marker-assisted selection in wheat - ictsd

210Marker-assisted selection – Current status and future perspectives in crops, livestock, forestry and fishThe QTL effects derived from eitherdaughter or granddaughter by ML or nonlinearregression will still be biased forseveral reasons. First, the usual assumptionsof interval mapping, a single QTLsegregating within the marker interval andno QTL in adjacent intervals, often donot reflect reality. Second, the dependantvariable is generally an “adjusted” record,either daughter yield deviations (DYD;VanRaden and Wiggans, 1991) or geneticevaluations. Israel and Weller (1998) demonstratedthat QTL effects derived fromanalysis of either genetic evaluations, yielddeviations or DYD will be underestimated.In addition to this downward bias, thereare two sources of upward bias for QTLeffects. First, the direction of the effectsis generally arbitrary, and therefore absolutevalues are retained and all effects are>0. Third, only the effects deemed “significant”are retained, and this is a selectedsample (Georges et al., 1995). Bayesiananalysis methods that account for bias ofQTL effect due to selection have recentlybeen developed by Weller, Schlezinger andRon (2005).current status of QTL detectionin dairy cattleGenome scans by the granddaughterdesign have been completed for Holsteinsfrom Canada (Nadesalingam, Plante andGibson, 2001), the Netherlands (Spelmanet al., 1996; Schrooten et al., 2000), France(Bennewitz, et al., 2003a; Boichard et al.,2003), Germany (Bennewitz, et al., 2003a;Kuhn et al., 2003a), New Zealand (Spelmanet al., 1999), and the United States (Georgeset al., 1995; Ashwell et al., 1996, 1997,1998a, 1998b, 2004; Ashwell, Van Tasselland Sonstegard, 2001; Zhang et al., 1998;Ashwell and Van Tassell, 1999; Heyen etal., 1999); Finnish Ayrshires (Vilkki et al.,1997; Viitala et al., 2003; Schulman et al.,2004); French Normande and Montbeliardecattle (Boichard et al., 2003); Norwegiancattle in Norway (Klungland et al., 2001;Olsen et al., 2002); and Swedish Red andWhite (SRB) (Holmberg and Andersson-Eklund, 2004). Daughter design analyseshave been performed for Israeli Holsteins(Mosig et al., 2001; Ron et al., 2004). Moststudies have considered the five economicmilk production traits: milk, fat and proteinproduction, and fat and protein concentration,although a number of studies havealso considered somatic cell score (SCS),female fertility, herd life, calving traits,health traits, temperament and conformationtraits. The SCS is a log base 2 functionof the concentration of somatic cells, andhas been shown to be a useful indicator ofudder health. Results are summarized inTable 1.Results for milk, fat and protein production,fat and protein concentration, andSCS from most of the studies listed aboveare summarized at www.vetsci.usyd.edu.au/reprogen/QTL_Map/. Results fromthese traits, and many others includingmeat production, are summarized at http://bovineqtl.tamu.edu. Significant effects werefound on all 29 autosomes, but most effectswere found only in single studies and havenot been repeated. Khatkar et al. (2004)performed a meta-analysis, combining datafrom most of these studies, and foundsignificant across-study effects on chromosomes1, 3, 6, 9, 10, 14 and 20.Methods of incorporatinginformation from genetic markersin genetic evaluation systemsHeritabilities of most economic traits indairy cattle are low to moderate. Geneticevaluation of dairy cattle is complicatedby confounding between genetic and