome sequencing of one Korean individual (KPGP9) via multiple insert-size libraries. The de novo whole-genome assembly resulted in 31,305 scaffolds with a scaffold N50 size of 13.23 Mb. Furthermore, through computational data analysis and experimental verification, we revealed that 182 TE-associated structural variation (TASV) insertions and 89 TASV deletions contributed 64,232 bp in sequence gain and 82,772 bp in sequence loss, respectively, in the KPGP9 genome relative to the hg19 reference genome. We also verified structural differences associated with TASVs by comparative analysis with TASVs in recent genomes (AK1 and TCGA genomes) and reported their details. Here, we constructed a new Korean de novo whole-genome assembly and provide the first study, to our knowledge, focused on the identification of TASVs in an individual Korean genome. Our findings again highlight the role of TEs as a major driver of structural variations in human individual genomes.

scholarly journals Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird-of-paradise

2019 ◽  
Author(s):  
Valentina Peona ◽  
Mozes P.K. Blom ◽  
Luohao Xu ◽  
Reto Burri ◽  
Shawn Sullivan ◽  
...  
Keyword(s):  
Dark Matter ◽  
Genome Assembly ◽  
Sex Chromosome ◽  
De Novo ◽  
Model Organism ◽  
Technology Choice ◽  
High Quality ◽  
Sequencing Technologies ◽  
Downstream Analysis ◽  
Genome Assemblies

AbstractGenome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies have opened up a whole new world of genomic biodiversity. Although these technologies generate high-quality genome assemblies, there are still genomic regions difficult to assemble, like repetitive elements and GC-rich regions (genomic “dark matter”). In this study, we compare the efficiency of currently used sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter starting from the same sample. By adopting different de-novo assembly strategies, we were able to compare each individual draft assembly to a curated multiplatform one and identify the nature of the previously missing dark matter with a particular focus on transposable elements, multi-copy MHC genes, and GC-rich regions. Thanks to this multiplatform approach, we demonstrate the feasibility of producing a high-quality chromosome-level assembly for a non-model organism (paradise crow) for which only suboptimal samples are available. Our approach was able to reconstruct complex chromosomes like the repeat-rich W sex chromosome and several GC-rich microchromosomes. Telomere-to-telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects around the completeness of both the coding and non-coding parts of the genomes.

scholarly journals dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Gokhan Yavas ◽  
Huixiao Hong ◽  
Wenming Xiao
Keyword(s):  
Quality Assessment ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Quality Score ◽  
De Novo Genome Assembly ◽  
Genome Assemblies ◽  
Reference Genomes ◽  
Better Than

Abstract Background Accurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly. Results To address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies. Conclusions The dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

scholarly journals A high-quality genome assembly from a single, field-collected spotted lanternfly (Lycorma delicatula) using the PacBio Sequel II system

GigaScience ◽  
2019 ◽  
Vol 8 (10) ◽  
Author(s):  
Sarah B Kingan ◽  
Julie Urban ◽  
Christine C Lambert ◽  
Primo Baybayan ◽  
Anna K Childers ◽  
...  
Keyword(s):  
Invasive Species ◽  
Genome Assembly ◽  
De Novo ◽  
Fragment Size ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Lycorma Delicatula ◽  
Long Read ◽  
Genome Assemblies ◽  
High Quality Genome

ABSTRACT Background A high-quality reference genome is an essential tool for applied and basic research on arthropods. Long-read sequencing technologies may be used to generate more complete and contiguous genome assemblies than alternate technologies; however, long-read methods have historically had greater input DNA requirements and higher costs than next-generation sequencing, which are barriers to their use on many samples. Here, we present a 2.3 Gb de novo genome assembly of a field-collected adult female spotted lanternfly (Lycorma delicatula) using a single Pacific Biosciences SMRT Cell. The spotted lanternfly is an invasive species recently discovered in the northeastern United States that threatens to damage economically important crop plants in the region. Results The DNA from 1 individual was used to make 1 standard, size-selected library with an average DNA fragment size of ∼20 kb. The library was run on 1 Sequel II SMRT Cell 8M, generating a total of 132 Gb of long-read sequences, of which 82 Gb were from unique library molecules, representing ∼36× coverage of the genome. The assembly had high contiguity (contig N50 length = 1.5 Mb), completeness, and sequence level accuracy as estimated by conserved gene set analysis (96.8% of conserved genes both complete and without frame shift errors). Furthermore, it was possible to segregate more than half of the diploid genome into the 2 separate haplotypes. The assembly also recovered 2 microbial symbiont genomes known to be associated with L. delicatula, each microbial genome being assembled into a single contig. Conclusions We demonstrate that field-collected arthropods can be used for the rapid generation of high-quality genome assemblies, an attractive approach for projects on emerging invasive species, disease vectors, or conservation efforts of endangered species.

