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R. K. Zote*, R. N. Dhawale, G. Chandel, S. B. Verulkar and A. S. Kotasthane


Rice (Oryza sativa L.) grain iron and zinc content is a polygenic complex trait having additive effect of multiple genes thus identification of QTLs and sequence analysis of genomic region encompassing them enable us to understand not only the inheritance of grain micronutrient content but also to develop Fe/Zn rich rice using marker assisted breeding techniques. Co-segregation analysis was performed with the F6 mapping population derived from a cross between rice cultivar Swarna x Moroberekan. The grain Fe content ranged from 9.68 to 19.98 μg/g with an average of 16.87 μg/g and grain Zn content ranged from 15.85 to 20.84 μg/g with an average of 25.76μg/g among the 73 homozygous rice mapping population. Similarly the grain protein content ranged from 5.34% to 7.18% with an average of 9.23%. In order to identify novel SSR based molecular markers, 5 known QTLs (qFE-1, qFE-9, qZN-5, qZN-7 and qZN-11) identified[9] for grain Fe/Zn content in rice were analyzed using in-silico tools. Out of 1063 novel SSRs loci present within the 5 QTL regions, 161 Class I SSRs with 2-6 nt long repeat motifs and 12–80 nt repeat lengths were identified. On the basis of position of metal related transporter or membrane transporter genes primers were designed for 22 novel Class- I SSR and validated in the parents for their polymorphism. Out of 34 previously designed primers, 4 randomly selected RM markers and 22 novel SSR designed markers, only 18 markers were found to be polymorphic. The allelic segregation analysis indicated that indica parent Swarna contributed about 60.6% whereas the japonica parent Moroberekan contributed about 34.32% of total amplified alleles on an average which clearly showed departure from the theoretically expected 1:1 ratio of equal contribution from the two parents. Out of 18 polymorphic SSRs, the co-segregation analysis performed for the 5 randomly selected SSR‟s markers. The all five markers; gRMm7-2, gRMm7-3, gRMm33-2, gRMm34- 1 and gRMm33-3 were significantly associated to grain iron and zinc contents.

Keywords: in-silico, Rice, allelic segregation, SSRs, Fe content, Fe/Zn, QTLs.

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