Genome annotation of disease-causing microorganisms.
Ontology highlight
ABSTRACT:
SUBMITTER: Dong Y
PROVIDER: S-EPMC7986607 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Discriminating between rare benign and pathogenic variation is a key challenge in clinical genetics, particularly as increasing numbers of nonsynonymous single-nucleotide polymorphisms (SNPs) are identified in resequencing studies. Here, we describe an approach for the functional annotation of nonsynonymous variants that identifies functionally important, disease-causing residues across protein families using multiple sequence alignment. We applied the methodology to long QT syndrome (LQT) genes, which cause sudden death, and their paralogues, which largely cause neurological disease. This approach accurately classified known LQT disease-causing variants (positive predictive value = 98.4%) with a better performance than established bioinformatic methods. The analysis also identified 1078 new putative disease loci, which we incorporated along with known variants into a comprehensive and freely accessible long QT resource (http://cardiodb.org/Paralogue_Annotation/), based on newly created Locus Reference Genomic sequences (http://www.lrg-sequence.org/). We propose that paralogous annotation is widely applicable for Mendelian human disease genes.
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Project description:Hand infections are a common presentation at the emergency departments. Without knowing the source of infection clinicians are dependent on systematic reports on the bacterial spectrum and susceptibility tests of the specific infection in their patient community. This study was based on a retrospective chart review of patients presenting to our outpatient clinic with acute hand infections. We documented patient demographics, the etiology, location, culture tests of the infection and analyzed if certain bacteria could be cultured significantly more often in certain etiologies or in specific sites of the hand infection. Susceptibility tests were added. Bacterial swabs of 204 patients were analyzed. Overall S. aureus was found in 53% of all cases, in only one case revealed methicillin-resistant S. aureus (MRSA). There was no significant difference in the bacterial spectrum according to the etiology of the hand infections, except for animal bites where Pasteurella multocida was the dominating bacteria in 63% of all cases. Amoxicillin-clavulanic acid, fluoroquinolones, and piperacillin were effective against the main bacteria. Our study confirms the previously published antibiotic resistance reports and reinforces the current antibiotic treatment guidelines also in this western European population.
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Project description:Mycobacterium tuberculosis strain MYC004 was isolated from a Mexican patient with tuberculous meningitis, the most aggressive form of tuberculosis. The draft genome sequence is the first of a meningeal strain of M. tuberculosis reported from Latin America and consists of 4,411,530 bp, including 4,251 protein-encoding genes.
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Project description:BackgroundAlthough acute bronchitis is quite common, there is relatively limited information regarding the microorganisms that are involved in this illness.MethodsWe performed a prospective study of acute bronchitis at 31 hospitals and clinics in Korea from July 2011 to June 2012. Sputum specimens were collected for polymerase chain reaction (PCR) and culture of microorganisms.ResultsOf the 811 enrolled patients, 291 had acceptable sputum specimens that were included for analysis of the etiologic distribution. With multiplex PCR testing, viruses were identified in 36.1% (105/291), most commonly rhinovirus (25.8%) and coronavirus (3.8%). Typical bacteria were isolated in 126/291 (43.3%) patients. Among these patients Haemophilus influenzae (n = 39) and Streptococcus pneumoniae (n = 30) were isolated most commonly; atypical bacteria were identified in 44 (15.1%) patients. Bacteria-only, virus-only, and mixed infections (bacteria plus virus) accounted for 36.7% (98/291), 17.2% (50/291), and 18.9% (55/291) of infections, respectively. In particular, 52.4% of patients with viral infection had a concurrent bacterial infection, and rhinovirus was the most common virus in mixed infections (40/55). Additionally, infections with typical bacteria were more common in patients with chronic lung disease (p = 0.029), and typical bacterial infections showed a trend towards a higher prevalence with older age (p = 0.001).ConclusionsBacteria were associated with almost half of community-acquired acute bronchitis cases. Additional studies are required to further illuminate the role of bacteria and to identify patient groups most likely to benefit from antibiotic treatment.
