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High quality RNA extraction from Maqui berry for its application in next-generation sequencing

Overview of attention for article published in SpringerPlus, August 2016
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Title
High quality RNA extraction from Maqui berry for its application in next-generation sequencing
Published in
SpringerPlus, August 2016
DOI 10.1186/s40064-016-2906-x
Pubmed ID
Authors

Carolina Sánchez, Javier Villacreses, Noelle Blanc, Loreto Espinoza, Camila Martinez, Gabriela Pastor, Patricio Manque, Soledad F. Undurraga, Victor Polanco

Abstract

Maqui berry (Aristotelia chilensis) is a native Chilean species that produces berries that are exceptionally rich in anthocyanins and natural antioxidants. These natural compounds provide an array of health benefits for humans, making them very desirable in a fruit. At the same time, these substances also interfere with nucleic acid preparations, making RNA extraction from Maqui berry a major challenge. Our group established a method for RNA extraction of Maqui berry with a high quality RNA (good purity, good integrity and higher yield). This procedure is based on the adapted CTAB method using high concentrations of PVP (4 %) and β-mercaptoethanol (4 %) and spermidine in the extraction buffer. These reagents help to remove contaminants such as polysaccharides, proteins, phenols and also prevent the oxidation of phenolic compounds. The high quality of RNA isolated through this method allowed its uses with success in molecular applications for this endemic Chilean fruit, such as differential expression analysis of RNA-Seq data using next generation sequencing (NGS). Furthermore, we consider that our method could potentially be used for other plant species with extremely high levels of antioxidants and anthocyanins.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 19%
Student > Ph. D. Student 10 19%
Student > Master 7 13%
Student > Doctoral Student 6 12%
Student > Bachelor 5 10%
Other 5 10%
Unknown 9 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 31%
Agricultural and Biological Sciences 16 31%
Chemistry 3 6%
Medicine and Dentistry 2 4%
Psychology 1 2%
Other 2 4%
Unknown 12 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 August 2016.
All research outputs
#20,337,788
of 22,883,326 outputs
Outputs from SpringerPlus
#1,461
of 1,851 outputs
Outputs of similar age
#322,131
of 367,231 outputs
Outputs of similar age from SpringerPlus
#202
of 238 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,851 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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