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Synthetic construct

ABSTRACT: shRNA Sensor Analysis of DSIR Selected shRNAs

PROVIDER: PRJNA263390 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	SRR1608310.fastq.gz	Fastqsanger.gz
	SRR1608320.fastq.gz	Fastqsanger.gz
	SRR1608330.fastq.gz	Fastqsanger.gz
	SRR1608340.fastq.gz	Fastqsanger.gz
	SRR1608350.fastq.gz	Fastqsanger.gz

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Project description:shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

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shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

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shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

Project description:shRNAs selected with the shERWOOD algorithm were converted to have a U at the 5' end of their guide. When endogenous 1U shRNAs were compared to artificial shRNA via the sensor algorithm, the endogenous shRNAs were found to be more efficacious. Purpose: Structural studies have hinted that the 5' end of shRNA guides is engulfed in the RISC complex. It has also been reported that shRNAs with a 5' U are more efficacious than those with other 5' caps. We wished to determine whether replacement of shRNA guide 5' nucleotides with a U, regardless of the corresponding target base, would increase their efficacy. Method: For each gene in the "druggable genome" 10 shRNAs were selected with the shERWOOD algorithm. In each case the score was assessed as if the guide had a 5' U. Sensor constructs were designed pairing 1U-guide shRNAs with their endogenous target. shRNAs were assessed for efficacy via the shRNA sensor assay (Fellmann et al. Mol Cell 2011). Results: shRNAs with artificial 5' Us were found to be less efficacious than those with an endogenous 5' U,

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shRNA Sensor Analysis of DSIR Selected shRNAs

Project description:Purpose: Generate a large, high quality database of paired shRNA efficacy/sequence datapoints. Methods:Twelve shRNAs for each Refseq annotated human gene were selected based on the DSIR algorithm. Twelve batches of ~22K shRNAs (corresponding to 12 agilent chips) were then assessed for efficacy via the sensor method outlined in Fellmann et al, Mol Cell, 2011. Conclusions: Neighboring nucleotide combinations are best at predicting shRNA efficacy.

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