scholarly journals Haplotype-Resolved Assembly for Synthetic Long Reads Using a Trio-Binning Strategy

2020 ◽  
Author(s):  
Mengyang Xu ◽  
Lidong Guo ◽  
Xiao Du ◽  
Lei Li ◽  
Li Deng ◽  
...  
Keyword(s):  
Long Range ◽  
De Novo ◽  
Diploid Species ◽  
Sequencing Data ◽  
Assembly Accuracy ◽  
Long Reads ◽  
Unique Markers ◽  
The Relationship ◽  
Assembly Tool

ABSTRACTThe accuracy and completeness of genome haplotyping are crucial for characterizing the relationship between human disease susceptibility and genetic variations, especially for the heterozygous variations. However, most of current variations are unphased genotypes, and the construction of long-range haplotypes remains challenging. We introduced a de novo haplotype-resolved assembly tool, HAST that exports two haplotypes of a diploid species for synthetic long reads with trio binning. It generates parental distinguishing k-mer libraries, partitions reads from the offspring according to the unique markers, and individually assembles them to resolve the haplotyping problem. Based on the stLFR co-barcoding data of an Asian as well as his parental massive parallel sequencing data, we utilized HAST to recover both haplotypes with a scaffold N50 of >11 Mb and an assembly accuracy of 99.99995% (Q63). The complete and accurate employment of long-range haplotyping information provided sub-chromosome level phase blocks (N50 ∼13 Mb) with 99.6% precision and 94.1% recall on average. We suggest that the accurate and efficient approach accomplishes the regeneration of the haplotype chromosomes with trio binning, thus promoting the determination of haplotype phase, the heterosis of crossbreeding, and the formation of autopolyploid and allopolyploid.

scholarly journals SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lidong Guo ◽  
Mengyang Xu ◽  
Wenchao Wang ◽  
Shengqiang Gu ◽  
Xia Zhao ◽  
...  
Keyword(s):  
High Efficiency ◽  
De Novo ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Draft Assembly ◽  
Screening Algorithm ◽  
Long Reads ◽  
Hybrid Genome ◽  
Genomics Research ◽  
Negative Effect

Abstract Background Synthetic long reads (SLR) with long-range co-barcoding information are now widely applied in genomics research. Although several tools have been developed for each specific SLR technique, a robust standalone scaffolder with high efficiency is warranted for hybrid genome assembly. Results In this work, we developed a standalone scaffolding tool, SLR-superscaffolder, to link together contigs in draft assemblies using co-barcoding and paired-end read information. Our top-to-bottom scheme first builds a global scaffold graph based on Jaccard Similarity to determine the order and orientation of contigs, and then locally improves the scaffolds with the aid of paired-end information. We also exploited a screening algorithm to reduce the negative effect of misassembled contigs in the input assembly. We applied SLR-superscaffolder to a human single tube long fragment read sequencing dataset and increased the scaffold NG50 of its corresponding draft assembly 1349 fold. Moreover, benchmarking on different input contigs showed that this approach overall outperformed existing SLR scaffolders, providing longer contiguity and fewer misassemblies, especially for short contigs assembled by next-generation sequencing data. The open-source code of SLR-superscaffolder is available at https://github.com/BGI-Qingdao/SLR-superscaffolder. Conclusions SLR-superscaffolder can dramatically improve the contiguity of a draft assembly by integrating a hybrid assembly strategy.

Computational Approaches for Transcriptome Assembly Based on Sequencing Technologies

2020 ◽  
Vol 15 (1) ◽  
pp. 2-16
Author(s):  
Yuwen Luo ◽  
Xingyu Liao ◽  
Fang-Xiang Wu ◽  
Jianxin Wang
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Critical Role ◽  
High Sensitivity ◽  
Biological Properties ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Massive Sequencing ◽  
Generation Sequencing

Transcriptome assembly plays a critical role in studying biological properties and examining the expression levels of genomes in specific cells. It is also the basis of many downstream analyses. With the increase of speed and the decrease in cost, massive sequencing data continues to accumulate. A large number of assembly strategies based on different computational methods and experiments have been developed. How to efficiently perform transcriptome assembly with high sensitivity and accuracy becomes a key issue. In this work, the issues with transcriptome assembly are explored based on different sequencing technologies. Specifically, transcriptome assemblies with next-generation sequencing reads are divided into reference-based assemblies and de novo assemblies. The examples of different species are used to illustrate that long reads produced by the third-generation sequencing technologies can cover fulllength transcripts without assemblies. In addition, different transcriptome assemblies using the Hybrid-seq methods and other tools are also summarized. Finally, we discuss the future directions of transcriptome assemblies.

scholarly journals SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme

2019 ◽  
Author(s):  
Lidong Guo ◽  
Mengyang Xu ◽  
Wenchao Wang ◽  
Shengqiang Gu ◽  
Xia Zhao ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Next Generation Sequencing ◽  
Long Range ◽  
De Novo ◽  
Next Generation ◽  
Negative Effects ◽  
Complementary Information ◽  
Screening Algorithm ◽  
Long Reads ◽  
Generation Sequencing

