UPM Institutional Repository

Estimation of genetic correlations on sweet corn inbred lines using SAS mixed model


Citation

Kashiani, Pedram and Saleh, Ghizan (2010) Estimation of genetic correlations on sweet corn inbred lines using SAS mixed model. American Journal of Agricultural and Biological Sciences, 5 (3). pp. 309-314. ISSN 1557-4989; ESSN: 1557-4997

Abstract

Problem statement:Genetic correlations among traits refer to the extent of relatedness among them due to genetic causes. Estimating genetic correlations for quantitative traits is tedious if done manually. Approach:However, the use of the computer software SAS, applying mixed-model analysis of variance has facilitated many recent studies in evolutionary quantitative genetics. Results:In this two-way statistical model, the variance component corresponding to the random statement is the covariance associated with a level of the random factor across levels of the fix factor. Therefore, the SAS model has a natural application for estimating genetic correlations among traits measured. Correlation studies were undertaken for 10 yield-related traits on a series of near-homozygous sweet corn inbred lines obtained from various tropical source populations. The SAS program was used to estimate genetic correlation coefficients among traits observed, where effects of blocks were considered fixed while effects of inbred lines as random. The "ASYCOV" was added to the "PROC MIXED" statement in order to produce the variance-covariance matrix of variance components. The "TYPE = UN" option requested in "RANDOM" statement resulted in an unstructured covariance matrix for each inbred line being estimated, while the "G" and "GCORR" options produced genetic variance-covariance matrix and genetic correlation matrix between traits, respectively. Results showed that there was no significant difference between genetic correlations estimated by SAS MIXED model and those estimated by manual calculation. Conclusion/Recommendations: This indicated that SAS has the natural capability to estimate genetic correlations among traits measured, as opposed to manual methods employing quantitative genetics equations.


Download File

[img] PDF
ajabssp.2010.309.314.pdf
Restricted to Repository staff only

Download (74kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Agriculture
DOI Number: https://doi.org/10.3844/ajabssp.2010.309.314
Publisher: Science Publications
Keywords: Genetic correlation; SAS; Proc mixed model; Inbred line; Sweet corn
Depositing User: Norhazura Hamzah
Date Deposited: 01 Nov 2013 02:19
Last Modified: 21 Nov 2017 02:02
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/ajabssp.2010.309.314
URI: http://psasir.upm.edu.my/id/eprint/14569
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item