copy do not david jordan sorghum qtl atlas€¦ · 16.06.2018 · spb-0810 m188404 txp43m343014...
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Sorghum QTL AtlasEmma Mace
David Jordan
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Why have we developed a QTL Atlas?How users can access the Atlas?
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The mechanisms governing the genetic control of many quantitative traits are only poorly understood and have yet to be fully exploited, despite a large volume of data having been generated.
How can we better improve the rate of progress in an applied breeding program focused on quantitative traits?
Why have we developed a QTL Atlas?
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OPY
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Why have we developed a QTL Atlas?
Over the last 2 decades, >150 QTL and GWAS studies have been published in sorghum, producing an enormous amount of information concerning the genetic basis of quantitative traits
• genomic location, • allelic effects, • epistatic interactions.
But making use of this information is not straight forward.
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Why have we developed a QTL Atlas?
There is no central repository of QTL studies that allows users to compare results of all current QTL and GWAS studies against a common framework
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NOT
COP
Y
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>150 studies > 6000 QTL in sorghum for over 220 traits identified
heterogeneous nature of QTL studies leading to variable reliability of QTL identified
from one study to the next
the time investment required to integrate the information and generate a comprehensive
QTL database
Why have we developed a QTL Atlas?
DO N
OT C
OPY
-
Heterogeneous nature of QTL studies…not all QTL are equal
The precision of initial QTL identification in QTL mapping studies is influenced by many factors including:
• population size and type, • precision of the phenotyping, • QTL analysis methodology • marker order, coverage and density.
DO N
OT C
OPY
-
The precision of initial QTL identification in QTL mapping studies is influenced by many factors including:
• population size and type, • precision of the phenotyping, • QTL analysis methodology • marker order, coverage and density.
Heterogeneous nature of QTL studies…not all QTL are equal
DO N
OT C
OPY
-
The precision of initial QTL identification in QTL mapping studies is influenced by many factors including:
• population size and type, • precision of the phenotyping, • QTL analysis methodology • marker order, coverage and density.
Heterogeneous nature of QTL studies…not all QTL are equal
DO N
OT C
OPY
-
The precision of initial QTL identification in QTL mapping studies is influenced by many factors including:
• population size and type, • precision of the phenotyping, • QTL analysis methodology • marker order, coverage and density.
Heterogeneous nature of QTL studies…not all QTL are equal
DO N
OT C
OPY
-
The precision of initial QTL identification in QTL mapping studies is influenced by many factors including:
• population size and type, • precision of the phenotyping, • QTL analysis methodology • marker order, coverage and density.
sPb-0145
sPb-2823
sPb-6061
sPb-0090 sPb-3386
sPb-0232
sPb-3798
sPb-8616
sPb-7695
sPb-4970
sPb-6434
sPb-1784
sPb-1017sPb-2075 sPb-2639sPb-4311sPb-6700
sPb-3361
sPb-3834
sPb-5737
sPb-8677
sPb-3853
sPb-9388
sPb-6857
sPb-3940
sPb-2562
sPb-8536
sPb-6882
sPb-4921
sPb-7186
sPb-4629
sPb-9894
sPb-8802
sPb-8138
sPb-4661
sPb-4734
sPb-9304
sPb-0906
sPb-5890
sPb-9312 sPb-7893
sPb-7030
sPb-9490
sPb-2551
sPb-3837
sPb-2457 sPb-8425
sPb-5030
sPb-9066
sPb-8436
sPb-1543
sPb-5230
sPb-0255
sPb-5403 sPb-7960
sPb-5765
sPb-7105
sPb-9931 sPb-8980
sPb-6825
sPb-1982
sPb-7381
sPb-8673
sPb-2630
sPb-9508
sPb-7944
sPb-7280
sPb-7086
sPb-5397 sPb-9365
sPb-6589
sPb-1503
sPb-9818
sPb-7126
sPb-5054
sPb-9372 sPb-0235sPb-0645
sPb-0380
sPb-1888
sPb-1272 sPb-5250
sPb-2846
sPb-9584
sPb-4385
sPb-2487
sPb-1323
sPb-3274sPb-1997 sPb-9449
sPb-8090sPb-8590
sPb-4011sPb-1895
sPb-0005
sPb-4156
sPb-8812 sPb-9227
sPb-8716
sPb-7460
sPb-2222
sPb-7473
sPb-9381
sPb-9999
sPb-9215 sPb-3958sPb-1722 sPb-4480sPb-8432 sPb-6875sPb-7643
