Literature DB >> 24506038

Genetic evaluation of recombinant inbred lines of rice (Oryza sativa L.) for grain zinc concentrations, yield related traits and identification of associated SSR markers.

Berhanu D Bekele1, G K Naveen1, S Rakhi1, H E Shashidhar1.   

Abstract

The objectives of the present study were to evaluate genetic variability parameters, correlations that exist for grain Zn concentration and yield related traits and identification of SSR markers linked to these traits in rice. One hundred seventy six Recombinant Inbred Lines (RILs) of Azucena X Moromutant were grown at University of Agricultural Sciences, Bangalore in augmented experimental design during wet seasons of 2010 and 2011. The study revealed significant genetic variability for all the traits. Grain yield per plant and grain zinc concentration showed higher phenotypic and genotypic co-efficient of variation. Significant positive correlation was observed for grain yield per plant with number of productive tillers per plant (r = 0.5) and number of tillers per plant (r = 0.4). Grain zinc concentration showed negative correlation with grain yield per plant (r = - 0.27). The path-coefficient analysis indicated the positive direct effect of number of productive tillers per plant on grain yield per plant (0.514). Grain zinc concentration showed negative direct effect on grain yield per plant (-0.186). Single-marker analysis using 26 SSR markers on RILs mapping population showed that RM212, RM263, RM6832, RM152, RM21, RM234 and RM3331 had association with grain zinc concentration and other yield related traits. But validation of these markers on fifty two rice genotypes showed that only three markers RM263, RM152 and RM21 had association with grain zinc concentration. Therefore, the genetic information generated and molecular markers identified from this study could be used for zinc biofortification programmes in rice.

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Year:  2013        PMID: 24506038     DOI: 10.3923/pjbs.2013.1714.1721

Source DB:  PubMed          Journal:  Pak J Biol Sci        ISSN: 1028-8880


  6 in total

1.  Genomic marker assisted identification of genetic loci and genes associated with variation of grain zinc concentration in rice.

Authors:  Kumkum Kumari; Pankaj Kumar; Vinay K Sharma; Santosh K Singh
Journal:  J Genet       Date:  2019-12       Impact factor: 1.166

2.  Physiological and agronomical evaluation of elite rice varieties for adaptation to heat stress.

Authors:  Vincent Ezin; Wassiou Worou Ahanchede; Mathieu Anatole Tele Ayenan; Adam Ahanchede
Journal:  BMC Plant Biol       Date:  2022-05-10       Impact factor: 5.260

3.  Examining Two Sets of Introgression Lines in Rice (Oryza sativa L.) Reveals Favorable Alleles that Improve Grain Zn and Fe Concentrations.

Authors:  Qin Xu; Tian-Qing Zheng; Xia Hu; Li-Rui Cheng; Jian-Long Xu; Yu-Min Shi; Zhi-Kang Li
Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

4.  Joint Exploration of Favorable Haplotypes for Mineral Concentrations in Milled Grains of Rice (Oryza sativa L.).

Authors:  Guo-Min Zhang; Tian-Qing Zheng; Zhuo Chen; Yong-Li Wang; Ying Wang; Yu-Min Shi; Chun-Chao Wang; Li-Yan Zhang; Jun-Tao Ma; Ling-Wei Deng; Wan Li; Tian-Tian Xu; Cheng-Zhi Liang; Jian-Long Xu; Zhi-Kang Li
Journal:  Front Plant Sci       Date:  2018-04-12       Impact factor: 5.753

Review 5.  Advances in breeding for high grain Zinc in Rice.

Authors:  B P Mallikarjuna Swamy; Mohammad Akhlasur Rahman; Mary Ann Inabangan-Asilo; Amery Amparado; Christine Manito; Prabhjit Chadha-Mohanty; Russell Reinke; Inez H Slamet-Loedin
Journal:  Rice (N Y)       Date:  2016-09-26       Impact factor: 4.783

6.  Genome-Wide Association Mapping in a Rice MAGIC Plus Population Detects QTLs and Genes Useful for Biofortification.

Authors:  Gwen Iris L Descalsota; B P Mallikarjuna Swamy; Hein Zaw; Mary Ann Inabangan-Asilo; Amery Amparado; Ramil Mauleon; Prabhjit Chadha-Mohanty; Emily C Arocena; Chitra Raghavan; Hei Leung; Jose E Hernandez; Antonio B Lalusin; Merlyn S Mendioro; Ma Genaleen Q Diaz; Russell Reinke
Journal:  Front Plant Sci       Date:  2018-09-20       Impact factor: 5.753

  6 in total

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