Enhancing genetic gain in the era of molecular breeding

Journal of Experimental Botany

Volumn 68, Issue 11, 2017, Pages 2641-2666

  Xu, Yunbi ^a,b   Li, Ping ^c   Zou, Cheng ^a   Lu, Yanli ^d   Xie, Chuanxiao ^a   Zhang, Xuecai ^b   Prasanna, Boddupalli M ^e   Olsen, Michael S ^e  

^a INSTITUTE OF PLANT PROTECTION   (China)

^b INTERNATIONAL MAIZE AND WHEAT IMPROVEMENT CENTER CIMMYT   (Mexico)

^c Nantong Xinhe Bio Technology   (China)

^d SICHUAN AGRICULTURAL UNIVERSITY   (China)

^e WORLD AGROFORESTRY CENTRE ICRAF   (Kenya)

Author keywords

Breeding cycle time; doubled haploids; envirotyping; genetic gain; genetic variation; genotyping; heritability; marker assisted selection; phenotyping; selection intensity

Indexed keywords

CROP; GENETIC VARIATION; GENETICS; MOLECULAR BIOLOGY; PLANT BREEDING; PROCEDURES;

CROPS, AGRICULTURAL; GENETIC VARIATION; MOLECULAR BIOLOGY; PLANT BREEDING;

EID: 85024491712     PISSN: 00220957     EISSN: 14602431     Source Type: Journal    
DOI: 10.1093/jxb/erx135     Document Type: Review

References (241)

