TY - JOUR
T1 - Additive and testcross genetic variances in crosses among recombinant inbreds
AU - Bernardo, R.
AU - Nyquist, W. E.
PY - 1998/7/1
Y1 - 1998/7/1
N2 - Breeders desire populations with a high mean performance and a large genetic variance. Theory and methods are lacking for predicting additive variance (V(A)) and testcross variance (V(T)) in biparental populations. Breeders have unsuccessfully attempted to predict V(A) based on the coefficient of coancestry (f) or molecular-marker similarity between parents. In this paper, we derive the expected values of V(A) and V(T) in biparental populations, examine the variability of V(A) among biparental crosses, and discuss how V(A) and V(T) may be predicted in applied breeding programs. Suppose i is a recombinant inbred derived from the cross between inbreds P1 and P2, and inbred j is not a direct descendant of i. Let V(A(i,j)) be the additive variance in the F2 of the (i x j) biparental cross. Let V(T(i,j)) be the variance among testcrosses of F2 individuals with a specific unrelated inbred or population. Assuming linkage equilibrium and the absence of epistasis, V(A(i,j)) = λ V(A(P1, j)) + (1 - λ) V(A(P2, j)), where λ = parental contribution of P1 to i. Similarly, V(T(i, j)) = λ V(T(P1, j)) + (1 - λ) V(T(P2, j)). Additive variance in crosses between recombinant inbreds cannot be modelled as a function of f if, as indicated in the literature, V(A) differs among crosses of founder inbreds. If molecular-marker similarity between parents is used as an estimate of f, then a strong linear relationship is likewise not expected between V(A) and marker similarity. Differences between the actual and expected λ led to variation in V(A). In applied breeding programs, modelling V(A) or V(T) in biparental crosses may be feasible with estimates of V(A) or V(T) in prior crosses and information on λ obtained from molecular-marker data.
AB - Breeders desire populations with a high mean performance and a large genetic variance. Theory and methods are lacking for predicting additive variance (V(A)) and testcross variance (V(T)) in biparental populations. Breeders have unsuccessfully attempted to predict V(A) based on the coefficient of coancestry (f) or molecular-marker similarity between parents. In this paper, we derive the expected values of V(A) and V(T) in biparental populations, examine the variability of V(A) among biparental crosses, and discuss how V(A) and V(T) may be predicted in applied breeding programs. Suppose i is a recombinant inbred derived from the cross between inbreds P1 and P2, and inbred j is not a direct descendant of i. Let V(A(i,j)) be the additive variance in the F2 of the (i x j) biparental cross. Let V(T(i,j)) be the variance among testcrosses of F2 individuals with a specific unrelated inbred or population. Assuming linkage equilibrium and the absence of epistasis, V(A(i,j)) = λ V(A(P1, j)) + (1 - λ) V(A(P2, j)), where λ = parental contribution of P1 to i. Similarly, V(T(i, j)) = λ V(T(P1, j)) + (1 - λ) V(T(P2, j)). Additive variance in crosses between recombinant inbreds cannot be modelled as a function of f if, as indicated in the literature, V(A) differs among crosses of founder inbreds. If molecular-marker similarity between parents is used as an estimate of f, then a strong linear relationship is likewise not expected between V(A) and marker similarity. Differences between the actual and expected λ led to variation in V(A). In applied breeding programs, modelling V(A) or V(T) in biparental crosses may be feasible with estimates of V(A) or V(T) in prior crosses and information on λ obtained from molecular-marker data.
KW - Additive variance
KW - Inbreeding
KW - Recombinant inbreds
KW - Testcross variance
UR - http://www.scopus.com/inward/record.url?scp=0031875861&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0031875861&partnerID=8YFLogxK
U2 - 10.1007/s001220050874
DO - 10.1007/s001220050874
M3 - Article
AN - SCOPUS:0031875861
SN - 0040-5752
VL - 97
SP - 116
EP - 121
JO - Theoretical And Applied Genetics
JF - Theoretical And Applied Genetics
IS - 1-2
ER -