Breeding without breeding: minimum fingerprinting effort with respect to the effective population size

Abstract

We present a probabilistic model to minimize the fingerprinting effort associated with the implementation of the “breeding without breeding” scheme under partial pedigree reconstruction. Our approach is directed at achieving a declared target population’s minimum effective population size (Ne), following the pedigree reconstruction and genotypic selection and is based on the graph theory algorithm. The primary advantage of the proposed method is to reduce the cost associated with fingerprinting before the implementation of the pedigree reconstruction for seed parent–offspring derived from breeding arboreta and production or natural populations. Stochastic simulation was conducted to test the method’s efficiency assuming a simple polygenic model and a single trait. Hypothetical population consisted of 30 parental trees that were paired at random (selfing excluded), resulting in 600 individuals (potential candidates for forwards selection). The male parentage was assumed initially unknown. The model was used to estimate the minimum genotyping sample size needed to reaching the prescribed Ne. Results were compared with the known pedigree data. The model was successful in revealing the true relationship pattern over the whole range of Ne. Two to three offspring entered genotyping to meet the Ne = 2 while 41 to 43 were required to satisfy the Ne = 14. Importantly, genetic gain was affected at the lower limits of the genotyping effort. Doubling the number of parents resulted in considerable reduction of the genotyping effort at higher Ne values.