Rice Genomics and Genetics 2015, Vol.6, No.1, 1-5
4
the roots were blotted gently with a blotting paper to
remove any free surface moisture and then weighed
immediately. For dry weight, the roots and shoots
were dried in an oven set to low heat (50°C)
overnight, and then cooled in a dry environment.
Once cooled, weighed on a scale. The thickness of
the root crown was measured using a vernier caliper.
3.3 Statistical analysis
The data was subsequently analyzed using OPSTAT
(
) to determine the
variability and phenotypic (r) correlation coefficient
analysis. Phenotypic correlation coefficients were
tested against standardized tabulated significant
value of r with (n–2) degree of freedom as per the
procedure (Fisher and Yates, 1963).
3.4 Molecular characterization and QTLmapping
A total of 94 F
2
plants selected on the basis of root
traits, grain weight and grain yield (15% best and
15% worst) covering the entire range of these
phenotypic traits were used for identification and
mapping of QTLs associated with traits promoting
aerobic adaptation. DNA was isolated from the leaf
tissues of F
2
plants using CTAB DNA isolation
(Saghai-Maroof et al., 1984). Molecular marker
analysis was carried out using 125 polymorphic SSR
primers by ethidium bromide stained polyacrylamide
gel electrophoresis (PAGE). PCR products from
SSR analysis were scored visually for presence or
absence of bands; data was scored as 1 (present) and
0 (absent) for each of the SSR locus. Genetic
similarities between the genotypes were measured
by the similarity coefficient based on the proportion
of shared electromorphs using ‘Simqual’ sub-program
of NTSYS-PC (Version 2.02 Exeter Software,
Setauket, NY, USA) package (Rohlf, 1993). The
resultant distance matrix data was used for
two-dimensional scaling of rice genotypes using
two-dimensional Principal Component Analysis
(PCA). QTL analysis was done by using Win QTL
cartographer version 2.5 (Shengchu Wang, Christopher
J. Basten and Zhao-Bang Zeng, 2012,
ncsu.edu/qtlcart/WQTLCart.htm) via composite
interval mapping (CIM). The threshold log likelihood
ratio (LOD) score was estimated empirically with
300 times permutations at a significant level of
P=0.05.
Author’s contributions
AK was involved in the conception of the experiment,
analysis, interpretation of the data, and drafting the article
and final approval of the version to be published; NS was
involved in revising manuscript content critically and final
approval of the version to be published; SJ was involved with
the analysis, interpretation of the data, in the critical revision
of the manuscript and final approval of the version to be
published; RKJ was involved in the design of the experiment,
the critical revision of the manuscript and final approval of
the version to be published.
Acknowledgements
The authors thank the Department of Science and Technology,
New Delhi, India (DST No. SR/SO/PS/0041/2009), for
providing financial support for this study.
References
Amudha K., Thiyagarajan K., Robin S., Prince S.J.K., Poornima R., and
Suji K.K., 2009, Heterosis under aerobic condition in rice, Electron.
J. Plant Breed., 1(4): 769-775
Babu N.N., Hittalmani S., Shivakumar N., and Nandini C., 2011, Effect
of drought on yield potential and drought susceptibility index of
promising aerobic rice (
Oryza sativa
L.) genotypes, Electron. J.
Plant Breed., 2(3): 295-302
Bernier J., Kumar A., Venuprasad R., Spaner D., and Atlin, G.N., 2007, A
large-effect QTL for grain yield under reproductive-stage drought
stress in upland rice, Crop Sci., 47: 507-516
Bernier J., Kumar A., Venuprasad R., Spaner D., Verulkar S., Mandal N.P.,
Sinha P.K., Peeraju P., Dongre P.R., Mahto R.N., and Atlin G., 2008,
Characterization of the effect of a QTL for drought resistance in rice,
qtl12.1, over a range of environments in the Philippines and eastern
India, Euphytica, 166(2): 207-217
Bouman B.A.M., 2002, Aerobic Rice (Han Dao): a new way of growing
rice in water short areas, Mol. Gen. Genet., 4: 53-61
Bouman B.A.M., Peng S., Castaneda A.R., and Visperas R.M., 2005,
Yield and water use of irrigated aerobic rice systems, Agric. Water
Manage., 74: 87-105
Courtois B., Ahmadi N., Khowaja F., Price A.H., Rami J.F., Frouin J.,
Hamelin C., and Ruiz M., 2009,
Rice Root Genetic Architecture:
Meta-analysis from a Drought QTL Database, Rice, 2: 115-128
Courtois B., Shen L., Petalcorin W., Carandang S., Mauleon R., and Li Z.,
2003, Locating QTL controlling constitutive root traits in the rice
population IAC 165 × Co39, Euphytica, 134: 335-345
Ekanayake I.J., O’toole J.C., Garrity D.P., and Masajo T.M., 1985,
Inheritance of root characters and their relations to drought
resistance in rice, Crop Sci., 25: 927-933
Fisher R.A., and Yates F., eds., 1963, Statistical tables for biological,
agricultural and medicinal research, 6th Ed., Oliver and Boyd,
Edinburgh, London, pp.63
Fukai S., and Cooper M., 1995, Development of drought-resistant
cultivars using physio-morphological traits in rice, Field Crop Res.,
40: 67-86
Girish T.N., Gireesha T.M., Vaishali M.G., Hanamareddy B.G., and
Hittalmani S., 2006, Response of a new IR50/Moroberekan
recombinant inbred population of rice (
Oryza sativa
L.) from an
