a molecular marker-assisted backcross breeding strategy ... · a molecular marker-assisted...
TRANSCRIPT
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A molecular marker-assisted backcrossbreeding strategy for improvingmultiple complex traits in rice
The China-EU workshop
Jianlong Xu
The Institute of Crop Sciences, ChineseAcademy of Agricultural Sciences
E-mail: [email protected]
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Actual yield in farmer field is much lower thantheoretical yield due to all kinds of biotic and abioticstresses. Future breeding will focus on: 1)improvingyield potential;2)reduce differences between actualyield and theoretical yield.
Yield potential Actual yield
Improving yield potential Filling yield gaps
Yield potential
02468
101214t/ha
Actual yield
Inbredindica rice
Hybridindica rice
Inbredjaponica rice
Difference > 35%
Goff and Salmeron 2004 Scientific American 291(2) 42-49
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Besides biotic stresses such as diseases and insects,drought, salinity, extreme low or high temperature, etc.are most important abiotic stresses affecting rice yield.
In the past, less efforts have been taken in rice breedingfor stress tolerance. So there is slow advance in stresstolerance breeding compared with other traits.
Drought
SalinityHigh temperature
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Most agronomic important traits are quantitatively inherited. Awide range of segregating populations derived from bi-parentalcrosses, including RILs, DHs, F2 and its derived populations, andBC or testcross populations, have been used for QTL mapping. Andmany major important QTLs have been cloned in rice. Contrastly,slow progresses have been made so far in MAS-based breeding forcomplex traits, mainly due to the following two aspects.
(1) Segregation populations derived from bi-parents can’t identifyfavorable alleles for the target traits. So we don’t have informationabout favorable alleles for the target trait which will be used inmolecular breeding.(2) QTL mapping is separate from practical breeding. Owing toQTL mapping results are seriously dependent on geneticbackground. So QTL information from mapping populations can’tbe directly applied in MAS-breeding.
Most agronomic important traits are quantitatively inherited. Awide range of segregating populations derived from bi-parentalcrosses, including RILs, DHs, F2 and its derived populations, andBC or testcross populations, have been used for QTL mapping. Andmany major important QTLs have been cloned in rice. Contrastly,slow progresses have been made so far in MAS-based breeding forcomplex traits, mainly due to the following two aspects.
(1) Segregation populations derived from bi-parents can’t identifyfavorable alleles for the target traits. So we don’t have informationabout favorable alleles for the target trait which will be used inmolecular breeding.(2) QTL mapping is separate from practical breeding. Owing toQTL mapping results are seriously dependent on geneticbackground. So QTL information from mapping populations can’tbe directly applied in MAS-breeding.
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So, integration of QTL mapping with MAS-basedbreeding in the same genetic background has beenstrongly recommended for complex quantitative traits byTanksley and Nelson (1996). So far, AB-QTL method hasbeen widely used in QTL identification from germplasm.However, there are still some defects:
(1) Relative high expenses resulting from phenotyping andgenotyping for a large mapping population.
(2) Favorable alleles can not be mined using populationsderived from bi-parents.
So, integration of QTL mapping with MAS-basedbreeding in the same genetic background has beenstrongly recommended for complex quantitative traits byTanksley and Nelson (1996). So far, AB-QTL method hasbeen widely used in QTL identification from germplasm.However, there are still some defects:
(1) Relative high expenses resulting from phenotyping andgenotyping for a large mapping population.
(2) Favorable alleles can not be mined using populationsderived from bi-parents.
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With the development of sequencing technologies and the sharp
decreased sequencing cost, genome wide association (GWS) has
been recently used for QTL mapping and allele mining from
germplasm resources and made good progresses. However, there
are still some problems with this method.
(1) Wide variations in plant height and heading date of a natural
population seriously affect growth and development for some
early and dwarf entries, thus resulting in inaccurate phenotyping
for those parts of entries.
(2) There is population structure effect on QTL association
mapping.
(3) GWS and MAS-based breeding is still separate.
With the development of sequencing technologies and the sharp
decreased sequencing cost, genome wide association (GWS) has
been recently used for QTL mapping and allele mining from
germplasm resources and made good progresses. However, there
are still some problems with this method.
(1) Wide variations in plant height and heading date of a natural
population seriously affect growth and development for some
early and dwarf entries, thus resulting in inaccurate phenotyping
for those parts of entries.
(2) There is population structure effect on QTL association
mapping.
(3) GWS and MAS-based breeding is still separate.
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Germplasm holds a large of genetic variation for improvingagricultural crops. However, in the past favorable genes fromgermplasm have not been efficiently used in plant breeding dueto linkage drag. Although backcross is effective to simplequalitative traits, it has not been successful to improvequantitative traits by backcross breeding procedure.
