Comparison of tRNA expression between HEK293 and HeLa cells
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina HiSeq 2500
ORGANISM(S): Homo sapiens
SUBMITTER: Hannah Benisty
PROVIDER: E-MTAB-8144 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:To quantify tRNA expression, we perform hydro-tRNA sequencing (Gogakos et al. 2017) in HACAT (keratinoytes) and HepG2 (liver) human cell lines. This study contains 6 samples. Three replicates for each of the five cell lines. This data complements our previously published data (GEO: GSE137834), which contained five additional cell lines from different tissues: HEK293 (kidney), HCT116 (colon), HeLa (cervix), MDA-MB-231 (breast), and BJ fibroblasts. Therefore, with these extra two cell lines, this constitutes a tissue-wide dataset of tRNA sequencing covering a total of seven human cell lines.
2021-03-15 | E-MTAB-9905 | biostudies-arrayexpress
Project description:We measured abundances of tRNAs by means of hydro-tRNA-seq (Gogakos et al., 2017), a method based on partial alkaline RNA hydrolysis that generates fragments suitable for sequencing, in the genome-reduced bacterium Mycoplasma pneumoniae.
2023-06-29 | E-MTAB-11930 | biostudies-arrayexpress
Project description:To investigate differential mitochondrial tRNA gene expression in wild type (WT) and mutant (E423P) mitochondrial RNA polymerase (POLRMT) overexpression flies, we performed Drsophila mitochondrial tRNA-seq according to the Hydro-tRNAseq method. tRNA-seq reads were subjected to 3' - adapter filtering , 3' - adapter trimming and quality control. The tRNAs expression levels were measured by tag count. For each tRNA sequence-based profile, the mapped reads number used to estimate the expression level of each tRNA. The tRNAs expression profiling was calculated based on uniquely mapped reads and including mapped reads, respectively. We found no difference in the relative abundance of mitochondrial individual tRNAs between WT and E423P overexpression flies.
2021-01-06 | GSE164324 | GEO
Project description:Here we report that the spatial organization of yeast tRNA genes depends upon both locus position and tRNA identity; supporting the idea that the genomic organization of tRNA loci utilizes tRNA dependent signals within the nucleoprotein-tRNA complexes that form into clusters. We use high-throughput sequencing coupled to Circular Chromosome Conformation Capture to detect interactions with two wild type tRNAs and these same positions replaced with suppressor tRNAs (SUP4-1). Detect DNA-DNA interactions (Circular chromosome conformation capture; 4C) with two wild type tRNAs and these same positions replaced with suppressor tRNAs (SUP4-1) Supplementary files: Alignment files generated by Topography v1.19 software.
2012-06-13 | E-GEOD-30103 | biostudies-arrayexpress
Project description:Increased proliferation and elevated levels of protein synthesis are characteristic of transformed and tumor cells. Though components of the translation machinery are often misregulated in cancers, how tRNA plays a role in cancer cells has not been explored. We compare genome-wide tRNA expression in tumorigenic versus non-tumorigenic breast cell lines, as well as tRNA expression in breast tumors versus normal breast tissues. In tumorigenic versus non-tumorigenic cell lines, nuclear-encoded tRNAs increase by up to 3-fold and mitochondrial-encoded tRNAs increase by up to 5-fold. In tumors versus normal breast tissues, both nuclear and mitochondrial-encoded tRNAs increase by up to 10-fold. This tRNA over-expression is selective and coordinates with the properties of cognate amino acids. Nuclear- and mitochondrial-encoded tRNAs exhibit distinct expression patterns, indicating that tRNAs can be used as biomarkers for breast cancer. We analyzed tRNA expression levels in 2 non-tumorigenic breast cell lines, 6 tumorigenic breast cancer cell lines, 3 normal breast tissue samples, and 9 breast tumor samples. We used a non-tumorigenic breast cell line (MCF10A) as a reference sample in all hybridizations. All data is dye-swapped.
