You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study
|
|---|---|
| Published in |
BMC Genomics, October 2017
|
| DOI | 10.1186/s12864-017-4221-5 |
| Pubmed ID | |
| Authors |
Jian Zhang, Kai Chen, Yunlong Pang, Shahzad Amir Naveed, Xiuqin Zhao, Xiaoqian Wang, Yun Wang, Michael Dingkuhn, Julie Pasuquin, Zhikang Li, Jianlong Xu |
| Abstract |
Ferrous iron (Fe) and zinc (Zn) at high concentration in the soil cause heavy metal toxicity and greatly affect rice yield and quality. To improve rice production, understanding the genetic and molecular resistance mechanisms to excess Fe and Zn in rice is essential. Genome-wide association study (GWAS) is an effective way to identify loci and favorable alleles governing Fe and Zn toxicty as well as dissect the genetic relationship between them in a genetically diverse population. A total of 29 and 31 putative QTL affecting shoot height (SH), root length (RL), shoot fresh weight (SFW), shoot dry weight (SDW), root dry weight (RDW), shoot water content (SWC) and shoot ion concentrations (SFe or SZn) were identified at seedling stage in Fe and Zn experiments, respectively. Five toxicity tolerance QTL (qSdw3a, qSdw3b, qSdw12 and qSFe5 / qSZn5) were detected in the same genomic regions under the two stress conditions and 22 candidate genes for 10 important QTL regions were also determined by haplotype analyses. Rice plants share partial genetic overlaps of Fe and Zn toxicity tolerance at seedling stage. Candidate genes putatively affecting Fe and Zn toxicity tolerance identified in this study provide valuable information for future functional characterization and improvement of rice tolerance to Fe and Zn toxicity by marker-assisted selection or designed QTL pyramiding. |
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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 22% |
| Researcher | 15 | 22% |
| Student > Master | 9 | 13% |
| Student > Bachelor | 3 | 4% |
| Professor > Associate Professor | 3 | 4% |
| Other | 8 | 12% |
| Unknown | 14 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 34 | 51% |
| Biochemistry, Genetics and Molecular Biology | 10 | 15% |
| Unspecified | 2 | 3% |
| Computer Science | 1 | 1% |
| Economics, Econometrics and Finance | 1 | 1% |
| Other | 2 | 3% |
| Unknown | 17 | 25% |
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 29 October 2017.
All research outputs
#18,575,277
of 23,007,053 outputs
Outputs from BMC Genomics
#8,226
of 10,693 outputs
Outputs of similar age
#251,532
of 328,360 outputs
Outputs of similar age from BMC Genomics
#157
of 202 outputs
Altmetric has tracked 23,007,053 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 10,693 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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 328,360 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 202 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.