Project description:Whole exome sequencing of 5 HCLc tumor-germline pairs. Genomic DNA from HCLc tumor cells and T-cells for germline was used. Whole exome enrichment was performed with either Agilent SureSelect (50Mb, samples S3G/T, S5G/T, S9G/T) or Roche Nimblegen (44.1Mb, samples S4G/T and S6G/T). The resulting exome libraries were sequenced on the Illumina HiSeq platform with paired-end 100bp reads to an average depth of 120-134x. Bam files were generated using NovoalignMPI (v3.0) to align the raw fastq files to the reference genome sequence (hg19) and picard tools (v1.34) to flag duplicate reads (optical or pcr), unmapped reads, reads mapping to more than one location, and reads failing vendor QC.

2016-02-01 | E-MTAB-4313 | biostudies-arrayexpress

Quantitative profiling of differentially expressed miRNAs in siCTL- and siOASL-transfected HUVECs

Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.

2022-09-06 | GSE186354 | GEO

A draft genome sequence of the elusive giant squid, Architeuthis dux

Project description:We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long-reads and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from three different tissue types from three other species of squid species (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein coding genes supported by evidence and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome.

2019-12-16 | PXD016522 | Pride

Exploring the gene expression profile upon FXR1 knockdown in H358 cells using RNA-seq

Project description:We performed the RNA-seq in control samples and FXR1 knockdown samples, and compared the gene expression profiles to explore the effect of FXR1 knockdown on gene expression. The study was performed in H358 cells. Doxycycline inducible shRNA3 (sh3) was used to knockdown FXR1. Control shRNA (ctrl) samples were used to get rid of the effect of Doxycycline treatment. Both the Doxycycline treament for 3 days (D3) and 5 days (D5) samples were collected. Each sample has three repeats (rep 1, rep 2, and rep 3). The mRNA profiles were generated by deep sequencing using Illumina.Sequenced reads were trimmed for adaptor sequence, then mapped to hg19 whole genome using STAR v2.5.3 with parameters --bamRemoveDuplicatesType UniqueIdentical --outSAMmultNmax 1. Raw reads and Reads Per Kilobase per Megabase of library size (RPKM) were calculated using HOMER (PMID: 20513432). Differential gene expression was analyzed using R package DESeq2 using the raw reads.

2017-10-04 | GSE101754 | GEO

RNA-seq of 6 tissues from Monodelphis domestica to investigate the evolution of gene expression levels in mammalian organs

Project description:This experiment contains the subset of data corresponding to gray short-tailed opossum RNA-Seq data from experiment E-GEOD-30352 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-30352/), which goal is to understand the dynamics of mammalian transcriptome evolution. To study mammalian transcriptome evolution at high resolution, we generated RNA-Seq data (∼3.2 billion Illumina Genome Analyser IIx reads of 76 base pairs) for the polyadenylated RNA fraction of brain (cerebral cortex or whole brain without cerebellum), cerebellum, heart, kidney, liver and testis (usually from one male and one female per somatic tissue and two males for testis) from nine mammalian species: placental mammals (great apes, including humans; rhesus macaque; mouse), marsupials (gray short-tailed opossum) and monotremes (platypus). Corresponding data (∼0.3 billion reads) were generated for a bird (red jungle fowl, a non-domesticated chicken) and used as an evolutionary outgroup.

2011-10-12 | E-MTAB-3719 | biostudies-arrayexpress

Epigenetic and genetic changes during mouse hematopoietic stem cell aging [Bisulfite-Seq]

Project description:To investigate the global DNA methylation changes in mouse hematopoietic stem cell aging, we performed whole-genome bisulfite sequencing (WGBS). We generated 1,494 million (4mo HSCs), and 1,493 million (24mo HSCs) raw reads; about 82.6% and 84.3%, respectively, were successfully aligned to either strand of the reference genome (mm9). Of all the cytosines present in the reference genome sequence, about 93% of Cs and 99% of CGs were covered in both datasets, with an average coverage of 46-fold (4mo) and 50-fold (24mo). In contrast to the age-associated hypomethylation observed in studies of somatic cells, mentioned above, HSCs showed an increase of methylation with age. The average methylation level over all 16 million covered CpGs increased from 83.5% in young (4mo) HSC to 84.6% in old (24mo) HSC. We observed a total of 448,166 differentially methylated CpGs (DMCs), defined as those having a 20% or more difference in methylation ratio, of which 38.5% (172,609) were hypomethylated (hypo-DMCs) and 61.5% (275,557) were hypermethylated (hyper-DMCs) with aging. For different genomic features, a slightly greater DNA methylation ratio increase was observed for the gene body, LINEs and SINEs, while CGIs and promoters showed balanced increases and decreases. Localization analysis of DMCs indicates that DNA encoding for ribosome RNA (rDNA) is primarily a hotspot for hypo-DMCs, while promoters without CpG islands, CpG island shores and LINE repetitive elements exhibit both hypo- and hyper-DMCs. Mouse hematopoietic stem cell DNA methylation profiles of 4 month and 24 month old WT mice were generated generated by deep sequencing, in duplicate, using Illumina Hiseq 2000.

2014-04-30 | E-GEOD-47815 | biostudies-arrayexpress

Canis lupus

Project description:Gray wolf Raw sequence reads from RRBS preps

| PRJNA488382 | ENA