2010-05-22 | E-GEOD-17945 | biostudies-arrayexpress
Project description:In the ribosome complex, tRNA is a critical element of mRNA translation. We reported a new technology for profiling ribosome-embedded tRNAs and their modifications. With the method, we generated a comprehensive survey of the quanity and quality of intra-ribosomal tRNAs (Ribo-tRNA-seq). Ribo-tRNA-seq can provide new insights on translation control mechanism in diverse biological contexts.
2018-03-19 | E-MTAB-6576 | biostudies-arrayexpress
Project description:tRNAs quantification by hydro-tRNA-seq in the genome-reduced bacterium Mycoplasma pneumoniae
| PRJEB54635 | ENA
Project description:Different subsets of the tRNA pool in human are expressed in different cellular conditions. The “proliferation-tRNAs” are induced upon normal and cancerous cell division, while the “differentiation tRNAs” are active in non-dividing, differentiated cells. Here we examine the essentiality of the various tRNAs upon cellular growth and arrest. We established a CRISPR-based editing procedure with sgRNAs that each target a tRNA family. We measured tRNA essentiality for cellular growth and found that most proliferation tRNAs are essential compared to differentiation tRNAs in rapidly growing cell lines. Yet in more slowly dividing lines, the differentiation tRNAs were more essential. In addition, we measured the essentiality of each tRNA family upon response to cell cycle arresting signals. Here we detected a more complex behavior with both proliferation-tRNAs and differentiation-tRNAs showing various levels of essentiality. These results provide the so-far most comprehensive functional characterization of human tRNAs with intricate roles in various cellular states.
2020-12-22 | GSE163609 | GEO
Project description:The human genome encodes hundreds of tRNA genes but their individual contribution to the tRNA pool is not fully understood. Deep sequencing of tRNA transcripts (tRNA-Seq) can estimate tRNA abundance at single gene resolution, but tRNA structures and post-transcriptional modifications impair these analyses. Here we present a bioinformatics strategy to investigate differential tRNA gene expression and use it to compare tRNA-Seq datasets from cultured human cells and human brain. We find that sequencing caveats affect quantitation of only a subset of human tRNA genes. Unexpectedly, we detect several cases where the differences in tRNA expression among samples do not involve variations at the level of isoacceptor tRNA sets (tRNAs charged with the same amino acid but using different anticodons); but rather among tRNA genes within the same isodecoder set (tRNAs having the same anticodon sequence). Because isodecoder tRNAs are functionally equal in terms of genetic translation, their differential expression may be related to non-canonical tRNA functions. We show that several instances of differential tRNA gene expression result in changes in the abundance of tRNA-derived fragments (tRFs) but not of mature tRNAs. Examples of differentially expressed tRFs include: PIWI-associated RNAs, tRFs present in tissue samples but not in cells cultured in vitro, and somatic tissue-specific tRFs. Our data support that differential expression of tRNA genes regulate non-canonical tRNA functions performed by tRFs.
2019-04-17 | GSE114904 | GEO
Project description:Different subsets of the tRNA pool in human are expressed in different cellular conditions. The “proliferation-tRNAs” are induced upon normal and cancerous cell division, while the “differentiation tRNAs” are active in non-dividing, differentiated cells. Here we examine the essentiality of the various tRNAs upon cellular growth and arrest. We established a CRISPR-based editing procedure with sgRNAs that each target a tRNA family. We measured tRNA essentiality for cellular growth and found that most proliferation tRNAs are essential compared to differentiation tRNAs in rapidly growing cell lines. Yet in more slowly dividing lines, the differentiation tRNAs were more essential. In addition, we measured the essentiality of each tRNA family upon response to cell cycle arresting signals. Here we detected a more complex behavior with both proliferation-tRNAs and differentiation-tRNAs showing various levels of essentiality. These results provide the so-far most comprehensive functional characterization of human tRNAs with intricate roles in various cellular states.
2020-12-22 | GSE163607 | GEO