2012. frank ordon. genomics based breeding research for improving resistance to biotic and abiotic stress in cereals

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<ul><li><p>www.jki.bund.de </p><p>Genomics based breeding research for </p><p>improving resistance to biotic and abiotic </p><p>stress in cereals </p><p> Dragan Perovic, Albrecht Serfling, Katja Perner, Sandra Frber, Cristina Silvar, Ilona Krmer, Antje Habeku, Doris Kopahnke, Heike Lehnert, Thomas Vatter, </p><p>Gwendolin Wehner, Esther Mitterbauer, Andreas Graner, Nils Stein </p><p>and Frank Ordon </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Acreage of cereals 2012 </p><p>Wheat and barley growing area (ha) </p><p>and average yield (t/ha) in 2012 </p><p> ha (Mio) t/ha </p><p>Wheat </p><p>World 215.49 3.11 </p><p>India 29.86 3.18 </p><p>Germany 3.06 7.33 </p><p> Barley </p><p>World 49.52 2.68 India 0.77 2.10 </p><p>Germany 1.68 6.19 </p><p> http://faostat.fao.org </p><p>home.arcor.de http://www.nurbier.de/category/biergeschichte/ http://www.abzonline.de/praxis/kasten-weizenbrot,707243491.html </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Challenges for plant production </p><p>Food security </p><p>Growing population </p><p>Bioenergy </p><p>Change in dietary habits </p><p>Climate change </p><p>Anstieg der weltweiten Mitteltemperatur fr die </p><p>Zeitspanne 071 - 2100 relativ zu der Zeitspanne 1961 - </p><p>1990. MPI Met </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Climatechange </p><p>http://www.umweltdaten.de/publikationen/fpdf-l/GGTSPU-styx2.bba.de-6248-7152625-DAT/3133.pdf </p><p>www.digiklix.de </p><p>Beschreibende Sortenliste 2010 </p><p>+1C = 10% yield reduction in wheat </p><p>-27% predicted for 2050 compared to 2000 in some regions Wheat Initiative </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>http://www.transgen.de/pflanzenforschung/pflanzengesundheit/ </p><p>Insects </p><p>Diseases </p><p>Weeds </p><p>Tota</p><p>l harv</p><p>est </p><p> Ric</p><p>e </p><p> Sorg</p><p>hum</p><p> Maiz</p><p>e </p><p> Oats</p><p> Wheat </p><p> Barley </p><p> Rye </p><p> Pota</p><p>to </p><p> Sugarc</p><p>ane</p><p>Average yield losses </p><p>Breeding for resistance to biotic and abiotic stress in cereals is of prime </p><p>importance to: </p><p>avoid yield losses </p><p>to ensure a consumer and environmental friendly production </p><p>Wheat (2012) </p><p>~140 million t </p><p>~$ 35 billion </p><p>FAOSTAT 2014 </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Mildew Leaf rust </p><p> No. Cultivars Yield </p><p>Year resistant susceptible resistant susceptible </p><p>1986 6 37 4.3* 5.6 </p><p>1995 24 41 6.5 6.3 </p><p>2005 52** 23 6.7 6.1 </p><p>2011 55 9 6.9 6.4 </p><p>Success of breeding for resistance in barley </p><p>BaMMV/BaYMV Ahlemeyer pers. comm. </p><p>1=minimum, 9=maximum </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Asfaw Adugna , 2004. Alternate Approaches in Deploying Genes for Disease Resistance in Crop </p><p>Plants. Asian Journal of Plant Sciences, 3: 618-623. </p><p>The never ending story </p><p>P. hordei P. striiformis B. graminis </p><p>P. teres