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. 2009 Apr 11;119(1):105–123. doi: 10.1007/s00122-009-1021-6

Table 1.

Detected QTLs of REML single-locus analysis (I), REML forward selection (II), Bayesian single-environmental (III), and Bayesian multi-environmental (IV) mapping for several traits in the spring barley population

QTLa Coded marker numberb SSR-marker group Chr.c Pos.d Bine R² (%)f RP(%)g QTL mapping strategies
Ih IIi IIIj IVk
Days until heading (h² ≈ 0.77)
QHea.S42-1H.1 5 GBM1042 1H 39 6 4.4 2.7 M*l MxEm
QHea.S42-1H.2 14 GBM1061 1H 115 13 0.7 0.9 Mm
QHea.S42-1H.3 16 HVABAIP 1H 144 13 4.0 1.8 MxE MxE
QHea.S42-2H.1 20 GBM1052 2H 42 4 (4) 21.6 −9.0 M* M* M MxE
QHea.S42-2H.2 22–23 EBmac684, GMS3 2H 80-86 7–8 4.9, 5.0 −1.9, −2.0 M* MxE MxE
QHea.S42-2H.3 29 EBmac415 2H 146 13 4.2 −3.3 MxE
QHea.S42-3H.1 31–32 HVLTPPB, EBmac705 3H 25–30 3 (3) 4.9, 4.5 −4.4, −4.3 M* MxE
QHea.S42-3H.2 39 GBM1043 3H 130 10 4.3 −1.9 M* M* MxE
QHea.S42-3H.3 40–41 HV13GEIII, HVM62 3H 155–165 13–14 (15) 7.3, 4.6 −2.9, −2.2 M* M* MxE M
QHea.S42-4H.1 54 EBmac701 4H 130 10 0.5 0.7 M
QHea.S42-4H.2 59–61 HVJASIP, HVM67, HDAMYB 4H 180–190 12–13 (12) 4.3, 4.9, 6.1 1.8, 1.9, 2.2 M* M* MxE
QHea.S42-5H.1 65 Bmag337 5H 43 5 0.3 −0.6 MxE
QHea.S42-5H.2 68 MGB338 5H 85 8 0.4 1.0 MxE
QHea.S42-6H.1 77 EBmac624 6H 107 7 4.5 −2.1 M*
QHea.S42-7H.1 92 BMS64 7H 146 8 4.1 −2.6 M* M*
Plant height (h² ≈ 0.76)
QHei.S42-2H.1 18–20 HVM36, GBM1035, GBM1052 2H 17–42 2–4 (3–4) 6.0, 5.3, 3.0 −8.9, −8.6, −11.5 M* M* MxE
QHei.S42-2H.2 22–24 EBmac684, GMS3, HVTUB 2H 80–92 7–8 13.5, 16.3, 9.9 −10.8, −12.0, −8.9 M* M* M
QHei.S42-3H.1 31–35 HVLTPPB, EBmac705, HVITR1, MGB410, Bmag603 3H 25–70 3–6 (3) 5.4, 5.4, 8.2, 6.1, 6.8 16.7, 16.7, 24.0, 12.9 M* M* MxE MxE
QHei.S42-3H.2 39 GBM1043 3H 130 10 7.6 8.9 M* M* M MxE
QHei.S42-3H.3 40–43 HV13GEIII, HVM62, MGB358, Bmac29 3H 155–190 13–16 (15) 22.0, 16.9, 10.5, 3.9 17.9, 15.1, 11.7, 7.3 M* M* MxE MxE
QHei.S42-4H.1 53–56 TACMD, EBmac701, EBmac635, EBmac679 4H 125–132 9-10 4.8, 6.3, 4.7, 5.1 −7.3, −8.4, −7.0, −7.3 M*
QHei.S42-4H.2 58–61 GBM1015, HVJASIP, HVM67, HDAMYB 4H 170–190 12–13 (11–12) 9.2, 14.6, 15.2, 5.8 −8.8, −11.0, −11.0,−7.1 M* M* MxE
QHei.S42-5H.1 65 Bmag337 5H 43 5 6.4 9.6 M*
QHei.S42-7H.1 83 Bmag7 7H 27 2 4.6 12.7 M*
Grain yield (h² ≈ 0.70)
QYld.S42-1H.1 6 MGB325 1H 52 6 5.0 −13.0 M*
QYld.S42-1H.2 8–11 HVM20, Bmag211, Bmag149, Bmag105 1H 65–75 7–8 4.9, 4.1, 4.8, 7.2 −12.9, −11.8, −12.8, −18.3 M* M* MxE M
QYld.S42-1H.3 16 HVABAIP 1H 144 13 5.8 −9.3 MxE MxE
QYld.S42-2H.1 25–26 Bmag381, Bmag125 2H 107–122 9–10 3.0, 4.2 −6.5, −8.4 M* MxE
QYld.S42-3H.1 31–35 HVLTPPB, EBmac705, HVITR1, MGB410, Bmag603 3H 25-70 3–6 (3) 13.8, 13.9, 13.7, 10.7, 12.4 −32.6, −32.5, −39.8, −22.8, −24.7 M* M* MxE MxE
QYld.S42-3H.2 39 GBM1043 3H 130 10 2.0 −5.3 M* MxE MxE
QYld.S42-3H.3 40–41 HV13GEIII, HVM62 3H 155-165 13–14 (15) 8.2, 6.1 −12.8, −10.7 M* MxE MxE
QYld.S42-3H.4 43 Bmac29 3H 190 16 0.1 −1.1 MxE
QYld.S42-5H.1 65 Bmag337 5H 43 5 3.6 −9.6 MxE
QYld.S42-5H.2 69 GMS61 5H 126 10 2.6 −12.9 MxE
QYld.S42-7H.1 92 BMS64 7H 146 8 4.2 −11.1 M*
Thousand grain weight (h² ≈ 0.54)
QTgw.S42-1H.1 8 HVM20 1H 65 7 1.5 −2.1 MxE
QTgw.S42-1H.2 16 HVABAIP 1H 144 13 0.5 1.0 MxE
QTgw.S42-2H.1 23 GMS3 2H 86 8 1.9 1.9 M* MxE MxE
QTgw.S42-2H.2 25–26 Bmag381, Bmag125 2H 107–122 9–10 0.3, 0.5 0.9, 0.9 MxE MxE
QTgw.S42-3H.1 38 HVM60 3H 110 9 (8) 4.5 3.1 M*
QTgw.S42-3H.2 40–42 HV13GEIII, HVM62, MGB358 3H 155–175 13–15 (15) 3.3, 4.3, 6.5 −2.8, −3.1, −3.8 M* M* MxE
QTgw.S42-4H.1 53–56 TACMD, EBmac701, EBmac635, EBmac679 4H 125–132 9–10 16.6, 16.3, 17.1, 16.8 −5.6, −5.7, −5.5, −5.5 M* M* MxE MxE
QTgw.S42-4H.2 59–61 HVJASIP, HVM67, HDAMYB 4H 180–190 12–13 (12) 8.8, 8.4, 8.7 −3.7, −3.6, −3.7 M* M* MxE
QTgw.S42-6H.1 75 GMS6 6H 96 5 1.4 −1.8 MxE
QTgw.S42-6H.2 79 GBM1008 6H 135 10 1.6 1.8 MxE
QTgw.S42-7H.1 92–95 BMS64, Bmag120, MGB317, EBmac755 7H 146–166 8–11 4.6, 4.7, 4.4, 4.2 −4.2, −4.3, −4.6, −3.6 M* M* MxE
Ears per m² (h² ≈ 0.21)
QEar.S42-1H.1 16 HVABAIP 1H 144 13 6.0 8.4 M*
QEar.S42-2H.1 18 HVM36 2H 17 2 (3) 5.8 9.5 M*
QEar.S42-2H.2 21–24 MGB391, EBmac684, GMS3, HVTUB 2H 67–92 6–8 6.4, 21.5, 24.2, 21.2 11.1, 15.3, 16.5, 14.7 M* MxE MxE
QEar.S42-3H.1 34–35 MGB410, Bmag603 3H 65–70 5–6 6.7, 6.5 −13.7, −13.8 M* M*
QEar.S42-3H.2 40–41 HV13GEIII, HVM62 3H 155–165 13–14 (15) 5.2, 4.6 −8.8, −7.9 M*
QEar.S42-4H.1 45–46 HVOLE, HVB23D 4H 21–25 3 5.2, 4.5 −9.7, −9.3 M*
QEar.S42-4H.2 53–56 TACMD, EBmac701, EBmac635, EBmac679 4H 125–132 9–10 10.0, 9.6, 9.5, 9.1 11.4, 11.3, 10.6, 10.6 M*
QEar.S42-4H.3 58–61 GBM1015, HVJASIP, HVM67, HDAMYB 4H 170–190 12–13 (11–12) 13.6, 23.9, 22.7, 9.0 12.0, 16.0, 15.4, 9.8 M* M* MxE MxE
QEar.S42-5H.1 62 MGB384 5H 0 2 6.8 −10.8 M* M*
QEar.S42-5H.2 65 Bmag337 5H 43 5 4.6 −8.3 M*
QEar.S42-6H.1 79 GBM1008 6H 135 10 5.1 −7.6 M*

