Dataset Information

NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.

ABSTRACT: BACKGROUND:Advances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance. RESULTS:Here, we present a new tool called NucBreak aimed at localizing structural errors in assemblies, including insertions, deletions, duplications, inversions, and different inter- and intra-chromosomal rearrangements. The approach taken by existing alternative tools is based on analysing reads that do not map properly to the assembly, for instance discordantly mapped reads, soft-clipped reads and singletons. NucBreak uses an entirely different and unique method to localise the errors. It is based on analysing the alignments of reads that are properly mapped to an assembly and exploit information about the alternative read alignments. It does not annotate detected errors. We have compared NucBreak with other existing assembly accuracy assessment tools, namely Pilon, REAPR, and FRCbam as well as with several structural variant detection tools, including BreakDancer, Lumpy, and Wham, by using both simulated and real datasets. CONCLUSIONS:The benchmarking results have shown that NucBreak in general predicts assembly errors of different types and sizes with relatively high sensitivity and with lower false discovery rate than the other tools. Such a balance between sensitivity and false discovery rate makes NucBreak a good alternative to the existing assembly accuracy assessment tools and SV detection tools. NucBreak is freely available at https://github.com/uio-bmi/NucBreak under the MPL license.

SUBMITTER: Khelik K

PROVIDER: S-EPMC7035700 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.

Khelik Ksenia K Sandve Geir Kjetil GK Nederbragt Alexander Johan AJ Rognes Torbjørn T

BMC bioinformatics 20200221 1

<h4>Background</h4>Advances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance.<h4>Results</h4>Here, we present a new tool called NucBreak aimed at localizing structural errors i ...[more]

PMID: 32085722

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Project description:BACKGROUND:Illumina sequencing of a marker gene is popular in metagenomic studies. However, Illumina paired-end (PE) reads sometimes cannot be merged into single reads for subsequent analysis. When mergeable PE reads are limited, one can simply use only first reads for taxonomy annotation, but that wastes information in the second reads. Presumably, including second reads should improve taxonomy annotation. However, a rigorous investigation of how best to do this and how much can be gained has not been reported. RESULTS:We evaluated two methods of joining as opposed to merging PE reads into single reads for taxonomy annotation using simulated data with sequencing errors. Our rigorous evaluation involved several top classifiers (RDP classifier, SINTAX, and two alignment-based methods) and realistic benchmark datasets. For most classifiers, read joining ameliorated the impact of sequencing errors and improved the accuracy of taxonomy predictions. For alignment-based top-hit classifiers, rearranging the reference sequences is recommended to avoid improper alignments of joined reads. For word-counting classifiers, joined reads could be compared to the original reference for classification. We also applied read joining to our own real MiSeq PE data of nasal microbiota of asthmatic children. Before joining, trimming low quality bases was necessary for optimizing taxonomy annotation and sequence clustering. We then showed that read joining increased the amount of effective data for taxonomy annotation. Using these joined trimmed reads, we were able to identify two promising bacterial genera that might be associated with asthma exacerbation. CONCLUSIONS:When mergeable PE reads are limited, joining them into single reads for taxonomy annotation is always recommended. Reference sequences may need to be rearranged accordingly depending on the classifier. Read joining also relaxes the constraint on primer selection, and thus may unleash the full capacity of Illumina PE data for taxonomy annotation. Our work provides guidance for fully utilizing PE data of a marker gene when mergeable reads are limited.

Project description:BackgroundThe seagrass Zostera marina is a monocotyledonous angiosperm belonging to a polyphyletic group of plants that can live submerged in marine habitats. Zostera marina L. is one of the most common seagrasses and is considered a cornerstone of marine plant molecular ecology research and comparative studies. However, the mechanisms underlying its adaptation to the marine environment still remain poorly understood due to limited transcriptomic and genomic data.Principal findingsHere we explored the transcriptome of Z. marina leaves under different environmental conditions using Illumina paired-end sequencing. Approximately 55 million sequencing reads were obtained, representing 58,457 transcripts that correspond to 24,216 unigenes. A total of 14,389 (59.41%) unigenes were annotated by blast searches against the NCBI non-redundant protein database. 45.18% and 46.91% of the unigenes had significant similarity with proteins in the Swiss-Prot database and Pfam database, respectively. Among these, 13,897 unigenes were assigned to 57 Gene Ontology (GO) terms and 4,745 unigenes were identified and mapped to 233 pathways via functional annotation against the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG). We compared the orthologous gene family of the Z. marina transcriptome to Oryza sativa and Pyropia yezoensis and 11,667 orthologous gene families are specific to Z. marina. Furthermore, we identified the photoreceptors sensing red/far-red light and blue light. Also, we identified a large number of genes that are involved in ion transporters and channels including Na+ efflux, K+ uptake, Cl- channels, and H+ pumping.ConclusionsOur study contains an extensive sequencing and gene-annotation analysis of Z. marina. This information represents a genetic resource for the discovery of genes related to light sensing and salt tolerance in this species. Our transcriptome can be further utilized in future studies on molecular adaptation to abiotic stress in Z. marina.

Dataset Information

NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.

Publications

NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.

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