Here we demonstrate a new breeding strategy of backcrosscombined molecular marker technology to efficiently identifyQTL and improve multiple complex traits based on designedQTL pyramiding (DQP).
Germplasm holds a large of genetic variation for improvingagricultural crops. However, in the past favorable genes fromgermplasm have not been efficiently used in plant breeding dueto linkage drag. Although backcross is effective to simplequalitative traits, it has not been successful to improvequantitative traits by backcross breeding procedure.
Here we demonstrate a new breeding strategy of backcrosscombined molecular marker technology to efficiently identifyQTL and improve multiple complex traits based on designedQTL pyramiding (DQP).
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RP x donors (many) F1s x RP BC1F1s x RP
~25 BC2F1s/donor x RP
x
BC2F3-5 bulk populations
BC3F1s x RP
1, 2, 3, 4, 5, 6, ……
BC3F2-3 bulk populations
Self and bulkharvest
Selection for target traitsand backcrossing
BC4F1s
BC4F2s
x
x
Self and bulkharvest
1, 2, 3, 4, 5, 6, ……
Screening for target traits such as tolerances to drought, salinity,high temperature, anaerobic germ., P & Zn def., BPH, etc.
Strategy of integration of QTL mining with QTL-designed pyramidingusing backcross introgression lines in elite background
Confirmation of the selected traits by replicated phenotypingthen genotyping of trait-specific lines (ILs)
Crosses made between sister ILshaving unlinked desirable
QTLs for target ecosystem
DQP & MAS for pyramiding desirableQTLs and against undesirable donor
segments for target ecosystem
Develop multiple stress tolerant lines for different ecosystems and releaseNILs for individual genes/QTLs for functional genomic studies
Screening for target traits such as tolerances to drought, salinity,high temperature, anaerobic germ., P & Zn def., BPH, etc.
QTL identification and allele mining
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A case study-develop trait-specific introgression lines (ILs)
using Huang-Hua-Zhan (HHZ)as a recurrent parent
A case study-develop trait-specific introgression lines (ILs)
using Huang-Hua-Zhan (HHZ)as a recurrent parent
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Huang-Hua-Zhan(HHZ):
◆ High yield, high grain quality and wideadaptation
◆ Registered by more than 5 provinces inChina
◆ Extended area up to 3 million hectare inChina so far
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Name
Cote D
’ivoir
Mali
Rw
anda
Senegal
Nigeria
Mozam
bique
Tanzania
Uganda
Bangladesh
Indonesia
Lao P
DR
Pakistan
Sri Lanka
Vietnam
Philippines
HHZ 2 1 3 1 1 3 1 2 2 1 2 1 1 1 2
Zhongzu14 2 1 4 1 1 1
Zhong-Hua 1 2 2 3 4 2 1 1 1 1
KCD1 2 6 1 2 1 1 1
RC8 1 6 1 3 1 1 1
List of the promising widely adaptable inbreds identified fromadaptation yield trials in SSA, SEA and SA
RC8 1 6 1 3 1 1 1
Weed Tolerant 1 1 2 4 2 1
HUA-565 2 3 3 1
FFZ 1 3 6 2 4 1 1 1
SAGC-4 2 3 2 1 1 1
WX763 2 1 1 1
SAGC-2 1 3 1 1
SIMAO 1 3
08fan4 3 1
08fan2 1 3 1 1
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Two batches of 16 populations with the recurrent parent, Huang-Hua-Zhan (HHZ) and 16 donors from 9 different countries
Batch Pop. Donor Country of origin Gen.(10 DS)
1 HHZ5 OM1723 Vietnam (I) BC1F5
1 HHZ8 Phalguna India (I) BC1F5
1 HHZ9 IR50 IRRI (I) BC1F5
1 HHZ11 IR64 IRRI (I) BC1F5
1 HHZ12 Teqing China (I) BC1F5
1 HHZ15 PSB Rc66 Philippines (I) BC1F5
1 HHZ17 CDR22 India (I) BC1F51 HHZ17 CDR22 India (I) BC1F5
1 HHZ19 PSB Rc28 Philippines (I) BC1F5
2 HHZ1 Yue-Xiang-Zhan China (I) BC1F4
2 HHZ2 Khazar Iran (J) BC1F4
2 HHZ3 OM1706 Vietnam (I) BC1F4
2 HHZ6 IRAT352 CIAT (upland) BC1F4
2 HHZ10 Zhong 413 China (I) BC1F4
2 HHZ14 R644 China (I) BC1F4
2 HHZ16 IR58025B IRRI (I) BC1F4
2 HHZ18 Bg304 Sri Lanka (I) BC1F4
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The Introgression Breeding Procedure for Batch 1
Develop first batch of 8 HHZ BC1F2 populations
DT screen SUB screen
3 SUBT plants
311 progeny tested for all target traits
Randompopulations
109 DT plants
