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Attention Score in Context
| Title |
Genetic Map Construction and Fiber Quality QTL Mapping Using the CottonSNP80K Array in Upland Cotton
|
|---|---|
| Published in |
Frontiers in Plant Science, February 2018
|
| DOI | 10.3389/fpls.2018.00225 |
| Pubmed ID | |
| Authors |
Zhaoyun Tan, Zhiqin Zhang, Xujing Sun, Qianqian Li, Ying Sun, Peng Yang, Wenwen Wang, Xueying Liu, Chunling Chen, Dexing Liu, Zhonghua Teng, Kai Guo, Jian Zhang, Dajun Liu, Zhengsheng Zhang |
| Abstract |
Cotton fiber quality traits are controlled by multiple quantitative trait loci (QTL), and the improvement of these traits requires extensive germplasm. Herein, an Upland cotton cultivar from America, Acala Maxxa, was crossed with a local high fiber quality cultivar, Yumian 1, and 180 recombinant inbred lines (RILs) were obtained. In order to dissect the genetic basis of fiber quality differences between these parents, a genetic map containing 12116 SNP markers was constructed using the CottonSNP80K assay, which covered 3741.81 cM with an average distance of 0.31 cM between markers. Based on the genetic map and growouts in three environments, we detected a total of 104 QTL controlling fiber quality traits. Among these QTL, 25 were detected in all three environments and 35 in two environments. Meanwhile, 19 QTL clusters were also identified, and nine contained at least one stable QTL (detected in three environments for a given trait). These stable QTL or QTL clusters are priorities for fine mapping, identifying candidate genes, elaborating molecular mechanisms of fiber development, and application in cotton breeding programs by marker-assisted selection (MAS). |
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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 18% |
| Researcher | 3 | 14% |
| Student > Doctoral Student | 2 | 9% |
| Student > Postgraduate | 2 | 9% |
| Student > Master | 2 | 9% |
| Other | 3 | 14% |
| Unknown | 6 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 50% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Unknown | 8 | 36% |
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 03 April 2018.
All research outputs
#20,476,619
of 23,036,991 outputs
Outputs from Frontiers in Plant Science
#16,475
of 20,588 outputs
Outputs of similar age
#291,831
of 330,050 outputs
Outputs of similar age from Frontiers in Plant Science
#420
of 472 outputs
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So far Altmetric has tracked 20,588 research outputs from this source. They receive a mean Attention Score of 4.0. 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 472 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.