sPb-9826
sPb-5834
sPb-6288
sPb-5841
sPb-6889 sPb-8201
sPb-7015
sPb-2465sPb-8208
sPb-2058
sPb-0232
sPb-0274
sPb-5358
txp58
sPb-9203 sPb-2683
sPb-4638
txp279
txp284
sPb-0277 sPb-4593sPb-0746
sPb-1984
sPb-7611
sPb-3577 sPb-1060
sPb-7984
sPb-8897
sPb-1631
txp4
txp3
sPb-3361
sPb-5737 sPb-3834
sPb-4054
sPb-1669 sPb-2055
sPb-6690
sPb-6857
sPb-1137sPb-1362 sPb-5108sPb-6122
sPb-8787
sPb-8349
txp285
sPb-6465
sPb-2521
sPb-4074
sPb-8446 sPb-2739sPb-7493 sPb-4718
sPb-1584
sPb-6741sPb-4506 sPb-2138sPb-8296 sPb-6559sPb-1811 sPb-1798sPb-9359 sPb-7310sPb-7274 sPb-5742sPb-1841 sPb-9987sPb-0867 sPb-7210sPb-9033 sPb-3903sPb-1295 sPb-8470sPb-2187
sPb-2842
sPb-5220
txp343
SB1-10
sPb-9303 sPb-6115
sPb-5119 sPb-9544sPb-5408
sPb-9009
txp303
sPb-5892
sPb-9642
sPb-8149
sPb-6323
sPb-7203
sPb-1454
sPb-6287
sPb-1396sPb-2874 sPb-0873
sPb-7892
sPb-5603 sPb-0017sPb-4732 sPb-1486
sPb-5101
sPb-8316 sPb-7064sPb-4740 sPb-9309sPb-2034
sPb-1414 sPb-2757sPb-1244 sPb-0571
sPb-2774
sPb-8673
sPb-6577
sPb-9007 sPb-8251sPb-4179
sPb-2491
sPb-6248
sPb-0703
sPb-7126
sPb-9818 sPb-7843
sPb-3396
sPb-9242
sPb-4432
sPb-0258
sPb-9700
sPb-1661sPb-7889
sPb-7312
sPb-1881
sPb-2228sPb-9743 sPb-4546sPb-0833sPb-3954
sPb-7823
sPb-6918 sPb-1825
sPb-5401 sPb-1291sPb-1051
sPb-1272 sPb-7082sPb-5250sPb-7648
sPb-2290sPb-5420sPb-4385
sPb-3434
sPb-7855
sPb-1991
sPb-8812 sPb-9227
sPb-3253
sPb-9538
sPb-7105
sPb-7905
sPb-1239 sPb-0771sPb-8338
sPb-6667
txp230
txp67
txp258
sPb-4156
sPb-6515
sPb-8306sPb-2735
sPb-2193sPb-3432 sPb-0248sPb-5005
sPb-8357
sPb-9592
sPb-0817
sPb-8150 sPb-6292
sPb-5917
sPb-7473
sPb-1962
sPb-5841
sPb-9064 sPb-8201
sPb-6889sPb-9215 sPb-1722sPb-3958 sPb-8432sPb-7643 sPb-4944sPb-6875sPb-4480
sPb-1040
M188427
umc84
sPb-8325
sPb-7161sPb-5521 sPb-0623sPb-2583 txp208SbRPG837
msbcir268
HVHGA1 HVGAD1umc107 msbcir347txp302 sPb-3891msbcir242msbcir228
M340904
M342631
sbAGFO8umc140
sPb-6917
sPb-6577
sPb-4329SbRPG873 um7
M189295
sPb-5315
M340898sPb-8041
sPb-6176
txp182 sPb-3618
umc83
sPb-4793
gpsb089
sPb-3727sPb-1191sPb-3525sPb-4234
M187880
M187200
sPb-2684sPb-2412 sPb-9216sPb-0810
M188404txp43 M343014txp88
sPb-0232M343356
sPb-5358
sPb-2602
sPb-6600
sPb-7567sPb-8492
M188582
M189251
msbcir304b
sPb-3311
msbcir286 gpsb173
sPb-3801
gap57sPb-8423sPb-7958sPb-6083gpsb051txp75M187238
M343241 M187616
gap36
msbcir336
bnl5.09
sPb-0233
M343279
SbRPG80
txp340 M342904M340364
msbcir306sPb-7611
sPb-4435
gpsb129 M340373
sPb-8743
sPb-7549 sPb-7657sPb-4855
M200042 M341662M341592 msbcir266
sPb-2754 gpsb011
gpsb174
M187772 sPb-0333
sPb-3103
txp25gpsb178 M342927M342711 sPb-8345M340957M341741
msbcir223 sPb-7668bsPb-7668txp211OPA7sPb-3086 sPb-1764sPb-9687M188881 M343289sPb-1127
M342329 M340416M342090SbRPG136sPb-3798
sPb-5347 sPb-8376
M342380
sPb-7177 sPb-8897sPb-5643
umc55
sPb-0364
sPb-5224sPb-4081msbcir238sPb-8616 sPb-4419gpsb087M187382M340431 M342471sPb-7695sPb-1920sPb-6434sPb-6288sPb-4970
M340888M343120 M343067
sPb-7882
M343086 M188424M342358M188643M188479 M342759M342673sPb-0350M340532
M342498
sbAGBO3
msbcir312
M341108 M188174
M187697 M188348
sPb-1970M187871 M187894
M188335
msbcir339 M189020
txp1
M342762
sPb-3917
sPb-2568
sPb-3361M340414 M342409M340589sPb-4862sPb-2229
sPb-6424sPb-1925
sPb-8706
SSmsbcir78
sPb-8568
sPb-0363
M342700 M189270sPb-5454M199861M340963
M340747 M342200
M188917 M342283
gpsb012sPb-2309 sPb-6714sPb-2461 sPb-5594M341408umc124 M342808sPb-1906 sPb-4915sPb-6982sPb-2055 sPb-1669sPb-0656 M188933M188681 M340763M188657M341540SBRPG846M342547sPb-0319M341223sPb-5409txp215sPb-9135
M187276
sPb-6857
M340732sPb-9388
SbRPG106
sPb-4226
gpsb086
sPb-2562
sPb-9076
sPb-7688sPb-5108 sPb-1362sPb-6122
sPb-1137
msbcir224 txp33
gap236sPb-9779 M187546
sPb-5922
csu58M340384 M341885M340852 M342663M340802 M188114txp31
msbcir276
sPb-2209
sPb-3965sPb-1496
sPb-9139 msbcir314
sPb-1725
sbAGEO1
sPb-1480
M341446 M341571
M188311
msbcir225
txp38
M188846 M342704sPb-6013
txp34
bnl5.37sPb-3228 sPb-6925M340973 M342779
M342567 M188347M188920 M342305
sPb-9894
sPb-6770
sPb-4074sPb-7493sPb-8446sPb-2739msbcir340sPb-4718
sPb-4233
sPb-7042
gpsb050
sPb-1853 msbcir323M187763
sPb-1932
M187985
M188323
M200413
RZ599
M188005 M188903
sPb-2944 sPb-6547
sPb-2842
M340930
M187716
M187502
sPb-8488
M343007sPb-7534txp12
M187661
sbAGGO2RZ166 M340886M341851 M340482
