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Tools for Genetic Studies in Experimental Populations of Polyploids

Overview of attention for article published in Frontiers in Plant Science, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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16 X users

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Title
Tools for Genetic Studies in Experimental Populations of Polyploids
Published in
Frontiers in Plant Science, April 2018
DOI 10.3389/fpls.2018.00513
Pubmed ID
Authors

Peter M. Bourke, Roeland E. Voorrips, Richard G. F. Visser, Chris Maliepaard

Abstract

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 291 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 291 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 20%
Researcher 47 16%
Student > Master 41 14%
Student > Doctoral Student 23 8%
Student > Bachelor 22 8%
Other 28 10%
Unknown 73 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 143 49%
Biochemistry, Genetics and Molecular Biology 48 16%
Environmental Science 5 2%
Nursing and Health Professions 2 <1%
Computer Science 2 <1%
Other 11 4%
Unknown 80 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 25 May 2018.
All research outputs
#4,155,383
of 25,628,260 outputs
Outputs from Frontiers in Plant Science
#2,032
of 24,900 outputs
Outputs of similar age
#75,034
of 341,476 outputs
Outputs of similar age from Frontiers in Plant Science
#49
of 431 outputs
Altmetric has tracked 25,628,260 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,900 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 91% 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 341,476 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 431 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.