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Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes

Overview of attention for article published in BMC Genomics, October 2015
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

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9 tweeters

Citations

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28 Dimensions

Readers on

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59 Mendeley
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Title
Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-2062-7
Pubmed ID
Authors

Hai-Ming Xu, Xiang-Dong Kong, Fei Chen, Ji-Xiang Huang, Xiang-Yang Lou, Jian-Yi Zhao

Abstract

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 20%
Researcher 10 17%
Student > Doctoral Student 7 12%
Student > Master 7 12%
Student > Bachelor 4 7%
Other 11 19%
Unknown 8 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 44%
Biochemistry, Genetics and Molecular Biology 18 31%
Engineering 3 5%
Computer Science 2 3%
Unknown 10 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 01 November 2015.
All research outputs
#4,798,761
of 16,638,522 outputs
Outputs from BMC Genomics
#2,456
of 9,107 outputs
Outputs of similar age
#81,908
of 287,961 outputs
Outputs of similar age from BMC Genomics
#283
of 996 outputs
Altmetric has tracked 16,638,522 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 9,107 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 72% of its peers.
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 287,961 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 996 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.