| Title |
A Versatile Vector Toolkit for Functional Analysis of Rice Genes
|
|---|---|
| Published in |
Rice, April 2018
|
| DOI | 10.1186/s12284-018-0220-7 |
| Pubmed ID | |
| Authors |
Feng He, Fan Zhang, Wenxian Sun, Yuese Ning, Guo-Liang Wang |
| Abstract |
Rice (Oryza sativa) is the main food for half of the world's population, and is considered the model for molecular biology studies of monocotyledon species. Although the rice genome was completely sequenced about 15 years ago, the function of most rice genes is still unknown. In this study, we developed a vector toolkit that contains 42 vectors for transient expression studies in rice protoplasts and stable expression analysis in transgenic rice. These vectors have been successfully used to study protein subcellular localization, protein-protein interaction, gene overexpression, and the CRISPR/Cas9-mediated gene editing. A novel feature of these vectors is that they contain a universal multiple cloning site, which enables more than 99% of the rice coding sequences to be conveniently transferred between vectors. The versatile vectors represent a highly efficient and high-throughput toolkit for functional analysis of rice genes. |
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 % |
|---|---|---|
| Unknown | 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 20% |
| Student > Ph. D. Student | 11 | 18% |
| Student > Bachelor | 5 | 8% |
| Student > Postgraduate | 5 | 8% |
| Student > Doctoral Student | 4 | 7% |
| Other | 6 | 10% |
| Unknown | 18 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 34% |
| Biochemistry, Genetics and Molecular Biology | 17 | 28% |
| Unspecified | 1 | 2% |
| Chemistry | 1 | 2% |
| Unknown | 21 | 34% |
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 23 April 2018.
All research outputs
#18,604,390
of 23,045,021 outputs
Outputs from Rice
#252
of 389 outputs
Outputs of similar age
#253,649
of 326,937 outputs
Outputs of similar age from Rice
#12
of 16 outputs
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We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.