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.
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
Project description:This study includes raw data of testis RNA-seq profiles from treated (nABX & LPHS, with nABX: non-absorbable antibiotics and LPHS: low-protein, high sugar diet) and control (CON) males of mature (57-62 weeks) and young (9-11 weeks) FVB & C57BL/6J backgrounds. Sequencing was done using 40bp paired-end reads on a NextSeq500 sequencer, obtaining an average of 25 million reads per sample.
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.
Project description:This study includes raw data of blastocyst single-embryo SMART-seq profiles generated by IVF using sperm derived from mature (50-57 weeks) and young (9-11 weeks) males of C57BL/6N background. After SMART-seq library preparation of single embryos, indexed samples were pooled and sequenced on the NextSeq 2000 using a P3 flow cell in 50bp paired-end mode, targeting an average of 5 million reads per sample.
Project description:Here, A549 cells expressing the ACE2 receptor were infected with SARS-CoV2, and pCHi-C was performed at 0 (mock), 8 and 24 hours post-infection. This repository provides the raw pCHi-C sequence reads and downstream processed CHiCAGO data (Rds files).
Project description:HDMYZ cells were treated with 2ug/ml ActD for 0, 4 and 12 hours. Small RNAs of 15-40 bases were gel-purified from 10 ug total RNA, and subjected to multiplex Illumina small RNA library preparation. Small RNA libraries were sequenced on a HiSeq2000 (Illumina) with 3 samples per lane. To quantify miRNA and isoform abundance, sequence reads were processed by the miRDeep2 package, with the following modifications. First, to remove adaptor sequence, we removed both the main adaptor sequence present in the sequencing reads, as well as the second most abundant adaptor variant. In addition, we did not restrict the size of small RNAs during adaptor removal. Second, we used miRBase v18 for mapping the reads. Third, for quantifying miRNA and isoform frequency, we limited reads to more or equal to 15 bases in length with zero mis-match during mapping. The number of reads that were mapped to known miRNAs was used to normalize read frequencies for each miRNA or each miRNA isoform. For quantification purposes, we only considered miRNAs or isoforms that had frequency >= 1x10e-6 in samples without ActD treatment, which correspond to ~21-30 reads in raw count. These miRNAs or isoforms were referred to as reliably quantifiable.To analyze mapping to the genome, we removed reads that mapped to miRNA precursors. The rest of the reads were then mapped to the genome with Bowtie.
Project description:Label-free protein sequencing is critically enabled by bottom-up, mass spectrometry-based proteomics workflows. Applications such as antibody sequencing or antigen discovery require de novo reconstruction of peptide and protein sequences. While trypsin has long served as the gold-standard protease in proteomics, its restricted C-terminal cleavage specificity constrains peptide diversity, particularly limiting coverage in antibody hypervariable complementarity-determining regions (CDRs). As a result, current workflows yield sparse reads and sequence gaps. Although multi-protease and hybrid-fragmentation strategies can notably improve coverage, they add complexity and compromise scalability and reproducibility. Here, we present a novel approach using HyperThermoacidic Archaeal (HTA) proteases Krakatoa or Vesuvius as powerful single-enzyme solutions for de novo antibody sequencing. Each protease generated over five times more unique peptide reads than trypsin or chymotrypsin with high redundancy across CDRs. Combined with EAciD fragmentation on a ZenoTOF 7600 system, this workflow enabled complete, unambiguous antibody sequencing. Despite most de novo tools being optimized for CID/HCD-tryptic data, analysis using PEAKS/DeepNovo and Stitch softwares showed that HTA-Proteases yielded up to fourfold higher alignment scores and fewer sequence mistakes across variable regions. Redundant reads increased more than threefold compared to standard proteases, boosting confidence in amino acid assignment and reducing ambiguity in final assemblies. Our alternative HTA-EAciD approach offers short digestion times, eliminates extensive cleanup, and enables analysis in a single LC-MS/MS run. This single-protease strategy delivers sequencing performance comparable to multi-enzyme workflows, providing a scalable, efficient, and highly confident approach for de novo sequencing in antibody discovery and beyond.