Genomics in bacterial taxonomy: impact on the genus Pseudomonas
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB36791 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The introduction of genomics is profoundly changing current bacterial taxonomy. Phylogenomics provides accurate methods for delineating species and allows us to infer the phylogeny of higher taxonomic ranks as well as those at the subspecies level. We present as a model the currently accepted taxonomy of the genus Pseudomonas and how it can be modified when new taxonomic methodologies are applied. A phylogeny of the species in the genus deduced from analyses of gene sequences or by whole genome comparison with different algorithms allows three main conclusions: (i) several named species are synonymous and have to be reorganized in a single genomic species; (ii) many strains assigned to known species have to be proposed as new genomic species within the genus; and (iii) the main phylogenetic groups defined by 4-, 100- and 120-gene multilocus sequence analyses are concordant with the groupings in the whole genome analyses. Moreover, the boundaries of the genus Pseudomonas are also discussed based on phylogenomic analyses in relation to other genera in the family Pseudomonadaceae. The new technologies will result in a substantial increase in the number of species and probably split the current genus into several genera or subgenera, although these classifications have to be supported by a polyphasic taxonomic approach.
| S-EPMC7074058 | biostudies-literature
Project description:Comparative genomics of the genus Winogradskyella
| PRJEB35806 | ENA
Project description:Even though urothelial cancer (UC) is the fourth common tumor type among males, progress in treatment development has been deficient. Pathological assessment provides the urologists with only a broad classification, complicated by frequent disagreement among pathologist and the co-existence of different grading systems. Consequently, there is a great need for an objective, reproducible and biologically relevant classification system to make treatment more efficient. In the present investigation we present a molecular taxonomy for UC stratification based on integrated genomics. We used gene expression profiles from 308 UC to define seven molecular subtypes using step-by-step partitions and a bootstrap approach. Results were validated in three independent and publically available data sets. The subtypes differ significantly with respect to expression of cell cycle genes, of receptor tyrosine kinases particularity FGFR3, ERBB2 (HER2), and EGFR, of an FGFR3 associated gene expression signature, of cytokaratins, and of cell adhesion genes. The subtypes also differ significantly with respect to FGFR3, PIK3CA, and TP53 mutations. The expression of key proteins was validated by IHC on TMA. A further inspection indicated that the subtypes could be reduced to four major types of UC; Urobasal/D-driven, Genomically unstable/E-driven, Evolved urobasal, and Basal/SCC like, with characteristic and highly divergent molecular phenotypes. We show that the molecular subtypes cut across pathological classification and that tumors classified as one subtype maintain their characteristic molecular phenotype irrespective of pathological stage and grade. Available data from the Drugbank database and the Cochrane central registry of controlled trials indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathological classification. The presented molecular taxonomy stratifies UC into subtypes with distinct molecular phenotypes and biological properties. We anticipate that the molecular taxonomy will be a useful tool in future clinical investigations. Total RNA from fresh-frozen resection samples of 308 urothelial carcinomas was hybridized to the Illumina HumanHT-12 V3.0 expression beadchip arrays (Illumina Inc) at the SCIBLU Genomics Centre at Lund University Sweden (http://www.lth.se/sciblu). Supplementary files: GSE32894_non-normalized_308UCsamples.txt file = Raw intensity values for 308 UC (urothelial tumor) samples subjected only to background correction. GSE32894_reps_normals_preprocess*.txt files = Descriptive details and non-normalized data for technical replicates and normal samples that were used only in the preprocessing of the data. This dataset partly overlaps with Series GSE32549. Names of the overlapping sample names are the same, but the title of each sample is unique to the hybridization.
2012-05-23 | E-GEOD-32894 | biostudies-arrayexpress
Project description:This clinical trial studies the effectiveness of a web-based cancer education tool called Helping Oncology Patients Explore Genomics (HOPE-Genomics) in improving patient knowledge of personal genomic testing results and cancer and genomics in general. HOPE-Genomics is a web-based education tool that teaches cancer/leukemia patients, and patients who may be at high-risk for developing cancer, about genomic testing and provide patients with information about their own genomic test results. The HOPE-Genomics tool may improve patient’s genomic knowledge and quality of patient-centered care. In addition, it may also improve education and care quality for future patients.
| 2378933 | ecrin-mdr-crc
Project description:Genomic taxonomy study of novel bacterial species
| PRJEB63549 | ENA
Project description:Evolutionary genomics of Australian Treefrogs (genus Litoria)
| PRJNA912233 | ENA
Project description:Pangenome, phylogenomics, and comparative genomics of Claviceps purpurea and the Claviceps genus
| PRJNA528707 | ENA
Project description:Even though urothelial cancer (UC) is the fourth common tumor type among males, progress in treatment development has been deficient. Pathological assessment provides the urologists with only a broad classification, complicated by frequent disagreement among pathologist and the co-existence of different grading systems. Consequently, there is a great need for an objective, reproducible and biologically relevant classification system to make treatment more efficient. In the present investigation we present a molecular taxonomy for UC stratification based on integrated genomics. We used gene expression profiles from 308 UC to define seven molecular subtypes using step-by-step partitions and a bootstrap approach. Results were validated in three independent and publically available data sets. The subtypes differ significantly with respect to expression of cell cycle genes, of receptor tyrosine kinases particularity FGFR3, ERBB2 (HER2), and EGFR, of an FGFR3 associated gene expression signature, of cytokaratins, and of cell adhesion genes. The subtypes also differ significantly with respect to FGFR3, PIK3CA, and TP53 mutations. The expression of key proteins was validated by IHC on TMA. A further inspection indicated that the subtypes could be reduced to four major types of UC; Urobasal/D-driven, Genomically unstable/E-driven, Evolved urobasal, and Basal/SCC like, with characteristic and highly divergent molecular phenotypes. We show that the molecular subtypes cut across pathological classification and that tumors classified as one subtype maintain their characteristic molecular phenotype irrespective of pathological stage and grade. Available data from the Drugbank database and the Cochrane central registry of controlled trials indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathological classification. The presented molecular taxonomy stratifies UC into subtypes with distinct molecular phenotypes and biological properties. We anticipate that the molecular taxonomy will be a useful tool in future clinical investigations.
2012-05-24 | GSE32894 | GEO
Project description:Integrative taxonomy and population genomics of Aeromonas media and related species
| PRJEB12344 | ENA