Yield traits
QTL/Allelicdiversity
discovery fortarget traits
82 HY plants
ST screen
120 ST plants
06WS
08WS
09DS
1st roundselection
2nd roundselection
108 PYT under DT, low input, NC
Dissection of geneticrelationships betweentarget trait and non-
target traits
QTL/Allelicdiversity
discovery fortarget traits
68 promising ILs
153 DT 171 SUB212 Yield 211 ST
09WS 512 trait-specific ILs
10DS
10WS/11DS 68 replicatedyield trials
Used as parents for designedQTL pyramiding
2 NCT in11WS
3 Demo
3rd roundselection
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Pop. SelectionSeedgeneration
Target traitNo of
selectedlines
Total noof lines ofeach trait
No. of linesof eachgeneration
HHZ5
1stselection(08WS)
BC1F3
Yield 11
47 47DT 21
ST 15
yield
yield-yield 21
36DT-yield 6
ST-yield 9HHZ5
2ndselection(09DS)
BC1F4 114
ST-yield 9
DT
yield-DT 6
51DT-DT 27
ST-DT 18
ST
yield-ST 6
27DT-ST 0
ST-ST 21
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Some introgression lines (HHZ background) and three checkSome introgression lines (HHZ background) and three checkvarieties were grown in 2010 wet season at IRRIvarieties were grown in 2010 wet season at IRRI
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Yield potential of promising 9 HHZ ILs in 2010 WS (S. Peng)
Grain yield and yield components of GSR lines compared withIR72, NSICRc158 and Mestizo7, IRRI, 2010WS.
DesignationGrain Yield
(t/ha) RankGrain
Filling % Panicle/m2Spikelets per
panicleTotal
spikelets/m2
IR72 5.96 abcde 6 72.9 def 357.8a 86.8 hi 31096.2 de
NSIRCRc158 5.86 bcde 7 80.0 abc 354.7 ab 98.0 fgh 34754.2 cde
Mestizo7 5.68 bcde 10 70.2 def 315.6 abcd 116.3 de 36748.7 cd
HHZ5-DT8-DT1-Y1 5.55 cde 12 75.7 abcd 285.4 d 127.8 bc 36462.6 cd
HHZ5-SAL10-DT1-DT1 6.14 abcd 4 73.9 cde 300.5 cd 121.5 bcd 36313.9 cd
HHZ5-SAL10-DT2-DT1 5.47 de 14 68.3 ef 281.8 d 124.2 bcd 34931.0 cde
HHZ5SAL10-DT3-Y2 5.69 bcde 9 76.0 abcd 276.6 d 131.9 ab 36474. 8 cd
HHZ8-SAL6-SAL3-Y2 6.55 ab 2 73.8 de 309.4 abcd 139.1 a 43039.4 ab
HHZ8-SAL9-DT2-Y1 5.78 bcde 8 81.5 a 308.3 bcd 100.9 fg 31089.6 de
HHZ8-SAL12-Y2-DT1 6.43 abc 3 72.2def 324.5 abcd 107.1 ef 34696.6 cde
HHZ12-DT10-SAL1-DT1 6.75 a 1 80.2 ab 323.4 abcd 117.5 cde 38118.6 bc
HHZ12-Y4-DT1-Y1 5.57 cde 11 75.6 abcd 347.4 abc 127.5 bcd 44300.9 a
Best line in WS: HHZ12-DT10-SAL1-DT1, high-yielding; resistant todrought, has aromatic properties, excellent phenotypic stand.
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HHZ8-SAL12-Y2-DT1
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DT HHZ5-Sal14-Sal2-Y2 APO (check)APO
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HHZ ILs HHZ ILsCK
Field evaluation of salinity tolerance in Infanta, Philippines
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QTL mapping for the target traitsusing trait-specific ILs
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Principle of using selected ILs and molecularmarkers to identify QTL
QTL detectionTaken allele frequency of the random population as an expected value,a significant deviation (excess or deficiency) of donor allele frequencyat single locus in the selected IL population from the expected levelimplies a positive selection favoring the donor allele (in excess), ornegative selection against the donor allele (in deficiency). Significantdeviation loci are considered as QTLs affecting the selected traits.
Gene action at putative QTLs● Excess of the donor homozygote additive gene action● Excess of the heterozygote overdominance gene action● Excess of both the donor homozygote and heterozygote partial
or complete dominance gene action
QTL detectionTaken allele frequency of the random population as an expected value,a significant deviation (excess or deficiency) of donor allele frequencyat single locus in the selected IL population from the expected levelimplies a positive selection favoring the donor allele (in excess), ornegative selection against the donor allele (in deficiency). Significantdeviation loci are considered as QTLs affecting the selected traits.
