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CandiSSR: An Efficient Pipeline used for Identifying Candidate Polymorphic SSRs Based on Multiple Assembled Sequences

Overview of attention for article published in Frontiers in Plant Science, January 2016
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Title
CandiSSR: An Efficient Pipeline used for Identifying Candidate Polymorphic SSRs Based on Multiple Assembled Sequences
Published in
Frontiers in Plant Science, January 2016
DOI 10.3389/fpls.2015.01171
Pubmed ID
Authors

En-Hua Xia, Qiu-Yang Yao, Hai-Bin Zhang, Jian-Jun Jiang, Li-Ping Zhang, Li-Zhi Gao

Abstract

Simple sequence repeats (SSRs), also known as microsatellites, are ubiquitous short tandem duplications commonly found in genomes and/or transcriptomes of diverse organisms. They represent one of the most powerful molecular markers for genetic analysis and breeding programs because of their high mutation rate and neutral evolution. However, traditionally experimental screening of the SSR polymorphic status and their subsequent applicability to genetic studies are extremely labor-intensive and time-consuming. Thankfully, the recently decreased costs of next generation sequencing and increasing availability of large genome and/or transcriptome sequences have provided an excellent opportunity and sources for large-scale mining this type of molecular markers. However, current tools are limited. Thus we here developed a new pipeline, CandiSSR, to identify candidate polymorphic SSRs (PolySSRs) based on the multiple assembled sequences. The pipeline allows users to identify putative PolySSRs not only from the transcriptome datasets but also from multiple assembled genome sequences. In addition, two confidence metrics including standard deviation and missing rate of the SSR repetitions are provided to systematically assess the feasibility of the detected PolySSRs for subsequent application to genetic characterization. Meanwhile, primer pairs for each identified PolySSR are also automatically designed and further evaluated by the global sequence similarities of the primer-binding region, ensuring the successful rate of the marker development. Screening rice genomes with CandiSSR and subsequent experimental validation showed an accuracy rate of over 90%. Besides, the application of CandiSSR has successfully identified a large number of PolySSRs in the Arabidopsis genomes and Camellia transcriptomes. CandiSSR and the PolySSR marker sources are publicly available at: http://www.plantkingdomgdb.com/CandiSSR/index.html.

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The data shown below were collected from the profiles of 3 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 16%
Student > Ph. D. Student 4 13%
Researcher 4 13%
Student > Master 4 13%
Student > Postgraduate 2 6%
Other 4 13%
Unknown 8 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 32%
Biochemistry, Genetics and Molecular Biology 9 29%
Arts and Humanities 1 3%
Mathematics 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 7 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 March 2017.
All research outputs
#14,243,953
of 22,837,982 outputs
Outputs from Frontiers in Plant Science
#8,156
of 20,152 outputs
Outputs of similar age
#205,855
of 393,726 outputs
Outputs of similar age from Frontiers in Plant Science
#139
of 458 outputs
Altmetric has tracked 22,837,982 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,152 research outputs from this source. They receive a mean Attention Score of 4.0. 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 393,726 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 458 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 65% of its contemporaries.