Ontology highlight
ABSTRACT:
PROVIDER: PRJNA614947 | ENA |
REPOSITORIES: ENA
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Project description:We provide raw gene sequences of 174 flowering time regulatory genes and gene othologs across a large barley population (895 barley lines) selected from a collection of landrace, cultivated barley, and research varieties of diverse origin. This set represents the whole variety of cultivated barley lifeforms, namely two- and six-row genotypes with winter, spring, and facultative growth habits. We applied a target capture method based on in-solution hybridization using the myBaits® technology (Arbor Biosciences, Ann Arbour, MI, USA) which is based on in-solution biotinylated RNA probes. Baits were designed for flowering time regulatory genes and gene othologs, and used for production of 80mer capture oligonucleotides for hybridization. Genomic DNA was extracted from leaves of a single two-week old barley plant per variety using the cetyl-trimethyl-ammonium bromide (CTAB) method. Physical shearing of genomic DNA was performed with an average size of 275 bp. Library preparation was conducted with KAPA Hyper Prep Kit (KAPA Biosystems, Wilmington, MA). Hybridization of customised RNA baits with capture pools was performed at 65°C for 24 hours. Each pooled sequence capture library was sequenced on an Illumina HiSeq3000 instrument using three lanes to generate paired-end reads per sample. Genome sequencing was conducted at AgriBio, (Centre for AgriBioscience, Bundoora, VIC, Australia).
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Project description:Purpose: To ensure that ABX464 acted specifically on HIV splicing and did not significantly or globally affect the splicing events of human genes, we used an assembly approach of HIV (YU2 strain) putative transcripts and human long non-coding sequences from paired-reads (2x75bp) captured on a NimbleGen SeqCap® EZ Developer Library (Roche/NimbleGen). Methods: Cells were infected with 80 ng of p24/106 cells of the YU-2 strain for 4 to 6 hours and then rinsed with PBS before medium renewal, followed by high-throughput RNAseq from custom SeqCap EZ capture libraries. Each raw dataset of the samples contained between 5 and 30 million paired-end reads (75 bp), with an average of approximately 12 million raw reads per sample. Results: The raw reads were then cleaned and assembled per library to generate contigs, giving an average of 930 contigs per sample for further analyses. Conclusions: Our results show that high-throughput analyses coupled with bioinformatics-specific tools offers a comprehensive and more accurate view of mRNA splicing within a cell.
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Project description:In the present study, RNA-seq technique was used to compare the expression profiles of lncRNAs from goat endometrium samples at gestational day 5 (pre-receptive endometrium, PE) and day 15 (receptive endometrium, RE). This yielded 18 gigabases (Gb) of sequence, representing approximately seven times the size of the genome (2.66 Gb). A total of 120 million raw reads were produced from the Illumina HiSeq 2500 platform. After discarding adaptor sequences and low-quality sequences, 90 to 97 million clear reads per sample were obtained, and the percentage of clean reads among raw tags in each library ranged from 75.79–81.03 %. A total of 668 lncRNAs were found to differ significantly in terms of expressional levels (P< 0.05) between the PE and RE libraries,98.35% of the DELs were mapped to “u” (Unknown, intergenic transcript).Our results included 76,844 lncRNAs that corresponded to 42,933 protein-coding genes within a range of 1-100 kb. It deserved to note that 783 target genes of the 200 DELs that were annotated to 153 GO terms meeting our designated criteria of P-values< 0.05, KEGG pathway annotation showed 242 target genes of the DELs were annotated for 146 KEGG pathways.
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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.
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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
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