Gene action at putative QTLs● Excess of the donor homozygote additive gene action● Excess of the heterozygote overdominance gene action● Excess of both the donor homozygote and heterozygote partial
or complete dominance gene action
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0
0.2
0.4
0.6
0.8
1
FA FH FB
Comparison of allele segregation between DT-selected ILpopulation and the random population
Drought selected F2
0
0.2
0.4
0.6
0.8
1
Random F2
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ST-ILs selected from fourintrogression populations in
Minghui86 background at theoverall growth stage
Minghui86/Shennong265 (40)
Minghui86/Zaoxian14 (33)
Minghui86/Gayabyeo (37)
ST-ILs selected from fourintrogression populations in
Minghui86 background at theoverall growth stage
Minghui86/Zaoxian14 (33)
Minghui86/Y134 (40)
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0.330.310.64<.000123.42.44Bin3,13RM231–0.290.340.050.000117.931.06Bin2,62RM240
0.570.220.780.000068.517.80Bin2,32LT620.250.030.28<.0001102.60.560.250.81<.000168.410.07Bin2,22RM290.380.631.00<.000124.043.24Bin1,81LT44
0.460.080.540.0000104.834.64Bin1,61LT35
Diff.Randompop.
ST-ILs
PX2
Frequency ofintrogressionPX2
Minghui8686/Shennong265 (15)Minghui86/Gayabyeo (13)
Physicalposition
/MbBinChr.Marker
0.650.000.650.000216.90.490.200.690.000056.62.57Bin1,11LT3
QTLs for ST detected in Minghui86/Gayabyeo and Minghui86/Shennong265 ILs
Frequency ofintrogression
ST-ILs Randompop.
Diff.
0.390.130.51<.000151.69.93Bin12,212LT365
0.500.090.59<.0001100.817.31Bin11,311RM2090.300.160.46<.000128.40.75Bin11,111LT3260.330.140.46<.000138.817.68Bin10,310LT319
0.540.240.780.000058.73.53Bin10,110LT3050.290.250.540.000615.05.46Bin9,19RM4440.340.270.610.000119.218.40Bin8,38LT268 0.770.000.77<.000124.0
0.480.330.80<.000141.14.49Bin8,18LT253–0.340.420.080.000118.620.50Bin6,46LT207
0.530.310.84<.000154.10.200.150.350.000615.00.63Bin6,16LT1860.520.280.80<.000161.726.37Bin5,65RM260.350.290.64<.0001187.56.99Bin5,25RM1690.310.230.54<.000121.5–0.380.490.110.000021.231.49Bin4,64LT1500.450.500.95<.000132.421.14Bin4,54LT140
0.280.200.490.000021.216.70Bin3,33LT97–0.310.420.110.000119.69.81Bin3,23RM7
0.330.310.64<.000123.42.44Bin3,13RM231
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0.310.100.41<.000147.136.06Bin3,53
–0.310.340.030.000216.834.94Bin2,62
0.390.070.46<.0001146.610.07Bin2,22
0.290.230.530.000117.727.11Bin1,51
1.310.151.47<.000164.717.89Bin1,41
2.74Bin1,11
RM85
RM266
RM29
RM246
Mo18
Mo3
0.020.510.53<.000145.50
0.160.030.19<.000121.7
QTLs for ST detected in Minghui86/Zaoxian14 and Minghui86/Y134 ILs
Diff.Randompop.
ST-ILs
PX2
Frequency ofintrogressionPX2
Minghui8686/Y134 (10)Minghui86/Zaoxian14 (9)
Physicalposition
/MbBinChr.Marker
Frequency ofintrogression
ST-ILs Randompop.
Diff.
