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Targeting epithelial-mesenchymal plasticity via ribosome inhibition to reduce chemoresistant metastasis of breast cancer

ABSTRACT: Targeting epithelial-mesenchymal plasticity via ribosome inhibition to reduce chemoresistant metastasis of breast cancer

PROVIDER: PRJNA739676 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR14870954_1.fastq.gz	Fastqsanger.gz
	SRR14870954_2.fastq.gz	Fastqsanger.gz
	SRR14870955_1.fastq.gz	Fastqsanger.gz
	SRR14870955_2.fastq.gz	Fastqsanger.gz
	SRR14870956_1.fastq.gz	Fastqsanger.gz

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Targeting epithelial-mesenchymal plasticity via ribosome inhibition to reduce chemoresistant metastasis of breast cancer [bulk RNA-seq]

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Project description:Protein translation is at the heart of cellular metabolism and its in-depth characterization is key for many lines of research. Recently, ribosome profiling became the state-of-the-art method to quantitatively characterize translation dynamics at a transcriptome-wide level. However, the strategy of library generation affects its outcomes. Here, we present a modified ribosomeprofiling protocol starting from yeast, human cells and vertebrate brain tissue. We use a DNA linker carrying four randomized positions at its 5’ and a reverse-transcription (RT) primer with three randomized positions to reduce artifacts during library preparation. The use of seven randomized nucleotides allows to efficiently detect library-generation artifacts. We find that the effect of polymerase chain reaction (PCR) artifacts is relatively small for global analyses when sufficient input material is used. However, when input material is limiting, our strategy improves the sensitivity of gene-specific analyses. Furthermore, randomized nucleotides alleviate the skewed frequency of specific sequences at the 3’ end of ribosome-protected fragments (RPFs) likely resulting from ligase specificity. Finally, strategies that rely on dual ligation show a high degree of gene-coverage variation. Taken together, our approach helps to remedy two of the main problems associated with ribosome-profiling data. This will facilitate the analysis of translational dynamics and increase our understanding of the influence of RNA modifications on translation.

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