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Simultaneous Identification of Multiple Causal Mutations in Rice

Overview of attention for article published in Frontiers in Plant Science, January 2017
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Title
Simultaneous Identification of Multiple Causal Mutations in Rice
Published in
Frontiers in Plant Science, January 2017
DOI 10.3389/fpls.2016.02055
Pubmed ID
Authors

Yan, Wei, Chen, Zhufeng, Lu, Jiawei, Xu, Chunjue, Xie, Gang, Li, Yiqi, Deng, Xing Wang, He, Hang, Tang, Xiaoyan

Abstract

Next-generation sequencing technologies (NGST) are being used to discover causal mutations in ethyl methanesulfonate (EMS)-mutagenized plant populations. However, the published protocols often deliver too many candidate sites and sometimes fail to find the mutant gene of interest. Accurate identification of the causal mutation from massive background polymorphisms and sequencing deficiencies remains challenging. Here we describe a NGST-based method, named SIMM, that can simultaneously identify the causal mutations in multiple independent mutants. Multiple rice mutants derived from the same parental line were back-crossed, and for each mutant, the derived F2 individuals of the recessive mutant phenotype were pooled and sequenced. The resulting sequences were aligned to the Nipponbare reference genome, and single nucleotide polymorphisms (SNPs) were subsequently compared among the mutants. Allele index (AI) and Euclidean distance (ED) were incorporated into the analysis to reduce noises caused by background polymorphisms and re-sequencing errors. Corrections of sequence bias against GC- and AT-rich sequences in the candidate region were conducted when necessary. Using this method, we successfully identified seven new mutant alleles from Huanghuazhan (HHZ), an elite indica rice cultivar in China. All mutant alleles were validated by phenotype association assay. A pipeline based on Perl scripts for SIMM is publicly available at https://sourceforge.net/projects/simm/.

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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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 6 16%
Student > Master 4 11%
Student > Doctoral Student 3 8%
Lecturer 2 5%
Other 1 3%
Unknown 13 34%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 42%
Biochemistry, Genetics and Molecular Biology 5 13%
Computer Science 1 3%
Engineering 1 3%
Design 1 3%
Other 0 0%
Unknown 14 37%
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 15 February 2017.
All research outputs
#14,048,845
of 22,953,506 outputs
Outputs from Frontiers in Plant Science
#7,339
of 20,383 outputs
Outputs of similar age
#221,698
of 418,227 outputs
Outputs of similar age from Frontiers in Plant Science
#187
of 516 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,383 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 60% 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 418,227 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 516 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 62% of its contemporaries.