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Transcriptomic analysis of the abundance of snoRNAs and their host genes in 4 different cell lines, using low structure bias TGIRT-seq

ABSTRACT: Transcriptomic analysis of the abundance of snoRNAs and their host genes in 4 different cell lines, using low structure bias TGIRT-seq

PROVIDER: PRJNA862949 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR20677230_1.fastq.gz	Fastqsanger.gz
	SRR20677230_2.fastq.gz	Fastqsanger.gz
	SRR20677231_1.fastq.gz	Fastqsanger.gz
	SRR20677231_2.fastq.gz	Fastqsanger.gz
	SRR20677232_1.fastq.gz	Fastqsanger.gz

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Transcriptomic analysis of the abundance of snoRNAs and their host genes in 4 different cell lines, using low structure bias TGIRT-seq

Project description:Small nucleolar RNAs (snoRNAs) are highly abundant non-coding RNAs whose canonical function is to guide the 2’-O-ribose methylation or pseudouridylation of ribosomal RNAs. They are often encoded in longer genes referred to as their host genes, the expression of which is required for their own biogenesis. Due to their very stable structure, reverse transcription of snoRNAs using standard viral reverse transcriptases is very inefficient, and does not provide an adequate view of the abundance of these small RNAs. We thus employed high-throughput, low structure bias TGIRT-seq sequencing to quantified the abundance of the entire ribodepleted transcriptome, including snoRNAs and their host genes, in 4 different cell lines.

2022-08-10 | GSE209924 | GEO

Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships

Project description:Background: Small nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions. Results: We used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver and brain). We identify 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. 59% of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, compared to only 16% of the correlated non-coding host gene/snoRNA pairs. Conclusions: Our results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.

2021-05-13 | GSE157846 | GEO

Comprehensive map of ribosomal 2′-O-methylation and C/D box snoRNAs in Drosophila melanogaster [Fib_KD_TGIRT-seq]

Project description:The majority of Nm modifications in eukaryotes are placed by Fibrillarin, a conserved methyltransferase belonging to a ribonucleoprotein complex guided by C/D box small nucleolar RNAs (C/D box snoRNAs). We built the first comprehensive map of Nm sites in Drosophila melanogaster rRNAs using two complementary approaches (RiboMethSeq and Nanopore direct RNA sequencing) and identified their corresponding C/D box snoRNAs by whole-transcriptome sequencing (TGIRT-seq).

2024-02-12 | GSE233853 | GEO

Comprehensive map of ribosomal 2′-O-methylation and C/D box snoRNAs in Drosophila melanogaster [Fib_KD_RiboMeth-seq]

2024-02-12 | GSE241400 | GEO

Comprehensive map of ribosomal 2′-O-methylation and C/D box snoRNAs in Drosophila melanogaster [Tissues_TGIRT-seq]

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High-grade Ovarian Cancer Associated H/ACA snoRNAs Promote Cancer Cell Proliferation and Survival

Project description:Small nucleolar RNAs (snoRNAs) are an omnipresent class of non-coding RNAs involved in the modification and processing of ribosomal RNA (rRNA). There are two types of snoRNAs, box C/D, which typically guide 2’-O-methylation, and box H/ACA, which guide pseudouridylation. As snoRNAs are required for ribosome production, the increase of which is a hallmark of cancer development, their expression would be expected to increase in proliferating cancer cells. However, the contributions of H/ACA box and C/D box snoRNAs to the biology of cancer cells remain unclear. To understand the contribution of snoRNAs to cancer progression and aggressiveness we examined their abundance patterns in high-grade serous ovarian carcinomas (HGSC) and serous borderline tumors (SBT), using a newly developed snoRNA sensitive sequencing technique. Surprisingly, the results indicate that while abundance of a selected group of H/ACA snoRNAs increases, most C/D snoRNAs remain stable or decrease in HGSC compared to SBT. This suggests that induction of ribosome biogenesis and translation in HGSC does not require a general increase in snoRNAs expression but depends upon the upregulation of a handful of key H/ACA snoRNAs. This subgroup accurately discriminates between SBT and HGSC underlining their potential as biomarkers of tumor aggressiveness. Remarkably, knockdown of HGSC associated H/ACA snoRNAs, but not their host genes, inhibits cell proliferation and induces apoptosis of model ovarian cancer cell lines. Together our data indicate that specific H/ACA snoRNAs promote tumor aggressiveness through the induction of cell proliferation and resistance to apoptosis.

2021-12-08 | GSE181496 | GEO

Identification of new snoRNAs in human muscle cells

Project description:Small non-coding RNAs (sncRNAs) represent an important class of regulatory RNAs involved in the regulation of transcription, RNA splicing or translation. Among these sncRNAs, small nucleolar RNAs (snoRNAs) mostly originate from intron splicing in humans and are central to posttranscriptional regulation of gene expression. Yet, the characterization of the complete repertoire of sncRNAs in a given cellular context and the functional annotation of the human transcriptome are far from complete. Here, we report the large-scale identification of sncRNAs in the size range of 50 to 200 nucleotides, without a priori on their biogenesis, structure and genomic origin, in the context of normal human muscle cells. We provided a complete set of experimental validation of novel candidate snoRNAs by evaluating the prerequisites for their biogenesis and functionality, leading to their validation as genuine snoRNAs. Interestingly, we also found intergenic snoRNAs, which we showed are in fact integrated into candidate introns of unannotated transcripts or degraded by the Nonsense Mediated Decay pathway. Hence, intergenic snoRNAs represent a new type of landmark for the identification of new transcripts that have gone undetected because of low abundance or degradation after the release of the snoRNA.

2021-09-28 | GSE178649 | GEO

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Causal signals between codon bias, mRNA structure and the efficiency of translation and elongation

Project description:Ribosome profiling data reports on the distribution of translating ribosomes, at steady-state, with codon-level resolution. We present a robust method to extract codon translation rates and protein synthesis rates from these data, and identify causal features associated with elongation and translation efficiency in physiological conditions in yeast. We show that neither elongation rate nor translational efficiency is improved by experimental manipulation of the abundance or body sequence of the rare AGG tRNA. Deletion of three of the four copies of the heavily used ACA tRNA shows a modest efficiency decrease that could be explained by other rate-reducing signals at gene start. This suggests that correlation between codon bias and efficiency arises as selection for codons to utilize translation machinery efficiently in highly translated genes. We also show a correlation between efficiency and RNA structure calculated both computationally and from recent structure probing data, as well as the Kozak initiation motif, which may comprise a mechanism to regulate initiation. We test whether tRNA abundance affects elongation or translation efficiency by changing the tRNA levels through deletion or over expression and measuring the ribosomal dwell time at each codon using a robust statistical method that accounts for flow conservation.

2015-01-05 | E-GEOD-63789 | biostudies-arrayexpress

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