Conifer transcriptome sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA482145 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those alleles could lead to new therapeutic strategies. Three cancer patients, three tumor samples per patient from different sites, two normal tissue samples from two different patients, four cell lines.
2015-12-12 | E-GEOD-75935 | biostudies-arrayexpress
Project description:There is a wide diversity of bioinformatic tools available for the assembly of next generation sequence and subsequence variant calling to identify genetic markers at scale. Integration of genomics tools such as genomic selection, association studies, pedigree analysis and analysis of genetic diversity, into operational breeding is a goal for New Zealand's most widely planted exotic tree species, Pinus radiata. In the absence of full reference genomes for large megagenomes such as in conifers, RNA sequencing in a range of genotypes and tissue types, offers a rich source of genetic markers for downstream application. We compared nine different assembler and variant calling software combinations in a single transcriptomic library and found that Single Nucleotide Polymorphism (SNPs) discovery could vary by as much as an order of magnitude (8,061 SNPs up to 86,815 SNPs). The assembler with the best realignment of the packages trialled, Trinity, in combination with several variant callers was then applied to a much larger multi-genotype, multi-tissue transcriptome and identified 683,135 in silico SNPs across a predicted 449,951 exons when mapped to the Pinus taeda ver 1.01e reference.
| S-EPMC6218030 | biostudies-literature
Project description:The conifer needle endophyte, Phialocephala scopiformis, was cultivated in media containing ground Pinus contorta wood as sole carbon source. After five and seven days growth, concentrated extracellular fluids were subjected to LC-MS/MS analyses.
2018-11-28 | PXD010720 | Pride
Project description:Transcriptome of the conifer Pinus cembra (Swiss stone pine) based on Swiss individuals
| PRJEB29997 | ENA
Project description:Transcriptome sequencing data were generated for four fresh prostate needle biopsies at the Australian Genome Research Facility, Australia, on the NovaSeq 6000 using the TruSeq stranded mRNA sample preparation. Samples were run in duplicate and 20 million, 100 base pair (bp) single end reads were generated for each. Data were accessed for transcript level expression and differential expression between two EZH2 rs78589034 variant carriers and two non-variant carriers.
2021-04-01 | E-MTAB-10271 | biostudies-arrayexpress
Project description:Deregulated gene expression is a hallmark of cancer, however most studies to date have analyzed short-read RNA-sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality. We performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which >66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell-line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information. Our results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.
2021-02-02 | PXD023373 | Pride
Project description:Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those alleles could lead to new therapeutic strategies.
2015-12-12 | GSE75935 | GEO
Project description:Clinically translatable large animal models have become indispensable for cardiovascular research, clinically relevant proof of concept studies and for novel diagnostic and therapeutic interventions. In particular, the pig as emerged as an essential cardiovascular disease model, because its heart, circulatory system, and blood supply are anatomically and functionally similar to that of humans. Unfortunately, molecular and omics-based studies in the pig are hampered by the incompleteness of the genome and the lack of diversity of the corresponding transcriptome annotation. Here, we employed Nanopore long-read sequencing and in-depth proteomics on top of Illumina RNA-seq to enhance the pig cardiac transcriptome annotation. We assembled 15,926 transcripts, stratified into coding and non-coding, and validated our results by complementary mass spectrometry. A manual review of several gene loci, which are associated with cardiac function, corroborated the utility of our enhanced annotation. All our data are available for download and is also provided as tracks for integration in genome browsers. We deem this resource as highly valuable for molecular research in an increasingly relevant large animal model.
2020-10-29 | PXD018985 | Pride
Project description:Mixed Conifer Forest, Northern Arizona, soil qSIP Raw sequence reads
| PRJNA649802 | ENA
Project description:We sequenced mRNA from dormant, reactivating, and actively growing C. lanceolata vascular cambium using tangential cryosections to generate the first transcriptome dynamics that may serve as a gene expression profile blueprint for cambium development and wood formation in the conifer.
2014-03-31 | GSE37152 | GEO