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De novo transcriptome assembly of the wild relative of tea tree (Camellia taliensis) and comparative analysis with tea transcriptome identified putative genes associated with tea quality and stress…

Overview of attention for article published in BMC Genomics, April 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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Title
De novo transcriptome assembly of the wild relative of tea tree (Camellia taliensis) and comparative analysis with tea transcriptome identified putative genes associated with tea quality and stress response
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1494-4
Pubmed ID
Authors

Hai-Bin Zhang, En-Hua Xia, Hui Huang, Jian-Jun Jiang, Ben-Ying Liu, Li-Zhi Gao

Abstract

Camellia taliensis is one of the most important wild relatives of cultivated tea tree, C. sinensis. The species extensively occupies mountainous habitats representing a wide-range abiotic tolerance and biotic resistance and thus harbors valuable gene resources that may greatly benefit genetic improvement of cultivated tea tree. However, owning to a large genome size of ~3 Gb and structurally complex genome, there are fairly limited genetic information and particularly few genomic resources publicly available for this species. To better understand the key pathways determining tea flavor and enhance tea tree breeding programs, we performed a high-throughput transcriptome sequencing for C. taliensis. In this study, approximate 241.5 million high-quality paired-end reads, accounting for ~24 Gb of sequence data, were generated from tender shoots, young leaves, flower buds and flowers using Illumina HiSeq 2000 platform. De novo assembly with further processing and filtering yielded a set of 67,923 transcripts with an average length of 685 bp and an N50 of 995 bp. Based on sequence similarity searches against public databases, a total of 39,475 transcripts were annotated with gene descriptions, conserved protein domains or gene ontology (GO) terms. Candidate genes for major metabolic pathways involved in tea quality were identified and experimentally validated using RT-qPCR. Further gene expression profiles showed that they are differentially regulated at different developmental stages. To gain insights into the evolution of these genes, we aligned them to the previously cloned orthologous genes in C. sinensis, and found that considerable nucleotide variation within several genes involved in important secondary metabolic biosynthesis pathways, of which flavone synthase II gene (FNSII) is the most variable between these two species. Moreover, comparative analyses revealed that C. taliensis shows a remarkable expansion of LEA genes, compared to C. sinensis, which might contribute to the observed stronger stress resistance of C. taliensis. We reported the first large-coverage transcriptome datasets for C. taliensis using the next-generation sequencing technology. Such comprehensive EST datasets provide an unprecedented opportunity for identifying genes involved in several major metabolic pathways and will accelerate functional genomic studies and genetic improvement efforts of tea trees in the future.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Uruguay 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Researcher 11 19%
Student > Master 9 16%
Student > Doctoral Student 4 7%
Professor 4 7%
Other 13 22%
Unknown 6 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 66%
Biochemistry, Genetics and Molecular Biology 5 9%
Unspecified 1 2%
Nursing and Health Professions 1 2%
Environmental Science 1 2%
Other 2 3%
Unknown 10 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 07 September 2016.
All research outputs
#4,016,790
of 22,805,349 outputs
Outputs from BMC Genomics
#1,647
of 10,650 outputs
Outputs of similar age
#51,144
of 264,063 outputs
Outputs of similar age from BMC Genomics
#46
of 265 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,650 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 84% 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 264,063 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 265 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.