19.71Bin12,412
20.52Bin10,310
18.63Bin9,39
0.59Bin9,19
29.26Bin7,77
12.32Bin7,37
–0.801.080.280.000614.763.40Bin6,16
0.510.030.54<.0001110.2826.91Bin5,65
1.310.611.920.001712.7015.55Bin5,45
6.99Bin5,25
0.290.280.56<.000120.52.02Bin4,14
0.310.100.41<.000147.136.06Bin3,53
RM519
RM147
RM189
RM296
RM248
Mo233
Mo192
Mo185
Mo173
RM169
RM518
RM85
–0.460.670.21<.000136.42–0.020.360.34<.000127.06
0.150.030.18<.000128.90
0.220.110.330.000415.47
–0.360.510.15<.000120.19
0.150.030.18<.000121.67
0.200.030.22<.000133.3
0.180.040.21<.000124.18
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ST-QTLs detected in at least the two differentST-IL populations
Gayabyeo Shennong265 Zaoxian14 Y134
Bin2.2 √ √ √ √Bin1.1 √ √ √Bin6.1 √ √ √Bin2.6 √ √Bin4.6 √ √Bin4.6 √ √Bin5.2 √ √Bin5.4 √ √Bin5.6 √ √Bin8.3 √ √Bin9.1 √ √Bin10.3 √ √
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QTLs affecting high yield (HY), drought tolerance (DT) and salinity tolerance (ST)detected in two pyramiding populations by frequency distortion of genotypes
Pop. Locus Ch. Posi. HY DT ST
X2
P Geneaction
X2
P Geneaction
X2
P Geneaction
IL3/IL4(DTP2)
F2
RM486 1 153.5 18.75 0 OD 27.34 0 OD 25.87 0 OD
OSR14 2 6.9 7.76 0.0206 PD
RM471 4 53.8 13.46 0.0011 OD
RM584 6 26.2 7.74 0.0208 OD
RM3 6 74.3 7.67 0.0216 AD 13.66 0.001 OD
RM2 7 8.08 0.0175 OD
RM547 8 58.1 19.97 0 OD 27.89 0 OD 30.97 0 ODRM547 8 58.1 19.97 0 OD 27.89 0 OD 30.97 0 OD
RM21 11 85.7 10.78 0.0045 AD
RM4A 12 5.2 11.93 0.0025 OD
IL5/IL6(STP1)
F2
RM297 1 155.9 10.45 0.0053 AD 6.49 0.0389 AD 9.93 0.0069 AD
RM324 2 66 6.31 0.0426 PD
RM55 3 168.2 6.51 0.0385 PD
RM3 6 74.3 13.44 0.0012 AD 9.48 0.0087 AD 7.7 0.0212 AD
RM444 9 3.3 56.43 0 PD
RM434 9 57.7 30.82 0 AD
RM4A 12 5.2 6.29 0.043 OD
RM519 12 62.6 8.19 0.0166 OD
RM235 12 91.3 12.67 0.0017 PD
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RM582 RM57266.4RM31271.6RM2478.4
RM594.9RM488101.4
RM246115.2
RM302147.8RM212148.7RM486153.5RM297155.9
Chr1
RM764.0
RM25179.1
RM411127.9
RM55 RM186168.2
RM227182.1
Chr3RM33521.5
RM47153.8
Chr4
RM1220.0
RM31118.8
RM87129.2
Chr5
1
1 11
4
2 2 2
3 3 3
2 1 1
1
1 1 3
1 1 1
4
2RM6
OSR14 RM1106.9
RM52158.4RM324 RM42466.0RM29068.0RM26270.2RM34182.7
RM47592.5
RM6154.7
Chr21 1
4
3
21 3 4
1 2 3 4
QTLs for HY identified in pyramiding populations
QTLs for DT identified in pyramiding populations
RM213186.4
RM4692.2RM190 RM5887.4RM58710.7RM51020.8RM225 RM584RM225
26.2
RM27640.3
RM374.3
Chr6RM236.0RM43243.5
RM1890.4
RM248116.6
Chr7RM408RM5060.0RM4075.7
RM54758.1
RM22380.5
RM21090.3
RM80103.7
RM447124.6
Chr8RM2960.0RM4443.3
RM56647.7
RM43457.7RM25766.1RM10873.3RM55376.7
Chr9RM2860.0
RM2185.7
RM206102.9
Chr11RM4A5.2
RM51962.6RM31365.5
RM23591.3
RM12 RM17109.1
Chr12
2
1
2 2 3 3 3
4 4
2
1 2 2 2
1
3 4
3
14
1
2
2 3
34
3
1 2 3 4
1 2 3 4
QTLs for DT identified in pyramiding populations
QTLs for ST identified in pyramiding populations
Distributions of QTLsaffecting HY, DT and ST
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Bacterial blight (BB) resistance and geneticdissection using abiotic trait-specific ILs
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Evaluation of BBEvaluation of BBresistance of 512 HHZresistance of 512 HHZILs against 14 strainsILs against 14 strainsofof XooXoo races, 2010 WSraces, 2010 WSat IRRIat IRRI
HHZ PSBRc66 HHZ15-SAL13-Y2 HHZ15-DT7-SAL1
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Xoo races R% MR/MS% S%
P1 76.4 13.2 10.4
P2 4.7 9.7 85.7
P3b 4.9 48.8 46.4
P3c 4.9 27.5 67.6
P4 22.4 59.2 18.4
P5 78.4 12.6 9.0
P6 5.1 9.9 85.1
