Table 2 Accuracies for genotyped individuals using single- and multi-trait models in scenario G9

From: Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome

Trait1

Region size2

Single-trait3

Multi-trait

BayesN0

ssSNPB1

ssBayesN0

ssSNPB2

BayesN0

ssSNPB1

ssBayesN0

ssSNPB2

L4

1 SNP

ab0.349e

ab0.452cd

ab0.470d

ab0.478c

b0.437d

b0.536b

b0.554b

a0.574a

100 SNPs

a0.365d

a0.460c

a0.478c

a0.479c

a0.481c

a0.559b

a0.590a

a0.590a

1 Chr

b0.335c

b0.434b

bc0.444b

bc0.445b

b0.402b

c0.493a

c0.497a

b0.499a

WG

b0.335d

b0.433b

c0.433bc

c0.433b

c0.362cd

d0.461ab

d0.472a

c0.473a

H

1 SNP

b0.587g

b0.683e

b0.689de

b0.700bc

b0.593f

b0.688cd

b0.699b

a0.712a

100 SNPs

a0.611f

a0.698d

a0.716b

a0.716b

a0.622e

a0.707c

a0.725a

a0.725a

1 Chr

c0.552e

c0.650bd

c0.651cd

c0.651abcd

c0.558e

c0.655ac

c0.657ab

b0.657ab

WG

d0.538d

c0.642c

c0.642bc

c0.643bc

d0.543d

d0.644abc

d0.646ab

c0.646a

  1. 1L and H: low (0.1) and high (0.4) heritability traits, respectively
  2. 2Chr chromosome, WG whole genome
  3. 3ssSNPB1 and ssSNPB2: Single-step SNPBLUP, for which the variance components were obtained from BayesN0 and ssBayesN0, respectively
  4. 4Different alphabets mean significantly different values at a Type 1 error rate of 0.05 with Bonferroni correction. Subscripts and superscripts stand for comparisons within column and row, respectively, for each trait