Similar Datasets
Project description:The Human Eye Transcriptome Atlas: A Searchable Transcriptome Database for Healthy and Diseased Human Eye Tissue
| PRJNA668653 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2023-07-20 | GSE231767 | GEO
Project description:Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas Project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.
| S-SCDT-89399_2_1559826858_jats | biostudies-other
Project description:BackgroundHuman-resident microbes can influence both health and disease. Investigating the microbiome using next-generation sequencing technology has revealed examples of mutualism and conflict between microbes and humans. Comparing to bacteria, the viral component of the microbiome (i.e., the "virome") is understudied. Somatic tissues of healthy individuals are usually inaccessible for the virome sampling; therefore, there is limited understanding of the presence and distribution of viruses in tissues in healthy individuals and how virus infection associates with human gene expression and perturbs immunological homeostasis.ResultsTo characterize the human virome in a tissue-specific manner, here we performed meta-transcriptomic analysis using the RNA-sequencing dataset from the Genotype-Tissue Expression (GTEx) Project. We analyzed the 8991 RNA-sequencing data obtained from 51 somatic tissues from 547 individuals and successfully detected 39 viral species in at least one tissue. We then investigated associations between virus infection and human gene expression and human disease onset. We detected some expected relationships; for instance, hepatitis C virus infection in the liver was strongly associated with interferon-stimulated gene upregulation and pathological findings of chronic hepatitis. The presence of herpes simplex virus type 1 in one subject's brain strongly associated with immune gene expression. While torque teno virus was detected in a broad range of human tissues, it was not associated with interferon responses. Being notable in light of its association with lymphoproliferative disorders, Epstein-Barr virus infection in the spleen and blood was associated with an increase in plasma cells in healthy subjects. Human herpesvirus 7 was often detected in the stomach; intriguingly, it associated with the proportion of human leukocytes in the stomach as well as digestive gene expression. Moreover, virus infections in the local tissues associated with systemic immune responses in circulating blood.ConclusionsTo our knowledge, this study is the first comprehensive investigation of the human virome in a variety of tissues in healthy individuals through meta-transcriptomic analysis. Further investigation of the associations described here, and application of this analytical pipeline to additional datasets, will be useful to reveal the impact of viral infections on human health.
| S-EPMC7269688 | biostudies-literature
Project description:Purpose:We develop an accessible and reliable RNA sequencing (RNA-seq) transcriptome database of healthy human eye tissues and a matching reactive web application to query gene expression in eye and body tissues. Methods:We downloaded the raw sequence data for 1375 RNA-seq samples across 54 tissues in the Genotype-Tissue Expression (GTEx) project as a noneye reference set. We then queried several public repositories to find all healthy, nonperturbed, human eye-related tissue RNA-seq samples. The 916 eye and 1375 GTEx samples were sent into a Snakemake-based reproducible pipeline we wrote to quantify all known transcripts and genes, removes samples with poor sequence quality and mislabels, normalizes expression values across each tissue, perform 882 differential expression tests, calculate GO term enrichment, and output all as a single SQLite database file: the Eye in a Disk (EiaD) dataset. Furthermore, we rewrote the web application eyeIntegration (available in the public domain at https://eyeIntegration.nei.nih.gov) to display EiaD. Results:The new eyeIntegration portal provides quick visualization of human eye-related transcriptomes published to date by database version, gene/transcript, 19 eye tissues, and 54 body tissues. As a test of the value of this unified pan-eye dataset, we showed that fetal and organoid retina are highly similar at a pan-transcriptome level, but display distinct differences in certain pathways and gene families, such as protocadherin and HOXB family members. Conclusions:The eyeIntegration v1.0 web app serves the pan-human eye and body transcriptome dataset, EiaD. This offers the eye community a powerful and quick means to test hypotheses on human gene and transcript expression across 54 body and 19 eye tissues.
| S-EPMC6660187 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2023-02-10 | GSE212090 | GEO
Project description:Background Pancreatic cancer is common in elderly persons, and less than 20% of patients present with localized, potentially curable tumors. Methods We compared the methylated sites and genes in pericarcinous tissues compared to cancer tissue, and blood compared to pericarcinous tissues in order to harvest methylation markers for putative diagnostic and therapy monitoring purposes. Results Of 15,397 CpG sites detected in 7,440 genes, 5,605 (36.4%, 5,605 of 15,397) CpG sites were hypomethylated and 5,870 (38.12%, 5,870 of 15,397) CpG sites were hypermethylated. We then performed Gene Ontology (GO) and KEGG analysis to systematically characterize the ten significantly differentially methylated genes: PTPRN2, MAD1L1, TNXB, PRDM16, GNAS, KCNQ1, TSNARE1, HDAC4, TBCD, and DIP2C. Meanwhile, function analysis of genes with differentially methylated sites located in promoter regions of overlap group was also performed. According to previous studies, we further screened 22 pancreatic cancer related key genes. The results suggested that these key genes can influence methylation. GO and KEGG analysis indicated that these genes are involved in a wide range of functions. Conclusions The identification of differentially methylated genes in this study provides valuable information for liquid biopsy methylation markers in pancreatic cancer.
| S-EPMC8798020 | biostudies-literature
Project description:Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein-level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.
| S-EPMC6379049 | biostudies-literature
Project description:BackgroundFor centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce.ResultsHere, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways.ConclusionsThe study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy.
| S-EPMC3518227 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2012-10-31 | GSE34200 | GEO