AbstractSynthetic long reads (SLR) with long-range co-barcoding information have been recently developed and widely applied in genomics researches. We proposed a scaffolding model of the co-barcoding information and developed a scaffolding tool with adopting a top-to-bottom scheme to make full use of the complementary information in SLR datasets and a screening algorithm to reduce negative effects from misassembled contigs in an input assembly. In comparison with other available SLR scaffolding tools, our tool obtained the best quality improvement for different input assemblies, especially for those assembled by the next-generation sequencing reads, where the improvement of contiguity is about several hundred-folds.

scholarly journals De novo determination of protein structure by NMR using orientational and long-range order restraints

2000 ◽  
Vol 298 (5) ◽  
pp. 927-936 ◽  
Author(s):  
Jean-Christophe Hus ◽  
Dominique Marion ◽  
Martin Blackledge
Keyword(s):  
Protein Structure ◽  
Long Range ◽  
De Novo ◽  
Range Order ◽  
Long Range Order

scholarly journals Clustering de Novo by Gene of Long Reads from Transcriptomics Data

2017 ◽  
Author(s):  
Camille Marchet ◽  
Lolita Lecompte ◽  
Corinne Da Silva ◽  
Corinne Cruaud ◽  
Jean-Marc Aury ◽  
...  
Keyword(s):  
De Novo ◽  
Free Access ◽  
Sequencing Data ◽  
Base Pairs ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Processing Step ◽  
Whole Transcriptome Sequencing ◽  
Long Read ◽  
Transcriptomics Data

AbstractLong-read sequencing currently provides sequences of several thousand base pairs. This allows to obtain complete transcripts, which offers an un-precedented vision of the cellular transcriptome.However the literature is lacking tools to cluster such data de novo, in particular for Oxford Nanopore Technologies reads, because of the inherent high error rate compared to short reads.Our goal is to process reads from whole transcriptome sequencing data accurately and without a reference genome in order to reliably group reads coming from the same gene. This de novo approach is therefore particularly suitable for non-model species, but can also serve as a useful pre-processing step to improve read mapping. Our contribution is both to propose a new algorithm adapted to clustering of reads by gene and a practical and free access tool that permits to scale the complete processing of eukaryotic transcriptomes.We sequenced a mouse RNA sample using the MinION device, this dataset is used to compare our solution to other algorithms used in the context of biological clustering. We demonstrate its is better-suited for transcriptomics long reads. When a reference is available thus mapping possible, we show that it stands as an alternative method that predicts complementary clusters.

scholarly journals Accurate Haplotype-Resolved Assembly Reveals The Origin Of Structural Variants For Human Trios

2021 ◽  
Author(s):  
Mengyang Xu ◽  
Lidong Guo ◽  
Xiao Du ◽  
Lei Li ◽  
Brock A Peters ◽  
...  
Keyword(s):  
De Novo ◽  
Substantial Improvement ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Homologous Chromosomes ◽  
Assembly Method ◽  
Long Reads ◽  
Long Read ◽  
Second Generation Sequencing ◽  
Generation Sequencing

Abstract Motivation Achieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging. Results To address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to co-barcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling co-barcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read based assembly method (TrioCanu) but with a significantly higher single-base accuracy (up to 99.99997% (Q65)). This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies. Availability The code of the analysis is available at https://github.com/BGI-Qingdao/HAST. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Contamination as a major factor in poor Illumina assembly of microbial isolate genomes

2016 ◽  
Author(s):  
Haeyoung Jeong ◽  
Jae-Goo Pan ◽  
Seung-Hwan Park
Keyword(s):  
Illumina Sequencing ◽  
De Novo ◽  
Repetitive Sequences ◽  
Low Frequency ◽  
Read Depth ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Sequencing Error ◽  
Sequencing Data ◽  
Long Reads

ABSTRACTThe nonhybrid hierarchical assembly of PacBio long reads is becoming the most preferred method for obtaining genomes for microbial isolates. On the other hand, among massive numbers of Illumina sequencing reads produced, there is a slim chance of re-evaluating failed microbial genome assembly (high contig number, large total contig size, and/or the presence of low-depth contigs). We generated Illumina-type test datasets with various levels of sequencing error, pretreatment (trimming and error correction), repetitive sequences, contamination, and ploidy from both simulated and real sequencing data and applied k-mer abundance analysis to quickly detect possible diagnostic signatures of poor assemblies. Contamination was the only factor leading to poor assemblies for the test dataset derived from haploid microbial genomes, resulting in an extraordinary peak within low-frequency k-mer range. When thirteen Illumina sequencing reads of microbes belonging to genera Bacillus or Paenibacillus from a single multiplexed run were subjected to a k-mer abundance analysis, all three samples leading to poor assemblies showed peculiar patterns of contamination. Read depth distribution along the contig length indicated that all problematic assemblies suffered from too many contigs with low average read coverage, where 1% to 15% of total reads were mapped to low-coverage contigs. We found that subsampling or filtering out reads having rare k-mers could efficiently remove low-level contaminants and greatly improve the de novo assemblies. An analysis of 16S rRNA genes recruited from reads or contigs and the application of read classification tools originally designed for metagenome analyses can help identify the source of a contamination. The unexpected presence of proteobacterial reads across multiple samples, which had no relevance to our lab environment, implies that such prevalent contamination might have occurred after the DNA preparation step, probably at the place where sequencing service was provided.

