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Mendeley readers
Attention Score in Context
| Title |
Cloning of quantitative trait genes from rice reveals conservation and divergence of photoperiod flowering pathways in Arabidopsis and rice
|
|---|---|
| Published in |
Frontiers in Plant Science, May 2014
|
| DOI | 10.3389/fpls.2014.00193 |
| Pubmed ID | |
| Authors |
Kazuki Matsubara, Kiyosumi Hori, Eri Ogiso-Tanaka, Masahiro Yano |
| Abstract |
Flowering time in rice (Oryza sativa L.) is determined primarily by daylength (photoperiod), and natural variation in flowering time is due to quantitative trait loci involved in photoperiodic flowering. To date, genetic analysis of natural variants in rice flowering time has resulted in the positional cloning of at least 12 quantitative trait genes (QTGs), including our recently cloned QTGs, Hd17, and Hd16. The QTGs have been assigned to specific photoperiodic flowering pathways. Among them, 9 have homologs in the Arabidopsis genome, whereas it was evident that there are differences in the pathways between rice and Arabidopsis, such that the rice Ghd7-Ehd1-Hd3a/RFT1 pathway modulated by Hd16 is not present in Arabidopsis. In this review, we describe QTGs underlying natural variation in rice flowering time. Additionally, we discuss the implications of the variation in adaptive divergence and its importance in rice breeding. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sri Lanka | 1 | 1% |
| France | 1 | 1% |
| Unknown | 91 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 25% |
| Student > Ph. D. Student | 15 | 16% |
| Student > Master | 15 | 16% |
| Student > Bachelor | 9 | 10% |
| Professor > Associate Professor | 5 | 5% |
| Other | 12 | 13% |
| Unknown | 14 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 62 | 67% |
| Biochemistry, Genetics and Molecular Biology | 12 | 13% |
| Environmental Science | 2 | 2% |
| Immunology and Microbiology | 1 | 1% |
| Decision Sciences | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 14 | 15% |
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 13 May 2014.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from Frontiers in Plant Science
#19,713
of 24,593 outputs
Outputs of similar age
#208,967
of 241,610 outputs
Outputs of similar age from Frontiers in Plant Science
#94
of 164 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,593 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 164 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.