scholarly journals PaKman: Scalable Assembly of Large Genomes on Distributed Memory Machines

2019 ◽  
Author(s):  
Priyanka Ghosh ◽  
Sriram Krishnamoorthy ◽  
Ananth Kalyanaraman
Keyword(s):  
Genome Assembly ◽  
Large Scale ◽  
Distributed Memory ◽  
High Throughput Sequencing ◽  
De Novo ◽  
State Of The Art ◽  
Fundamental Problem ◽  
Parallel Computer ◽  
Assembly Process ◽  
Data Movement

AbstractDe novo genome assembly is a fundamental problem in the field of bioinformatics, that aims to assemble the DNA sequence of an unknown genome from numerous short DNA fragments (aka reads) obtained from it. With the advent of high-throughput sequencing technologies, billions of reads can be generated in a matter of hours, necessitating efficient parallelization of the assembly process. While multiple parallel solutions have been proposed in the past, conducting a large-scale assembly at scale remains a challenging problem because of the inherent complexities associated with data movement, and irregular access footprints of memory and I/O operations. In this paper, we present a novel algorithm, called PaKman, to address the problem of performing large-scale genome assemblies on a distributed memory parallel computer. Our approach focuses on improving performance through a combination of novel data structures and algorithmic strategies for reducing the communication and I/O footprint during the assembly process. PaKman presents a solution for the two most time-consuming phases in the full genome assembly pipeline, namely, k-mer counting and contig generation.A key aspect of our algorithm is its graph data structure, which comprises fat nodes (or what we call “macro-nodes”) that reduce the communication burden during contig generation. We present an extensive performance and qualitative evaluation of our algorithm, including comparisons to other state-of-the-art parallel assemblers. Our results demonstrate the ability to achieve near-linear speedups on up to 8K cores (tested); outperform state-of-the-art distributed memory and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly. For instance, PaKman is able to generate a high-quality set of assembled contigs for complex genomes such as the human and wheat genomes in a matter of minutes on 8K cores.

scholarly journals Overlap graph-based generation of haplotigs for diploids and polyploids

2018 ◽  
Author(s):  
Jasmijn A. Baaijens ◽  
Alexander Schönhuth
Keyword(s):  
Recent Work ◽  
Genome Assembly ◽  
De Novo ◽  
Iterative Scheme ◽  
State Of The Art ◽  
Simulated Data ◽  
Specific Sequence ◽  
New Approach ◽  
Link Type ◽  
Polyploid Genome

AbstractHaplotype aware genome assembly plays an important role in genetics, medicine, and various other disciplines, yet generation of haplotype-resolved de novo assemblies remains a major challenge. Beyond distinguishing between errors and true sequential variants, one needs to assign the true variants to the different genome copies. Recent work has pointed out that the enormous quantities of traditional NGS read data have been greatly underexploited in terms of haplotig computation so far, which reflects that methodology for reference independent haplotig computation has not yet reached maturity. We present POLYTE (POLYploid genome fitTEr) as a new approach to de novo generation of haplotigs for diploid and polyploid genomes. Our method follows an iterative scheme where in each iteration reads or contigs are joined, based on their interplay in terms of an underlying haplotype-aware overlap graph. Along the iterations, contigs grow while preserving their haplotype identity. Benchmarking experiments on both real and simulated data demonstrate that POLYTE establishes new standards in terms of error-free reconstruction of haplotype-specific sequence. As a consequence, POLYTE outperforms state-of-the-art approaches in various relevant aspects, where advantages become particularly distinct in polyploid settings. POLYTE is freely available as part of the HaploConduct package at https://github.com/HaploConduct/HaploConduct, implemented in Python and C++.

scholarly journals Metassembler: Merging and optimizing de novo genome assemblies

2015 ◽  
Author(s):  
Alejandro Hernandez Wences ◽  
Michael Schatz
Keyword(s):  
Open Source ◽  
Genome Assembly ◽  
De Novo ◽  
A Genome ◽  
Genome Assemblies ◽  
Multiple Algorithms

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. We apply it to the four genomes from the Assemblathon competitions and show it consistently and substantially improves the contiguity and quality of each assembly. We also develop guidelines for metassembly by systematically evaluating 120 permutations of merging the top 5 assemblies of the first Assemblathon competition. The software is open-source at http://metassembler.sourceforge.net.

scholarly journals LongStitch: High-quality genome assembly correction and scaffolding using long reads

2021 ◽  
Author(s):  
Lauren Coombe ◽  
Janet X Li ◽  
Theodora Lo ◽  
Johnathan Wong ◽  
Vladimir Nikolic ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Draft Genome ◽  
Model Organisms ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Long Reads ◽  
Long Read ◽  
Genomic Regions ◽  
Genome Assemblies

Background Generating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads. Results LongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 2.0-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently runs in under five hours using less than 23GB of RAM. Conclusions Due to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch.

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