Title |
High-throughput and quantitative genome-wide messenger RNA sequencing for molecular phenotyping
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Published in |
BMC Genomics, August 2015
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DOI | 10.1186/s12864-015-1788-6 |
Pubmed ID | |
Authors |
John E. Collins, Neha Wali, Ian M. Sealy, James A. Morris, Richard J. White, Steven R. Leonard, David K. Jackson, Matthew C. Jones, Nathalie C. Smerdon, Jorge Zamora, Christopher M. Dooley, Samantha N. Carruthers, Jeffrey C. Barrett, Derek L. Stemple, Elisabeth M. Busch-Nentwich |
Abstract |
We present a genome-wide messenger RNA (mRNA) sequencing technique that converts small amounts of RNA from many samples into molecular phenotypes. It encompasses all steps from sample preparation to sequence analysis and is applicable to baseline profiling or perturbation measurements. Multiplex sequencing of transcript 3' ends identifies differential transcript abundance independent of gene annotation. We show that increasing biological replicate number while maintaining the total amount of sequencing identifies more differentially abundant transcripts. This method can be implemented on polyadenylated RNA from any organism with an annotated reference genome and in any laboratory with access to Illumina sequencing. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 11% |
Brazil | 1 | 11% |
Germany | 1 | 11% |
France | 1 | 11% |
Unknown | 5 | 56% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 56% |
Scientists | 4 | 44% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Portugal | 1 | 2% |
Switzerland | 1 | 2% |
Netherlands | 1 | 2% |
Chile | 1 | 2% |
Sweden | 1 | 2% |
Benin | 1 | 2% |
Denmark | 1 | 2% |
Unknown | 47 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 31% |
Student > Ph. D. Student | 13 | 24% |
Student > Master | 6 | 11% |
Student > Bachelor | 5 | 9% |
Other | 4 | 7% |
Other | 5 | 9% |
Unknown | 4 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 29 | 54% |
Biochemistry, Genetics and Molecular Biology | 10 | 19% |
Engineering | 3 | 6% |
Computer Science | 2 | 4% |
Environmental Science | 1 | 2% |
Other | 2 | 4% |
Unknown | 7 | 13% |