Summary of the reactions of the 512 HHZ ILs to the 14 Xoo races
P6 5.1 9.9 85.1
P7 46.6 42.8 10.6
P8 31.0 54.0 15.0
P9a 12.3 16.2 71.5
P10 12.1 15.7 72.2
P9c 4.7 6.6 88.7
P9b 5.1 25.0 69.8
P9d 50.8 33.6 15.6
Average 25.7±25.9 26.8±17.3 47.6±31.4
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PXO61
PXO86
PXO79
PXO34
0PX
O71
PXO11
2PX
O99
PXO145
PXO280
PXO33
9
PXO34
1
PXO34
7PXO349
PXO36
3average
HHZ 9.8 21.2 13.1 25.7 10.4 2.4 29.6 5.0 8.6 28.8 8.4 26.6 15.2 24.6 16.4
PSBRC66 6.4 18.5 16.4 21.4 11.6 0.7 13.0 2.6 8.8 4.1 7.0 12.0 3.4 17.3 10.2
HHZ15-SAL13-Y2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ15-SAL-13-Y3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ15-DT7-SAL1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
Ten HHZ ILs with broad resistance to all 14 races of bacterialblight pathogen, Xanthomonas oryzae
pv oryzae from N. VeraCruz
HHZ15-DT7-SAL1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ15-DT7-SAL3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ15-DT7-SAL6 0.2 0.2 0.2 0.2 9.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.9
PSBRC28 2.8 20.3 21.6 24.0 11.2 3.9 22.4 4.7 9.2 26.0 8.5 23.7 22.9 21.9 21.9
HHZ19-SAL-14-Y3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ19-DT8-SAL2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
HHZ19-SAL12-SAL4 0.2 0.7 0.9 0.5 0.2 0.2 0.2 0.2 0.4 0.2 0.3 0.9 0.2 0.2 0.4
HHZ19-SAL14-SAL4 0.2 1.0 0.6 0.3 0.2 0.2 0.2 0.2 0.3 0.2 0.7 0.2 0.2 0.2 0.3
HHZ19-SAL15-SAL2 0.2 3.8 2.2 0.6 0.4 0.4 0.8 0.5 0.3 0.3 0.3 0.6 0.4 0.4 0.8
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2 3 4 5 61
RM4952.8
RM42819.3RM15136.2RM24357.3RM113RM29478.4
RM49379.7RM992.4RM594.9RM488101.4RM246115.2RM473A120.2RM443122.7
RM212148.7RM6154.7
1
3
1
1
1
2
1
1
1
1
1
2
5
3
2
41
Xa29
RM1090.0RM1544.8RM1106.9RM21114.4RM27917.3RM42328.7RM17447.5RM7149.8RM43858.4RM42466.0RM2968.9RM47592.5
RM106123.2RM263127.5RM526136.3
RM6154.7
RM207RM406186.4RM48190.2RM207191.2
2
4
1
1
1
2
2
2
6
1
1
5
3
RM23115.7
RM54535.3
RM21867.8
RM282100.6
RM411127.9RM16131.5
RM426157.3RM186168.2RM448171.2RM520191.3RM416191.6RM130208.2RM148224.2RM85231.0
1
1
1
1
3
RM5378.5
RM11976.1
RM27394.4RM25299.0
RM127150.1
1
1 1
Xa2 Xa1
Xa12
Xa14
RM1220.0
RM1328.6
RM43743.4RM16957.9
RM16378.7RM44092.7
RM26RM31118.8RM274126.6RM87129.2RM163138.7
1
3
1
1
2
1
1
1
4
2
1
xa5
RM5080.0RM1972.2RM1907.4RM51020.8RM20425.1RM21726.2RM40240.3RM54942.7RM12143.8RM13651.2RM374.3
RM45499.3RM162108.3RM528121.6RM30125.4RM439139.9 1
6
1
1
1
1
1 410
1
Xa7
Xa27(t)
Xa33(t)
At least 51 loci conferring resistance to 14 races of BB resistance inAsia identified in 512 HHZ ILs
8 10
9
117
RM48190.2RM207191.2
RM148224.2RM85231.0
RM227286.0
1
1
RM295RM436
0.0
RM18030.1RM50133.3RM54234.7RM44539.3RM43243.5RM1147.0RM18261.0RM23488.2RM1890.4RM47893.8RM42996.9RM420RM473
115.3
1
1
1
2
3
5
1
2
3124.6
xa8
RM4075.7RM1529.4
RM12657.0RM32RM72
60.9
RM51580.5
RM256101.5RM80103.7RM477121.8RM447124.6RM264128.6
2
1
1
5
6
1
xa13
RM2960.0RM52413.2
RM10532.1
RM43457.7RM10873.3RM10782.4RM18990.7
RM245112.3
RM105’186.6
1
1
1
2 1
2
RM4740.0RM24415.0
RM18458.3RM25870.8RM258'78.8RM294A87.1
1
2
7
11
RM55240.6RM53655.1
RM22977.8
RM254110.0RM224120.1 6
1
RM123 7
Xa3, Xa26Xa21
Xa22Xa4
Xa36
Xa10
Xa23
Xa30(t)
Xa34(t)
12
RM4150.0RM203.2RM1920.9RM11732.3
RM51962.6
RM17109.1 1
1
3
1
1Xa32(t)
Xa25(t)
12 17 1915985 11 represent QRLs detected in HHZ5、HHZ8、HHZ9、HHZ11、HHZ12、HHZ15、HHZ17 and HHZ19;The digitsstand for the number of strains effective by the QTL;“” means chromosomal locations of BB-QTLs previously mapped.
