UMass Chan Medical School Faculty Publications

UMMS Affiliation

Department of Medicine, Division of Cardiovascular Medicine

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Article Preprint


Computational Biology | Genomics | Nucleic Acids, Nucleotides, and Nucleosides


Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.


RNA-seq, small RNAs, microRNAs, exRNAs, accuracy, bias, reproducibility, genomics

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The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.

DOI of Published Version



bioRxiv 113050; doi: Link to preprint on bioRxiv service.


Preprint PDF has different title: Systematic assessment of next generation sequencing for quantitative small RNA profiling: a multiple protocol study across multiple laboratories.

Full author list omitted for brevity. For the full list of authors, see article.

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Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.