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Genotyping-by-Sequencing and Its Exploitation for Forage and Cool-Season Grain Legume Breeding

Overview of attention for article published in Frontiers in Plant Science, May 2017
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Genotyping-by-Sequencing and Its Exploitation for Forage and Cool-Season Grain Legume Breeding
Published in
Frontiers in Plant Science, May 2017
DOI 10.3389/fpls.2017.00679
Pubmed ID
Authors

Paolo Annicchiarico, Nelson Nazzicari, Yanling Wei, Luciano Pecetti, Edward C. Brummer

Abstract

Genotyping-by-Sequencing (GBS) may drastically reduce genotyping costs compared with single nucleotide polymorphism (SNP) array platforms. However, it may require optimization for specific crops to maximize the number of available markers. Exploiting GBS-generated markers may require optimization, too (e.g., to cope with missing data). This study aimed (i) to compare elements of GBS protocols on legume species that differ for genome size, ploidy, and breeding system, and (ii) to show successful applications and challenges of GBS data on legume species. Preliminary work on alfalfa and Medicago truncatula suggested the greater interest of ApeKI over PstI:MspI DNA digestion. We compared KAPA and NEB Taq polymerases in combination with primer extensions that were progressively more selective on restriction sites, and found greater number of polymorphic SNP loci in pea, white lupin and diploid alfalfa when adopting KAPA with a non-selective primer. This protocol displayed a slight advantage also for tetraploid alfalfa (where SNP calling requires higher read depth). KAPA offered the further advantage of more uniform amplification than NEB over fragment sizes and GC contents. The number of GBS-generated polymorphic markers exceeded 6,500 in two tetraploid alfalfa reference populations and a world collection of lupin genotypes, and 2,000 in different sets of pea or lupin recombinant inbred lines. The predictive ability of GBS-based genomic selection was influenced by the genotype missing data threshold and imputation, as well as by the genomic selection model, with the best model depending on traits and data sets. We devised a simple method for comparing phenotypic vs. genomic selection in terms of predicted yield gain per year for same evaluation costs, whose application to preliminary data for alfalfa and pea in a hypothetical selection scenario for each crop indicated a distinct advantage of genomic selection.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
Unknown 51 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 27%
Student > Ph. D. Student 10 19%
Other 6 12%
Student > Master 6 12%
Student > Doctoral Student 4 8%
Other 3 6%
Unknown 9 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 63%
Biochemistry, Genetics and Molecular Biology 5 10%
Business, Management and Accounting 1 2%
Computer Science 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 11 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 September 2018.
All research outputs
#13,040,534
of 22,977,819 outputs
Outputs from Frontiers in Plant Science
#5,654
of 20,419 outputs
Outputs of similar age
#149,139
of 310,727 outputs
Outputs of similar age from Frontiers in Plant Science
#205
of 617 outputs
Altmetric has tracked 22,977,819 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,419 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 71% 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 310,727 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 51% of its contemporaries.
We're also able to compare this research output to 617 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.