1. Abe A, Kosugi S, Yoshida K, et al. 2012. Genome sequencing reveals agronomically important loci in rice using MutMap. Nature Biotechnology 30, 174-178.
2. Abudayyeh OO, Gootenberg JS, Konermann S, et al. 2016. C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector. Science 353, aaf5573.
3. Akbari M, Wenzl P, Caig V, et al. 2006. Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome. Theoretical and Applied Genetics 113, 1409-1420.
4. Allwright MR, Taylor G. 2016. Molecular breeding for improved second generation bioenergy crops. Trends in Plant Science 21, 43-54.
5. Anacleto R, Cuevas RP, Jimenez R, Llorente C, Nissila E, Henry R, Sreenivasulu N. 2015. Prospects of breeding high-quality rice using postgenomic tools. Theoretical and Applied Genetics 128, 1449-1466.
6. Araus JL, Cairns JE. 2014. Field high-throughput phenotyping: The new crop breeding frontier. Trends in Plant Science 19, 52-61.
7. Asaro A, Ziegler G, Ziyomo C, Hoekenga OA, Dilkes BP, Baxter I. 2017. The interaction of genotype and environment determines variation in the maize kernel ionome. G3 (Bethesda, Md.) 6, 4175-4183.
8. Bassi FM, Bentley AR, Charmet G, Ortiz R, Crossa J. 2016. Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.). Plant Science 242, 23-36.
9. Bernardo R. 2008. Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Science 48, 1649-1664.
10. Bernardo R. 2014. Genomewide selection when major genes are known. Crop Science 54, 68-75.
11. Betti M, Bauwe H, Busch FA, et al. 2016. Manipulating photorespiration to increase plant productivity: recent advances and perspectives for crop improvement. Journal of Experimental Botany 67, 2977-2988.
12. Bevan MW, Uauy C, Wulff BB, Zhou J, Krasileva K, Clark MD. 2017. Genomic innovation for crop improvement. Nature 543, 346-354.
13. Beyene Y, Semagn K, Crossa J, et al. 2015. Improving maize grain yield under drought stress and non-stress environments in sub-Saharan Africa using marker-assisted recurrent selection. Crop Science 56, 344-353.
14. Beyene Y, Semagn K, Mugo S, et al. 2015. Genetic gains in grain yield through genomic selection in eight bi-parental maize populations under drought stress. Crop Science 55, 154-163.
15. Beyene Y, Semagn K, Mugo S, et al. 2016. Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures. Euphytica 208, 285-297.
16. Bommert P, Nagasawa NS, Jackson D. 2013. Quantitative variation in maize kernel row number is controlled by the FASCIATED EAR2 locus. Nature Genetics 45, 334-337.
17. Brooks C, Nekrasov V, Lippman ZB, Van Eck J. 2014. Efficient gene editing in tomato in the first generation using the clustered regularly interspaced short palindromic repeats/CRISPR-associated9 system. Plant Physiology 166, 1292-1297.
18. Brozynska M, Furtado A, Henry RJ. 2016. Genomics of crop wild relatives: expanding the gene pool for crop improvement. Plant Biotechnology Journal 14, 1070-1085.
19. Brummer EC, Barber WT, Collier SM, Cox TS, Johnson R, Murray SC, Olsen RT, Pratt RC, Thro AM. 2011. Plant breeding for harmony between agriculture and the environment. Frontiers in Ecology and the Environment 9, 561-568.
20. Buckler ES, Ilut DC, Wang X, Kretzschmar T, Gore M, Mitchell SE. 2016. rAmpSeq: using repetitive sequences for robust genotyping. BioRxiv preprint first posted online December 24, 2016; doi: http://dx.doi.org/10.1101/096628, accessed April 26 2017.
21. Bukowski R, Guo X, Lu Y, et al. 2015. Construction of the third generation Zea mays haplotype map. BioRxiv preprint first posted online September 16, 2015, doi: http://dx.doi.org/10.1101/026963, accessed April 26 2017.
22. Caldwell DG, McCallum N, Shaw P, Muehlbauer GJ, Marshall DF, Waugh R. 2004. A structured mutant population for forward and reverse genetics in barley (Hordeum vulgare L.). The Plant Journal 40, 143-150.
23. Carroll D. 2011. Genome engineering with zinc-finger nucleases. Genetics 188, 773-782.
24. Castillo-Juárez H, Campos-Montes GR, Caballero-Zamora A, Montaldo HH. 2015. Genetic improvement of Pacific white shrimp [Penaeus (Litopenaeus) vannamei]: perspectives for genomic selection. Frontiers in Genetics 6, 93.