M340990 sPb-2084sPb-0854 sPb-9041
M200347
umc68sPb-4649M340664 M342464M342470 M187539gpsb073txp24
M340375 M341949csu26
M342928M342010M342065
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M342320 M342191M341902 M342643M187461M187118sPb-4692 M340433
gpsb028
txp21sPb-0110M341593M341500
msbcir329 M188451
gpsb159M341693 sPb-4041sPb-0906
txp65
sPb-0381
sPb-7047 sPb-5256
gpsb84 M188102M340916 sPb-5692bgpsb005M342865 sPb-4131sPb-3977sPb-5317 sPb-1282M188898 msbcir248sPb-5390sPb-8247 sPb-0510umc8 gpsb017gpsb165
sPb-5408 sPb-9080
sPb-3995
sPb-0932
sPb-1989
M187365
M340444 M340397sPb-6787 M340953sPb-5399 M189058sPb-6861txp15 M340502M340464 M341521sPb-6341M188512M341155sPb-7893 sPb-9312sPb-2187 M341517sPb-8470M188205 sPb-9054
M343065M188878sPb-4086 M342398csu166
sPb-6855
sPb-7106
gpsb003
txp23
M188834
gpsb176
SbRPG608
sPb-9490
sbKAFGK1
sPb-2570 sPb-9858
sPb-1181
sPb-2161 M342033M343312 M341274M342046 M340547sPb-3418sPb-5562 sPb-7892msbcir222
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gpsb032
sPb-1677 sPb-9772
sPb-1491
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sPb-9511
sPb-8963
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M187805
sPb-8362 sPb-5564sPb-6017 M342664
gap7 gap72
sPb-5506 sPb-7660M187589M342089 M340758SSmsbcir92 M341530
sPb-4947
sPb-4503 sPb-3019
M341635
sPb-5030
txp145 sPb-4324
txp265 txp274sPb-1755 sPb-7777
gpsb127 M188023
sPb-7290
M341712 M340945M341047M342581M342391M342764gpsb069M341192
sPb-5802 sPb-7581
umc44
sPb-0255
bnl10.13
sPb-1721M187824M189179M343162 sPb-3962txp95sPb-6526M342082
sPb-5086 M340415sPb-9830sPb-5212 sPb-8954sPb-9422sPb-0581 sPb-7627sPb-1657sPb-8410
sPb-9667
M187362
gpsb169SbRPG225M340483 M188251M341110gpsb019 M188096M341392 M342492M343304M342678
gpsb148msbcir348
umc85M341299
sPb-1311
sPb-4878sPb-2566
M342381 gpsb114
sPb-5277M341472
sPb-8296
SbRPG22
sPb-1244sPb-0508 sPb-3708sPb-7531sPb-0571sPb-6252 sPb-2757sPb-1414sPb-7992
gap342gpsb010
M343313sPb-6863 sPb-7687sPb-3541sPb-9206 sPb-8340
gpsb031
msbcir246
sPb-8251 sPb-4179sPb-9007
msbcir300 M340509
sPb-9351txp295
sPb-6927
sPb-3258sbAGBO2sPb-5688sPb-9750 M341979bnl5.59
sPb-6798
sPb-8608
sPb-9299
txp273
gpsb041
gpsb104
gpsb023
M188849
SbRPG931
sPb-1130sPb-5054M341589
sPb-7630
sPb-5825
sPb-3247
sPb-8260
M341597
M343025 M343001
sPb-9279
M341867
sPb-7856 msbcir240
sPb-4768a
M340629 M340408M341359sPb-2140 sPb-4200sPb-2474 sPb-8057sPb-3195SbRPG125
sPb-9242M342657gpsb067sPb-4934sPb-5980sPb-2271 sPb-4432sPb-8059 M187350sPb-0435
sPb-3014
sPb-9762 sPb-3236sPb-5886 sPb-0325sPb-0441 sPb-6807sPb-3312 sPb-1265
sPb-3189
txp354
sPb-0258
gpsb103
msbcir337a sPb-0856
sPb-7375
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txp105
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sPb-1291
sPb-4614
SbRPG950
sPb-0445
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M188061sPb-7460sPb-7686 gpsb020
M343231 sPb-2968sPb-1732 sPb-0852sPb-4006
M189112 M188652M342540
M342839sPb-6089 gpsb079M340730 M340810sPb-1991
umc38
sPb-4933
M341480SbRPG743 M188412sPb-0975 sPb-4416M340974
sPb-8542
sPb-8777M340536
sPb-3298sPb-6748M188560
sPb-9306
sPb-8764
sPb-1324 sPb-8873sPb-4786 sPb-6852sPb-6280 sPb-6043sPb-5055 M188501M342028 M341817sPb-5312 sPb-3158sPb-9272SbRPG821
M342543M341251M342741 M341021M342494M187902msbcir337b msbcir317M188207
sPb-7193
sPb-0005
gap42
M340587M342280 M341115umc64sPb-6515
sPb-0303sPb-7367 sPb-7955sPb-8368 sPb-9091M340964 sPb-9410sPb-4787 sPb-9962sPb-6506
M188934 M341036gap85sPb-8366
SbRPG917sPb-5281 sPb-8306M340704
sPb-1945
W AXY6msbcir331 msbcir324M189136
M342557
M187940 sPb-6720
gpsb027
SbRPG921
sPb-9517asPb-8357
umc113
sPb-3828 M341294
sPb-1104
sPb-5917
sPb-2149
sPb-0494
sPb-1962M340774 M342244M340871 M188983sPb-9999
sPb-6331
M341606M341123
M187142
txp217 sPb-4121bnl7.24msbcir283 sPb-6271
M340333
sPb-3696
sPb-9682
sPb-8019
sPb-2935 sPb-8232
SbRPG742
M342842
M342954 M340856M340712 M340495gap1
sPb-0859
msbcir262 msbcir227sPb-0162
M343252 M342053M342566
RZ143
sPb-4588 sPb-5814gpsb145
Heterogeneous nature of QTL studies…not all QTL are equal
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SBI-01 SBI-02 SBI-03 SBI-04 SBI-05 SBI-06 SBI-07 SBI-08 SBI-09 SBI-10
Some QTL have a large confidence interval (CI), others have a small CI.
Some are highly significant, others less significant.
