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Transcriptome analysis in petals and leaves of chrysanthemums with different chlorophyll levels

Overview of attention for article published in BMC Plant Biology, November 2017
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Title
Transcriptome analysis in petals and leaves of chrysanthemums with different chlorophyll levels
Published in
BMC Plant Biology, November 2017
DOI 10.1186/s12870-017-1156-6
Pubmed ID
Authors

Akemi Ohmiya, Katsutomo Sasaki, Kenji Nashima, Chihiro Oda-Yamamizo, Masumi Hirashima, Katsuhiko Sumitomo

Abstract

Chlorophylls (Chls) are magnesium-containing tetrapyrrole macromolecules responsible for the green color in plants. The Chl metabolic pathway has been intensively studied and nearly all the enzymes involved in the pathway have been identified and characterized. Synthesis and activity of these enzymes are tightly regulated in tissue- and developmental stage-specific manners. Leaves contain substantial amounts of Chls because Chls are indispensable for photosynthesis. In contrast, petals generally contain only trace amounts of Chls, which if present would mask the bright petal color. Limited information is available about the mechanisms that control such tissue-specific accumulation of Chls. To identify the regulatory steps that control Chl accumulation, we compared gene expression in petals and leaves of chrysanthemum cultivars with different Chl levels. Microarray and quantitative real-time PCR analyses showed that the expression levels of Chl biosynthesis genes encoding glutamyl-tRNA reductase, Mg-protoporphyrin IX chelatase, Mg-protoporphyrin IX monomethylester cyclase, and protochlorophyllide oxidoreductase were well associated with Chl content: their expression levels were lower in white petals than in green petals, and were highest in leaves. Among Chl catabolic genes, expression of STAY-GREEN, encoding Mg-dechelatase, which is a key enzyme controlling Chl degradation, was considerably higher in white and green petals than in leaves. We searched for transcription factor genes whose expression was well related to Chl level in petals and leaves and found three such genes encoding MYB113, CONSTANS-like 16, and DREB and EAR motif protein. From our transcriptome analysis, we assume that a low rate of Chl biosynthesis and a high rate of Chl degradation lead to the absence of Chls in white chrysanthemum petals. We identified several candidate transcription factors that might affect Chl accumulation in chrysanthemum petals. Functional analysis of these transcription factors will provide a basis for future molecular studies of tissue-specific Chl accumulation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Student > Ph. D. Student 4 14%
Student > Bachelor 3 11%
Student > Master 2 7%
Lecturer > Senior Lecturer 1 4%
Other 2 7%
Unknown 10 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 39%
Biochemistry, Genetics and Molecular Biology 4 14%
Medicine and Dentistry 1 4%
Unknown 12 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 December 2017.
All research outputs
#14,959,314
of 23,008,860 outputs
Outputs from BMC Plant Biology
#1,287
of 3,283 outputs
Outputs of similar age
#192,253
of 324,977 outputs
Outputs of similar age from BMC Plant Biology
#27
of 82 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,283 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 54% 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 324,977 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 82 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 62% of its contemporaries.