Building Ultra-High-Density Linkage Maps Based on Efficient Filtering of Trustable Markers.

The study is focused on addressing the problem of building genetic maps in the presence of ∼10-10 of markers per chromosome. We consider a spectrum of situations with intrachromosomal heterogeneity of recombination rate, different level of genotyping errors, and missing data. In the ideal scenario of the absence of errors and missing data, the majority of markers should appear as groups of cosegregating markers ("twins") representing no challenge for map construction.

Identification of the sex-determining region in flathead grey mullet (Mugil cephalus).

Elucidation of the sex-determination mechanism in flathead grey mullet (Mugil cephalus) is required to exploit its economic potential by production of genetically determined monosex populations and application of hormonal treatment to parents rather than to the marketed progeny. Our objective was to construct a first-generation linkage map of the M. cephalus in order to identify the sex-determining region and sex-determination system.

Experimental evolution of recombination and crossover interference in Drosophila caused by directional selection for stress-related traits.

Background: Population genetics predicts that tight linkage between new and/or pre-existing beneficial and deleterious alleles should decrease the efficiency of natural selection in finite populations. By decoupling beneficial and deleterious alleles and facilitating the combination of beneficial alleles, recombination accelerates the formation of high-fitness genotypes. This may impose indirect selection for increased recombination.

Fast and accurate construction of ultra-dense consensus genetic maps using evolution strategy optimization.

Our aim was to develop a fast and accurate algorithm for constructing consensus genetic maps for chip-based SNP genotyping data with a high proportion of shared markers between mapping populations. Chip-based genotyping of SNP markers allows producing high-density genetic maps with a relatively standardized set of marker loci for different mapping populations. The availability of a standard high-throughput mapping platform simplifies consensus analysis by ignoring unique markers at the stage of consensus mapping thereby reducing mathematical complicity of the problem and in turn analyzing bigger size mapping data using global optimization criteria instead of local ones.