QTL Mapping
Ben Hui Liu
Abstract
Ben Hui Liu
Abstract
This chapter discusses methods for quantitative trait locus (QTL) mapping using natural populations. It describes single-marker analysis using open-pollinated populations in plants and the sib-pair approach. The QTL mapping methods for experimental populations are based on cosegregation among the putative QTLs and the markers, as are QTL mapping methods using natural populations. The basic rationale behind the sib-pair method is that the variation of a trait value between sibs must be related to the probability of identity by descent for the genes or QTLs controlling the trait. The sib-pair method has been used extensively for QTL mapping in humans. The chapter discusses implementation of sib-pair methods including hypothesis tests and parameter estimation. J. K. Haseman and R. C. Elston give an approach to obtain maximum likelihood estimates of the recombination fraction and the genetic effects, which required iterative procedures to obtain the solution.
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This chapter discusses methods for quantitative trait locus (QTL) mapping using natural populations. It describes single-marker analysis using open-pollinated populations in plants and the sib-pair approach. The QTL mapping methods for experimental populations are based on cosegregation among the putative QTLs and the markers, as are QTL mapping methods using natural populations. The basic rationale behind the sib-pair method is that the variation of a trait value between sibs must be related to the probability of identity by descent for the genes or QTLs controlling the trait. The sib-pair method has been used extensively for QTL mapping in humans. The chapter discusses implementation of sib-pair methods including hypothesis tests and parameter estimation. J. K. Haseman and R. C. Elston give an approach to obtain maximum likelihood estimates of the recombination fraction and the genetic effects, which required iterative procedures to obtain the solution.
Key concepts: Quantitative trait locus, Inclusive composite interval mapping, Computer science, Biology, Genetics, Gene mapping, Gene, Chromosome