Increasing quality, throughput and speed of sample preparation for strand-specific messenger RNA sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Simon Haile, Richard D. Corbett, Tina MacLeod, Steve Bilobram, Duane Smailus, Philip Tsao, Heather Kirk, Helen McDonald, Pawan Pandoh, Miruna Bala, Martin Hirst, Diane Miller, Richard A. Moore, Andrew J. Mungall, Jacquie Schein, Robin J. Coope, Yussanne Ma, Yongjun Zhao, Rob A. Holt, Steven J. Jones, Marco A. Marra

ABSTRACT

BACKGROUND: RNA-Sequencing (RNA-seq) is now commonly used to reveal quantitative spatiotemporal snapshots of the transcriptome, the structures of transcripts (splice variants and fusions) and landscapes of expressed mutations. However, standard approaches for library construction typically require relatively high amounts of input RNA, are labor intensive, and are time consuming. METHODS: Here, we report the outcome of a systematic effort to optimize and streamline steps in strand-specific RNA-seq library construction. RESULTS: This work has resulted in the identification of an optimized messenger RNA isolation protocol, a potent reverse transcriptase for cDNA synthesis, and an efficient chemistry and a simplified formulation of library construction reagents. We also present an optimization of bead-based purification and size selection designed to maximize the recovery of cDNA fragments. CONCLUSIONS: These developments have allowed us to assemble a rapid high throughput pipeline that produces high quality data from amounts of total RNA as low as 25 ng. While the focus of this study is on RNA-seq sample preparation, some of these developments are also relevant to other next-generation sequencing library types. More... »

PAGES

515

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12864-017-3900-6

DOI

http://dx.doi.org/10.1186/s12864-017-3900-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090356744

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28679365


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12864-017-3900-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12864-017-3900-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12864-017-3900-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12864-017-3900-6'


 

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