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An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

ABSTRACT: Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs, variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved. Deep sequencing libraries from either a randomized RNA oligo or an equimolar miRNA mix were analyzed for evenness of capture.

ORGANISM(S): synthetic construct

SUBMITTER: Melissa Moore

PROVIDER: E-GEOD-63606 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Project description:Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs, variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.

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