search
for
 About Bioline  All Journals  Testimonials  Membership  News  Donations


Chilean Journal of Agricultural Research
Instituto de Investigaciones Agropecuarias, INIA
ISSN: 0718-5820
EISSN: 0718-5839
Vol. 76, No. 3, 2016, pp. 300-306
Bioline Code: cj16039
Full paper language: English
Document type: Research Article
Document available free of charge

Chilean Journal of Agricultural Research, Vol. 76, No. 3, 2016, pp. 300-306

 en Multiple marker-traits associations for maize agronomic traits
Mikic, Sanja; Kondic-Spika, Ankica; Brbaklic, Ljiljana; Stanisavljevic, Dusan; Trkulja, Dragana; Tomicic, Marina; Nastasic, Aleksandra; Kobiljski, Borislav; Prodanovic, Slaven & Surlan Momirovic, Gordana

Abstract

Association analysis is a relatively novel approach in quantitative traits studies that allows high resolution mapping and time efficient and direct application on breeding material. Since the markers, which are close to the quantitative trait loci stable across environments and genetic backgrounds, may be valuable for marker assisted selection, we chose microsatellite markers previously linked to traits of interest in various mapping studies. A set of 36 microsatellite markers positioned near important maize ( Zea mays check for this species in other resources L.) agronomic loci was used to evaluate genetic diversity and determine population structure. To verify the associations between the markers and traits, a panel of diverse maize inbred lines was genotyped with microsatellites and phenotyped for flowering time, yield and yield components. A relatively high level of polymorphism detected in number of alleles per locus (8.2), average polymorphic information content value (0.64), and average gene diversity (0.684) lines showed the analyzed panel of maize inbred contained significant genetic diversity and was suitable for association mapping. The population structure estimated by model-based clustering method grouped maize inbred lines into three clusters. The association analysis using the general linear and mixed linear models determined significant correlations between several agronomic traits and three microsatellites on chromosomes 3, 5, and 8, namely umc1025, bnlg1237, and bnlg162 consistent across the environments, explaining from 4.7% to 18.2% of total phenotypic variations. The results suggest that the chromosome regions containing quantitative trait loci (QTLs) associated with multiple yield-related traits consistently across environments are potentially important targets for selection.

Keywords
Association analysis; inbred lines; linkage; pleiotropy; SSR markers; Zea mays

 
© Copyright 2017 - Chilean Journal of Agricultural Research
Alternative site location: http://www.inia.cl

Home Faq Resources Email Bioline
© Bioline International, 1989 - 2019, Site last up-dated on 11-Sep-2019.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Internet Data Center of Rede Nacional de Ensino e Pesquisa, RNP, Brazil