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01685 am a22002533u 4500 |
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138384.2 |
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|a dc
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|a Abudayyeh, Omar O.
|e author
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1 |
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|a Broad Institute of MIT and Harvard
|e contributor
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|a McGovern Institute for Brain Research at MIT
|e contributor
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|a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
|e contributor
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|a Massachusetts Institute of Technology. Department of Biological Engineering
|e contributor
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|a Harvard University-
|e contributor
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| 700 |
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|a Gootenberg, Jonathan S
|e author
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|a Kellner, Max J.
|e author
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|a Zhang, Feng
|e author
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| 245 |
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|a Nucleic Acid Detection of Plant Genes Using CRISPR-Cas13
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| 260 |
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|b Mary Ann Liebert Inc,
|c 2022-01-06T16:05:34Z.
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|z Get fulltext
|u https://hdl.handle.net/1721.1/138384.2
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|a Nucleic acid detection is vital for agricultural applications including trait detection during breeding, pest surveillance, and pathogen identification. Here, we use a modified version of the CRISPR-based nucleic acid detection platform SHERLOCK to quantify levels of a glyphosate resistance gene in a mixture of soybeans and to detect multiple plant genes in a single reaction. SHERLOCK is rapid (∼15 min), quantitative, and portable, and can process crude soybean extracts as input material for minimal nucleic acid sample preparation. This field-ready SHERLOCK platform with color-based lateral flow readout can be applied for detection and quantitation of genes in a range of agricultural applications.
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|a en
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|a Article
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| 773 |
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|t 10.1089/CRISPR.2019.0011
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| 773 |
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|t The CRISPR Journal
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