Transcriptomics de novo sequencing data of Messastrum gracile SE-MC4 under exponential and stationary growth stages

Abstract Background Due to the complexity of microbial communities, de novo assembly on next generation sequencing data is commonly unable to produce complete microbial genomes. Metagenome assembly binning becomes an essential step that could group the fragmented contigs into clusters to represent microbial genomes based on contigs’ nucleotide compositions and read depths. These features work well on the long contigs, but are not stable for the short ones. Contigs can be linked by sequence overlap (assembly graph) or by the paired-end reads aligned to them (PE graph), where the linked contigs have high chance to be derived from the same clusters. Results We developed METAMVGL, a multi-view graph-based metagenomic contig binning algorithm by integrating both assembly and PE graphs. It could strikingly rescue the short contigs and correct the binning errors from dead ends. METAMVGL learns the two graphs’ weights automatically and predicts the contig labels in a uniform multi-view label propagation framework. In experiments, we observed METAMVGL made use of significantly more high-confidence edges from the combined graph and linked dead ends to the main graph. It also outperformed many state-of-the-art contig binning algorithms, including MaxBin2, MetaBAT2, MyCC, CONCOCT, SolidBin and GraphBin on the metagenomic sequencing data from simulation, two mock communities and Sharon infant fecal samples. Conclusions Our findings demonstrate METAMVGL outstandingly improves the short contig binning and outperforms the other existing contig binning tools on the metagenomic sequencing data from simulation, mock communities and infant fecal samples.

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

BMC Bioinformatics ◽

10.1186/s12859-021-04081-z ◽

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.

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Identification of UBAP1 mutations in juvenile hereditary spastic paraplegia in the 100,000 Genomes Project

European Journal of Human Genetics ◽

10.1038/s41431-020-00720-w ◽

2020 ◽

Vol 28 (12) ◽

pp. 1763-1768

Author(s):

Thomas Bourinaris ◽

◽

Damian Smedley ◽

Valentina Cipriani ◽

Isabella Sheikh ◽

...

Keyword(s):

Hereditary Spastic Paraplegia ◽

De Novo ◽

Age At Onset ◽

Genetic Diagnosis ◽

Spastic Paraplegia ◽

Sequencing Data ◽

Juvenile Form ◽

Pathogenic Variants ◽

Degenerative Disorders ◽

Significant Gene

AbstractHereditary spastic paraplegia (HSP) is a group of heterogeneous inherited degenerative disorders characterized by lower limb spasticity. Fifty percent of HSP patients remain yet genetically undiagnosed. The 100,000 Genomes Project (100KGP) is a large UK-wide initiative to provide genetic diagnosis to previously undiagnosed patients and families with rare conditions. Over 400 HSP families were recruited to the 100KGP. In order to obtain genetic diagnoses, gene-based burden testing was carried out for rare, predicted pathogenic variants using candidate variants from the Exomiser analysis of the genome sequencing data. A significant gene-disease association was identified for UBAP1 and HSP. Three protein truncating variants were identified in 13 patients from 7 families. All patients presented with juvenile form of pure HSP, with median age at onset 10 years, showing autosomal dominant inheritance or de novo occurrence. Additional clinical features included parkinsonism and learning difficulties, but their association with UBAP1 needs to be established.

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Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data

BMC Bioinformatics ◽

10.1186/s12859-017-1927-y ◽

2017 ◽

Vol 18 (1) ◽

Cited By ~ 21

Author(s):

Kosai Al-Nakeeb ◽

Thomas Nordahl Petersen ◽

Thomas Sicheritz-Pontén

Keyword(s):

Mitochondrial Dna ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

De Novo Assembly ◽

De Novo ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data

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ON PREPROCESSING AND ANTISYMMETRY IN DE NOVO PEPTIDE SEQUENCING: IMPROVING EFFICIENCY AND ACCURACY

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720008003503 ◽

2008 ◽

Vol 06 (03) ◽

pp. 467-492 ◽

Cited By ~ 7

Author(s):

KANG NING ◽

NAN YE ◽

HON WAI LEONG

Keyword(s):

Mass Spectrometry ◽

Tandem Mass Spectrometry ◽

Computational Models ◽

De Novo ◽

Noise Removal ◽

Peptide Sequencing ◽

De Novo Sequencing ◽

Tandem Mass ◽

De Novo Peptide Sequencing ◽

De Novo Peptide

Peptide sequencing plays a fundamental role in proteomics. Tandem mass spectrometry, being sensitive and efficient, is one of the most commonly used techniques in peptide sequencing. Many computational models and algorithms have been developed for peptide sequencing using tandem mass spectrometry. In this paper, we investigate general issues in de novo sequencing, and present results that can be used to improve current de novo sequencing algorithms. We propose a general preprocessing scheme that performs binning, pseudo-peak introduction, and noise removal, and present theoretical and experimental analyses on each of the components. Then, we study the antisymmetry problem and current assumptions related to it, and propose a more realistic way to handle the antisymmetry problem based on analysis of some datasets. We integrate our findings on preprocessing and the antisymmetry problem with some current models for peptide sequencing. Experimental results show that our findings help to improve accuracies for de novo sequencing.

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