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Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments

Overview of attention for article published in Frontiers in Plant Science, March 2018
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Title
Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments
Published in
Frontiers in Plant Science, March 2018
DOI 10.3389/fpls.2018.00366
Pubmed ID
Authors

Diego Cerrudo, Shiliang Cao, Yibing Yuan, Carlos Martinez, Edgar Antonio Suarez, Raman Babu, Xuecai Zhang, Samuel Trachsel

Abstract

To increase genetic gain for tolerance to drought, we aimed to identify environmentally stable QTL inper seand testcross combination under well-watered (WW) and drought stressed (DS) conditions and evaluate the possible deployment of QTL using marker assisted and/or genomic selection (QTL/GS-MAS). A total of 169 doubled haploid lines derived from the cross between CML495 and LPSC7F64 and 190 testcrosses (tester CML494) were evaluated in a total of 11 treatment-by-population combinations under WW and DS conditions. In response to DS, grain yield (GY) and plant height (PHT) were reduced while time to anthesis and the anthesis silking interval (ASI) increased for both lines and hybrids. Forty-eight QTL were detected for a total of nine traits. The allele derived from CML495 generally increased trait values for anthesis, ASI, PHT, the normalized difference vegetative index (NDVI) and the green leaf area duration (GLAD; a composite trait of NDVI, PHT and senescence) while it reduced trait values for leaf rolling and senescence. The LOD scores for all detected QTL ranged from 2.0 to 7.2 explaining 4.4 to 19.4% of the observed phenotypic variance with R2ranging from 0 (GY, DS, lines) to 37.3% (PHT, WW, lines). Prediction accuracy of the model used for genomic selection was generally higher than phenotypic variance explained by the sum of QTL for individual traits indicative of the polygenic control of traits evaluated here. We therefore propose to use QTL-MAS in forward breeding to enrich the allelic frequency for a few desired traits with strong additive QTL in early selection cycles while GS-MAS could be used in more mature breeding programs to additionally capture alleles with smaller additive effects.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 21%
Researcher 22 20%
Student > Bachelor 11 10%
Student > Master 9 8%
Student > Doctoral Student 7 6%
Other 7 6%
Unknown 33 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 50%
Biochemistry, Genetics and Molecular Biology 11 10%
Psychology 2 2%
Engineering 2 2%
Earth and Planetary Sciences 1 <1%
Other 3 3%
Unknown 37 33%
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 22 January 2019.
All research outputs
#12,879,856
of 23,041,514 outputs
Outputs from Frontiers in Plant Science
#5,251
of 20,598 outputs
Outputs of similar age
#156,893
of 332,297 outputs
Outputs of similar age from Frontiers in Plant Science
#171
of 466 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,598 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 73% 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 332,297 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 52% of its contemporaries.
We're also able to compare this research output to 466 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.