Tobias Lanzl, Albrecht E. Melchinger, Chris‑Carolin Schön

Theoretical and Applied Genetics; Nov. 2023; vol. 136:236

Key message

Mating designs determine the realized additive genetic variance in a population sample. Deflated or inflated variances can lead to reduced or overly optimistic assessment of future selection gains.

Abstract

The additive genetic variance V_A  inherent to a breeding population is a major determinant of short- and long-term genetic gain. When estimated from experimental data, it is not only the additive variances at individual loci (QTL) but also covariances between QTL pairs that contribute to estimates of V_A . Thus, estimates of V_A depend on the genetic structure of the data source and vary between population samples. Here, we provide a theoretical framework for calculating the expectation and variance of V_A from genotypic data of a given population sample. In addition, we simulated breeding populations derived from different numbers of parents (P = 2, 4, 8, 16) and crossed according to three different mating designs (disjoint, factorial and half-diallel crosses). We calculated the variance of V_A and of the parameter b reflecting the covariance component in V_A standardized by the genic variance. Our results show that mating designs resulting in large biparental families derived from few disjoint crosses carry a high risk of generating progenies exhibiting strong covariances between QTL pairs on different chromosomes. We discuss the consequences of the resulting deflated or inflated V_A estimates for phenotypic and genome-based selection as well as for applying the usefulness criterion in selection. We show that already one round of recombination can effectively break negative and positive covariances between QTL pairs induced by the mating design. We suggest to obtain reliable estimates of V_A and its components in a population sample by applying statistical methods differing in their treatment of QTL covariances.

See https://link.springer.com/article/10.1007/s00122-023-04447-2

Figure 1; (A) Crossing schemes of the three mating designs (disjoint cross (DC), factorial cross (FC), and half-diallel cross (HC)) exemplified with four parental lines (P1,P2,P3,P4). (B) Flowchart for one replication of the simulation, starting with the sampling of P∈{2,4,8,16} parental lines and N∈{50,250,1000} genotypes in the simulated populations. G1, G2, G3, G4 refer to the generation of intermating and G1-DH, G2-DH, G3-DH, G4-DH to the DH populations derived from the respective generation