scholarly journals OMGS: Optical Map-based Genome Scaffolding

2019 ◽  
Author(s):  
Weihua Pan ◽  
Tao Jiang ◽  
Stefano Lonardi
Keyword(s):  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Optimization Problems ◽  
Sequence Assembly ◽  
Genome Scaffolding ◽  
Contig Sequence ◽  
Optical Map ◽  
Linkage Information ◽  
Optical Maps

AbstractDue to the current limitations of sequencing technologies,de novogenome assembly is typically carried out in two stages, namely contig (sequence) assembly and scaffolding. While scaffolding is computationally easier than sequence assembly, the scaffolding problem can be challenging due to the high repetitive content of eukaryotic genomes, possible mis-joins in assembled contigs and inaccuracies in the linkage information. Genome scaffolding tools either use paired-end/mate-pair/linked/Hi-C reads or genome-wide maps (optical, physical or genetic) as linkage information. Optical maps (in particular Bionano Genomics maps) have been extensively used in many recent large-scale genome assembly projects (e.g., goat, apple, barley, maize, quinoa, sea bass, among others). However, the most commonly used scaffolding tools have a serious limitation: they can only deal with one optical map at a time, forcing users to alternate or iterate over multiple maps. In this paper, we introduce a novel scaffolding algorithm called OMGS that for the first time can take advantages of multiple optical maps. OMGS solves several optimization problems to generate scaffolds with optimal contiguity and correctness. Extensive experimental results demonstrate that our tool outperforms existing methods when multiple optical maps are available, and produces comparable scaffolds using a single optical map. OMGS can be obtained fromhttps://github.com/ucrbioinfo/OMGS

scholarly journals Accurate long-read de novo assembly evaluation with Inspector

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yu Chen ◽  
Yixin Zhang ◽  
Amy Y. Wang ◽  
Min Gao ◽  
Zechen Chong
Keyword(s):  
Genome Assembly ◽  
De Novo Assembly ◽  
In Silico ◽  
Large Scale ◽  
De Novo ◽  
Small Scale ◽  
De Novo Genome Assembly ◽  
Consensus Sequences ◽  
Assembly Evaluation ◽  
Long Read

AbstractLong-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

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 A chromosome-level assembly of the Atlantic herring – detection of a supergene and other signals of selection

2019 ◽  
Author(s):  
Mats E. Pettersson ◽  
Christina M. Rochus ◽  
Fan Han ◽  
Junfeng Chen ◽  
Jason Hill ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Hybrid Approach ◽  
Ecological Adaptation ◽  
Atlantic Herring ◽  
Total Size ◽  
Bony Fishes ◽  
Chromosome Level

ABSTRACTThe Atlantic herring is a model species for exploring the genetic basis for ecological adaptation, due to its huge population size and extremely low genetic differentiation at selectively neutral loci. However, such studies have so far been hampered because of a highly fragmented genome assembly. Here, we deliver a chromosome-level genome assembly based on a hybrid approach combining ade novoPacBio assembly with Hi-C-supported scaffolding. The assembly comprises 26 autosomes with sizes ranging from 12.4 to 33.1 Mb and a total size, in chromosomes, of 726 Mb. The development of a high-resolution linkage map confirmed the global chromosome organization and the linear order of genomic segments along the chromosomes. A comparison between the herring genome assembly with other high-quality assemblies from bony fishes revealed few interchromosomal but frequent intrachromosomal rearrangements. The improved assembly makes the analysis of previously intractable large-scale structural variation more feasible; allowing, for example, the detection of a 7.8 Mb inversion on chromosome 12 underlying ecological adaptation. This supergene shows strong genetic differentiation between populations from the northern and southern parts of the species distribution. The chromosome-based assembly also markedly improves the interpretation of previously detected signals of selection, allowing us to reveal hundreds of independent loci associated with ecological adaptation in the Atlantic herring.

scholarly journals A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds

2018 ◽  
Author(s):  
Andreas Wallberg ◽  
Ignas Bunikis ◽  
Olga Vinnere Pettersson ◽  
Mai-Britt Mosbech ◽  
Anna K. Childers ◽  
...  
Keyword(s):  
Apis Mellifera ◽  
Genome Assembly ◽  
De Novo ◽  
Hybrid Approach ◽  
Chromosome Length ◽  
Chromatin Interaction ◽  
De Novo Genome Assembly ◽  
Functional Genetic Variation ◽  
Linkage Information ◽  
Interaction Map