Some are detected from a single source (bi-parental mapping population), whereas others are detected in multiple sources (from a diversity panel)***
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**
*****
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*
*
*
QTL
col
our-c
odin
g
QTL
col
our-c
odin
g
Heterogeneous nature of QTL studies…not all QTL are equal
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SBI-01 SBI-02 SBI-03 SBI-04 SBI-05 SBI-06 SBI-07 SBI-08 SBI-09 SBI-10
***
***
******
**
**
**
*****
***
**
*
*
*
The resulting complexity of the QTL landscape means that delimiting the QTL confidence
intervals identified across multiple highly diverse studies is a major challenge
Heterogeneous nature of QTL studies…not all QTL are equal
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SBI-01 SBI-02 SBI-03 SBI-04 SBI-05 SBI-06 SBI-07 SBI-08 SBI-09 SBI-10
***
***
******
**
**
**
*****
***
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*
*
*
Any attempt to project QTL locations from multiple experiments onto a single genetic or physical map
must take into account factors on which the reliability of the initial QTL study depends.
Heterogeneous nature of QTL studies…not all QTL are equal
DO N
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OPY
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>150 studies > 6000 QTL in sorghum for over 220 traits identified
heterogeneous nature of QTL studies leading to variable reliability of QTL identified
from one study to the next
the time investment required to integrate the information and generate a comprehensive
QTL database
Why have we developed a QTL Atlas?
DO N
OT C
OPY
-
>150 studies > 6000 QTL in sorghum for over 220 traits identified
heterogeneous nature of QTL studies leading to variable reliability of QTL identified
from one study to the next
the time investment required to integrate the information and generate a comprehensive
QTL database
Why have we developed a QTL Atlas?
DO N
OT C
OPY
-
>150 studies > 6000 QTL in sorghum for over 220 traits identified
heterogeneous nature of QTL studies leading to variable reliability of QTL identified
from one study to the next
the time investment required to integrate the information and generate a comprehensive
QTL database
This consisted of: • 44 QTL studies• 771 QTL• 161 unique traitsAll 771 QTL were aligned to• Version 1 of the sorghum genome assembly• The sorghum consensus genetic linkage map
Why have we developed a QTL Atlas?
We have estimated the CIs for projected QTL following:CI = 530/(NR2) for F2 (described by Darvasi & Soller 1997)CI = 163/(NR2) for RI (described by Guo et al. 2006) where N is the number of lines in the mapping population and R2 is the proportion of phenotypic variation explained by the identified QTL. DO
NOT
COP
Y
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>150 studies > 6000 QTL in sorghum for over 220 traits identified
heterogeneous nature of QTL studies leading to variable reliability of QTL identified
from one study to the next
the time investment required to integrate the information and generate a comprehensive
QTL database
The updated Sorghum QTL Atlas currently consists of: • >150 QTL and GWAS studies• ~6000 QTL and significant marker-trait
associations• >220 unique traitsAll 6000 QTL are aligned to• All 3 versions of the sorghum genome assembly• The sorghum consensus genetic linkage map• Zea mays genome (agpv2)• Oryza sativa genome (release 7)
Why have we developed a QTL Atlas?
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• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• In what populations have QTL for my trait(s) of interest been identified?
• How often has a particular QTL been identified in other studies/populations?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
QTL atlas we have developed will enable researchers to answer the following sorts of questions:
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OPY
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• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• In what populations have QTL for my trait(s) of interest been identified?
• How often has a particular QTL been identified in other studies/populations?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
QTL atlas we have developed will enable researchers to answer the following sorts of questions:
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OPY
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csu5870.0MT3670.7txp3171.1txp33673.2txp18375.2msbcir27676.3sPb-878777.4
txp44480.2
txs58485.4txp50387.5txS143987.6umc6387.8R87.9txp12088.4txp43589.2sPb-220991.6
sPb-224695.7
cdo116098.9txp231101.1sPb-3965102.8txp59103.2sPb-1496104.0
txS307106.7txS545108.9bcd828110.2isu121111.5msbcir314112.0txp114113.7txp437115.8sPb-1725116.5ST458117.1
