Dataset Information

Bioinformatic curation and alignment of genotyped hepatitis B virus (HBV) sequence data from the GenBank public database.

ABSTRACT: BACKGROUND:Hepatitis B virus (HBV) DNA sequence data from thousands of samples are present in the public sequence databases. No publicly available, up-to-date, multiple sequence alignments, containing full-length and subgenomic fragments per genotype, are available. Such alignments are useful in many analysis applications, including data-mining and phylogenetic analyses. RESULTS:By issuing a query, all HBV sequence data from the GenBank public database was downloaded (67,893 sequences). Full-length and subgenomic sequences, which were genotyped by the submitters (30,852 sequences), were placed into a multiple sequence alignment, for each genotype (genotype A: 5868 sequences, B: 4630, C: 7820, D: 8300, E: 2043, F: 985, G: 189, H: 108, I: 23), according to the results of offline BLAST searches against a custom reference library of full-length sequences. Further curation was performed to improve the alignment. CONCLUSIONS:The algorithm described in this paper generates, for each of the nine HBV genotypes, multiple sequence alignments, which contain full-length and subgenomic fragments. The alignments can be updated as new sequences become available in the online public sequence databases. The alignments are available at http://hvdr.bioinf.wits.ac.za/alignments.

SUBMITTER: Bell TG

PROVIDER: S-EPMC5084120 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Bioinformatic curation and alignment of genotyped hepatitis B virus (HBV) sequence data from the GenBank public database.

Bell Trevor G TG Yousif Mukhlid M Kramvis Anna A

SpringerPlus 20161028 1

<h4>Background</h4>Hepatitis B virus (HBV) DNA sequence data from thousands of samples are present in the public sequence databases. No publicly available, up-to-date, multiple sequence alignments, containing full-length and subgenomic fragments per genotype, are available. Such alignments are useful in many analysis applications, including data-mining and phylogenetic analyses.<h4>Results</h4>By issuing a query, all HBV sequence data from the GenBank public database was downloaded (67,893 seque ...[more]

PMID: 27843753

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Project description:BackgroundThe DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron.ResultsTo improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. Nine freely available blastn rRNA databases created and maintained with Ribovore are used for checking incoming GenBank submissions and used by the blastn browser interface at NCBI. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8350 taxa.ConclusionRibovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.

Project description:BackgroundAutomated gene-calling is still an error-prone process, particularly for the highly plastic genomes of fungal species. Improvement through quality control and manual curation of gene models is a time-consuming process that requires skilled biologists and is only marginally performed. The wealth of available fungal genomes has not yet been exploited by an automated method that applies quality control of gene models in order to obtain more accurate genome annotations.ResultsWe provide a novel method named alignment-based fungal gene prediction (ABFGP) that is particularly suitable for plastic genomes like those of fungi. It can assess gene models on a gene-by-gene basis making use of informant gene loci. Its performance was benchmarked on 6,965 gene models confirmed by full-length unigenes from ten different fungi. 79.4% of all gene models were correctly predicted by ABFGP. It improves the output of ab initio gene prediction software due to a higher sensitivity and precision for all gene model components. Applicability of the method was shown by revisiting the annotations of six different fungi, using gene loci from up to 29 fungal genomes as informants. Between 7,231 and 8,337 genes were assessed by ABFGP and for each genome between 1,724 and 3,505 gene model revisions were proposed. The reliability of the proposed gene models is assessed by an a posteriori introspection procedure of each intron and exon in the multiple gene model alignment. The total number and type of proposed gene model revisions in the six fungal genomes is correlated to the quality of the genome assembly, and to sequencing strategies used in the sequencing centre, highlighting different types of errors in different annotation pipelines. The ABFGP method is particularly successful in discovering sequence errors and/or disruptive mutations causing truncated and erroneous gene models.ConclusionsThe ABFGP method is an accurate and fully automated quality control method for fungal gene catalogues that can be easily implemented into existing annotation pipelines. With the exponential release of new genomes, the ABFGP method will help decreasing the number of gene models that require additional manual curation.

Dataset Information

Bioinformatic curation and alignment of genotyped hepatitis B virus (HBV) sequence data from the GenBank public database.

Publications

Bioinformatic curation and alignment of genotyped hepatitis B virus (HBV) sequence data from the GenBank public database.

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