Statistical analysis and simulations that account for simultaneous effects of positive, negative, and no crossover interference in multilocus recombination data.

Crossover interference (COI) is a widespread feature of homologous meiotic recombination. It can be quantified by the classical coefficient of coincidence (CoC), but this characteristic is highly variable and specific to the pair of chromosomal intervals considered. Several models have been proposed to characterize COI at the chromosomal level. In the gamma model, the strength of interference is characterized by a shape parameter ν. In contrast, the gamma-sprinkled two-pathway model (GS) accounts for both interference-dependent and independent crossover (CO) events by fitting a mixture of gamma distributions with v > 1 and v = 1 with proportions 1-p and p. In reality, COI may vary along the chromosome, resulting in а poor fit of the employed model to the analyzed data. Additional inconsistency can be caused by the common neglect of possible negative crossover interference (NCOI) in the model, although the phenomenon was previously reported for several organisms. We present an extension of the GS model to account for possible NCOI and provide suitable software for estimating the parameters of the extended GS model. On real chromosome data from a conifer (larch, Larix principis-rupprechtii), sugar beet (Beta vulgaris), and wheatgrass (Thinopyrum intermedium), we demonstrate a potential efficient separation of three crossover (CO) processes on chromosomes: CO repulsion (positive COI), CO clustering (negative COI), and independent CO events (no COI).