sPb-6121121.6M341446125.3txs1927126.0txp440127.1sPb-8349128.2bcd738129.0M342704130.6txp442131.9S1329132.5sPb-4921133.7isu166134.5txs1226135.4msbcir225136.0txp285136.6txp421137.4txp38138.1txp448138.7sPb-9977140.8txp420141.4txS301144.0sPb-4629144.9txp34147.8txp424148.9bnl5.37149.1sPb-6925149.9isu68150.6AltSB152.0sPb-9894153.7txS1075154.6ms3155.3sPb-6770158.0A159.8txp69160.2txp425162.1Str58162.6CUa1163.2txp426164.2sPb-1642168.3sPb-8802172.3
Pericarp colour (R)
Awns (A)
Scenario 1: No selection
Scenario 2: Selection for red grain (R_)
Scenario 3: Selection for lemon yellow grain (rr)
Scenario 4: Selection for red grain (R_) and no awns (A_)
Scenario 5: Selection for lemon yellow grain (rr) and awns (aa)
0.0
0.2
0.4
0.6
0.8
1.0
Frequency of the senescent parent allele
stg2stg1
stg2stg1
Awnless
A_
Awned
aa
98.4% of progeny with stg2 favourable alleles
90.6% of progeny with stg1 favourable alleles
-
csu5870.0MT3670.7txp3171.1txp33673.2txp18375.2msbcir27676.3sPb-878777.4
txp44480.2
txs58485.4txp50387.5txS143987.6umc6387.8R87.9txp12088.4txp43589.2sPb-220991.6
sPb-224695.7
cdo116098.9txp231101.1sPb-3965102.8txp59103.2sPb-1496104.0
txS307106.7txS545108.9bcd828110.2isu121111.5msbcir314112.0txp114113.7txp437115.8sPb-1725116.5ST458117.1
sPb-6121121.6M341446125.3txs1927126.0txp440127.1sPb-8349128.2bcd738129.0M342704130.6txp442131.9S1329132.5sPb-4921133.7isu166134.5txs1226135.4msbcir225136.0txp285136.6txp421137.4txp38138.1txp448138.7sPb-9977140.8txp420141.4txS301144.0sPb-4629144.9txp34147.8txp424148.9bnl5.37149.1sPb-6925149.9isu68150.6AltSB152.0sPb-9894153.7txS1075154.6ms3155.3sPb-6770158.0A159.8txp69160.2txp425162.1Str58162.6CUa1163.2txp426164.2sPb-1642168.3sPb-8802172.3
Pericarp colour (R)
Awns (A)
stg2stg1
stg2stg1
Using QTL information to inform breeding strategy
Highlights the importance of knowing what other QTL are nearby the trait of interest that could be impacted by any selection applied
DO N
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OPY
-
050
100150
200
1 2 3 4 5 6 7 8 9 10
020
4060
80100
120140
QTL distribution heat-map
Highlights the importance of knowing what other QTL are nearby the trait of interest that could be impacted by any selection applied
DO N
OT C
OPY
-
050
100150
200
1 2 3 4 5 6 7 8 9 10
020
4060
80100
120140
QTL distribution heat-map
DO N
OT C
OPY
-
SM SC BR AB P M L10 8 2 5 7 2 110 8 2 5 6 2 111 8 2 8 7 2 112 8 2 10 7 2 113 7 6 11 6 2 112 7 8 12 6 2 113 9 7 13 7 4 114 10 7 11 5 4 116 10 3 11 6 4 116 10 2 7 7 4 118 9 2 7 10 4 123 9 1 7 10 4 123 10 1 7 9 4 124 10 0 6 8 4 133 10 0 6 10 4 140 10 2 6 10 4 145 10 9 8 16 4 147 10 20 8 18 4 140 11 20 8 18 4 133 12 21 8 18 4 127 12 18 6 12 4 027 11 7 5 10 4 026 11 7 3 10 4 024 10 4 3 10 4 020 10 0 9 10 4 016 8 1 9 9 4 016 8 5 9 10 5 016 10 5 9 11 4 016 10 5 3 11 4 016 9 5 3 12 4 016 8 1 3 9 4 016 9 1 3 10 4 018 11 1 3 10 4 017 11 1 3 9 4 017 14 1 3 8 5 017 14 1 4 7 5 014 17 1 4 6 5 014 21 1 3 7 5 012 21 1 5 8 7 012 23 1 4 7 8 012 23 1 4 7 12 0
Abbreviation Trait category Number of QTL/significancesL Leaf 441M Maturity 401P Panicle 1660AB Resistance abiotic 1753BR Resistance biotic 388SC Stem composition 421SM Stem morphology 750
DO N
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OPY
-
SM SC BR AB P M L10 8 2 5 7 2 110 8 2 5 6 2 111 8 2 8 7 2 112 8 2 10 7 2 113 7 6 11 6 2 112 7 8 12 6 2 113 9 7 13 7 4 114 10 7 11 5 4 116 10 3 11 6 4 116 10 2 7 7 4 118 9 2 7 10 4 123 9 1 7 10 4 123 10 1 7 9 4 124 10 0 6 8 4 133 10 0 6 10 4 140 10 2 6 10 4 145 10 9 8 16 4 147 10 20 8 18 4 140 11 20 8 18 4 133 12 21 8 18 4 127 12 18 6 12 4 027 11 7 5 10 4 026 11 7 3 10 4 024 10 4 3 10 4 020 10 0 9 10 4 016 8 1 9 9 4 016 8 5 9 10 5 016 10 5 9 11 4 016 10 5 3 11 4 016 9 5 3 12 4 016 8 1 3 9 4 016 9 1 3 10 4 018 11 1 3 10 4 017 11 1 3 9 4 017 14 1 3 8 5 017 14 1 4 7 5 014 17 1 4 6 5 014 21 1 3 7 5 012 21 1 5 8 7 012 23 1 4 7 8 012 23 1 4 7 12 0
Abbreviation Trait category Number of QTL/significancesL Leaf 441M Maturity 401P Panicle 1660AB Resistance abiotic 1753BR Resistance biotic 388SC Stem composition 421SM Stem morphology 750
1122724392365
DO N
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OPY
-
SM SC BR AB P M L10 8 2 5 7 2 110 8 2 5 6 2 111 8 2 8 7 2 112 8 2 10 7 2 113 7 6 11 6 2 112 7 8 12 6 2 113 9 7 13 7 4 114 10 7 11 5 4 116 10 3 11 6 4 116 10 2 7 7 4 118 9 2 7 10 4 123 9 1 7 10 4 123 10 1 7 9 4 124 10 0 6 8 4 133 10 0 6 10 4 140 10 2 6 10 4 145 10 9 8 16 4 147 10 20 8 18 4 140 11 20 8 18 4 133 12 21 8 18 4 127 12 18 6 12 4 027 11 7 5 10 4 026 11 7 3 10 4 024 10 4 3 10 4 020 10 0 9 10 4 016 8 1 9 9 4 016 8 5 9 10 5 016 10 5 9 11 4 016 10 5 3 11 4 016 9 5 3 12 4 016 8 1 3 9 4 016 9 1 3 10 4 018 11 1 3 10 4 017 11 1 3 9 4 017 14 1 3 8 5 017 14 1 4 7 5 014 17 1 4 6 5 014 21 1 3 7 5 012 21 1 5 8 7 012 23 1 4 7 8 012 23 1 4 7 12 0
Abbreviation Trait category Number of QTL/significancesL Leaf 441M Maturity 401P Panicle 1660AB Resistance abiotic 1753BR Resistance biotic 388SC Stem composition 421SM Stem morphology 750