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Resequencing 512 HHZ-ILs for GWS analysisSo far, re-sequencing have been finished for 512 HHZ-ILs and now is being analyzedfor genotyic data. Phenotyping has been finished in multiple environments (IRRI,Hainan, Hangzhou, etc.) . GWS will be used to identify QTL and mine favorablealleles for the target traits using the compound population.
HHZ5:HHZ/OM1723
HHZ8: HHZ/Phalguna
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IL mappingAB-QTLTranditional
mapping
Main-effect QTL 10(2)3.8 (303) 16.5
Epistatic QTL 3.5(2)5.5 (7) Large
Droughttolerance
17.4
Large
Submergencetolerance
Comparison of QTL mapping efficiency among tranditional
mapping, AB-QTL and IL mapping
Epistatic QTL 3.5(2)5.5 (7) Large
Population size 200±200± 31.6
Phenotyping LargeLarge Less
Large
26
Less
Multiple allele mining NoNo Yes Yes
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Pyramiding of high yield (HY), drought andsalinity tolerance (DT, ST) using the
selected ILs
Pyramiding of high yield (HY), drought andsalinity tolerance (DT, ST) using the
selected ILs
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Development of HY-, DT- andST-ILs for QTL mapping
SN89366 Bg94-1 GH122 YJ7 JXSM
Feng-Ai-Zhan 1 (FAZ1) Backcross & selfingwith HY selection
Pyramiding of QTLsfor HY, DT and ST
IL1 IL2× IL3 IL4× IL5 IL6× IL7 IL8×
For DT For ST
F1 F1 F1 F1
F2 populations
Pop. 1 Pop. 2 Pop. 3 Pop. 4 Pop. 5BC3F5
HY & DT ILs HY & ST ILs
DT screening ST screening
HY &DT ILs
FAZ1/SN89366 (IL1)
FAZ1/Bg94-1 (IL2)
FAZ1/GH122 (IL3)
FAZ1/YJ7 (IL4)
FAZ1/SN89366 (IL5)
FAZ1/Bg94-1 (IL6)
FAZ1/JXSM (IL7)
FAZ1/BG94-1 (IL8)
HY &ST ILs
60 randomplants
~30 HYplants
~30 DTplants
~30 STplants
Confirmed or cross-testing ofselected ILs for QTL mapping
New breeding lines with HY, DT and/or ST
Promising lines for RYT
QTL mapping QTL mapping
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Selected pop. Intercrossor
repeatedscreening
trait
No. ofselected
lines
Line # Yield of introgression line (g) Salt tolerance of introgression line at the seedling stage
Traitvalue
Checkof
highervalue
parent
±%comp.with
check
No. of survival days Score of salt toxicity of leaves
Traitvalue
Check ofhigherparent
±%compcheck
Traitvalue
Check ofhigherparent
±%compcheck
DT selected (30)
HY 1 QP49 43.5 30.1 44.8 10 8.8 13.6 4.5 5.5 18.2
ST 10
QP47 31.8 30.1 5.5 11 8.8 20.6 4.5 5.5 18.2
QP48 29.8 30.1 -0.9 11 8.8 22.9 4.5 5.5 18.2
QP63 24.3 30.1 -19.3 12 8.8 36.4 4.5 5.5 18.2
QP60 26.3 30.1 -12.6 12 8.8 31.8 4 5.5 27.3
QP61 28.8 30.1 -4.3 11 8.8 30.3 4 5.5 27.3
QP36 28 30.1 -7 11 8.8 29.5 4 5.5 27.3
Promising pyramiding lines selected from intercross or repeatedscreening for HY and ST from IL1x IL2 population
QP36 28 30.1 -7 11 8.8 29.5 4 5.5 27.3
QP37 28.2 30.1 -6.3 11 8.8 29.7 5 5.5 9.1
HY selected (30)
HY 2QP163 38.6 30.1 28.4 9.6 8.8 9.1 5 5.5 9.1
QP167 36.6 30.1 21.8 11.4 8.8 29.5 4 5.5 27.3
ST 7
QP171 35.8 30.1 18.9 10 8.8 17.1 4.5 5.5 18.2
QP169 32.1 30.1 6.7 12 8.8 33 4.5 5.5 18.2
QP168 25.4 30.1 -15.6 13 8.8 51.1 4 5.5 27.3
QP166 28.3 30.1 -6 11 8.8 29.1 4 5.5 27.3
QP164 23 30.1 -23.4 11 8.8 25.7 4 5.5 27.3
QP170 17.4 30.1 -42.2 11 8.8 25.1 4.5 5.5 18.2
QP165 24.5 30.1 -18.7 11 8.8 20.6 4 5.5 27.3
ST selected (33) HY 2QP327 36.6 30.1 21.6 NA NA NA NA NA NA
QP337 34.9 30.1 15.9 NA NA NA NA NA NA
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Based on phenotypic and QTL information of trait-specific ILs, a new line withHY, DT and ST was developed by pyramiding of different target QTLs
Zhong-Guang-Lv 1(HY, DT & ST)
RYT in Yunnan province in 2011
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Zhong-Guang-You 2
RYT in Guangxi province in 2010-11
