Project description:Asian salamander Hynobiidae is commonly observed in the Far East Asia regions, including Korea, Japan, China, and the eastern region of Russia. In Korea, there are four Hynobiidae species known to be lived: Hynobius leechii, Hynobius quelpaertensis, Hynobius yangi, and recently reported Hynobius unisacculus. However, even H. leechii which is broadly colonized in Korea peninsula seems to have a new species candidate, which has distinctive genetic and phenotypic characteristics. Genomic resources are essential to understand the current status of these species, but due to the large size of their genomes (about 16 to 20 Gb), it is not easy to analyze. To reveal the genomic characteristics of these species, we constructed more than ten thousands of protein-coding gene sequences from multiple samples of each species, using the de novo transcriptome assembly approach from RNA-Seq data, confirming their taxonomic relationship which was reported based on mitochondrial DNA and marker genes. Also, by comparing previously reported transcriptome of Hynobius chinensis and Hynobius retardatus, lived in China and Japan, respectively, we found that Korean species have unique genetic signatures. By comparing vertebrate model organism genes, we reported Hynobidaii specific proteins. These data would be a useful resource to study other Caudata species in the future. This research was supported by the National Institute of Biological Resources, Republic of Korea, under the project "Genetic diversity of animal resources” (NIBR201703203 and NIBR201803101).
Project description:We performed shallow whole genome sequencing (WGS) on circulating free (cf)DNA extracted from plasma or cerebrospinal fluid (CSF), and shallow WGS on the tissue DNA extracted from the biopsy in order to evaluate the correlation between the two biomaterials. After library construction and sequencing (Hiseq3000 or Ion Proton), copy number variations were called with WisecondorX.
Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).
Project description:This dataset holds three runs of our new Atrandi-SPC based single-cell WGS protocol, one for each lysis protocol (R1-R3 in the study)
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.