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De novo sequencing, assembly and characterisation of Aloe vera transcriptome and analysis of expression profiles of genes related to saponin and anthraquinone metabolism

Overview of attention for article published in BMC Genomics, June 2018
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

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Title
De novo sequencing, assembly and characterisation of Aloe vera transcriptome and analysis of expression profiles of genes related to saponin and anthraquinone metabolism
Published in
BMC Genomics, June 2018
DOI 10.1186/s12864-018-4819-2
Pubmed ID
Authors

Pragati Choudhri, Muniya Rani, Rajender S. Sangwan, Ravinder Kumar, Anil Kumar, Vinod Chhokar

Abstract

Aloe vera is a perennial, succulent, drought-resistant plant that exhibits many pharmacological characteristics such as wound healing ability against skin burns, anti-ulcer, anti-inflammatory, anti-tumor, anti-viral, anti-hypercholesterolemic, anti-hyperglycemic, anti-asthmatic and much more. Despite great medicinal worth, little genomic information is available on Aloe vera. This study is an initiative to explore the full-scale functional genomics of Aloe vera by generating whole transcriptome sequence database, using Illumina HiSeq technology and its progressive annotation specifically with respect to the metabolic specificity of the plant. Transcriptome sequencing of root and leaf tissue of Aloe vera was performed using Illumina paired-end sequencing technology. De novo assembly of high quality paired-end reads, resulted into 1,61,733 and 2,21,792 transcripts with mean length of 709 and 714 nucleotides for root and leaf respectively. The non-redundant transcripts were clustered using CD-HIT-EST, yielding a total of 1,13,063 and 1,41,310 unigenes for root and leaf respectively. A total of 6114 and 6527 CDS for root and leaf tissue were enriched into 24 different biological pathway categories using KEGG pathway database. DGE profile prepared by calculating FPKM values was analyzed for differential expression of specific gene encoding enzymes involved in secondary metabolite biosynthesis. Sixteen putative genes related to saponin, lignin, anthraquinone, and carotenoid biosynthesis were selected for quantitative expression by real-time PCR. DGE as well as qRT PCR expression analysis represented up-regulation of secondary metabolic genes in root as compared to leaf. Furthermore maximum number of genes was found to be up-regulated after the induction of methyl jasmonate, which stipulates the association of secondary metabolite synthesis with the plant's defense mechanism during stress. Various transcription factors including bHLH, NAC, MYB were identified by searching predicted CDS against PlantTFdb. This is the first transcriptome database of Aloe vera and can be potentially utilized to characterize the genes involved in the biosynthesis of important secondary metabolites, metabolic regulation, signal transduction mechanism, understanding function of a particular gene in the biology and physiology of plant of this species as well as other species of Aloe genus.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 16%
Researcher 12 11%
Student > Master 9 8%
Student > Doctoral Student 6 6%
Student > Bachelor 6 6%
Other 13 12%
Unknown 45 42%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 21%
Biochemistry, Genetics and Molecular Biology 20 19%
Medicine and Dentistry 4 4%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Chemical Engineering 3 3%
Other 7 6%
Unknown 48 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 05 August 2018.
All research outputs
#14,254,705
of 25,163,238 outputs
Outputs from BMC Genomics
#4,719
of 11,177 outputs
Outputs of similar age
#162,965
of 337,002 outputs
Outputs of similar age from BMC Genomics
#101
of 254 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,177 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,002 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.