25. Ceballos H, Morante N, Sánchez T, Ortiz D, Aragón I, Chávez AL, Pizarro M, Calle F, Dufour D. 2013. Rapid cycling recurrent selection for increased carotenoids content in cassava roots. Crop Science 53, 2342-2351.
26. Chen L, Hao L, Parry MA, Phillips AL, Hu YG. 2014. Progress in TILLING as a tool for functional genomics and improvement of crops. Journal of Integrative Plant Biology 56, 425-443.
27. Chia JM, Song C, Bradbury PJ, et al. 2012. Maize HapMap2 identifies extant variation from a genome in flux. Nature Genetics 44, 803-807.
28. Comai L, Young K, Till BJ, et al. 2004. Efficient discovery of DNA polymorphisms in natural populations by Ecotilling. The Plant Journal 37, 778-786.
29. Cong L, Ran FA, Cox D, et al. 2013. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819-823.
30. Cooper M, Messina CD, Podlich D, Totir LR, Baumgarten A, Hausmann NJ, Wright D, Graham G. 2014. Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction. Crop and Pasture Science 65, 311-336.
31. Cooper M, Technow F, Messina C, Gho C, Totir LR. 2016. Use of crop growth models (CGM) with whole genome prediction (WGP): application of CGM-WGP to a maize multi-environment trial. Crop Science 56, 2141-2156.
32. Crossa J. 2012. From genotype×environment interaction to gene×environment interaction. Current Genomics 13, 225-244.
33. Crossa J, Beyene Y, Kassa S, et al. 2013. Genomic prediction in maize breeding populations with genotyping-by-sequencing. G3 (Bethesda, Md.) 3, 1903-1926.
34. Crossa J, Pérez P, Hickey J, et al. 2014. Genomic prediction in CIMMYT maize and wheat breeding programs. Heredity 112, 48-60.
35. Daetwyler HD, Hayden MJ, Spangenberg GC, Hayes BJ. 2015. Selection on optimal haploid value increases genetic gain and preserves more genetic diversity relative to genomic selection. Genetics 200, 1341-1348.
36. De La Fuente GN, Frei Uk, Lübberstedt T. 2013. Accelerating plant breeding. Trends in Plant Science 18, 667-672.
37. Doebley J, Stec A, Gustus C. 1995. Teosinte branched1 and the origin of maize: evidence for epistasis and the evolution of dominance. Genetics 141, 333-346.
38. Doench JG, Fusi N, Sullender M, et al. 2016. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature Biotechnology 34, 184-191.
39. Dong X, Xu X, Li L, Liu C, Tian X, Li W, Chen S. 2014. Marker-assisted selection and evaluation of high oil in vivo haploid inducers in maize. Molecular Breeding 34, 1147-1158.
40. Dreisigacker S, Sukumaran S, Guzmán C, He X, Lan C, Bonnett D, Crossa J. 2016. Molecular marker-based selection tools in spring bread wheat improvement: CIMMYT experience and prospects. In: Rajpal VR, Rao SR, Raina SN, eds. Molecular breeding for sustainable crop improvement, sustainable development and biodiversity. Switzerland: Springer International Publishing, 421-474.
41. Duangjit J, Causse M, Sauvage C. 2016. Efficiency of genomic selection for tomato fruit quality. Molecular Breeding 36, 29.
42. Dudley JW, Lambert RJ. 2004. 100 generations of selection for oil and protein in corn. Plant Breeding Reviews 24, 79-110.
43. Dwivedi SL, Ceccarelli S, Blair MW, Upadhyaya HD, Are AK, Ortiz R. 2016. Landrace germplasm for improving yield and abiotic stress adaptation. Trends in Plant Science 21, 31-42.
44. Eathington SR, Crosbie TM, Edwards MD, Reiter RS, Bull JK. 2007. Molecular markers in a commercial breeding program. Crop Science 47, S154-S163.
45. El-Soda M, Malosetti M, Zwaan BJ, Koornneef M, Aarts MG. 2014. Genotype×environment interaction QTL mapping in plants: lessons from Arabidopsis. Trends in Plant Science 19, 390-398.
46. Endelman JB, Atlin GN, Beyene Y, Semagn K, Zhang X, Sorrells ME, Jannink J-L. 2014. Optimal design of preliminary yield trials with genomewide markers. Crop Science 54, 48-59.
47. Fahlgren N, Gehan MA, Baxter I. 2015. Lights, camera, action: highthroughput plant phenotyping is ready for a close-up. Current Opinion in Plant Biology 24, 93-99.
48. Falconer DS, Mackay TFC. 1996. Introduction to quantitative genetics, 4th edn. London: Longman Group Ltd.
49. Fan D, Liu T, Li C, Jiao B, Li S, Hou Y, Luo K. 2015. Efficient CRISPR/ Cas9-mediated targeted mutagenesis in populus in the first generation. Scientific Reports 5, 12217.
