CODA (crossover distribution analyzer): quantitative characterization of crossover position patterns along chromosomes

Abstract

BackgroundDuring meiosis, homologous chromosomes exchange segments via the formation of crossovers. This phenomenon is highly regulated; in particular, crossovers are distributed heterogeneously along the physical map and rarely arise in close proximity, a property referred to as "interference". Crossover positions form patterns that give clues about how crossovers are formed. In several organisms including yeast, tomato, Arabidopsis, and mouse, it is believed that crossovers form via at least two pathways, one interfering, the other not.ResultsWe have developed a software package - "CODA", for CrossOver Distribution Analyzer - which allows one to quantitatively characterize crossover patterns by fitting interference models to experimental data. Two families of interfering models are provided: the "gamma" model and the "beam-film" model. The user can specify single or two-pathways modeling, and the software package infers the model's parameters and their confidence intervals. CODA can handle data produced from measurements on bivalents or gametes, in the form of continuous crossover positions or marker genotyping. We illustrate the possibilities on data from Wheat, corn and mouse.ConclusionsCODA extends the kind of crossover data that could be analyzed so far to include gametic data (rather than only bivalents/tetrads) when using two-pathways modeling. It will also enable users to perform analyses based on the beam-film model. CODA implements that model's complex physics and mathematics, and uses a summary statistic to overcomes the lack of a computable likelihood which has hampered its use till now.

Combined fluorescent and electron microscopic imaging unveils the specific properties of two classes of meiotic crossovers

“…Note that even SCs with only zero or one RN contribute information to the Maximum Likelihood estimation of ν. Confidence intervals for the fitted ν's are computed based on the Fisher information matrix using CODA software (50).…”

“…Its parameter ν quantifies the strength of interference: Absence of interference corresponds to the value ν = 1 and increasing interference corresponds to increasing ν > 1. For any realization of COs on an SC, it is possible to calculate its likelihood within the Gamma model assuming a value of ν (49); this allows us to use the maximum likelihood method to determine for each chromosome its "optimal" ν, i.e., that which best fits the experimental data (50). Note that even SCs with only zero or one RN contribute information to the Maximum Likelihood estimation of ν.…”

Factors Underlying Restricted Crossover Localization in Barley Meiosis

“…Overall, nearly 40% of the MLH3 foci were separated by less than 20% of arm length. These data were analyzed using the CODA gamma distribution method to quantify the strength of interference (nu), whereby a value for nu = 1 indicates no interference; >1 positive interference; <1 negative interference (37). This analysis gave values for nu of 1.44 and 1.58 for 2H and 3H…”

Immunocytological Analysis of Meiotic Recombination in the Gray Goose (<b><i>Anser anser</i></b>)

“…The ν values vary between 0 (no interference) to 20 (absolute interference, or only 1 crossover per chromosome) [Falque et al, 2009;Gauthier et al, 2011]. The distances were fitted to gamma distributions by a maximum-likelihood method.…”