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Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon

Overview of attention for article published in Frontiers in Plant Science, November 2017
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Title
Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon
Published in
Frontiers in Plant Science, November 2017
DOI 10.3389/fpls.2017.02055
Pubmed ID
Authors

Satoru Koda, Yoshihiko Onda, Hidetoshi Matsui, Kotaro Takahagi, Yukiko Uehara-Yamaguchi, Minami Shimizu, Komaki Inoue, Takuhiro Yoshida, Tetsuya Sakurai, Hiroshi Honda, Shinto Eguchi, Ryuei Nishii, Keiichi Mochida

Abstract

We report the comprehensive identification of periodic genes and their network inference, based on a gene co-expression analysis and an Auto-Regressive eXogenous (ARX) model with a group smoothly clipped absolute deviation (SCAD) method using a time-series transcriptome dataset in a model grass, Brachypodium distachyon. To reveal the diurnal changes in the transcriptome in B. distachyon, we performed RNA-seq analysis of its leaves sampled through a diurnal cycle of over 48 h at 4 h intervals using three biological replications, and identified 3,621 periodic genes through our wavelet analysis. The expression data are feasible to infer network sparsity based on ARX models. We found that genes involved in biological processes such as transcriptional regulation, protein degradation, and post-transcriptional modification and photosynthesis are significantly enriched in the periodic genes, suggesting that these processes might be regulated by circadian rhythm in B. distachyon. On the basis of the time-series expression patterns of the periodic genes, we constructed a chronological gene co-expression network and identified putative transcription factors encoding genes that might be involved in the time-specific regulatory transcriptional network. Moreover, we inferred a transcriptional network composed of the periodic genes in B. distachyon, aiming to identify genes associated with other genes through variable selection by grouping time points for each gene. Based on the ARX model with the group SCAD regularization using our time-series expression datasets of the periodic genes, we constructed gene networks and found that the networks represent typical scale-free structure. Our findings demonstrate that the diurnal changes in the transcriptome in B. distachyon leaves have a sparse network structure, demonstrating the spatiotemporal gene regulatory network over the cyclic phase transitions in B. distachyon diurnal growth.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 27%
Researcher 4 10%
Student > Bachelor 4 10%
Professor > Associate Professor 4 10%
Student > Master 4 10%
Other 7 17%
Unknown 7 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 34%
Biochemistry, Genetics and Molecular Biology 11 27%
Computer Science 4 10%
Nursing and Health Professions 1 2%
Mathematics 1 2%
Other 2 5%
Unknown 8 20%
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 02 January 2018.
All research outputs
#13,573,826
of 23,009,818 outputs
Outputs from Frontiers in Plant Science
#6,737
of 20,507 outputs
Outputs of similar age
#216,053
of 438,547 outputs
Outputs of similar age from Frontiers in Plant Science
#176
of 436 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,507 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 64% 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 438,547 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 436 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 56% of its contemporaries.