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Facile mutant identification via a single parental backcross method and application of whole genome sequencing based mapping pipelines

Overview of attention for article published in Frontiers in Plant Science, January 2013
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
Facile mutant identification via a single parental backcross method and application of whole genome sequencing based mapping pipelines
Published in
Frontiers in Plant Science, January 2013
DOI 10.3389/fpls.2013.00362
Pubmed ID
Authors

Robert S. Allen, Kenlee Nakasugi, Rachel L. Doran, Anthony A. Millar, Peter M. Waterhouse

Abstract

Forward genetic screens have identified numerous genes involved in development and metabolism, and remain a cornerstone of biological research. However, to locate a causal mutation, the practice of crossing to a polymorphic background to generate a mapping population can be problematic if the mutant phenotype is difficult to recognize in the hybrid F2 progeny, or dependent on parental specific traits. Here in a screen for leaf hyponasty mutants, we have performed a single backcross of an Ethane Methyl Sulphonate (EMS) generated hyponastic mutant to its parent. Whole genome deep sequencing of a bulked homozygous F2 population and analysis via the Next Generation EMS mutation mapping pipeline (NGM) unambiguously determined the causal mutation to be a single nucleotide polymorphisim (SNP) residing in HASTY, a previously characterized gene involved in microRNA biogenesis. We have evaluated the feasibility of this backcross approach using three additional SNP mapping pipelines; SHOREmap, the GATK pipeline, and the samtools pipeline. Although there was variance in the identification of EMS SNPs, all returned the same outcome in clearly identifying the causal mutation in HASTY. The simplicity of performing a single parental backcross and genome sequencing a small pool of segregating mutants has great promise for identifying mutations that may be difficult to map using conventional approaches.

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X Demographics

The data shown below were collected from the profiles of 2 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 2%
United Kingdom 2 2%
Netherlands 1 <1%
Germany 1 <1%
Australia 1 <1%
Mexico 1 <1%
China 1 <1%
United States 1 <1%
Unknown 108 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 31%
Researcher 32 27%
Student > Master 14 12%
Student > Bachelor 6 5%
Professor > Associate Professor 5 4%
Other 11 9%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 77 65%
Biochemistry, Genetics and Molecular Biology 20 17%
Computer Science 2 2%
Medicine and Dentistry 2 2%
Engineering 2 2%
Other 1 <1%
Unknown 14 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 September 2013.
All research outputs
#18,347,414
of 22,721,584 outputs
Outputs from Frontiers in Plant Science
#13,582
of 19,967 outputs
Outputs of similar age
#218,062
of 280,761 outputs
Outputs of similar age from Frontiers in Plant Science
#216
of 517 outputs
Altmetric has tracked 22,721,584 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 19,967 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 280,761 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 517 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 53% of its contemporaries.