R. commune U. nuda </p><p>BaMMV/BaYMV BYDV </p><p>Barley Wheat </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Marker type RFLPs Genomic SSRs AFLPs EST </p><p>SNPs/SSRs DArTs BOPAs/OPAs iSelect Genotyping by </p><p>sequencing </p><p>Throughput single marker </p><p>application single marker </p><p>application few marker application </p><p>single marker application 6K 1,5K 9K 50K </p><p>Multiplexing no mutiplexing few markers multiplexing </p><p>low multiplexing </p><p>few markers multiplexing </p><p>platform/ simultaneous </p><p>analysis </p><p>platform/ simultaneous </p><p>analysis </p><p>platform/ simultaneous </p><p>analysis </p><p>platform/ simultaneous </p><p>analysis </p><p>simultaneous multiplexing NGS/GBS </p><p>Amount of D N A Large amount low amount low amount low amount low amount low amount low amount low amount low amount </p><p>Quality of D N A very good average average average very good very good very good very good very good </p><p>Plant breeders toolbox </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Marker based harnessing of genetic resources: B. graminis </p><p>7HS: 12.1 cM 5.3 cM 1.5cM </p><p>7HL: 41.9 cM 2.8 cM 1.3cM </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Nested association mapping </p><p>NAM population HEB-25 </p><p> 25 wild accessions (H. spontaneum) </p><p> 1 elite recipient (Barke) </p><p> 1420 BC1S3 lines </p><p> TASSEL 4 (Q + K) </p><p> Significant differences (p </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Marker based harnessing of genetic resources: P. triticina </p><p>0</p><p>0,25</p><p>0,5</p><p>0,75</p><p>1</p><p>1996 1998 2000 2002 2004 2005 2006 2007 2008</p><p>Sorten ohne Resistenzgen Sorten mit LR37Thatcher NIL-</p><p>Lr37 </p><p>Thatcher without </p><p>resistance </p><p>Isolates Lr10 Lr11 Lr17 Lr18 Lr20 Lr28 Lr37 Lr49 T. monococcum T. boeticum </p><p>77WxR s s s s s s s s r s </p><p>167/176WxR s s s s s s s s r ps </p><p>Tommi 1 s s s s s s s s r s </p><p>13/20WxR s s s s s s s s r s </p><p>4136 ps s s s s r s s r s </p><p>s </p><p>ps </p><p>r </p><p>Analyzed isolates </p><p>virulent against all </p><p>known Lr-genes </p><p>located on the A </p><p>genome </p><p>The prehaustorial resistance of T. monococcum </p><p>0</p><p>20</p><p>40</p><p>60</p><p>80</p><p>12 24 48 72 96</p><p>HM</p><p>C/ </p><p>Infe</p><p>ction </p><p>Time after inoculation (h) </p><p>Borenos wxr77</p><p>Pi272560 wxr77</p><p>Susceptible </p><p>accession </p><p>Resistant </p><p>accession </p><p>Su</p><p>sce</p><p>ptible</p><p> acce</p><p>ssio</p><p>n </p><p>Resis</p><p>tan</p><p>t </p><p> acce</p><p>ssio</p><p>n </p><p>24 hai 96 hai 168 hai </p><p>24 hai 96 hai 168 hai </p><p>HMC </p><p>Lr37: 2004 2013 </p><p>Serfling et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Molecular characterization of the prehaustorial resistance by Massive </p><p>Analysis of cDNA (MACE) </p><p> Number of RNA samples: 12 </p><p>Time after inoculation </p><p>0 to 8 hai 8 to 16 hai 16-24 hai </p><p>Resistant accession rust inoculated 1 1 1 </p><p>Resistant accession mock inoculated 1 1 1 </p><p>Susceptible accession rust inoculated 