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Project description:Information is given in tabular form derived from a synopsis of the human gene map which has been updated continuously since 1973 as part of Mendelian Inheritance in Man (Johns Hopkins University Press, 10th ed, 1992) and of OMIM (Online Mendelian Inheritance in Man, available generally since 1987). The part of the synopsis reproduced here consists of chromosome by chromosome gene lists of loci for which there are associated disorders (table 1), a pictorial representation of this information (fig 1a-d), and an index of disorders for which the causative mutations have been mapped (table 2). In table 1, information on genes that have been located to specific chromosomal positions and are also the site of disease producing mutations is arranged by chromosome, starting with chromosome 1 and with the end of the short arm of the chromosome in each case. In table 2 an alphabetized list of these disorders and the chromosomal location of the mutation in each case are provided. Both in the 'Disorder' field of table 1 and in table 2, the numbers 1, 2, or 3 in parentheses after the name of the disorder indicate that its chromosomal location was determined by mapping of the wildtype gene (1), by mapping of the clinical phenotype (2), or by both strategies (3).
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Project description:Human disease causing Kinetoplastid wgs raw sequence reads
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Project description:While the C. elegans genome is extensively annotated, relatively little information is available for other Caenorhabditis species. The nematode genome annotation assessment project (nGASP) was launched to objectively assess the accuracy of protein-coding gene prediction software in C. elegans, and to apply this knowledge to the annotation of the genomes of four additional Caenorhabditis species and other nematodes. Seventeen groups worldwide participated in nGASP, and submitted 47 prediction sets across 10 Mb of the C. elegans genome. Predictions were compared to reference gene sets consisting of confirmed or manually curated gene models from WormBase.The most accurate gene-finders were 'combiner' algorithms, which made use of transcript- and protein-alignments and multi-genome alignments, as well as gene predictions from other gene-finders. Gene-finders that used alignments of ESTs, mRNAs and proteins came in second. There was a tie for third place between gene-finders that used multi-genome alignments and ab initio gene-finders. The median gene level sensitivity of combiners was 78% and their specificity was 42%, which is nearly the same accuracy reported for combiners in the human genome. C. elegans genes with exons of unusual hexamer content, as well as those with unusually many exons, short exons, long introns, a weak translation start signal, weak splice sites, or poorly conserved orthologs posed the greatest difficulty for gene-finders.This experiment establishes a baseline of gene prediction accuracy in Caenorhabditis genomes, and has guided the choice of gene-finders for the annotation of newly sequenced genomes of Caenorhabditis and other nematode species. We have created new gene sets for C. briggsae, C. remanei, C. brenneri, C. japonica, and Brugia malayi using some of the best-performing gene-finders.
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Project description:Not available
2009-12-01 | PRD000122 | Pride
Project description:Rice is a major staple food crop in the world. Over 80% of rice cultivation area is under indica rice. Currently, genomic resources are lacking for indica as compared to japonica rice. In this study, we generated deep-sequencing data (Illumina and Pacific Biosciences sequencing) for one of the indica rice cultivars, HR-12 from India.We assembled over 86% (389 Mb) of rice genome and annotated 56,284 protein-coding genes from HR-12 genome using Illumina and PacBio sequencing. Comprehensive comparative analyses between indica and japonica subspecies genomes revealed a large number of indica specific variants including SSRs, SNPs and InDels. To mine disease resistance genes, we sequenced few indica rice cultivars that are reported to be highly resistant (Tetep and Tadukan) and susceptible (HR-12 and Co-39) against blast fungal isolates in many countries including India. Whole genome sequencing of rice genotypes revealed high rate of mutations in defense related genes (NB-ARC, LRR and PK domains) in resistant cultivars as compared to susceptible. This study has identified R-genes Pi-ta and Pi54 from durable indica resistant cultivars; Tetep and Tadukan, which can be used in marker assisted selection in rice breeding program.This is the first report of whole genome sequencing approach to characterize Indian rice germplasm. The genomic resources from our work will have a greater impact in understanding global rice diversity, genetics and molecular breeding.
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Project description:Genome annotation is the process of identifying the location and function of a genome's encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, we present Apollo, an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform. Some of Apollo's newer user interface features include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible.
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