Institute of Crop Sciences, CAAS Development and application of Axiom Wheat660K, a high density SNP array Jizeng Jia Institute of Crop Sciences, CAAS  IWC 2015, Sydney

Background Wheat was a leading crop on research in the world before rice genome sequenced Wheat research lags behind rice after rice sequenced in 2001 Rice wheat wheat Rice 1985-2000 2001-2014 2001-2014

Background Two major reasons resulted in this situation Difficult to get gene: Shortage of genome sequence and fine mapping information Difficult to confirm the gene function: Very low ratio of transformation 凝胶时代： 限制性酶切片段长度多态性分析(RFLP) 寡核苷酸连接分析(OLA) 等位基因特异聚合酶链反应分析(ASPCR) 单链构象多态性分析(SSCP) 变性梯度凝胶电泳分析(DGGE) 高通量时代： 特异位点杂交(ASH) 特异位点引物延伸(ASPE) 特异位点切割(ASC) 特异位点连接(ASL) 单碱基延伸(SBCE)

JT has made the breakthrough for wheat transformation , and we introduced their techniques and the transformation efficiency reaches to 40% We report here the development of Wheat660, a high density SNP array, which will accelerate the breakthrough of gene discovery and genomic breeding in wheat

SNP-the third generation molecular marker First generation molecular marker: RFLP, its application lasted for about 5 years only Second generation molecular marker: SSR, lasted for more than 20 years SNP is the third generation marker, with advantage of huge number of loci, high throughput, it should be lasted much more longer

Outlines Axiom Wheat660K development Axiom Wheat660K application

Affy techniques can produce SNP array with a density SNP more than 600K/slides However, the high density can be generated in diploid species only Wheat is hexaploid, in order to develop the high density array, we developed a new strategy: select SNPs with diploid characters

Procedure of Weat660 development Wheat accessions Screening 4x660K by Affymetrix 2nd generation data Producing 4x660K mapping Test 4x660k array vs 192 wheat accessions Genome-specific SNP Wheat660 Screening 10x660K

Total data: 6+Tb De novo, resequence, transcriptome and GBS   Species accessions Genome Data type Data 1 T. urartu G1812 UR203 UR206 AA resequencing 170x 2 Ae. tauschii AL8/78(Y2282) Y2280 DD 92x 3 T. turgidum LDN PS4 AABB 5x 4 T. aestivum AK58 32 accessions 78 accessions AABBDD De novo, transcriptome and GBS sequencing 272x 500G 20x Total data: 6+Tb Common wheat varieties come from world wide

SNP analysis Total 51,380,485 SNPs discovered SNPs outside of genes:50,375,584 SNPs in genes: 1,004,901 #SNP  in exon: 589,236 #SNP  in inron: 415,665 From all 99,386 wheat genes SNPs in Tandem repeat：1,516,247 SNPs in TE： 37,945,716 23 million candidate SNPs to Affymetrix for further screening

Chromosome distribution of 51 millions SNPs 1A 3,037,061 1B 2,527,422 1D 1,295,018 2A 4,213,482 2B 4,125,640 2D 998,762 3A 2,532,902 3B 5,055,792 3D 743,180 4A 3,443,133 4B 1,953,790 4D 1,071,141 5A 3,029,073 5B 3,298,191 5D 1,296,462 6A 2,559,818 6B 2,856,559 6D 1,194,569 7A 2,724,036 7B 2,083,129 7D 1,341,325 subtotal 21,539,505 21,900,523 7,940,457 total 51,380,485 % 41.9% 42.6% 15.5%

Procedure of Weat660 development Wheat accessions 4x660K by Affymetrix 2nd generation data Producing 4x660K mapping Screening 4x660k array vs 192 wheat accessions Genome-specific SNP Wheat660K Screening 10x660K

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Wheat660 has good performance The highest density array in polyploid Genome-specific SNPs “Diploidization” A single array with 630,517 SNPs

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Distribution on genome evenly homoeologous group　 A genome B genome D genome wheat660 90Kchip 1 30,978 2,072 24,199 3,471 23,966 1,024 2 31,371 2,090 39,062 3,250 28,228 1,491 3 20,176 1,800 50,067 2,491 19,779 883 4 28,068 1,928 15,159 1,444 17,036 296 5 18,209 2,454 38,075 2,964 27,007 1,004 6 20,147 2,133 26,178 2,528 20,870 571 7 30,226 2,662 18,750 2,461 31,570 1,250 subtotal 179,175 15,139 211,490 18,609 168,456 6,519 % 32.0% 37.6% 37.8% 46.2 30.1% 16.2 我将4个群体能够做上的标记汇总后总共为359811个，没有显示度。但和上述数字整合有难度，主要是去除冗余有难度。 Genetic density : 13 SNP/cM, Physical density: 3 SNP/100K

Cover almost genes of wheat Containing 630,517 SNPs #SNPs out of genes: 503,173 #SNPs in genes: 106,587 in 99,386 genes One gene One SNP , every gene has a SNP in wheat, almost every gene has a functional marker SNPs  in exon: 63,604 SNPs  in inron: 43,059 Stop codon : 1247 Phase 1 14689 23.2% 2 12035 19.0% 3 36726 57.8% 密码子相位（Phase ）：指SNP发生在三联体密码子的第几位

