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:We use nucleosome maps obtained by high-throughput sequencing to study sequence specificity of intrinsic histone-DNA interactions. In contrast with previous approaches, we employ an analogy between a classical one-dimensional fluid of finite-size particles in an arbitrary external potential and arrays of DNA-bound histone octamers. We derive an analytical solution to infer free energies of nucleosome formation directly from nucleosome occupancies measured in high-throughput experiments. The sequence-specific part of free energies is then captured by fitting them to a sum of energies assigned to individual nucleotide motifs. We have developed hierarchical models of increasing complexity and spatial resolution, establishing that nucleosome occupancies can be explained by systematic differences in mono- and dinucleotide content between nucleosomal and linker DNA sequences, with periodic dinucleotide distributions and longer sequence motifs playing a secondary role. Furthermore, similar sequence signatures are exhibited by control experiments in which genomic DNA is either sonicated or digested with micrococcal nuclease in the absence of nucleosomes, making it possible that current predictions based on highthroughput nucleosome positioning maps are biased by experimental artifacts. Included are raw (eland) and mapped (wig) reads. The mapped reads are provided in eland and wiggle formats, and the raw reads are included in the eland file. This series includes only Mnase control data. The sonicated control is part of this already published accession, as is a in vitro nucleosome map: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15188 We also studied data (in vitro and in vivo maps as well as a model) from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13622 and from: http://www.ncbi.nlm.nih.gov/sra/?term=SRA001023
Project description:Purpose: In order to understand the functional significance of sperm transcriptome in stallion fertility, the aim of this study was to generate a detailed body of knowledge about the sperm RNA profile that defines a normal fertile stallion. Methods: The 50 bp single-end ABI SOLiD raw reads were directly aligned with the horse reference sequence EcuCab2 using ABI aligner software (NovoalignCS version 1.00.09, novocraft.com) which uses multiple indexes in the reference genome, identifies candidate alignment locations for each primary read, and allows completion of the alignment. Results: Next generation sequencing (NGS) of total RNA from the sperm of two reproductively normal stallions generated about 70 million raw reads and more than 3 Gb of sequence per sample; over half of these aligned with the EcuCab2 reference genome. Altogether, 19,257 sequence tags with average coverage ≥1 (normalized number of transcripts) were mapped in the horse genome. Conclusion: The sequence of stallion sperm transcriptome is an important foundation for the discovery of transcripts of known and novel genes, and non-coding RNAs, thus improving the annotation of the horse genome sequence draft and providing markers for evaluating stallion fertility. Reproductively fertile Stallion sperm transcriptome as revealed by RNA sequencing
Project description:Purpose: Here we describe the modulation of a gene expression program involved in cell fate. Methods: We depleted U2AF1 in human induced pluripotent stem cells (hiPSCs) to the level found in differentiated cells using an inducible shRNA system, followed by high-throughput RNAseq, revealing a gene expression program involved in cell fate determination. Results: Approximately 85% of the total raw reads were mapped to the human genome sequence (GRCh37), giving an average of 200 million human reads per sample for total RNA and 15 million human reads per sample for small RNA libraries. Conclusions: Our results show that transcriptional control of gene expression in hiPSCs can be set by the CSF U2AF1, establishing a direct link between transcription and AS during cell fate determination. Overall design: hiPSCs were differentiated into the three germ layers following the described protocol in the study (Gifford et al., 2013).