AbstractBackgroundThe ability to generate long sequencing reads and access long-range linkage information is revolutionizing the quality and completeness of genome assemblies. Here we use a hybrid approach that combines data from four genome sequencing and mapping technologies to generate a new genome assembly of the honeybee Apis mellifera. We first generated contigs based on PacBio sequencing libraries, which were then merged with linked-read 10x Chromium data followed by scaffolding using a BioNano optical genome map and a Hi-C chromatin interaction map, complemented by a genetic linkage map.ResultsEach of the assembly steps reduced the number of gaps and incorporated a substantial amount of additional sequence into scaffolds. The new assembly (Amel_HAv3) is significantly more contiguous and complete than the previous one (Amel_4.5), based mainly on Sanger sequencing reads. N50 of contigs is 120-fold higher (5.381 Mbp compared to 0.053 Mbp) and we anchor >98% of the sequence to chromosomes. All of the 16 chromosomes are represented as single scaffolds with an average of three sequence gaps per chromosome. The improvements are largely due to the inclusion of repetitive sequence that was unplaced in previous assemblies. In particular, our assembly is highly contiguous across centromeres and telomeres and includes hundreds of AvaI and AluI repeats associated with these features.ConclusionsThe improved assembly will be of utility for refining gene models, studying genome function, mapping functional genetic variation, identification of structural variants, and comparative genomics.

scholarly journals A contiguous de novo genome assembly of sugar beet EL10 (Beta vulgaris L.)

2020 ◽  
Author(s):  
J. Mitchell (Mitch) McGrath ◽  
Andrew Funk ◽  
Paul Galewski ◽  
Shujun Ou ◽  
Belinda Townsend ◽  
...  
Keyword(s):  
Sugar Beet ◽  
Beta Vulgaris ◽  
Genome Assembly ◽  
Copy Number ◽  
Large Scale ◽  
De Novo ◽  
Gene Annotation ◽  
Gene Copy ◽  
De Novo Genome Assembly ◽  
Short Read

AbstractA contiguous assembly of the inbred ‘EL10’ sugar beet (Beta vulgaris ssp. vulgaris) genome was constructed using PacBio long read sequencing, BioNano optical mapping, Hi-C scaffolding, and Illumina short read error correction. The EL10.1 assembly was 540 Mb, of which 96.7% was contained in nine chromosome-sized pseudomolecules with lengths from 52 to 65 Mb, and 31 contigs with a median size of 282 kb that remained unassembled. Gene annotation incorporating RNAseq data and curated sequences via the MAKER annotation pipeline generated 24,255 gene models. Results indicated that the EL10.1 genome assembly is a contiguous genome assembly highly congruent with the published sugar beet reference genome. Gross duplicate gene analyses of EL10.1 revealed little large-scale intra-genome duplication. Reduced gene copy number for well-annotated gene families relative to other core eudicots was observed, especially for transcription factors. Variation in genome size in B. vulgaris was investigated by flow cytometry among 50 individuals drawn from EL10 progeny and three unrelated germplasm accessions, producing estimates from 633 to 875 Mb/1C. Read depth mapping with short-read whole genome sequences from other sugar beet germplasm suggested that relatively few regions of the sugar beet genome appeared associated with high-copy number variation.

scholarly journals De novo Nanopore read quality improvement using deep learning

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang
Keyword(s):  
Error Correction ◽  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Error Rates ◽  
De Novo Genome Assembly ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Read Error Correction

Abstract Background Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. Results Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. Conclusions MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub.

scholarly journals MiniScrub: de novo long read scrubbing using approximate alignment and deep learning

2018 ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang
Keyword(s):  
Open Source Software ◽  
Genome Assembly ◽  
Large Scale ◽  
Structural Variation ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Reference Genomes

AbstractLong read sequencing technologies such as Oxford Nanopore can greatly de-crease the complexity of de novo genome assembly and large structural variation iden-tification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. Many methods for resolving these errors require access to reference genomes, high-fidelity short reads, or reference genomes, which are often not available. De novo error correction modules are available, often as part of assembly tools, but large-scale errors still remain in resulting assemblies, motivating further innovation in this area. We developed a novel Convolutional Neu-ral Network (CNN) based method, called MiniScrub, for de novo identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments. MiniScrub first generates read-to-read alignments by MiniMap, then encodes the alignments into images, and finally builds CNN models to predict low-quality segments that could be scrubbed based on a customized quality cutoff. Applying MiniScrub to real world con-trol datasets under several different parameters, we show that it robustly improves read quality. Compared to raw reads, de novo genome assembly with scrubbed reads pro-duces many fewer mis-assemblies and large indel errors. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub

scholarly journals OMACC: an Optical-Map-Assisted Contig Connector for improving de novo genome assembly