1 1 1 </p><p>Susceptible accession mock inoculated 1 1 1 </p><p> Number of differentially expressed tags after comparison of the inoculated resistant and susceptible accession 0-24 hai </p><p> Quantitativelly differentially expressed 6810 6780 4832 1648 </p><p> Qualitativelly differentially expressed 4413 3592 3592 340 </p><p>In silico map on the basis of SNP detection of annotated </p><p>tags </p><p> 1A 2A 3A 4A 5A 6A 7A </p><p>Comprises 1136 genes in which </p><p>4358 SNPs were detected </p><p>Serfling et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Detailed analysis of peroxidases and chitinases </p><p>-6</p><p>-4</p><p>-2</p><p>0</p><p>2</p><p>4</p><p>6</p><p> 0</p><p>-8 h</p><p>ai</p><p>8-1</p><p>6 h</p><p>ai</p><p>16</p><p>-24 h</p><p>ai</p><p> 0</p><p>-8 h</p><p>ai</p><p>8-1</p><p>6 h</p><p>ai</p><p>16</p><p>-24 h</p><p>ai</p><p> 0</p><p>-8 h</p><p>ai</p><p>8-1</p><p>6 h</p><p>ai</p><p>16</p><p>-24 h</p><p>ai</p><p> 0</p><p>-8 h</p><p>ai</p><p>8-1</p><p>6 h</p><p>ai</p><p>16</p><p>-24 h</p><p>ai</p><p> 0</p><p>-8 h</p><p>ai</p><p>8-1</p><p>6 h</p><p>ai</p><p>16</p><p>-24 h</p><p>ai</p><p>Pox6 Pox1 Prx113 Pox 54 Pox prec.</p><p>Lo</p><p>g2 o</p><p>f exp</p><p>ressio</p><p>n I</p><p>no</p><p>cu</p><p>late</p><p>d/ </p><p> n</p><p>on</p><p> in</p><p>ocu</p><p>late</p><p>d </p><p>Resistant accession Susceptible accession</p><p>By Go terms identified Peroxidases </p><p>-2</p><p>-1.5</p><p>-1</p><p>-0.5</p><p>0</p><p>0.5</p><p>1</p><p>1.5</p><p>2</p><p>2.5</p><p> 0-8hai</p><p>8-16hai</p><p>16-24hai</p><p> 0-8hai</p><p>8-16hai</p><p>16-24hai</p><p>Chitinase1 Chitinase 2 </p><p>By Go terms identified Chitinases </p><p>Serfling et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Re</p><p>sis</p><p>tan</p><p>t </p><p>acce</p><p>sssio</p><p>n </p><p>Su</p><p>sce</p><p>ptible</p><p>acce</p><p>sssio</p><p>n </p><p>Resistant </p><p>accession </p><p>Susceptible </p><p>accession </p><p>0 6 12 24 48 72 96 168 hai </p><p>* </p><p>* * </p><p>* </p><p>M</p><p>ol H</p><p>2O</p><p>2 </p><p>Diaminobenzidine stain </p><p>Peroxidase activity </p><p>Re</p><p>sis</p><p>tan</p><p>t </p><p>acce</p><p>sssio</p><p>n </p><p>Su</p><p>sce</p><p>ptible</p><p>acce</p><p>sssio</p><p>n </p><p>0 </p><p>15 </p><p>30 </p><p>45 </p><p>60 </p><p>Pe</p><p>rox</p><p>ida</p><p>se</p><p> ac</p><p>tivit</p><p>y </p><p>(Un</p><p>its</p><p> min</p><p>-1) </p><p>0 6 12 24 48 72 96 168 hai </p><p>* Ch</p><p>itin</p><p>as</p><p>e a</p><p>cti</p><p>vit</p><p>y </p><p>(Un</p><p>its</p><p> min</p><p>-1) </p><p>0 </p><p>6 </p><p>12 </p><p>18 </p><p>30 </p><p>24 </p><p>* </p><p>* </p><p>* </p><p>* * </p><p>Chitinase activity </p><p>Characterization of prehaustorial resistance </p><p>Calcofluor stain </p><p>? ? </p><p>0</p><p>0.05</p><p>0.1</p><p>0.15</p><p>0.2</p><p>0.25</p><p>0 50 100 150 200 250 300</p><p>Calibration curveMol H2O2 l</p><p>-1</p><p>Absorption</p><p>0 min ai</p><p>15 min ai</p><p>30 min ai</p><p>Serfling et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Chr cM Number of markers </p><p>1A 217.7 588 </p><p>2A 260.1 771 </p><p>3A 171.2 503 </p><p>4A 111.5 339 </p><p>5A 236.7 570 </p><p>6A 232.6 620 </p><p>7A 258.4 727 </p><p>Total 1488.3 4118 </p><p>LOD </p><p>3.15 </p><p>24.4% </p><p>LOD </p><p>3.32 </p><p>16.5% </p><p>LOD </p><p>3.84 </p><p>13.0% </p><p>LOD </p><p>3.62 </p><p>13.3% </p><p>Phenotyping: </p><p>Number of haustorial mother </p><p>cells 72 hai (F2/F3) </p><p>Identification of QTL for pre-haustorial resistance </p><p>Serfling et al. unpublished </p><p>Localization of </p><p>candidate </p><p>genes in QTLs </p><p>is ongoing </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Gene isolation: BaYMV/BaYMV-2 resistance </p><p>distance marker 5H </p><p>HOR4224 (r) x HOR10714 (s) Based on 3369 F2 - plants, </p><p>Resolution 0.015% rec. </p><p>Exome capture </p><p>Perner et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Gene isolation: BaMMV resistance </p><p>GBS </p><p>Frber et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>rym4/rym5 </p><p>Isolation of resistance genes - allele mining </p><p>Hofinger et al. 2011. Molecular Ecology 20, 3653-3668 </p><p>A. Graner </p><p>1000 accessions selected </p><p> 27 resistant haplotypes </p><p>40 novel exon haplotypes </p><p>known haplotypes </p><p>13 susceptible </p><p>non allelic genes </p><p>identification of </p><p>8 novel eIF4E alleles </p><p>resequencing </p><p>resistance tests </p><p>test crosses, </p><p>resistance tests </p><p>year1 </p><p>year2/3 </p><p>year3 </p><p>eIF4E allele mining </p><p>Hv-eIF4E </p><p>HvPDIL5-1 </p><p>rym11 </p><p>Yang et al. 2014. www.pnas.org/cgi/doi/10.1073/pnas.1320362111 </p><p>Yang et al. 2014. Theor. Appl. Genet </p><p>Kanyuka et al. </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Allele Editing: Directed mutagenesis using endonucleases </p><p>Puchta and Fauser (2014) The Plant Journal </p><p>ZFNs Zinc-Finger Nucleases </p><p>TALENs Transcription Activator-Like Effector Nucleases </p><p>CRISPR Clustered Regularly Interspaced Short Palindromic Repeats </p><p>Cas CRISPR-associated, RNA-guided endonuclase </p><p>Meganucleases </p><p>A. Graner </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Wheat powdery mildew resistance </p><p>A. Graner </p><p>Allele Editing: Directed mutagenesis using endonucleases </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Drought stress in the juvenile stage </p><p>EQTL </p><p>156 BARLEY GENOTYPES </p><p>PHENOTYPING Biomass yield </p><p>Chlorophyll content Chlorophyll fluorescence </p><p>Osmotic adjustment Content of free proline </p><p>Total content of soluble sugars </p><p>DROUGHT STRESS Stress application starts 7das BBCH11 BBCH33 4 weeks stress period Stress 20% water capacity of soil 3 replicates per genotype 3 years trials </p><p> CONTROL STRESS </p><p>CONTROL STRESS </p><p>GWAS </p><p>QTL </p><p>GENE EXPRESSION </p><p>PROTEIN DETECTION </p><p>Illumina 9k iSelect SNP Chip Consensus Map of markers </p><p>SNP Scoring LD and Population structure </p><p>Significant SNPs Chomosome 5H + 2H </p><p>NCBI BlastX Protein function UniProt </p><p>Genetic map </p><p>GENOTYPING </p><p>DR</p><p>OU</p><p>GH</p><p>T S</p><p>TR</p><p>ES</p><p>S </p><p>LE</p><p>AF S</p><p>EN</p><p>ES</p><p>CE</p><p>NC</p><p>E </p><p>qPCR Fluidigm Chip array Drought stress genes Genes for leaf senescence Genes out of GWAS </p><p>Tassel 3.0 Detection of QTL </p><p>Localisation of QTL </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Correlations (Pearson) and Heritability: </p><p> Treatment BY SPAD ETR OA CFP CSS </p><p>h Control 0.80 0.64 0.08 0.00 0.13 0.13 </p><p>Stress 0.58 0.61 0.50 0.27 0.29 0.30 </p><p>BY Control 0.395 *** 0.091 -0.127 -0.328 *** -0.220 ** </p><p> Stress 0.361 *** -0.087 -0.124 0.307 *** 0.367 *** </p><p>SPAD Control 0.160 * -0.185 * -0.239 ** -0.192 * </p><p> Stress -0.105 0.034 0.425 *** 0.418 *** </p><p>ANOVA: significant effects (p </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Trait Number of genomic regions associated with the traits on the seven linkage groups (barley chromosomes) </p><p>*highest R 1H 2H 3H 4H 5H 6H 7H Total QTL </p><p>BY 81.7 cM (3 SNP) 2 cM (3 SNP) 76.2 cM (1 SNP) 99.1 cM (1 SNP) 46.7 cM (8 SNP) 48.3 cM (1 SNP) 19 (32 SNPs) 0.20% </p><p> 92.2 cM (1 SNP) 5.5 cM (1 SNP) 135.5 cM (1 SNP)* 59.7 cM (1 SNP) 70.2 cM (1 SNP) </p><p> 12.1 cM (1 SNP) 80.3 cM (1 SNP) 133.9 cM (1 SNP) </p><p> 90.2 cM (3 SNP) 110.1 cM (1 SNP) </p><p> 139.1 cM (1 SNP) </p><p> 152.4 cM (1 SNP) </p><p> 167.7 cM (1 SNP) </p><p>SPAD 49.2 cM (1 SNP)* 44.2 cM (4 SNP) 128.3 cM (1 SNP) 3 (6 SNPs) 3.80% </p><p>ETR 59.4 cM (1 SNP) 2.1 cM (1 SNP)* 2 (2 SNPs) 5.50% </p><p>OA 116.8 cM (1 SNP) 51.8 cM (1 SNP) 2.4 cM (1 SNP) 52.3 cM (1 SNP) 46.5 cM (1 SNP) 10.3 cM (1 SNP) 106.5 cM (1 SNP) 22 (29 SNPs) 3.50% </p><p> 60.8 cM (2 SNP) 36.8 cM (2 SNP) 110.2 cM (1 SNP) 55.7 cM (1 SNP) 47.5 cM (1 SNP) </p><p> 81.5 cM (4 SNP)* 51.8 cM (1 SNP) 95 cM (1 SNP) 51 cM (2 SNP) </p><p> 135.8 cM (1 SNP) 61.9 cM (1 SNP) 137.9 cM (1 SNP) </p><p> 146.5 cM (1 SNP) 89.4 cM (1 SNP) </p><p> 100.7 cM (2 SNP) </p><p>CSS 95.8 cM (1 SNP)* 1 (1 SNP) 1.60% </p><p>Total QTL 4 (6 SNPs) 10 (18 SNPs) 8 (10 SNPs) 3 (3 SNPs) 12 (22 SNPs) 4 (5 SNPs) 6 (6 SNPs) 47 (70 SNPs) </p><p>Wehner et al. (submitted) </p><p>Drought stress in the juvenile stage </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>FTSH3_BY_0.2%</p><p>PME49_CSS_1.6%</p><p>1H</p><p>SUS4_SPAD_3.8%</p><p>YSL2_OA_0.7%YSL15_OA_0.7%GDH2_OA_1.4%AMP1_OA_2.3%GPX1_BY_0.2%</p><p>2H</p><p>FBL21_OA_2.8%</p><p>ACO1_OA_2.3%</p><p>3H</p><p>PYL5_OA_2.5%</p><p>4H</p><p>AVP1_SPAD_BY_0.2%ATM_SPAD_BY_2.6%TRIUR3_SPAD_BY_3.1%SAPK9_SPAD_BY_3.1%</p><p>DREB1A_SPAD_OA_2.4%</p><p>EGY1_OA_1.4%</p><p>5H 6H</p><p>CHX_ETR_5.5%</p><p>ERF062_BY_0.2%</p><p>7H</p><p>0</p><p>5</p><p>10</p><p>15</p><p>20</p><p>25</p><p>30</p><p>35</p><p>40</p><p>45</p><p>50</p><p>55</p><p>60</p><p>65</p><p>70</p><p>75</p><p>80</p><p>85</p><p>90</p><p>95</p><p>100</p><p>105</p><p>110</p><p>115</p><p>120</p><p>125</p><p>130</p><p>135</p><p>140</p><p>145</p><p>150</p><p>155</p><p>160</p><p>165</p><p>170</p><p>Genetic map of QTLs including the significant associated SNP marker positions for </p><p>significant blasted proteins (BlastX) linked to drought stress or leaf senescence, </p><p>related traits for drought stress treatment and percentage of phenotypic variance </p><p>(explained R in %) of