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. 2017 Oct;23(4):891-909.
doi: 10.1007/s12298-017-0464-5. Epub 2017 Oct 4.

Marker-assisted identification of restorer gene(s) in iso-cytoplasmic restorer lines of WA cytoplasm in rice and assessment of their fertility restoration potential across environments

Amit Kumar  1   2 , Prolay Kumar Bhowmick  1 , Vikram Jeet Singh  1 , Manoj Malik  1 , Ashish Kumar Gupta  3 , R Seth  4 , M Nagarajan  5 , S Gopala Krishnan  1 , Ashok Kumar Singh  1
Affiliations

Marker-assisted identification of restorer gene(s) in iso-cytoplasmic restorer lines of WA cytoplasm in rice and assessment of their fertility restoration potential across environments

Amit Kumar et al. Physiol Mol Biol Plants. 2017 Oct.

Abstract

Iso-cytoplasmic restorers possess the same male sterile cytoplasm as the cytoplasmic male sterile (CMS) lines, thereby minimizing the potential cyto-nuclear conflict in the hybrids. Restoration of fertility of the wild abortive CMS is governed by two major genes namely, Rf3 and Rf4. Therefore, assessing the allelic status of these restorer genes in the iso-cytoplasmic restorers using molecular markers will not only help in estimating the efficiency of these genes either alone or in combination, in fertility restoration in the hybrids in different environments, but will also be useful in determining the efficacy of these markers. In the present study, the efficiency of molecular markers in identifying genotypes carrying restorer allele of the gene(s) Rf3 and Rf4, restoring male fertility of WA cytoplasm in rice was assessed in a set of 100 iso-cytoplasmic rice restorers using gene linked as well as candidate gene based markers. In order to validate the efficacy of markers in identifying the restorers, a sub-set of selected 25 iso-cytoplasmic rice restorers were crossed with four different cytoplasmic male sterile lines namely, IR 79156A, IR 58025A, Pusa 6A and RTN 12A, and the pollen and spikelet fertility of the F1s were evaluated at three different locations. Marker analysis showed that Rf4 was the predominant fertility restorer gene in the iso-cytoplasmic restorers and Rf3 had a synergistic effect on fertility restoration. The efficiency of gene based markers, DRCG-RF4-14 and DRRM-RF3-10 for Rf4 (87%) and Rf3 (84%) genes was higher than respective gene-linked SSR markers RM6100 (80%) and RM3873 (82%). It is concluded that the gene based markers can be effectively used in identifying fertility restorer lines obviating the need for making crosses and evaluating the F1s. Though gene based markers are more efficient, there is a need to identify functional polymorphisms which can provide 100% efficiency. Three iso-cytoplasmic restorers namely, PRR 300, PRR 363 and PRR 396 possessing both Rf4 and Rf3 genes and good fertility restoration have been identified which could be used further in hybrid rice breeding.

Keywords: Fertility restorer genes; Gene based markers; Hybrids; Iso-cytoplasmic restorers; Pollen fertility.

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Figures

Fig. 1
Fig. 1
A representative amplification profile of the gene based and linked markers for fertility restoration in the iso-cytoplasmic restorer lines. Marker: DNA Ladder 100 bp, DRRM-RF3-10: R—210 bp, NR—190 bp, DRCG-RF4-14: R—800 bp, NR—900 bp, RM3873: R—210 bp, NR—155 bp, RM 6100: R—150 bp, NR—140 bp where, R = Restorer allele, NR = Non-restorer allele
Fig. 2
Fig. 2
a GGE biplot of rice hybrids for pollen fertility based on which won where pattern. Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396, b GGE biplot of rice hybrids for spikelet fertility based on which won where pattern. Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396
Fig. 2
Fig. 2
a GGE biplot of rice hybrids for pollen fertility based on which won where pattern. Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396, b GGE biplot of rice hybrids for spikelet fertility based on which won where pattern. Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396
Fig. 3
Fig. 3
a GGE biplot of ideal genotype and comparison of the genotypes with the ideal genotype (pollen fertility). Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396, b GGE biplot of ideal genotype and comparison of the genotypes with the ideal genotype (spikelet fertility). Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396
Fig. 3
Fig. 3
a GGE biplot of ideal genotype and comparison of the genotypes with the ideal genotype (pollen fertility). Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396, b GGE biplot of ideal genotype and comparison of the genotypes with the ideal genotype (spikelet fertility). Restorer lines used: 1. PRR 300, 2.PRR 307, 3.PRR 311, 4.PRR 314, 5.PRR 317, 6.PRR 323, 7.PRR 326, 8.PRR 329, 9.PRR 334, 10.PRR 337, 11.PRR 342, 12.PRR 347, 13.PRR 348, 14.PRR 354, 15.PRR 358, 16.PRR 363, 17.PRR 367, 18.PRR 368, 19.PRR 372, 20.PRR 376, 21.PRR 381, 22.PRR 386, 23.PRR 390, 24.PRR 395, 25.PRR 396
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References

    1. Alavi M, Ahamadidhan A, Kamkar B, Kalateh M. Mapping Rf3 locus in rice by SSR and CAPS markers. Int J Genet Mol Biol. 2009;7:121–126.
    1. Alvarado R (1999) Influence of air temperature on rice population, length of period from sowing to flowering and spikelet sterility. In: Hill JE, Hardy B (eds) Proceedings of the second temperate rice conference. Sacramento, California, pp 63–68
    1. Betran FJ, Ribaut JM, Beck D, De Leon DG. Genetic diversity, specific combining ability, heterosis in tropical maize under stress and non-stress environments. Crop Sci. 2003;43:797–806. doi: 10.2135/cropsci2003.7970. - DOI
    1. Chaudhury RC, Virmani SS, Khush GS. CMS lines in rice. Andhra Agric J. 1981;38:302–303.
    1. Falodun D, Njoku KL, Ogunyebi AL, Akinola MO. Spikelet numbers, filled grains and spikelet fertility potential of NERICA rice (Mecux, Tox and WitA.4) grown in hydrocarbon polluted soils. J Res Environ Sci Toxicol. 2012;1(8):201–206.

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