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Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits

Overview of attention for article published in Theoretical & Applied Genetics, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 2,146)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

blogs
1 blog
twitter
22 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
16 Mendeley
Title
Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits
Published in
Theoretical & Applied Genetics, March 2017
DOI 10.1007/s00122-017-2872-x
Pubmed ID
Authors

Brigitte Mangin, Nicolas Pouilly, Marie-Claude Boniface, Nicolas B. Langlade, Patrick Vincourt, Felicity Vear, Stéphane Muños

Abstract

SNP genotyping of 114 cultivated sunflower populations showed that the multiplication process and the main traits selected during breeding of sunflower cultivars drove molecular diversity of the populations. The molecular diversity in a set of 114 cultivated sunflower populations was studied by single-nucleotide polymorphism genotyping. These populations were chosen as representative of the 400 entries in the INRA collection received or developed between 1962 and 2011 and made up of land races, open-pollinated varieties, and breeding pools. Mean allele number varied from 1.07 to 1.90. Intra-population variability was slightly reduced according to the number of multiplications since entry but some entries were probably largely homozygous when received. A principal component analysis was used to study inter-population variability. The first 3 axes accounted for 17% of total intra-population variability. The first axis was significantly correlated with seed oil content, more closely than just the distinction between oil and confectionary types. The second axis was related to the presence or absence of restorer genes and the third axis to flowering date and possibly to adaptation to different climates. Our results provide arguments highlighting the effect of the maintenance process on the within population genetic variability as well as on the impact of breeding for major agronomic traits on the between population variability of the collection. Propositions are made to improve sunflower population maintenance procedures to keep maximum genetic variability for future breeding.

Twitter Demographics

The data shown below were collected from the profiles of 22 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 44%
Student > Master 2 13%
Researcher 2 13%
Other 1 6%
Student > Doctoral Student 1 6%
Other 3 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 81%
Unspecified 2 13%
Biochemistry, Genetics and Molecular Biology 1 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 13 July 2019.
All research outputs
#743,377
of 13,361,190 outputs
Outputs from Theoretical & Applied Genetics
#44
of 2,146 outputs
Outputs of similar age
#26,056
of 257,079 outputs
Outputs of similar age from Theoretical & Applied Genetics
#5
of 59 outputs
Altmetric has tracked 13,361,190 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,146 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 97% 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 257,079 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 89% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.