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The large-scale investigation of gene expression in Leymus chinensis stigmas provides a valuable resource for understanding the mechanisms of poaceae self-incompatibility

Overview of attention for article published in BMC Genomics, January 2014
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1 tweeter

Citations

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Title
The large-scale investigation of gene expression in Leymus chinensis stigmas provides a valuable resource for understanding the mechanisms of poaceae self-incompatibility
Published in
BMC Genomics, January 2014
DOI 10.1186/1471-2164-15-399
Pubmed ID
24886329
Authors

Qingyuan Zhou, Junting Jia, Xing Huang, Xueqing Yan, Liqin Cheng, Shuangyan Chen, Xiaoxia Li, Xianjun Peng, Gongshe Liu

Abstract

Many Poaceae species show a gametophytic self-incompatibility (GSI) system, which is controlled by at least two independent and multiallelic loci, S and Z. Until currently, the gene products for S and Z were unknown. Grass SI plant stigmas discriminate between pollen grains that land on its surface and support compatible pollen tube growth and penetration into the stigma, whereas recognizing incompatible pollen and thus inhibiting pollination behaviors. Leymus chinensis (Trin.) Tzvel. (sheepgrass) is a Poaceae SI species. A comprehensive analysis of sheepgrass stigma transcriptome may provide valuable information for understanding the mechanism of pollen-stigma interactions and grass SI.

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Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 25%
Student > Ph. D. Student 7 25%
Student > Doctoral Student 5 18%
Student > Bachelor 3 11%
Researcher 3 11%
Other 3 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 68%
Biochemistry, Genetics and Molecular Biology 8 29%
Mathematics 1 4%

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 27 May 2014.
All research outputs
#3,058,355
of 3,814,325 outputs
Outputs from BMC Genomics
#2,829
of 3,497 outputs
Outputs of similar age
#75,560
of 94,905 outputs
Outputs of similar age from BMC Genomics
#201
of 251 outputs
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So far Altmetric has tracked 3,497 research outputs from this source. They receive a mean Attention Score of 3.4. 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 251 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.

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