Title |
A High-Throughput Method for Illumina RNA-Seq Library Preparation
|
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Published in |
Frontiers in Plant Science, January 2012
|
DOI | 10.3389/fpls.2012.00202 |
Pubmed ID | |
Authors |
Ravi Kumar, Yasunori Ichihashi, Seisuke Kimura, Daniel H. Chitwood, Lauren R. Headland, Jie Peng, Julin N. Maloof, Neelima R. Sinha |
Abstract |
With the introduction of cost effective, rapid, and superior quality next generation sequencing techniques, gene expression analysis has become viable for labs conducting small projects as well as large-scale gene expression analysis experiments. However, the available protocols for construction of RNA-sequencing (RNA-Seq) libraries are expensive and/or difficult to scale for high-throughput applications. Also, most protocols require isolated total RNA as a starting point. We provide a cost-effective RNA-Seq library synthesis protocol that is fast, starts with tissue, and is high-throughput from tissue to synthesized library. We have also designed and report a set of 96 unique barcodes for library adapters that are amenable to high-throughput sequencing by a large combination of multiplexing strategies. Our developed protocol has more power to detect differentially expressed genes when compared to the standard Illumina protocol, probably owing to less technical variation amongst replicates. We also address the problem of gene-length biases affecting differential gene expression calls and demonstrate that such biases can be efficiently minimized during mRNA isolation for library preparation. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 25% |
Netherlands | 1 | 6% |
Switzerland | 1 | 6% |
Australia | 1 | 6% |
Unknown | 9 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 9 | 56% |
Members of the public | 7 | 44% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 2% |
Brazil | 2 | <1% |
Germany | 2 | <1% |
United Kingdom | 2 | <1% |
Japan | 2 | <1% |
Canada | 2 | <1% |
Ethiopia | 1 | <1% |
New Zealand | 1 | <1% |
Mexico | 1 | <1% |
Other | 5 | 1% |
Unknown | 386 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 102 | 25% |
Researcher | 95 | 23% |
Student > Master | 55 | 13% |
Student > Bachelor | 33 | 8% |
Student > Doctoral Student | 18 | 4% |
Other | 62 | 15% |
Unknown | 48 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 226 | 55% |
Biochemistry, Genetics and Molecular Biology | 81 | 20% |
Immunology and Microbiology | 6 | 1% |
Medicine and Dentistry | 6 | 1% |
Environmental Science | 5 | 1% |
Other | 29 | 7% |
Unknown | 60 | 15% |