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Molecular recurrent selection systems for improvingmultiple complex traits based on trait-specific
ILs and dominant male sterile (DMS) line
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Jiafuzhan (Rr, sterile)
Jiafuzhan (rr, fertile)
Development of a DMS line in HHZ background
Spontaneous mutation
X Jiafuzhan (rr, fertile)
Jiafuzhan (1Rr sterile : 1rr fertile)
X Jiafuzhan (rr, fertile)
X HHZ (rr)
F1 (1Rr sterile : 1rr fertile)
X HHZ (rr), backcross 4-5 times
HHZ (1Rr sterile : 1rr fertile)
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Composition of the molecular RS (MRS) populations:
30-50 ILs/PLs carrying favorable QTL alleles from differentdonors plus the DMS line in the same genetic backgrounds (HHZ)
Ovals or boxes ofdifferent colorsrepresent different ILscarrying genes/QTLsfor different targettraits
Development of RSpopulation is stillunder the way
MRS population in HHZ GB
Bulk harvestseeds fromfertile plantsto be screenedfor target traits
Ovals or boxes ofdifferent colorsrepresent different ILscarrying genes/QTLsfor different targettraits
Development of RSpopulation is stillunder the way
Bulk harvestseeds fromfertile plantsto be screenedfor target traits
Bulk harvestseeds fromsterile plantsfor next roundof RS
HHZ MSline
Each fertile individual has even chance to pollinate with DMS plants,ensuring all possible recombinations produced inside the RS population
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50% fertile plants
RS populations based on trait-specificILs and a DMS line in the same GB
Irrigated(YP)
Abioticstresses
Bioticstresses
Trait-improvedlines
NewILs/PLs
Continuedintrogression
breeding/DQP50% DMS plants
Combine DMS-line based RS system with whole genome selection
RILs
GSmodel
Trait screening
New MRSpopulation for
next round
New lines with multipletraits by pyramiding
Trait-improvedlines
RYT and NCTunder different
target Es
Farmers in dif.target Es
Continuationof MRS
GSmodel
GS
GS
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◆ Most donors contributed performance enhancing alleles formost traits regardless of their own performances;
◆ Appropriate screening is the key to identify promising BCprogenies with improved target traits;
◆ Extremely selected ILs are best materials for main-effect QTLdetection and also for pyramiding of non-allelic favorablealleles from various donors to improve multiple complextraits
◆ Abiotic stress tolerance and biotic resistance may share partialgenetic overlap, thus being beneficial to rice breeding formultiple resistance
DMS-based molecular recurrent selection systems are higheffective for improving multiple complex traits by pedigree orGS
Summary◆ Most donors contributed performance enhancing alleles for
most traits regardless of their own performances;
◆ Appropriate screening is the key to identify promising BCprogenies with improved target traits;
◆ Extremely selected ILs are best materials for main-effect QTLdetection and also for pyramiding of non-allelic favorablealleles from various donors to improve multiple complextraits
◆ Abiotic stress tolerance and biotic resistance may share partialgenetic overlap, thus being beneficial to rice breeding formultiple resistance
DMS-based molecular recurrent selection systems are higheffective for improving multiple complex traits by pedigree orGS
◆
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AcknowledgementResearch Team
Z.K. LiY.M. GaoB.Y. FuL.H. ZhuY. Li. ZhouX.Q. ZhaoT. Q. ZhengJauhar Ali (IRRI)
Funding:Chinese Ministry of AgricultureThe Generation Challenge ProgramChinese Ministry of Science &TechnologyThe BMGF GSR project
Z.K. LiY.M. GaoB.Y. FuL.H. ZhuY. Li. ZhouX.Q. ZhaoT. Q. ZhengJauhar Ali (IRRI)
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Thank You forYour Attention!