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      A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut ( Arachis hypogaea L.)

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          Abstract

          Late leaf spot (LLS) and rust are two major foliar diseases of groundnut ( Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTL rust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing.

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          The online version of this article (doi:10.1007/s00122-010-1366-x) contains supplementary material, which is available to authorized users.

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          Most cited references31

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          Precision mapping of quantitative trait loci.

          Adequate separation of effects of possible multiple linked quantitative trait loci (QTLs) on mapping QTLs is the key to increasing the precision of QTL mapping. A new method of QTL mapping is proposed and analyzed in this paper by combining interval mapping with multiple regression. The basis of the proposed method is an interval test in which the test statistic on a marker interval is made to be unaffected by QTLs located outside a defined interval. This is achieved by fitting other genetic markers in the statistical model as a control when performing interval mapping. Compared with the current QTL mapping method (i.e., the interval mapping method which uses a pair or two pairs of markers for mapping QTLs), this method has several advantages. (1) By confining the test to one region at a time, it reduces a multiple dimensional search problem (for multiple QTLs) to a one dimensional search problem. (2) By conditioning linked markers in the test, the sensitivity of the test statistic to the position of individual QTLs is increased, and the precision of QTL mapping can be improved. (3) By selectively and simultaneously using other markers in the analysis, the efficiency of QTL mapping can be also improved. The behavior of the test statistic under the null hypothesis and appropriate critical value of the test statistic for an overall test in a genome are discussed and analyzed. A simulation study of QTL mapping is also presented which illustrates the utility, properties, advantages and disadvantages of the method.
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            A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

            The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.
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              Genomics-assisted breeding for crop improvement.

              Genomics research is generating new tools, such as functional molecular markers and informatics, as well as new knowledge about statistics and inheritance phenomena that could increase the efficiency and precision of crop improvement. In particular, the elucidation of the fundamental mechanisms of heterosis and epigenetics, and their manipulation, has great potential. Eventually, knowledge of the relative values of alleles at all loci segregating in a population could allow the breeder to design a genotype in silico and to practice whole genome selection. High costs currently limit the implementation of genomics-assisted crop improvement, particularly for inbreeding and/or minor crops. Nevertheless, marker-assisted breeding and selection will gradually evolve into 'genomics-assisted breeding' for crop improvement.
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                Author and article information

                Contributors
                +91-40-30713305 , +91-40-30713074 , r.k.varshney@cgiar.org
                Journal
                Theor Appl Genet
                TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik
                Springer-Verlag (Berlin/Heidelberg )
                0040-5752
                1432-2242
                6 June 2010
                6 June 2010
                September 2010
                : 121
                : 5
                : 971-984
                Affiliations
                [1 ]University of Agricultural Sciences (UAS), Krishinagar, Dharwad, 580 005 Karnataka India
                [2 ]International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, 502 324 Andhra Pradesh India
                [3 ]Genomics towards Gene Discovery Sub Programme, Generation Challenge Programme (GCP), c/o CIMMYT, Int APDO, Postal 6-641, 06600 Mexico, DF, Mexico
                Author notes

                Communicated by M. Xu.

                Article
                1366
                10.1007/s00122-010-1366-x
                2921499
                20526757
                643942b6-840e-4353-9f0c-30c084e05409
                © The Author(s) 2010
                History
                : 7 December 2009
                : 15 May 2010
                Categories
                Original Paper
                Custom metadata
                © Springer-Verlag 2010

                Genetics
                Genetics

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