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Attention Score in Context
| Title |
QTL Detection and Elite Alleles Mining for Stigma Traits in Oryza sativa by Association Mapping
|
|---|---|
| Published in |
Frontiers in Plant Science, August 2016
|
| DOI | 10.3389/fpls.2016.01188 |
| Pubmed ID | |
| Authors |
Xiaojing Dang, Erbao Liu, Yinfeng Liang, Qiangming Liu, Caleb M. Breria, Delin Hong |
| Abstract |
Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across 2 years and assessed their genotypic variation with 249 simple sequence repeat (SSR) markers. By combining phenotypic and genotypic data, a genome-wide association (GWA) map was generated. Large phenotypic variations in stigma length (STL), stigma brush-shaped part length (SBPL) and stigma non-brush-shaped part length (SNBPL) were found. Significant positive correlations were identified among stigma traits. In total, 2072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs) for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL, and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 22% |
| Researcher | 3 | 17% |
| Student > Master | 2 | 11% |
| Student > Bachelor | 1 | 6% |
| Other | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 6 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 50% |
| Nursing and Health Professions | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Unknown | 7 | 39% |
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 25 August 2016.
All research outputs
#18,467,278
of 22,882,389 outputs
Outputs from Frontiers in Plant Science
#13,816
of 20,270 outputs
Outputs of similar age
#279,252
of 361,775 outputs
Outputs of similar age from Frontiers in Plant Science
#292
of 464 outputs
Altmetric has tracked 22,882,389 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,270 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 464 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.