Neuropterida
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1132765 | ENA |
REPOSITORIES: ENA
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Project description:Genotyping studies suggest that there is genetic variability among P. gingivalis strains, however the extent of variability remains unclear, and the regions of variability have only partially been identified. We previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type P. gingivalis strains in several diverse populations, identifying 6 predominant heteroduplex types and many minor ones. In addition we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another, and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of P. gingivalis strains. The availability of whole genome microarrays based on the genomic sequence of strain W83 has allowed a more comprehensive analysis of P. gingivalis strain variability, using the entire genome. The objectives of this study were to define the phylogeny of P. gingivalis strains using the entire genome, to compare the phylogeny based on genome content to the phylogeny based on a single locus (ISR), and to identify genes that are associated with the strongly disease-associated strain W83 that could be important for virulence. Keywords: Comparative genomic hybridization
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Project description:In principle, whole-genome sequencing (WGS) of the human genome even at low coverage offers higher resolution for genomic copy number variation (CNV) detection compared to array-based technologies, which is currently the first-tier approach in clinical cytogenetics. There are, however, obstacles in replacing array-based CNV detection with that of low-coverage WGS such as cost, turnaround time, and lack of systematic performance comparisons. With technological advances in WGS in terms of library preparation, instrument platforms, and data analysis algorithms, obstacles imposed by cost and turnaround time are fading. However, a systematic performance comparison between array and low-coverage WGS-based CNV detection has yet to be performed. Here, we compared the CNV detection capabilities between WGS (short-insert, 3kb-, and 5kb-mate-pair libraries) at 1X, 3X, and 5X coverages and standardly used high-resolution arrays in the genome of 1000-Genomes-Project CEU genome NA12878. CNV detection was performed using standard analysis methods, and the results were then compared to a list of Gold Standard NA12878 CNVs distilled from the 1000-Genomes Project. Overall, low-coverage WGS is able to detect drastically more (approximately 5 fold more on average) Gold Standard CNVs compared to arrays and is accompanied with fewer CNV calls without secondary validation. Furthermore, we also show that WGS (at ≥1X coverage) is able to detect all seven validated deletions larger than 100 kb in the NA12878 genome whereas only one of such deletions is detected in most arrays. Finally, we show that the much larger 15 Mbp Cri-du-chat deletion can be clearly seen at even 1X coverage from short-insert WGS.
2018-06-26 | GSE105092 | GEO
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