50. FAO. 2011. The state of the world's land and water resources for food and agriculture. Rome, Italy: Food and Agriculture Organization of the United Nations.
51. Farkhari M, Lu Y, Shah T, Zhang S, Naghavi MR, Rong T, Xu Y. 2011. Recombination frequency variation in maize as revealed by genomewide single-nucleotide polymorphisms. Plant Breeding 130, 533-539.
52. Fermont AM, Fermont AM, Asten PJAV, Tittonell P, Wijk MTV, Giller KE. 2009. Closing the cassava yield gap: an analysis from smallholder farms in East Africa. Field Crops Research 112, 24-36.
53. Fischer RA, Edmeades GO. 2010. Breeding and cereal yield progress. Crop Science 50, 85-98.
54. Fischer T, Byerlee D, Edmeades G. 2014. Crop yields and global food security. Canberra, Australia: ACIAR.
55. Fischer T, Byerlee D, Edmeades G. 2014. Crop yields and global food security: will yield increase continue to feed the world? ACIAR Monograph 158. Canberra, Australia: ACIAR.
56. Frary A, Nesbitt TC, Grandillo S, Knaap E, Cong B, Liu J, Meller J, Elber R, Alpert KB, Tanksley SD. 2000. fw2.2: A quantitative trait locus key to the evolution of tomato fruit size. Science 289, 85-88.
57. Gao S, Martinez C, Skinner DJ, Krivanek AF, Crouch JH, Xu Y. 2008. Development of a seed DNA-based genotyping system for markerassisted selection in maize. Molecular Breeding 22, 477-494.
58. Gauffier C, Lebaron C, Moretti A, Constant C, Moquet F, Bonnet G, Caranta C, Gallois JL. 2016. A TILLING approach to generate broadspectrum resistance to potyviruses in tomato is hampered by eIF4E gene redundancy. The Plant Journal 85, 717-729.
59. Ghanem ME, Marrou H, Sinclair TR. 2015. Physiological phenotyping of plants for crop improvement. Trends in Plant Science 20, 139-144.
60. Goddard ME, Hayes BJ. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics 10, 381-391.
61. Golicz AA, Batley J, Edwards D. 2016. Towards plant pangenomics. Plant Biotechnology Journal 14, 1099-1105.
62. Gomez KA. 1977. On-farm assessment of yield constraints: methodological problems. In: Constraints to high yields on Asian rice farms: an interim report. Los Baños, Philippines: IRRI, 1-16.
63. Gore MA, Chia JM, Elshire RJ, et al. 2009. A first-generation haplotype map of maize. Science 326, 1115-1117.
64. Gowda M, Das B, Makumbi D, Babu R, Semagn K, Mahuku G, Olsen MS, Bright JM, Beyene Y, Prasanna BM. 2015. Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm. Theoretical and Applied Genetics 128, 1957-1968.
65. Greene EA, Codomo CA, Taylor NE, et al. 2003. Spectrum of chemically induced mutations from a large-scale reverse-genetic screen in Arabidopsis. Genetics 164, 731-740.
66. Habyarimana E. 2016. Genomic prediction for yield improvement and safeguarding of genetic diversity in CIMMYT spring wheat (Triticum aestivum L.). Australian Journal of Crop Science 10, 127-136.
67. Hall AJ, Richards RA. 2013. Prognosis for genetic improvement of yield potential and water-limited yield of major grain crops. Field Crops Research 143, 18-33.
68. Hansey CN, Vaillancourt B, Sekhon RS, de Leon N, Kaeppler SM, Buell CR. 2012. Maize (Zea mays L.) genome diversity as revealed by RNA-sequencing. PLoS One 7, e33071.
69. Hasegawa Y, Suyama Y, Seiwa K. 2009. Pollen donor composition during the early phases of reproduction revealed by DNA genotyping of pollen grains and seeds of Castanea crenata. New Phytologist 182, 994-1002.
70. He S, Schulthess AW, Mirdita V, Zhao Y, Korzun V, Bothe R, Ebmeyer E, Reif JC, Jiang Y. 2016. Genomic selection in a commercial winter wheat population. Theoretical and Applied Genetics 129, 641-651.
71. Heffner EL, Lorenz AJ, Jannink JL, Sorrells ME. 2010. Plant breeding with genomic selection: gain per unit time and cost. Crop Science 50, 1681-1690.
72. Henderson IR. 2012. Control of meiotic recombination frequency in plant genomes. Current Opinion in Plant Biology 15, 556-561.
73. Henry RJ, Rangan P, Furtado A. 2016. Functional cereals for production in new and variable climates. Current Opinion in Plant Biology 30, 11-18.
74. Heslot N, Jannink JL, Sorrells ME. 2015. Perspectives for genomic selection applications and research in plants. Crop Science 55, 1-12.
75. Hirsch CN, Flint-Garcia SA, Beissinger TM, et al. 2014. Insights into the effects of long-term artificial selection on seed size in maize. Genetics 198, 409-421.
