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      Precision mapping of quantitative trait loci.

      1
      Genetics
      Oxford University Press (OUP)

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          Abstract

          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
          Genetics
          Genetics
          Oxford University Press (OUP)
          0016-6731
          0016-6731
          Apr 1994
          : 136
          : 4
          Affiliations
          [1 ] Department of Statistics, North Carolina State University, Raleigh 27695-8203.
          Article
          10.1093/genetics/136.4.1457
          1205924
          8013918
          a612c3b8-8a44-445f-a54e-d4ee3ec79add
          History

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