Inheritance of Resistance of Soybean for Meloidogyne incognita and Identification of Molecular Marker for Marker Assisted Selection

Oliveira, Leonardo Augusto De and Montecelli, Tatiane Dalla Nora and Montecelli, Tatiane and Lazzari, Fabiane and Schuster, Ivan (2015) Inheritance of Resistance of Soybean for Meloidogyne incognita and Identification of Molecular Marker for Marker Assisted Selection. Journal of Scientific Research and Reports, 8 (3). pp. 1-8. ISSN 23200227

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Abstract

Aims: To study the inheritance of resistance to Meloidogyne incognita in soybean cultivar CD 201, and identify molecular markers linked to resistance genes/QTLs in soybean.

Study Design: The phenotypic assay was a complete randomized design, and mendelian hypothesis was applied.

Place and Duration of Study: Biotechnology lab, Coodetec, BR 467, km98. Cascavel, PR, Brazil, between July 2012 to July 2013.

Methodology: The population was created by the crossing the cultivars CD 201 (resistant) and BRS 133 (susceptible). F2:3 families were phenotyped for resistance to M. incognita and microsatellite molecular markers were used to identify genes/QTLs associated with resistance. Inheritance hypothesis was tested by Chi square test.

Results: The resistance to M. incognita in soybean cultivar CD 201 is given by three epistatic additive genes, two dominant and one recessive. Among the markers, Satt358 is linked to a dominant gene/QTL of resistance explaining 9.9% of the variability in resistance in the evaluated population. The use of this marker allows increasing the frequency resistant or moderately resistant lines in soybean breeding programs. Sixty nine percent of F2:3 families that have at least one allele for resistance in marker Satt358 have resistant or moderately resistant phenotype, and no F2:3 families that is homozygous with the susceptible allele in this locus have resistant phenotype.

Conclusion: This finding can help soybean breeders to develop highly resistant cultivar to M. incognita, both, by phenotypic selection and marker assisted selection.

Item Type: Article
Subjects: European Repository > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 13 Jun 2023 04:07
Last Modified: 04 Dec 2023 03:28
URI: http://go7publish.com/id/eprint/2434

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