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Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

Overview of attention for article published in BMC Genomics, January 2016
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Title
Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions
Published in
BMC Genomics, January 2016
DOI 10.1186/s12864-016-2378-y
Pubmed ID
Authors

Li Song, Silvas Prince, Babu Valliyodan, Trupti Joshi, Joao V. Maldonado dos Santos, Jiaojiao Wang, Li Lin, Jinrong Wan, Yongqin Wang, Dong Xu, Henry T. Nguyen

Abstract

Soybean is a major crop that provides an important source of protein and oil to humans and animals, but its production can be dramatically decreased by the occurrence of drought stress. Soybeans can survive drought stress if there is a robust and deep root system at the early vegetative growth stage. However, little is known about the genome-wide molecular mechanisms contributing to soybean root system architecture. This study was performed to gain knowledge on transcriptome changes and related molecular mechanisms contributing to soybean root development under water limited conditions. The soybean Williams 82 genotype was subjected to very mild stress (VMS), mild stress (MS) and severe stress (SS) conditions, as well as recovery from the severe stress after re-watering (SR). In total, 6,609 genes in the roots showed differential expression patterns in response to different water-deficit stress levels. Genes involved in hormone (Auxin/Ethylene), carbohydrate, and cell wall-related metabolism (XTH/lipid/flavonoids/lignin) pathways were differentially regulated in the soybean root system. Several transcription factors (TFs) regulating root growth and responses under varying water-deficit conditions were identified and the expression patterns of six TFs were found to be common across the stress levels. Further analysis on the whole plant level led to the finding of tissue-specific or water-deficit levels specific regulation of transcription factors. Analysis of the over-represented motif of different gene groups revealed several new cis-elements associated with different levels of water deficit. The expression patterns of 18 genes were confirmed byquantitative reverse transcription polymerase chain reaction method and demonstrated the accuracy and effectiveness of RNA-Seq. The primary root specific transcriptome in soybean can enable a better understanding of the root response to water deficit conditions. The genes detected in root tissues that were associated with key hormones, carbohydrates, and cell wall-related metabolism could play a vital role in achieving drought tolerance and could be promising candidates for future functional characterization. TFs involved in the soybean root and at the whole plant level could be used for future network analysis between TFs and cis-elements. All of these findings will be helpful in elucidating the molecular mechanisms associated with water stress responses in soybean roots.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 154 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 24%
Student > Master 26 17%
Researcher 19 12%
Professor > Associate Professor 10 6%
Other 8 5%
Other 28 18%
Unknown 27 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 83 54%
Biochemistry, Genetics and Molecular Biology 22 14%
Environmental Science 4 3%
Social Sciences 3 2%
Computer Science 3 2%
Other 8 5%
Unknown 32 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 17 May 2016.
All research outputs
#12,942,432
of 22,840,638 outputs
Outputs from BMC Genomics
#4,569
of 10,655 outputs
Outputs of similar age
#180,300
of 395,862 outputs
Outputs of similar age from BMC Genomics
#110
of 263 outputs
Altmetric has tracked 22,840,638 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 55% 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 395,862 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 53% of its contemporaries.
We're also able to compare this research output to 263 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 56% of its contemporaries.