Mapping multiple QTL for birth weight in cattle Using a mixed model approach

Abstract

A mixed model approach was developed, allowing for the rapid detection of multiple QTL across the complete genome in half sib designs. The method fits all the markers simultaneously as independent random effects with common variance within linkage groups nested within sires. For the linkage groups with significant marker variance a QTL profile is predicted as a weighted function of the marker BLUP for each marker position and used to identify a putative QTL location. A putative QTL covariate was then calculated for that position from flanking markers and added to the model as a fixed effect nested within sires. If this did not explain all the marker variance, the process was repeated. The method was applied to analysis birth weight data from 356 animals representing three beef cattle half-sib families scored for 249 markers spread across 29 bovine autosomes. The results indicated significant evidence for QTL affecting birth weight on BTA1, 5, 13, 14, 21, 22 and 24.