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Overcoming limitations of dominant marker data: Population structure of the parasitic plant Cistanche phelypaea (L.) Cout. inferred from RAPD markers (CROSBI ID 496149)

Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija

Šatović, Zlatko ; Roman, Belen ; Alfaro, Carmen ; Rubiales, Diego ; Cubero, Jose Ignacio ; Pujadas, Antonio Overcoming limitations of dominant marker data: Population structure of the parasitic plant Cistanche phelypaea (L.) Cout. inferred from RAPD markers // Abstracts - COST Action 849: Parasitic Plant Management in Sustainable Agriculture - Thematic meeting "Genetic diversity of parasitic plants" / Rubiales, Diego (ur.). Cordoba, 2004. str. 10-10-x

Podaci o odgovornosti

Šatović, Zlatko ; Roman, Belen ; Alfaro, Carmen ; Rubiales, Diego ; Cubero, Jose Ignacio ; Pujadas, Antonio

engleski

Overcoming limitations of dominant marker data: Population structure of the parasitic plant Cistanche phelypaea (L.) Cout. inferred from RAPD markers

RAPD and AFLP markers have been widely used to assess genetic diversity and population structure because of the rapidity and ease with which a high number of polymorphic markers can be generated. Genetic variation is represented by the presence or absence of amplified DNA fragments (bands), whose signals behave as dominant markers and the data analysis is hampered by the lack of complete genotypic information. Recent advances in statistical methods (Lynch and Milligan, 1994 ; Stewart and Excoffier, 1996 ; Zhivotovsky, 1999 ; Pritchard et al., 2000 ; Holsinger et al., 2002) make analyses of population structure based on dominant marker data possible although some problems of bias cannot be completely eliminated. The analysis of molecular variance (AMOVA) is usually used to partition the total phenotypic variance into within populations, among populations within subspecies, and between subspecies (Excoffier et al., 1992). The AMOVA can be performed on Dice distance matrix among individuals treating an RAPD (or AFLP) profile as a haplotype (Huff et al., 1993). The variance components can be tested statistically by non-parametric randomisation tests. A Bayesian method with non-uniform prior distribution of allele frequencies (Zhivotovsky, 1999) could be used assuming Hardy-Weinberg genotypic proportions in order to estimate marker allele frequencies. Genetic diversity and population genetic structure can be computed following the treatment of Lynch and Milligan (1994). Expected heterozygosity or Nei's gene diversity (Nei, 1973) can be calculated for each population and the total gene diversity (Ht), the average gene diversity within populations (Hw), the average gene diversity among populations in excess of that observed within populations (Hb), and finally Wright's Fst can be obtained. Yet another Bayesian method developed by Holsinger et al. (2002) can be used in order to estimate FIS (inbreeding coefficient) from dominant marker data. The estimates of FIS often seem to be unreliable and have to be regarded with great caution. Nevertheless, estimates of  B (= FST) can also be obtained without estimating FIS (FIS free model). Finally, the model-based clustering program STRUCTURE (Pritchard et al., 2000) can be used to estimate the underlying population structure. This Bayesian method enables identification of clusters of genetically similar individuals from multilocus genotypes without prior knowledge of their population affiliation. In this approach, it is assumed that there are K populations contributing to the gene pool of the sampled populations.

dominant markers; population structure; biodiversity; AMOVA; Bayesian methods

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Podaci o prilogu

10-10-x.

2004.

objavljeno

Podaci o matičnoj publikaciji

Abstracts - COST Action 849: Parasitic Plant Management in Sustainable Agriculture - Thematic meeting "Genetic diversity of parasitic plants"

Rubiales, Diego

Cordoba:

Podaci o skupu

COST Action 849: Parasitic Plant Management in sustainable Agriculture - Thematic meeting "Genetic diversity of parasitic plants"

pozvano predavanje

19.02.2004-21.02.2004

Córdoba, Španjolska

Povezanost rada

Poljoprivreda (agronomija), Biologija, Biotehnologija