aNames of the QTLs consisting of the qualifier “Q”, the trait abbreviation, the determined population, the mapped chromosome and a QTL number to distinguish between QTLs on the same chromosome. Markers with a distance ≤20 cM were considered to be a single QTL

bThe markers were coded according to their chromosomal location

cChromosomal location of the SSR markers

dPosition of the SSR markers on the chromosome in centiMorgan (cM) (von Korff et al. 2004). If several markers were significant, the cM range is given

eBin marker class following Kleinhofs and Graner (2001); Costa et al. (2001). In the case of several significant markers, the Bin class range is displayed. An additional number in brackets gives the Bin class following Marcel et al. (2007). As the Bin class of Marcel et al. (2007) was available only for some markers, in the case of several significant markers belonging to the same QTL, these markers are given in italics

fGenetic variance explained by a marker calculated using REML method in SAS Proc Mixed

gRelative performance of the homozygous exotic genotype

hREML single-locus QTL mapping

iREML forward selection approach

jBayesian multi-locus single-environmental analysis

kBayesian multi-locus multi-environmental analysis

lMarker main effect obtained from REML analysis

mM Marker main effect, MxE Marker interaction effect. Both effects are derived from Bayesian analysis and have to be interpreted differently as in REML method. In Bayesian mapping the model was oversaturated so that marker main and interaction effects are not independently identifiable