76. Hirsch CN, Foerster JM, Johnson JM, et al. 2014. Insights into the maize pan-genome and pan-transcriptome. The Plant Cell 26, 121-135.
77. Hoffmann AA, Willi Y. 2008. Detecting genetic responses to environmental change. Nature Reviews Genetics 9, 421-432.
78. Huang X, Wei X, Sang T, et al. 2010. Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genetics 42, 961-967.
79. International HapMap 3 Consortium. 2010. Integrating common and rare genetic variation in diverse human populations. Nature 467, 52-58.
80. Jacobson A, Lian L, Zhong S, Bernardo R. 2014. General combining ability model for genomewide selection in a biparental cross. Crop Science 54, 895-905.
81. James JW, McBride G. 1958. The spread of genes by natural and artificial selection in a closed poultry flock. Journal of Genetics 56, 55-62.
82. Javot H, Penmetsa RV, Terzaghi N, Cook DR, Harrison MJ. 2007. A Medicago truncatula phosphate transporter indispensable for the arbuscular mycorrhizal symbiosis. Proceedings of the National Academy of Sciences, USA 104, 1720-1725.
83. Jia Y, Sun X, Sun J, et al. 2014. Association mapping for epistasis and environmental interaction of yield traits in 323 cotton cultivars under 9 different environments. PLoS One 9, e95882.
84. Jiang Y, Reif JC. 2015. Modeling epistasis in genomic selection. Genetics 201, 759-768.
85. Jin M, Liu H, He C, Fu J, Xiao Y, Wang Y, Xie W, Wang G, Yan J. 2016. Maize pan-transcriptome provides novel insights into genome complexity and quantitative trait variation. Scientific Reports 6, 18936.
86. Johnson T, Barton N. 2005. Theoretical models of selection and mutation on quantitative traits. Philosophical Transactions of the Royal Society B: Biological Sciences 360, 1411-1425.
87. Jonas E, de Koning DJ. 2015. Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs. Frontiers in Genetics 6, 49.
88. Kainer D, Lanfear R, Foley WJ, Külheim C. 2015. Genomic approaches to selection in outcrossing perennials: focus on essential oil crops. Theoretical and Applied Genetics 128, 2351-2365.
89. Kelliher T, Starr D, Richbourg L, et al. 2017. MATRILINEAL, a spermspecific phospholipase, triggers maize haploid induction. Nature 542, 105-109.
90. Kitney R, Freemont P. 2012. Synthetic biology-The state of play. FEBS Letters 586, 2029-2036.
91. Klukas C, Chen D, Pape JM. 2014. Integrated analysis platform: an open-source information system for high-throughput plant phenotyping. Plant Physiology 165, 506-518.
92. Knol EF, Nielsen B, Knap PW. 2016. Genomic selection in commercial pig breeding. Animal Frontiers 6, 15-22.
93. Koning NBJ, Van Ittersum MK, Becx GA, et al. 2008. Long-term global availability of food: continued abundance or new scarcity? NJAS Wageningen Journal of Life Sciences 55, 229-292.
94. Kover PX, Valdar W, Trakalo J, Scarcelli N, Ehrenreich IM, Purugganan MD, Durrant C, Mott R. 2009. A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genetics 5, e1000551.
95. Kumar APK, McKeown PC, Boualem A, Ryder P, Brychkova G, Bendahmane A, Sarkar A, Chatterjee M, Spillane C. 2017. TILLING by Sequencing (TbyS) for targeted genome mutagenesis in crops. Molecular Breeding 37, 14.
96. Kumar V, Khan AW, Saxena RK, Garg V, Varshney RK. 2016. First-generation HapMap in Cajanus spp. reveals untapped variations in parental lines of mapping populations. Plant Biotechnology Journal 14, 1673-1681.
97. Laborte AG, de Bie KCAJM, Smaling EMA, Moya PF, Boling AA, Van Ittersum MK. 2012. Rice yields and yield gaps in Southeast Asia: past trends and future outlook. European Journal of Agronomy 36, 9-20.
98. Lai J, Li R, Xu X, et al. 2010. Genome-wide patterns of genetic variation among elite maize inbred lines. Nature Genetics 42, 1027-1030.
99. Lakew B, Henry RJ, Eglinton J, Baum M, Ceccarelli S, Grando S. 2012. SSR analysis of introgression of drought tolerance from the genome of Hordeum spontaneum into cultivated barley (Hordeum vulgare ssp. vulgare). Euphytica 191, 231-243.
100. Lam HM, Xu X, Liu X, et al. 2010. Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nature Genetics 42, 1053-1059.
