Zongo, Adama ; Khera, Pawan ; Sawadogo, Mahamadou ; Shasidhar, Yaduru ; Sriswathi, Manda ; Vishwakarma, Manish K. ; Sankara, Philippe ; Ntare, Bonny R. ; Varshney, Rajeev K. ; Pandey, Manish K. ; Desmae, Haile (2017) SSR markers associated to early leaf spot disease resistance through selective genotyping and single marker analysis in groundnut ( Arachis hypogaea L.) Biotechnology Reports, 15 . pp. 132-137. ISSN 2215-017X
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Official URL: http://doi.org/10.1016/j.btre.2017.07.005
Related URL: http://dx.doi.org/10.1016/j.btre.2017.07.005
Abstract
Groundnut (Arachis hypogaea L.) is an important oilseed and food crop of the world. Breeding for disease resistance is one of major objectives in groundnut breeding. Early leaf spot (ELS) is one of the major destructive diseases worldwide and in West Africa, particularly in Burkina Faso causing significant yield losses. Conventional breeding approaches have been employed to develop improved varieties resistant to ELS. Molecular dissection of resistance traits using QTL analysis can improve the efficiency of resistance breeding. In the present study, an ELS susceptible genotype QH243C and an ELS resistant genotype NAMA were crossed and the F2 population genotypic and F3 progenies phenotypic data were used for marker-trait association analysis. Parents were surveyed with 179 simple sequence repeat (SSR) markers out of which 103 SSR markers were found to be polymorphic between the parents. These polymorphic markers were utilized to genotype the F2 population followed by marker-trait analysis through single marker analysis (SMA) and selective genotyping of the population using 23 resistant and 23 susceptible genotypes. The SMA revealed 13 markers while the selective genotyping method identified 8 markers associated with ELS resistance. Four markers (GM1911, GM1883, GM1000 and Seq13E09) were found common between the two trait mapping methods. These four markers could be employed in genomics-assisted breeding for selection of ELS resistant genotypes in groundnut breeding.
Item Type: | Article |
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Source: | Copyright of this article belongs to Elsevier B.V.. |
ID Code: | 124873 |
Deposited On: | 07 Dec 2021 12:24 |
Last Modified: | 07 Dec 2021 12:24 |
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