QC
ldEmer9.11
QBrix9.1
QD
BMsA9.1
QPanBrLg9.3
New
13
QC
ldChl9.25
QC
ldChl9.26
New
80
New
679
New
705
New
1690
New
1689
QSTKR
9.1
QSTKR
9.2
QSTKR
9.3
QSTKR
9.4
QH
gt9.9
QH
gt9.10
QSTKR
9.5
QSTKR
9.6
QC
ldEmer9.12
QC
ldEmer9.13
QC
ldDM
GR
9.17
QC
ldChl9.27
New
1556
QSalt_W
gt9.1
QSalt_W
gt9.2
QSD
W9.4
New
495
QH
gt9.13 QSTKR9.7
QG
rnWgt9.5
QH
gt9.14
QPanLgth9.4
QH
gt9.15
QH
gt9.16
QH
gt9.17
QH
gt9.18
QH
gt9.19
QH
gt9.20
New
1645
New
1653 QStJYld9.1
QH
gt9.21
QH
gt9.22
QH
gt9.23
QBrix9.2
New
1596
New
799
QH
gt9.24
QH
gt9.25
QH
gt9.26
QH
gt9.27
QH
gt9.28
QH
gt9.29
QH
gt9.30
QH
gt9.31
QH
gt9.32
QH
gt9.33
QSTKR
9.8
QSTKR
9.9
QH
gt9.70
QH
gt9.34
QH
gt9.35
QH
gt9.36
QH
gt9.37
QH
gt9.38
QH
gt9.39
QH
gt9.40
QH
gt9.41
QG
rnPrA9.5
QG
rnPrA9.6
QPanW
gt9.4
QH
gt9.42
QH
gt9.43
QH
gt9.44
QPanLgth9.5
QSTKR
9.10
QSTKR
9.11
QSTKR
9.12
QSTKR
9.13
New
971
New
1104
QG
rnPrA9.7
QH
gt9.71
QG
rnPrA9.8
QG
rnPrA9.9
QSTKR
9.14
QSTKR
9.15
QSTKR
9.16
QG
rnPrA9.10
QSTKR
9.17
QSTKR
9.18
QSTKR
9.19
QSTKR
9.20
QSTKR
9.21
QSTKR
9.22
QSTKR
9.23
QSTKR
9.24
QSTKR
9.25
QSTKR
9.26
QSTKR
9.27
QG
rnPrA9.11
QG
rnPrA9.12
QH
gt9.45
QPanW
gt9.2
QG
rnWgt9.4
QH
gt9.46
QH
gt9.47
QYld9.3
QYld9.4
QPanW
th9.2
QH
gt9.48
QD
BMsB9.1
QBrix9.3
QH
gt9.49
QSTKR
9.28
QSTKR
9.29
QSTKR
9.30
QSugYld9.3
QStJYld9.2
QH
gt9.64
QH
gt9.65
QH
gt9.66
QH
gt9.67
QG
LA9.3
QSTKR
9.31
QSTKR
9.32
QSTKR
9.33
QSTKR
9.34
QH
gt9.50 QHgt9.51
QG
LA9.4
QH
gt9.52
QSD
W9.6
New
972
New
1105
New
1169
New
973
New
1106
New
1170
QTN
9.7
New
1496
New
1497
New
1498
QTN
9.8
QD
TFl9.34
QD
TFl9.35
QSTKR
9.35
QSTKR
9.36
QSTKR
9.37
QSTKR
9.38
QH
gt9.72
QPanExr9.2
QSD
W9.7
New
1583
QH
gt9.73
QPanExr9.3
QSFW
9.3
QStJYld9.3
QH
gt9.53
QG
rnPrA9.13
QD
TFl9.18
QH
gt9.54
QH
gt9.55
QH
gt9.56
QH
gt9.57
QH
gt9.58 New552
QSFW
9.4
QM
dgAN9.1
QH
rvYld9.1
QH
gt9.59 New
416 QVYld9.1
QVYld9.2
QH
rvYld9.2
QD
BMsA9.2
QD
BMsA9.3
QG
rnPrA9.14
Height (Dw1) Stalk rot resistance Tillering Maturity
23 QTL studies16 GWAS studiesDO
NOT
COP
Y
-
• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• In what populations have QTL for my trait(s) of interest been identified?
• How often has a particular QTL been identified in other studies/populations?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
QTL atlas we have developed will enable researchers to answer the following sorts of questions:
DO N
OT C
OPY
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Study Number of QTL Population Analysis Burrell et al 2015 2 BTx623/SC748-5 QTLFelderhoff et al 2016 2 Bk7/Early-Hegari-Sart QTLKlein et al 2001 1 RTx430/Sureno QTLMohan et al 2010 4 296B/IS18551 QTLPerumal et al 2009 1 SC748-5/BTx623 QTLUpadhyaya et al 2013 8 mini-core set GWAS
Anthracnose resistance
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
One of oldest and largest gene families known in plants. Involved in detection and response to diverse pathogens (bacteria, viruses, fungi, nematodes,
insects and oomycetes)
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
• Co-locating QTL for anthracnose resistance from same source (SC748-5) across 2 studies
• Co-locating with known NBS-LRR genes• Very near major effect gene for striga
resistance (lgs)• Highly significant (LOD>20 and R2 72%
in Burrell et al 2015)
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
R2=10.3%LOD = 3.8
R2=8.6%LOD = 3.2
R2=6.9%LOD = 3.1
R2=39.5%LOD = 12.5 R2=55.1%
LOD = 20.3
R2=35%-log10P = 20.3
R2=54%-log10P = 9.3
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
Genetic architecture of the trait• Number of QTL/significant SNPs• Distribution• Significance/effect size• Sources of resistance
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10Additional information critical for molecular breeding strategy development• Proximity to known disease resistance genes• Proximity to major effect genes• Proximity to large effect QTL for other traits
DO N
OT C
OPY
-
Tb1Sh1
Ma3Y
QAnth1.1
QAnth1.2
QAnth1.3
QAnth1.4
SBI-01
Rf2
B2
Z
Ma5
SBI-02
Pla
R
AltSBms3
A
SBI-03
bmr6
QAnth4.1
SBI-04
opr
lgs
QAnth5.2
QAnth5.3
QAnth5.1
SBI-05
Ma6
Ma1
dw2
gc
d
Rs1
Lg
P
QAnth6.1
QAnth6.2
QAnth6.3
QAnth6.4
QAnth6.5
QAnth6.6
SBI-06
bmr12
I
dw3
QAnth7.1
SBI-07
Pu
Rf1
Shs1
QAnth8.1
SBI-08
Dw1
QAnth9.1
SBI-09
bmrlf
wxma4Rs2
Trit
QAnth10.1
SBI-10
lgs
New
796
New
92
New
98 QD
TFl5.14
QD
TFl5.15
QC
ldLAR5.8
QC
ldLAR5.9
QC
ldLAR5.10
QC
ldChl5.31
QC
ldChl5.32
New
885
New
886 QTN5.7
MaturityGrain yieldLeaf appearance rate Chlorophyll contentTranspiration rateTillering
QTL co-locating with the anthracnose QTL on SBI-05
Additional information critical for molecular breeding strategy development• Proximity to known disease resistance genes• Proximity to major effect genes• Proximity to large effect QTL for other traits
DO N
OT C
OPY
-
• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• In what populations have QTL for my trait(s) of interest been identified?