2013 ◽  
Vol 7 (Suppl 6) ◽  
pp. S7 ◽  
Author(s):  
Yi-Min Chen ◽  
Chun-Hui Yu ◽  
Chi-Chuan Hwang ◽  
Tsunglin Liu
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
De Novo Genome Assembly ◽  
Optical Map

scholarly journals De novo genome assembly of the marine teleost, Bluefin Trevally (Caranx melampygus)

2021 ◽  
Author(s):  
Brandon D Pickett ◽  
Jessica R Glass ◽  
Perry G Ridge ◽  
John S K Kauwe
Keyword(s):  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Demographic History ◽  
Population Expansion ◽  
Marine Teleost ◽  
Population Demography ◽  
Population Declines ◽  
Effective Population ◽  
De Novo Genome Assembly

Abstract The bluefin trevally, Caranx melampygus, also known as the bluefin kingfish or bluefin jack, is known for its remarkable, bright-blue fins. This marine teleost is a widely-prized sportfish, but few resources have been devoted to the genomics and conservation of this species because it is not targeted by large-scale commercial fisheries. Population declines from recreational and artisanal overfishing have been observed in Hawai‘i, USA, resulting in both an interest in aquaculture and concerns about the long-term conservation of this species. Most research to-date has been performed in Hawai‘i, raising questions about the status of bluefin trevally populations across its Indo-Pacific range. Genomic resources allow for expanded research on stock status, genetic diversity, and population demography. We present a high-quality, 711Mbp nuclear genome assembly of a Hawaiian bluefin trevally from noisy long-reads with a contig NG50 of 1.2Mbp and longest contig length of 8.9Mbp. As measured by single-copy orthologs, the assembly was 95% complete, and the genome is comprised of 16.9% repetitive elements. The assembly was annotated with 33.1K protein-coding genes, 71.4% of which were assigned putative functions, using RNA-seq data from eight tissues from the same individual. This is the first whole-genome assembly published for the carangoid genus Caranx. Using this assembled genome, a multiple sequentially Markovian coalescent model was implemented to assess population demography. Estimates of effective population size suggest population expansion has occurred since the Late Pleistocene. This genome will be a valuable resource for comparative phylogenomic studies of carangoid fishes and will help elucidate demographic history and delineate stock structure for bluefin trevally populations throughout the Indo-Pacific.

scholarly journals Improved de novo Genome Assembly: Linked-Read Sequencing Combined with Optical Mapping Produce a High Quality Mammalian Genome at Relatively Low Cost

2017 ◽  
Author(s):  
DW Mohr ◽  
A Naguib ◽  
NI Weisenfeld ◽  
V Kumar ◽  
P Shah ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Low Cost ◽  
Cost Effective ◽  
Conserved Synteny ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Optical Maps ◽  
Commercial Applications ◽  
Hybrid Scaffolds

AbstractCurrent short-read methods have come to dominate genome sequencing because they are cost-effective, rapid, and accurate. However, short reads are most applicable when data can be aligned to a known reference. Two new methods for de novo assembly are linked-reads and restriction-site labeled optical maps. We combined commercial applications of these technologies for genome assembly of an endangered mammal, the Hawaiian Monk seal.We show that the linked-reads produced with 10X Genomics Chromium chemistry and assembled with Supernova v1.1 software produced scaffolds with an N50 of 22.23 Mbp with the longest individual scaffold of 84.06 Mbp. When combined with Bionano Genomics optical maps using Bionano RefAligner, the scaffold N50 increased to 29.65 Mbp for a total of 170 hybrid scaffolds, the longest of which was 84.78 Mbp. These results were 161X and 215X, respectively, improved over DISCOVAR de novo assemblies. The quality of the scaffolds was assessed using conserved synteny analysis of both the DNA sequence and predicted seal proteins relative to the genomes of humans and other species. We found large blocks of conserved synteny suggesting that the hybrid scaffolds were high quality. An inversion in one scaffold complementary to human chromosome 6 was found and confirmed by optical maps.The complementarity of linked-reads and optical maps is likely to make the production of high quality genomes more routine and economical and, by doing so, significantly improve our understanding of comparative genome biology.

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