Functional SNPs in Wheat660 Gene SNP of W660K LR1 AX-111285463 Lr10 AX-94423519 AX-94706430 AX-86165263 Lr21 AX-94595542 Lr34 AX-95209823 AX-95171358 AX-94406256 Pm3-B AX-108898068 AX-109293047 AX-94562727 Pm6 AX-95168737 AX-94938928 AX-94775968 Sr33 AX-94590720 AX-94489369 AX-111538251 Sr35 AX-94965691 AX-94753878 AX-109857391 TaPHS AX-94631945 AX-108790772 AX-95241932 Ppd-D1 AX-94852677 AX-94651272 AX-94407958 VRN1 AX-108997623 AX-108771865 AX-109824320 VRN2 AX-109821686 AX-109270864 AX-108736083 VRN3 AX-86186145 AX-86185431 Q AX-95250150 AX-94759421 AX-86185478 密码子相位（Phase ）：指SNP发生在三联体密码子的第几位

820 SNPs on pathway of Oxidative phosphorylation

702 SNPs on pathway of ribosome（translation）

339 SNPs in pathway annotation : carbon metabolism

Wheat660 has good performance High density Call rate: 97% Auto reading Genotypin PolyHighResolution: 19.3%, 14.5%, 21.8% and 24% respectively

Outlines Axiom Wheat660K development Axiom Wheat660K application Construction of high density of wheat genetic maps Construction of Wheat Hapmap Gene detection

Construction of fine genetic maps by use of Wheat660 Jing_DH Xia_DH Zhang_RIL Wang_RIL Population type DH RIL13 RIL10 #of individuals 141 181 182 170 #SNP 121,681 91,260 137,512 95,552 %HighPolymorphic SNP 19.3% 14.5% 21.8% 15.2% Genetic density(SNP/cM) 29 22 33 23 Physical density (SNP/100k) 0.7 0.5 0.8 0.6 各图图距汇总 合计 4966.672 6153.761 19401.43 7655.763 名称 Jing zhang Wang xia 1a 209.83 281.687 945.775 470.836 1b 238.069 235.208 965.778 292.541 1d 206.532 235.863 551.788 245.174 2a 278.031 417.71 1239.749 512.169 2b 152.392 336.296 1419.997 468.054 2d 286.33 284.146 673.098 405.531 3a 303.752 370.321 1006.593 467.525 3b 287.963 309.22 1360.321 475.867 3d 268.174 252.579 511.733 288.548 4a 254.716 352.845 1048.087 401.631 4b 140.932 180.623 723.838 187.887 4d 87.824 172.706 369.821 180.904 5a 286.43 326.462 1535.503 490.876 5b 228.649 314.213 1372.239 510.113 5d 241.249 365.454 601.081 368.289 6a 237.557 250.103 676.98 273.093 6b 140.035 204.575 1050.62 243.937 6d 280.483 261.739 498.955 319.627 7a 303.18 415.139 1220.929 463.775 7b 251.212 284.86 927.181 313.14 7d 283.332 302.012 701.368 276.246

Comparison genetic map between the Wheat660 maps and the international wheat genetic maps

SNP distribution on genetic maps of common wheat 550 common wheat varieties were genotyped with Wheat660 The SNP distribution evenly in general, however, super cluster were discovered in each chromosome 1 log 5 25 125 625

1 log 5 25 125 625

1 log 5 25 125 625

BIN #SNP #in Gene #Out Gene % In Gene Bin77 437 108 329 24.7% Bin90 541 111 430 20.5% Bin119 401 51 350 12.7% allBin 27107 3438 23669

Outlines Axiom Wheat660K development Axiom Wheat660K application Construction of high density of wheat genetic maps Fine mapping of interesting genes

Gene detection Natural population: 800 accessions GMAIL (genome wide multiple allele introgression lines) population

Fine mapping of the heading date genes Gene fine mapping by using pooling strategy Heading date gene Segregation population: Am3/L953*6F4

44 SNP 11 mapped on 2A, 6 on 58-59 cM region Pool1 916 Pool4 422 Pool3 478 Pool2 917 11 mapped on 2A, 6 on 58-59 cM region 33 mapped on 2D, 9 mapped on 64-65 cM region

Fine mapping of the plant height genes 12 SNP Pool1 916 Pool4 422 Pool3 478 Pool2 917 12 common SNP among 4 pools 8 mapped on 2D, 6 4 located on 64-66 cM region

Summary We developed a highest density and efficient wheat SNP array, Wheat660k Wheat660k cover almost wheat genes Highest density genetic maps were constructed Chromosomal inversions of some synthetic wheat were revealed There are very low efficient recombination regions in wheat Wheat 660K is an efficient tool for gene fine mapping

Works on the way Construction of wheat HapMap Fine mapping and cloning of genes conferring agronomic important traits Development of Wheat50k for wheat genomic breeding

Acknowledge Aimin Zhang Affymetrix Ruilian Jing CapitalBio Zhonghu He Jirui Wang Guangyao Zhao Xiuxing Kong Lifeng Gao Dangqun Cui Zhengang Ru Affymetrix CapitalBio 973 Project