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| Title |
Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis
|
|---|---|
| Published in |
Genetics and Molecular Biology, October 2017
|
| DOI | 10.1590/1678-4685-gmb-2017-0013 |
| Pubmed ID | |
| Authors |
Hongyi Nie, Xiaoyan Liu, Jiao Pan, Wenfeng Li, Zhiguo Li, Shaowu Zhang, Shenglu Chen, Xiaoqing Miao, Nenggan Zheng, Songkun Su |
| Abstract |
China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production. |
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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 20% |
| Student > Master | 4 | 13% |
| Researcher | 3 | 10% |
| Student > Bachelor | 3 | 10% |
| Student > Doctoral Student | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 9 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 43% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Nursing and Health Professions | 1 | 3% |
| Earth and Planetary Sciences | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 10 | 33% |
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 06 October 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Genetics and Molecular Biology
#647
of 772 outputs
Outputs of similar age
#291,731
of 331,926 outputs
Outputs of similar age from Genetics and Molecular Biology
#9
of 15 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 772 research outputs from this source. They receive a mean Attention Score of 4.8. 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 15 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.