Polyploidization increases meiotic recombination frequency in Arabidopsis: a close look at statistical modeling and data analysis

See research article at http://www.biomedcentral.com/1741-7007/9/24 webciteMany species, particularly flowering plants, have usually experienced a state of polyploidy in their evolutionary history. Meiotic recombination creates novel configurations of genetic variants maintained in the genome of a species for facilitating natural and artificial selection. Thus, to understand how a diploid species differs in frequency of meiotic recombination from its polyploid ancestor has a significant impact in both evolutionary biology and plant and animal genetic breeding. It has been well established that the evolution of polyploid genomes is an extremely dynamic process compared to that of diploids, characterized by extensive genetic and epigenetic changes occurring in the nuclear genome following polyploidization [1-3]. Little is known about the mechanism underpinning the genetic changes. To address this fundamental question, Pecinka and colleagues described in a recently published paper by BMC Biology a direct comparison in frequency of meiotic recombination of the diploid and tetraploid genomes of Arabidopsis [4]. One of the most striking methodological challenges to the study is to properly evaluate the recombination parameter in populations of the species at different levels of polyploidy, particularly in autopolyploids. In fact, linkage analysis with autotetraploids has been a historical problem that can be traced back to the pioneering works of the prominent mathematical geneticists [5-7].There are at least two major challenges to the tetrasomic linkage analysis. Firstly, double reduction, the most distinct characteristic of polysomic inheritance, allows sister chromatids to enter into the same gamete during meiosis and thus cause systematic distortion in allele segregation [8]. Secondly, multiplex allele segregation makes it almost impossible to infer the underlying genotype directly from PRC-based phenotype data even for co-dominant markers such as a single nucleotide