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      Identification of candidate genome regions controlling disease resistance in Arachis

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          Abstract

          Background

          Worldwide, diseases are important reducers of peanut ( Arachis hypogaea) yield. Sources of resistance against many diseases are available in cultivated peanut genotypes, although often not in farmer preferred varieties. Wild species generally harbor greater levels of resistance and even apparent immunity, although the linkage of agronomically un-adapted wild alleles with wild disease resistance genes is inevitable. Marker-assisted selection has the potential to facilitate the combination of both cultivated and wild resistance loci with agronomically adapted alleles. However, in peanut there is an almost complete lack of knowledge of the regions of the Arachis genome that control disease resistance.

          Results

          In this work we identified candidate genome regions that control disease resistance. For this we placed candidate disease resistance genes and QTLs against late leaf spot disease on the genetic map of the A-genome of Arachis, which is based on microsatellite markers and legume anchor markers. These marker types are transferable within the genus Arachis and to other legumes respectively, enabling this map to be aligned to other Arachis maps and to maps of other legume crops including those with sequenced genomes. In total, 34 sequence-confirmed candidate disease resistance genes and five QTLs were mapped.

          Conclusion

          Candidate genes and QTLs were distributed on all linkage groups except for the smallest, but the distribution was not even. Groupings of candidate genes and QTLs for late leaf spot resistance were apparent on the upper region of linkage group 4 and the lower region of linkage group 2, indicating that these regions are likely to control disease resistance.

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          Most cited references 57

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          AFLP: a new technique for DNA fingerprinting.

          A novel DNA fingerprinting technique called AFLP is described. The AFLP technique is based on the selective PCR amplification of restriction fragments from a total digest of genomic DNA. The technique involves three steps: (i) restriction of the DNA and ligation of oligonucleotide adapters, (ii) selective amplification of sets of restriction fragments, and (iii) gel analysis of the amplified fragments. PCR amplification of restriction fragments is achieved by using the adapter and restriction site sequence as target sites for primer annealing. The selective amplification is achieved by the use of primers that extend into the restriction fragments, amplifying only those fragments in which the primer extensions match the nucleotides flanking the restriction sites. Using this method, sets of restriction fragments may be visualized by PCR without knowledge of nucleotide sequence. The method allows the specific co-amplification of high numbers of restriction fragments. The number of fragments that can be analyzed simultaneously, however, is dependent on the resolution of the detection system. Typically 50-100 restriction fragments are amplified and detected on denaturing polyacrylamide gels. The AFLP technique provides a novel and very powerful DNA fingerprinting technique for DNAs of any origin or complexity.
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            Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

            The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.
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              Precision mapping of quantitative trait loci.

               Z Zeng (1994)
              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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                Author and article information

                Journal
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central
                1471-2229
                2009
                22 August 2009
                : 9
                : 112
                Affiliations
                [1 ]Embrapa Genetic Resources and Biotechnology, C.P. 02372, CEP 70.770-900, Brasília, DF, Brazil
                [2 ]Catholic University of Brasília, Campus II, SGAN 916, CEP 70.790-160, Brasília, DF, Brazil
                [3 ]The Sainsbury Laboratory, Colney Lane, Norwich NR4 7UH, UK
                [4 ]University of Munich Ludwig-Maximilians (LMU) Department of Biology, Maria-Ward-Strasse 1a, 80638, Munich, Germany
                [5 ]International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Greater Hyderabad 502 324, India
                [6 ]University of Brasília, Campus Darcy Ribeiro, Brasília, DF, Brazil
                Article
                1471-2229-9-112
                10.1186/1471-2229-9-112
                2739205
                19698131
                Copyright © 2009 Leal-Bertioli et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Plant science & Botany

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