A note on the rationale for estimating genealogical coancestry from molecular markers

We show how the expected values of the empirical measures of similarity based on molecular marker data are functions of the genealogical coancestry. From these formulas, it is easy to derive estimators of genealogical coancestry from molecular data. We include variation of allelic frequencies in the estimators.The estimators are illustrated with simulated examples and with a real dataset from dairy cattle. In general, estimators are accurate and only slightly biased. From the real data set, estimators based on covariances are more compatible with genealogical coancestries than those based on molecular coancestries. A frequently used estimator based on the average of estimated coancestries produced inflated coancestries and numerical instability. The consequences of unknown gene frequencies in the founder population are briefly discussed, along with alternatives to overcome this limitation.Estimators of genealogical coancestry based on molecular data are easy to derive. Estimators based on molecular covariance are more accurate than those based on identity by state. A correction considering the random distribution of allelic frequencies improves accuracy of these estimators, especially for populations with very strong drift.The concept of coancestry (or kinship) between two individuals plays a central role in practical applications of genetics. In animal breeding, coancestry coefficients are required both to estimate genetic parameters and to carry out genetic evaluations [1]. In sociobiology, they are important to make evolutionary interpretations of social behavior and to determine parameters of the biology of reproduction. In the field of animal conservation, they constitute fundamental tools to estimate inbreeding depression and to optimize genetic management in a conservation program. Several estimators of coancestries based on molecular information have been proposed, including recent estimators that are designed to deal with a large number of markers [2-7]. Th