scholarly journals gapFinisher: a reliable gap filling pipeline for SSPACE-LongRead scaffolder output

2017 ◽  
Author(s):  
Juhana I Kammonen ◽  
Olli-Pekka Smolander ◽  
Lars Paulin ◽  
Pedro AB Pereira ◽  
Pia Laine ◽  
...  
Keyword(s):  
De Novo ◽  
Draft Genome ◽  
Sequence Information ◽  
Sequencing Data ◽  
Gap Filling ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Unix Command ◽  
Sequencing Platforms ◽  
Scaffolding Software

Unknown sequences, or gaps, are largely present in most published genomes across public databases. Gap filling is an important finishing step in de novo genome assembly, especially in large genomes. The gap filling problem is nontrivial and while many computational tools exist partially solving the problem, several have shortcomings as to the reliability and correctness of the output, i.e. the gap filled draft genome. SSPACE-LongRead is a scaffolding software that utilizes long reads from multiple third-generation sequencing platforms in finding links between contigs and combining them. The long reads potentially contain sequence information to fill the gaps, but SSPACE-LongRead currently lacks this functionality. We present an automated pipeline called gapFinisher to process SSPACE-LongRead output to fill gaps after the actual scaffolding. gapFinisher is based on controlled use of a gap filling tool called FGAP and works on all standard Linux/UNIX command lines. We conclude that performing the workflows of SSPACE-LongRead and gapFinisher enables users to fill gaps reliably. There is no need for further scrutiny of the existing sequencing data after performing the analysis.

scholarly journals GALA: gap-free chromosome-scale assembly with long reads

2020 ◽  
Author(s):  
Mohamed Awad ◽  
Xiangchao Gan
Keyword(s):  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Genetic Maps ◽  
Sequencing Data ◽  
C Elegans ◽  
Assembly Method ◽  
Long Reads ◽  
Long Read ◽  
Assembly Technology

AbstractHigh-quality genome assembly has wide applications in genetics and medical studies. However, it is still very challenging to achieve gap-free chromosome-scale assemblies using current workflows for long-read platforms. Here we propose GALA (Gap-free long-read assembler), a chromosome-by-chromosome assembly method implemented through a multi-layer computer graph that identifies mis-assemblies within preliminary assemblies or chimeric raw reads and partitions the data into chromosome-scale linkage groups. The subsequent independent assembly of each linkage group generates a gap-free assembly free from the mis-assembly errors which usually hamper existing workflows. This flexible framework also allows us to integrate data from various technologies, such as Hi-C, genetic maps, a reference genome and even motif analyses, to generate gap-free chromosome-scale assemblies. We de novo assembled the C. elegans and A. thaliana genomes using combined Pacbio and Nanopore sequencing data from publicly available datasets. We also demonstrated the new method’s applicability with a gap-free assembly of a human genome with the help a reference genome. In addition, GALA showed promising performance for Pacbio high-fidelity long reads. Thus, our method enables straightforward assembly of genomes with multiple data sources and overcomes barriers that at present restrict the application of de novo genome assembly technology.

scholarly journals New gains with a slimmer genome – An automated approach to improve reference genome assemblies

2020 ◽  
Author(s):  
Mikko Kivikoski ◽  
Pasi Rastas ◽  
Ari Löytynoja ◽  
Juha Merilä
Keyword(s):  
Gasterosteus Aculeatus ◽  
Reference Genome ◽  
De Novo ◽  
Biological Research ◽  
Integrative Approach ◽  
Sequencing Data ◽  
Pungitius Pungitius ◽  
Model Study ◽  
Long Reads ◽  
Genome Assemblies

AbstractThe utility of genome-wide sequencing data in biological research depends heavily on the quality of the reference genome. Although the reference genomes have improved, it is evident that the assemblies could still be refined, especially in non-model study organisms. Here, we describe an integrative approach to improve contiguity and haploidy of a reference genome assembly. With two novel features of Lep-Anchor software and a combination of dense linkage maps, overlap detection and bridging long reads we generated an improved assembly of the nine-spined stickleback (Pungitius pungitius) reference genome. We were able to remove a significant number of haplotypic contigs, detect more genetic variation and improve the contiguity of the genome, especially that of X chromosome. However, improved scaffolding cannot correct for mosaicism of erroneously assembled contigs, demonstrated by a de novo assembly of a 1.7 Mbp inversion. Qualitatively similar gains were obtained with the genome of three-spined stickleback (Gasterosteus aculeatus).

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