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In Silico Identification and Validation of Potential microRNAs in Kinnow Mandarin (Citrus reticulata Blanco)

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, May 2017
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Title
In Silico Identification and Validation of Potential microRNAs in Kinnow Mandarin (Citrus reticulata Blanco)
Published in
Interdisciplinary Sciences: Computational Life Sciences, May 2017
DOI 10.1007/s12539-017-0235-6
Pubmed ID
Authors

Prashant Mohanpuria, Naveen Duhan, Navraj Kaur Sarao, Manvir Kaur, Mandip Kaur

Abstract

MicroRNAs (miRNAs) are a large family of 19-25 nucleotides, regulatory, non-coding RNA molecules that control gene expression by cleaving or inhibiting the translation of target gene transcripts in animals and plants. Despite the important functions of miRNAs related to regulation of plant growth and development processes, metabolism, and abiotic and biotic stresses, little is known about the disease-related miRNA. Here, we present a new pipeline for miRNA analysis using expressed sequence tags (ESTs)-based bioinformatics approach in Kinnow mandarin, a commercially important citrus fruit crop. For this, 56,041 raw EST sequences of Citrus reticulata Blanco were retrieved from EST database in NCBI through step-by-step filtering and processing methods and 130 miRNAs were predicted. Upon blast with Citrus sinensis transcriptome data, these produced potential targets related to disease resistance proteins, pectin lyase-like superfamily proteins, lateral organ boundaries (LOB) domain-containing proteins 11, and protein phosphatase 2C family proteins, protein kinases, dehydrogenases, and methyltransferases. Majority of the predicted miRNAs were of 22, 23, and 24 nucleotides in length. To validate these computationally predicted miRNA, poly(A)-tailed Reverse Transcription-PCR was applied to detect the expression of seven miRNA which showed disease-related potential targets, in citrus greening diseased leaf tissues in comparison to the healthy tissues of Kinnow mandarin. Our study provides information on regulatory roles of these potential miRNAs for the citrus greening disease development, miRNA targets, and would be helpful for future research of miRNA function in citrus.

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Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 21%
Student > Ph. D. Student 2 14%
Researcher 2 14%
Student > Master 1 7%
Professor > Associate Professor 1 7%
Other 1 7%
Unknown 4 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 36%
Agricultural and Biological Sciences 3 21%
Computer Science 1 7%
Unknown 5 36%
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 25 May 2017.
All research outputs
#18,550,124
of 22,974,684 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#167
of 297 outputs
Outputs of similar age
#239,047
of 313,704 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#2
of 5 outputs
Altmetric has tracked 22,974,684 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 297 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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