Table 1. Summary of GWP approaches organized by the assumption of marker variances in the present study.

Approach	Marker Variances		Reference/R Package
	Homoscedastic	Heteroscedastic
BLUP	x		Meuwissen et al. (2001)
rrBlupM6	x		Piepho et al. (2012)
RIR	x		Hofheinz et al. (2012)
BL		x	Pérez et al. (2010)
HEM		x	Shen et al. (2013)
RMLA		x	New approach
RMLV		x	New approach
RRWA		x	New approach

GWP, genome-wide prediction; BLUP, best linear unbiased prediction; RIR, ridge regression employing preliminary estimates of the heritability; BL, Bayesian LASSO ; HEM, heteroscedastic effects model; RMLA, estimation of the error and genetic variance components with restricted maximum likelihood and partitioning according to analysis of variance components; RMLV, modification of the restricted maximum likelihood procedure that yields heteroscedastic variances; RRWA, ridge regression with weighing factors according to analysis of variance components.