Academic journal article Genetics

Estimation of Multilocus Linkage Disequilibria in Diploid Populations with Dominant Markers

Academic journal article Genetics

Estimation of Multilocus Linkage Disequilibria in Diploid Populations with Dominant Markers

Article excerpt


Analysis of population structure and organization with DNA-based markers can provide important information regarding the history and evolution of a species. Linkage disequilibrium (LD) analysis based on allelic associations between different loci is emerging as a viable tool to unravel the genetic basis of population differentiation. In this article, we derive the EM algorithm to obtain the maximum-likelihood estimates of the linkage disequilibria between dominant markers, to study the patterns of genetic diversity for a diploid species. The algorithm was expanded to estimate and test linkage disequilibria of different orders among three dominant markers and can be technically extended to manipulate an arbitrary number of dominant markers. The feasibility of the proposed algorithm is validated by an example of population genetic studies of hickory trees, native to southeastern China, using dominant random amplified polymorphic DNA markers. Extensive simulation studies were performed to investigate the statistical properties of this algorithm. The precision of the estimates of linkage disequilibrium between dominant markers was compared with that between codominant markers. Results from simulation studies suggest that three-locus LD analysis displays increased power of LD detection relative to two-locus LD analysis. This algorithm is useful for studying the pattern and amount of genetic variation within and among populations.

(ProQuest-CSA LLC: ... denotes formulae omitted.)

THE pattern and extent of nonrandom associations among polymorphic markers distributed over the genome are related to the evolutionary rate of population structure for a species (TISHKOFF et al. 1996, 2001; STEPHENS et al. 2001; ARDLIE et al. 2002; WEISS and CLARK 2002). One measure of such nonrandom associations, linkage disequilibrium (LD), is often affected by various evolutionary forces, such as selection, genetic drift, mutation, admixture, population structure, etc., which have operated in the population. For this reason, by estimating and testing for the extent and distribution of LD throughout the genome, the evolution of population structure can be inferred (TISHKOFF and WILLIAMS 2002). There is a wealth of literature on the application of the LD analysis to understand the population evolution of humans (REICH et al. 2001; ARDLIE et al. 2002; DAWSON et al. 2002; GABRIEL et al. 2002) as well as a variety of plants and animals (Remington et al. 2001; HANSSON et al. 2004; LIU et al. 2006).

Unlike humans and several model systems, such as mouse and Arabidopsis, in which high-resolution LD maps have been constructed with codominant markers, such as single-nucleotide polymorphisms (SNPs) and microsatellites,many underrepresented species, like forest trees, still heavily rely upon simple and cheap dominant marker techniques. These markers including random amplified polymorphic DNA (RAPD) (WILLIAMS et al. 1990) and amplified fragment length polymorphism (AFLP) (VOS et al. 1995) can be genotyped arbitrarily from the genome with no need of prior knowledge about the structure and sequence of the genome. There have been extensive publications on the use of dominant markers to explore the amount, structure, and distribution of genetic variation in a population (YAN et al. 1999; ZHIVOTOVSKY 1999; HOLSINGER et al. 2002; MILLER and SCHAAL 2006) and manage biological resources and diversity in agriculture and forestry (KUANG et al. 1998; SILBIGER et al. 1998; KREMER et al. 2005). In the postgenomic era, proteomic techniques have become increasingly available to produce dominant markers such as presence/absence sport (PAS) and protein quantitative locus (PQL) (THIELLEMENTET al. 1999; ZIVY and DE VIENNE 2000; CONSOLI et al. 2002). Proteomic markers are often related to biological functions and, therefore, will play an important role in the genetic study of variation in a natural or an experimental population.

For a dominant marker, the plus allele, shown as the presence of a band on the gel, dominates over the null allele, shown as the absence of a band (unamplifiable by PCR). …

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