• How often has a particular QTL been identified in other studies/populations?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
QTL atlas we have developed will enable researchers to answer the following sorts of questions:
DO N
OT C
OPY
-
QTL database resource developed to enable researchers to answer the following sorts of questions:
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
DO N
OT C
OPY
-
QTL database resource developed to enable researchers to answer the following sorts of questions:
Target QTL location in sorghum
Syntenic location in maize and rice
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
DO N
OT C
OPY
-
• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• How many QTL have been identified for my trait(s) of interest in a specific genotype?
• In what populations have QTL for my trait(s) of interest been identified?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many highly significant QTL have been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
• How often has a particular QTL been identified in other studies/populations?
QTL database resource developed to enable researchers to answer the following sorts of questions:
Syntenic location in maize and rice
Identify all predicted gene models in QTL CI in maize and rice
Linking to whole genome assembly resources for both species
DO N
OT C
OPY
-
• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• How many QTL have been identified for my trait(s) of interest in a specific genotype?
• In what populations have QTL for my trait(s) of interest been identified?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many highly significant QTL have been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
• How often has a particular QTL been identified in other studies/populations?
QTL database resource developed to enable researchers to answer the following sorts of questions:
Os03g20020Os03g19990Os03g19970Os03g19940Os03g19920Os03g19900Os03g19890Os03g19820Os03g19780Os03g19760Os03g19720Os03g19700Os03g19690Os03g19670PhyBOs03g19580Os03g19540Os03g19520Os03g19410Os03g19380Os03g19370Os03g19310Os03g19300Os03g19290
Sobic.001G391600Sobic.001G392000Sobic.001G392100Sobic.001G392200Sobic.001G392300Sobic.001G392400Sobic.001G392600Sobic.001G392700Sobic.001G392800Sobic.001G393000Sobic.001G393200Sobic.001G393300Sobic.001G393401Sobic.001G393500Sobic.001G393600Sobic.001G393700Sobic.001G393900Sobic.001G394000PhyB Sobic.001G394600Sobic.001G394800Sobic.001G394900Sobic.001G395000Sobic.001G395100Sobic.001G395200Sobic.001G395500Sobic.001G395600Sobic.001G395700Sobic.001G395900Sobic.001G396000Sobic.001G396100Sobic.001G396300Sobic.001G396400Sobic.001G396500Sobic.001G396600Sobic.001G396700Sobic.001G396800Sobic.001G396900
GRMZM2G084940GRMZM2G385931GRMZM2G030794GRMZM2G317160GRMZM2G018941GRMZM2G550861
GRMZM2G008490
GRMZM2G089720GRMZM2G135968
PhyB
GRMZM2G013639GRMZM2G422295 GRMZM2G422295GRMZM2G011483
GRMZM2G140432GRMZM2G301823GRMZM2G038015
GRMZM2G383790 GRMZM2G383790GRMZM2G084389
48,8
76,6
94 –
51,3
18,9
93
10,8
48,4
74 –
11,2
83,3
40
Identify all predicted gene models in QTL CI in maize and rice
Maize chromosome 1Rice chromosome 3
Genes within the predicted location of the QTL in riceand maize
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• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• How many QTL have been identified for my trait(s) of interest in a specific genotype?
• In what populations have QTL for my trait(s) of interest been identified?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many highly significant QTL have been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
• How often has a particular QTL been identified in other studies/populations?
QTL database resource developed to enable researchers to answer the following sorts of questions:
Os03g20020Os03g19990Os03g19970Os03g19940Os03g19920Os03g19900Os03g19890Os03g19820Os03g19780Os03g19760Os03g19720Os03g19700Os03g19690Os03g19670PhyBOs03g19580Os03g19540Os03g19520Os03g19410Os03g19380Os03g19370Os03g19310Os03g19300Os03g19290
Sobic.001G391600Sobic.001G392000Sobic.001G392100Sobic.001G392200Sobic.001G392300Sobic.001G392400Sobic.001G392600Sobic.001G392700Sobic.001G392800Sobic.001G393000Sobic.001G393200Sobic.001G393300Sobic.001G393401Sobic.001G393500Sobic.001G393600Sobic.001G393700Sobic.001G393900Sobic.001G394000PhyB Sobic.001G394600Sobic.001G394800Sobic.001G394900Sobic.001G395000Sobic.001G395100Sobic.001G395200Sobic.001G395500Sobic.001G395600Sobic.001G395700Sobic.001G395900Sobic.001G396000Sobic.001G396100Sobic.001G396300Sobic.001G396400Sobic.001G396500Sobic.001G396600Sobic.001G396700Sobic.001G396800Sobic.001G396900
GRMZM2G084940GRMZM2G385931GRMZM2G030794GRMZM2G317160GRMZM2G018941GRMZM2G550861
GRMZM2G008490
GRMZM2G089720GRMZM2G135968
PhyB
GRMZM2G013639GRMZM2G422295 GRMZM2G422295GRMZM2G011483
GRMZM2G140432GRMZM2G301823GRMZM2G038015
GRMZM2G383790 GRMZM2G383790GRMZM2G084389
Identify all predicted gene models in QTL CI in maize and rice
The atlas provides links to external resources to further interrogate the genes in rice and maize
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• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• How many QTL have been identified for my trait(s) of interest in a specific genotype?
