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On-line Access: 2013-01-31

Received: 2012-03-12

Revision Accepted: 2012-08-08

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Journal of Zhejiang University SCIENCE B 2013 Vol.14 No.2 P.162-170

http://doi.org/10.1631/jzus.B1200075


Effect of the scale of quantitative trait data on the representativeness of a cotton germplasm sub-core collection


Author(s):  Jian-cheng Wang, Jin Hu, Ya-jing Guan, Yan-fang Zhu

Affiliation(s):  Seed Science Center, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   jhu@zju.edu.cn

Key Words:  Sub-core collection, Mixed linear model, Least distance stepwise sampling, Monte Carlo simulation, CR threshold method


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Jian-cheng Wang, Jin Hu, Ya-jing Guan, Yan-fang Zhu. Effect of the scale of quantitative trait data on the representativeness of a cotton germplasm sub-core collection[J]. Journal of Zhejiang University Science B, 2013, 14(2): 162-170.

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author="Jian-cheng Wang, Jin Hu, Ya-jing Guan, Yan-fang Zhu",
journal="Journal of Zhejiang University Science B",
volume="14",
number="2",
pages="162-170",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1200075"
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%T Effect of the scale of quantitative trait data on the representativeness of a cotton germplasm sub-core collection
%A Jian-cheng Wang
%A Jin Hu
%A Ya-jing Guan
%A Yan-fang Zhu
%J Journal of Zhejiang University SCIENCE B
%V 14
%N 2
%P 162-170
%@ 1673-1581
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1200075

TY - JOUR
T1 - Effect of the scale of quantitative trait data on the representativeness of a cotton germplasm sub-core collection
A1 - Jian-cheng Wang
A1 - Jin Hu
A1 - Ya-jing Guan
A1 - Yan-fang Zhu
J0 - Journal of Zhejiang University Science B
VL - 14
IS - 2
SP - 162
EP - 170
%@ 1673-1581
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1200075


Abstract: 
A cotton germplasm collection with data for 20 quantitative traits was used to investigate the effect of the scale of quantitative trait data on the representativeness of plant sub-core collections. The relationship between the representativeness of a sub-core collection and two influencing factors, the number of traits and the sampling percentage, was studied. A mixed linear model approach was used to eliminate environmental errors and predict genotypic values of accessions. sub-core collections were constructed using a least distance stepwise sampling (LDSS) method combining standardized Euclidean distance and an unweighted pair-group method with arithmetic means (UPGMA) cluster method. The mean difference percentage (MD), variance difference percentage (VD), coincidence rate of range (CR), and variable rate of coefficient of variation (VR) served as evaluation parameters. monte Carlo simulation was conducted to study the relationship among the number of traits, the sampling percentage, and the four evaluation parameters. The results showed that the representativeness of a sub-core collection was affected greatly by the number of traits and the sampling percentage, and that these two influencing factors were closely connected. Increasing the number of traits improved the representativeness of a sub-core collection when the data of genotypic values were used. The change in the genetic diversity of sub-core collections with different sampling percentages showed a linear tendency when the number of traits was small, and a logarithmic tendency when the number of traits was large. However, the change in the genetic diversity of sub-core collections with different numbers of traits always showed a strong logarithmic tendency when the sampling percentage was changing. A CR threshold method based on monte Carlo simulation is proposed to determine the rational number of traits for a relevant sampling percentage of a sub-core collection.

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