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Genome-wide identification of soybean microRNA responsive to soybean cyst nematodes infection by deep sequencing

Overview of attention for article published in BMC Genomics, August 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
Genome-wide identification of soybean microRNA responsive to soybean cyst nematodes infection by deep sequencing
Published in
BMC Genomics, August 2017
DOI 10.1186/s12864-017-3963-4
Pubmed ID
Authors

Bin Tian, Shichen Wang, Timothy C. Todd, Charles D. Johnson, Guiliang Tang, Harold N. Trick

Abstract

The soybean cyst nematode (SCN), Heterodera glycines, is one of the most devastating diseases limiting soybean production worldwide. It is known that small RNAs, including microRNAs (miRNAs) and small interfering RNAs (siRNAs), play important roles in regulating plant growth and development, defense against pathogens, and responses to environmental changes. In order to understand the role of soybean miRNAs during SCN infection, we analyzed 24 small RNA libraries including three biological replicates from two soybean cultivars (SCN susceptible KS4607, and SCN HG Type 7 resistant KS4313N) that were grown under SCN-infested and -noninfested soil at two different time points (SCN feeding establishment and egg production). In total, 537 known and 70 putative novel miRNAs in soybean were identified from a total of 0.3 billion reads (average about 13.5 million reads for each sample) with the programs of Bowtie and miRDeep2 mapper. Differential expression analyses were carried out using edgeR to identify miRNAs involved in the soybean-SCN interaction. Comparative analysis of miRNA profiling indicated a total of 60 miRNAs belonging to 25 families that might be specifically related to cultivar responses to SCN. Quantitative RT-PCR validated similar miRNA interaction patterns as sequencing results. These findings suggest that miRNAs are likely to play key roles in soybean response to SCN. The present work could provide a framework for miRNA functional identification and the development of novel approaches for improving soybean SCN resistance in future studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 16%
Researcher 9 13%
Student > Ph. D. Student 8 11%
Student > Bachelor 7 10%
Student > Doctoral Student 7 10%
Other 10 14%
Unknown 18 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 33%
Biochemistry, Genetics and Molecular Biology 12 17%
Engineering 3 4%
Computer Science 2 3%
Medicine and Dentistry 2 3%
Other 6 9%
Unknown 22 31%
Attention Score in Context

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 22 March 2018.
All research outputs
#7,408,420
of 23,316,003 outputs
Outputs from BMC Genomics
#3,489
of 10,742 outputs
Outputs of similar age
#116,866
of 318,371 outputs
Outputs of similar age from BMC Genomics
#67
of 223 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 10,742 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 66% 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 318,371 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 62% of its contemporaries.
We're also able to compare this research output to 223 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 69% of its contemporaries.