• In what populations have QTL for my trait(s) of interest been identified?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many highly significant QTL have been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
• How often has a particular QTL been identified in other studies/populations?
QTL database resource developed to enable researchers to answer the following sorts of questions:
Identify all predicted gene models in maize and riceIdentify which genes within the QTL CI are under selection in sorghum, maize and rice
Previously published studies identifying genes under selection
SorghumRice Maize
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The utility of comparative genomics
Take advantage of known gene order conservation (synteny)
QTL
>4x as many QTL and GWAS studies in rice and maize compared to sorghum
• Make use of information gained in other species• Compare locations of QTL for specific traits
across species• Compare genes underlying QTL across species
• Functional characterisation in other species • Selection signals on the same gene in other
species
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• What other QTL are nearby my trait of interest that could be effected by any selection I apply?
• In what populations have QTL for my trait(s) of interest been identified?
• How often has a particular QTL been identified in other studies/populations?
• What is the largest effect size QTL that has been identified for my trait(s) of interest?
• How many GWAS studies versus standard QTL mapping studies have been undertaken for my trait of interest?
• Which genes are within the QTL CI for my target trait in sorghum and also in the syntenic locations in maize and rice?
QTL atlas we have developed will enable researchers to answer the following sorts of questions:
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Why have we developed a QTL Atlas?How users can access the Atlas?
https://aussorgm.org.au/sorghum-qtl-atlas/
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology DO
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Leaf Age-related leaf sensecence Leaf composition Leaf morphology Leaf yield Photosynthesis Stomata Sugar-related traits
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Panicle Germination Glume morphology Grain & Panicle Yield Grain Composition Panicle Architecture Pollen Fertility
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Resistance abiotic Cold tolerance Drought tolerance Heat tolerance Phosphorus tolerance Salt tolerance
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Resistance biotic Anthracnose resistance Aphid resistance Bacterial leaf stripe Drechstera leaf blight resistance Ergot resistance Grain mold resistance Green bug resistance Head bug resistance Leaf scorch Midge resistance Milo disease resistance Rice weevil resistance Rust resistance Shoot fly resistance Southern root-knot nematode resistance Stalk rot resistance Striga resistance Target leaf spot resistance Zonate leaf spot resistance
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Stem composition Stem biomass yield Stem composition Sugar-related traits
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223 unique traits have been classified into 7 broad trait categories, modified from Mace and Jordan (2011): • Leaf• Maturity• Panicle• Resistance abiotic• Resistance biotic• Stem composition• Stem morphology
Stem morphology Height Lodging tolerance Plant colour Regrowth Rhizomatousness Roots Stem morphology Tillering
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Version 1.4Version 2.0Version 3.0
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cM locations of the sorghum consensus map
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Felderhoff
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e.g. txp302, Dsenhsbm64, S1_10629136DO N
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Users can search for QTL in sorghum based on the syntenic location in either maize or rice
Users can specify the location in:
• the maize genome assembly (B73 RefGen_v1; Schnable et al 2009) or
• the rice genome assembly, O. sativa subsp. japonica (Release 7; Goff et al 2002; Yu et al 2002), or
• provide a candidate gene ID from either species (e.g. GRMZM2G108663; LOC_Os01g01080.1).
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LOC_Os09g26840
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Users can further modify their original search to limit to specific populations, publications, genome locations and export the output in a variety of formats
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https://aussorgm.org.au/sorghum-qtl-atlas/
In summary:This is the first database resource that has integrated all existing QTL and GWAS studies for sorghum used parameters from the original studies to take into account factors influencing the reliability of the initial
QTL study aligned to all current genome assemblies, predicted the syntenic locations in maize and rice, and provided
links to the underlying genes across species, as well as details of any signatures of selection previously identified.
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https://aussorgm.org.au/sorghum-qtl-atlas/
In summary:The database provides researchers with a new tool to integrate data across multiple studies and types of studies (QTL, GWAS) and across species to compare positions across studies and to determine allelic relationships among QTL. This will allow for: more comprehensive dissection of the genetic architecture of complex traits, identification of suitable targets for molecular breeding strategies
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AcknowledgementsConcept David JordanProgramming and database development support David Innes Michael Hassall Jared BaxterHelp with QTL projection Xuemin Wang Yongfu TaoStatistics support Colleen Hunt Adrian Hathorn
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https://aussorgm.org.au/sorghum-qtl-atlas/
@EmmaOmics
@SorgGuy
@AusSORGM
emma.mace@uq.edu.au
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Sorghum QTL AtlasSlide Number 2Why have we developed a QTL Atlas?Why have we developed a QTL Atlas?Why have we developed a QTL Atlas?Why have we developed a QTL Atlas?Heterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalHeterogeneous nature of QTL studies…not all QTL are equalWhy have we developed a QTL Atlas?Why have we developed a QTL Atlas?Why have we developed a QTL Atlas?Why have we developed a QTL Atlas?Slide Number 19Slide Number 20Slide Number 21Slide Number 22Slide Number 23Slide Number 24Slide Number 25Slide Number 26Slide Number 27Slide Number 28Slide Number 29Slide Number 30Slide Number 31Slide Number 32Slide Number 33Slide Number 34Slide Number 35Slide Number 36Slide Number 37Slide Number 38Slide Number 39Slide Number 40Slide Number 41Slide Number 42Slide Number 43The utility of comparative genomicsSlide Number 45Slide Number 46Slide Number 47Slide Number 48Slide Number 49Slide Number 50Slide Number 51Slide Number 52Slide Number 53Slide Number 54Slide Number 55Slide Number 56Slide Number 57Slide Number 58Slide Number 59Slide Number 60Slide Number 61Slide Number 62Slide Number 63Slide Number 64Slide Number 65Slide Number 66Slide Number 67Slide Number 68Slide Number 69Slide Number 70Slide Number 71Slide Number 72Slide Number 73Slide Number 74Slide Number 75Slide Number 76Slide Number 77Slide Number 78Slide Number 79Slide Number 80Slide Number 81AcknowledgementsSlide Number 83
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