the SNPs for all linkage groups (barley chromosomes). </p><p>cM </p><p>Wehner et al. (submitted) </p><p>Drought stress in the juvenile stage </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>New breeding goals: Mycorrhization and drought stress </p><p>Experimental design: </p><p> 94 Genotypes, 2 Years, 3 Replications </p><p> Treatments </p><p> Mycorrhization (Myco, N-Myco) </p><p> Irrigation (25% and 75% maximal water capacity, MWC) </p><p>Quantification root colonization: </p><p> Ink vinegar staining (Vierheilig et al., 1998) </p><p> Magnified intersection method (McGonigle et al., 1990) </p><p>N-myco Myco Myco Myco Myco </p><p>Myco 25% MWC Myco 75% MWC </p><p>Lehnert et al. (in preparation) </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Trait: Root colonization (%) </p><p>Myco 25% MWC Myco 75% MWC </p><p>-lo</p><p>g10(p</p><p>) </p><p>-lo</p><p>g10(p</p><p>) </p><p>Chromosome Chromosome </p><p>Lehnert et al. (in preparation) </p><p>New breeding goals: Mycorrhization and drought stress </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p> Trait: Biomass (g), Yield (g), Ears per plant, 1000 grain weight (g), </p><p> Grains per ear </p><p>Lehnert et al. (in preparation) </p><p>New breeding goals: Mycorrhization and drought stress </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>amb: 400 ppm </p><p>eCO2: 700 ppm </p><p>New breeding goals: CO2 </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Mitterbauer et al. (in preparation) </p><p>Yie</p><p>ld </p><p>Ea</p><p>rs/p</p><p>lan</p><p>t T</p><p>KW</p><p>Ke</p><p>rne</p><p>l/E</p><p>ar </p><p>(2-r</p><p>ow</p><p>ed</p><p>) K</p><p>ern</p><p>el/E</p><p>ar </p><p>(6-r</p><p>ow</p><p>ed</p><p>) P</p><p>rote</p><p>in </p><p>New breeding goals: CO2 </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p> Genome wide association </p><p>analyses </p><p> (QK mixed model </p><p>approach; </p><p> minor allele frequency </p><p>&gt;5%) </p><p> 3886 marker </p><p>Yield response (E/A) </p><p>Biomass response (E/A) </p><p>Kernel #/ear(E/A) </p><p>Stem weight (E/A) </p><p>Mitterbauer et al. (in preparation) </p><p>New breeding goals: CO2 </p></li><li><p>Institute for Resistance Research and Stress Tolerance </p><p>Summary and future prospects </p><p> Genomic tools facilitate an enhanced marker development and isolation of major </p><p>genes and QTL for resistance to biotoc and abiotic stress leading to a deeper </p><p>understanding of trait development and the transfer of marker based selection to the </p><p>allele level. </p><p>This will lead to a more directed and faster use of genetic variation. </p><p>High throughput marker systems also offer the opportunity to implement new </p><p>breeding goals efficiently into applied breeding procedures. </p><p>Knowledge on gene sequences will facilitate the targeted editing of respective alleles </p><p>in the future by endonucleases. </p><p>Genomic tools will speed up breeding for resistance to biotic </p><p>and abiotic stress </p><p>http://www.nature.com/mtna/journal/v1/n1/full/mtna20115a.html </p><p>Fer

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