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Attention Score in Context
| Title |
Isolation of ripening-related genes from ethylene/1-MCP treated papaya through RNA-seq
|
|---|---|
| Published in |
BMC Genomics, August 2017
|
| DOI | 10.1186/s12864-017-4072-0 |
| Pubmed ID | |
| Authors |
Yan Hong Shen, Bing Guo Lu, Li Feng, Fei Ying Yang, Jiao Jiao Geng, Ray Ming, Xiao Jing Chen |
| Abstract |
Since papaya is a typical climacteric fruit, exogenous ethylene (ETH) applications can induce premature and quicker ripening, while 1-methylcyclopropene (1-MCP) slows down the ripening processes. Differential gene expression in ETH or 1-MCP-treated papaya fruits accounts for the ripening processes. To isolate the key ripening-related genes and better understand fruit ripening mechanisms, transcriptomes of ETH or 1-MCP-treated, and non-treated (Control Group, CG) papaya fruits were sequenced using Illumina Hiseq2500. A total of 18,648 (1-MCP), 19,093 (CG), and 15,321 (ETH) genes were detected, with the genes detected in the ETH-treatment being the least. This suggests that ETH may inhibit the expression of some genes. Based on the differential gene expression (DGE) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, 53 fruit ripening-related genes were selected: 20 cell wall-related genes, 18 chlorophyll and carotenoid metabolism-related genes, four proteinases and their inhibitors, six plant hormone signal transduction pathway genes, four transcription factors, and one senescence-associated gene. Reverse transcription quantitative PCR (RT-qPCR) analyses confirmed the results of RNA-seq and verified that the expression pattern of six genes is consistent with the fruit senescence process. Based on the expression profiling of genes in carbohydrate metabolic process, chlorophyll metabolism pathway, and carotenoid metabolism pathway, the mechanism of pulp softening and coloration of papaya was deduced and discussed. We illustrate that papaya fruit softening is a complex process with significant cell wall hydrolases, such as pectinases, cellulases, and hemicellulases involved in the process. Exogenous ethylene accelerates the coloration of papaya changing from green to yellow. This is likely due to the inhibition of chlorophyll biosynthesis and the α-branch of carotenoid metabolism. Chy-b may play an important role in the yellow color of papaya fruit. Comparing the differential gene expression in ETH/1-MCP-treated papaya using RNA-seq is a sound approach to isolate ripening-related genes. The results of this study can improve our understanding of papaya fruit ripening molecular mechanism and reveal candidate fruit ripening-related genes for further research. |
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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 56 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 20% |
| Student > Master | 9 | 16% |
| Researcher | 6 | 11% |
| Student > Bachelor | 5 | 9% |
| Student > Doctoral Student | 4 | 7% |
| Other | 1 | 2% |
| Unknown | 20 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 34% |
| Biochemistry, Genetics and Molecular Biology | 9 | 16% |
| Medicine and Dentistry | 3 | 5% |
| Chemical Engineering | 1 | 2% |
| Computer Science | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 22 | 39% |
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 02 September 2017.
All research outputs
#17,913,495
of 22,999,744 outputs
Outputs from BMC Genomics
#7,611
of 10,692 outputs
Outputs of similar age
#226,832
of 316,373 outputs
Outputs of similar age from BMC Genomics
#132
of 210 outputs
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So far Altmetric has tracked 10,692 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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