101. Laviola BG, Oliveira AMCE, Bhering LL, Alves AA, Rocha RB, Gomes BEL, Cruz CD. 2013. Estimates of repeatability coefficients and selection gains in Jatropha indicate that higher cumulative genetic gains can be obtained by relaxing the degree of certainty in predicting the best families. Industrial Crops and Products 51, 70-76.
102. Li T, Liu B, Spalding MH, Weeks DP, Yang B. 2012. High-efficiency TALEN-based gene editing produces disease-resistant rice. Nature Biotechnology 30, 390-392.
103. Li YH, Zhou G, Ma J, et al. 2014. De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits. Nature Biotechnology 32, 1045-1052.
104. Li Z, Sillanpää MJ. 2015. Dynamic quantitative trait locus analysis of plant phenomic data. Trends in Plant Science 20, 822-833.
105. Liang Z, Zhang K, Chen K, Gao C. 2014. Targeted mutagenesis in Zea mays using TALENs and the CRISPR/Cas system. Journal of Genetics and Genomics 41, 63-68.
106. Lin K, Zhang N, Severing EI, Nijveen H, Cheng F, Visser RG, Wang X, de Ridder D, Bonnema G. 2014. Beyond genomic variation-comparison and functional annotation of three Brassica rapa genomes: A turnip, a rapid cycling and a Chinese cabbage. BMC Genomics 15, 250.
107. Liu C, Li X, Meng D, et al. 2017. A 4-bp insertion at ZmPLA1 encoding a putative phospholipase A generates haploid induction in maize. Molecular Plant 10, 520-522.
108. Liu H, Meuwissen TH, Sørensen AC, Berg P. 2015. Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs. Genetics, Selection, Evolution 47, 19.
109. Long SP, Zhu XG, Naidu SL, Ort DR. 2006. Can improvement in photosynthesis increase crop yields? Plant, Cell and Environment 29, 315-330.
110. Lu C, Shen L, Tan Z, Xu Y, He P, Chen Y, Zhu L. 1996. Comparative mapping of QTLs for agronomic traits of rice across environments using a doubled haploid population. Theoretical and Applied Genetics 93, 1211-1217.
111. Lu F, Romay MC, Glaubitz JC, et al. 2015. High-resolution genetic mapping of maize pan-genome sequence anchors. Nature Communications 6, 6914.
112. Lu J, Lv Y, Li T, Zhao H, Zhang T. 2015. Identification and characterization of presence/absence variation in maize genotype Mo17. Genes and Genomics 37, 503-515.
113. Mace ES, Tai S, Gilding EK, et al. 2013. Whole-genome sequencing reveals untapped genetic potential in Africa's indigenous cereal crop sorghum. Nature Communications 4, 2320.
114. Mahfouz MM, Li L, Shamimuzzaman M, Wibowo A, Fang X, Zhu JK. 2011. De novo-engineered transcription activator-like effector (TALE) hybrid nuclease with novel DNA binding specificity creates double-strand breaks. Proceedings of the National Academy of Sciences, USA 108, 2623-2628.
115. Mali P, Yang L, Esvelt KM, Aach J, Guell M, DiCarlo JE, Norville JE, Church GM. 2013. RNA-guided human genome engineering via Cas9. Science 339, 823-826.
116. Malosetti M, Ribaut JM, van Eeuwijk FA. 2013. The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis. Frontiers in Physiology 4, 44.
117. Massman JM, Jung H-JG, Bernardo R. 2013. Genomewide selection versus marker-assisted recurrent selection to improve grain yield and stover-quality traits for cellulosic ethanol in maize. Crop Science 53, 58-66.
118. Masuka B, Araus JL, Sonder K, Das B, Cairns JE. 2012. Deciphering the code: successful abiotic stress phenotyping for molecular breeding. Journal of Integrative Plant Biology 54, 238-249.
119. McNally K. 2014. 3000 Rice genomes-update and plans. 4th International Workshop on Next Generation Genomics and Integrated Breeding for Crop Improvement, February 19-21, 2014. Patancheru, India: ICRISAT.
120. Melamed-Bessudo C, Shilo S, Levy AA. 2016. Meiotic recombination and genome evolution in plants. Current Opinion in Plant Biology 30, 82-87.
121. Melchinger AE, Schipprack W, Würschum T, Chen S, Technow F. 2013. Rapid and accurate identification of in vivo-induced haploid seeds based on oil content in maize. Scientific Reports 3, 2129.
122. Meuwissen T. 2003. Genomic selection: The future of marker-assisted selection and animal breeding. In: Marker-assisted selection: A fast track to increase genetic gain in plant and animal breeding? Session II: MAS in animals, 54-59.
123. Meuwissen TH, Hayes BJ, Goddard ME. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819-1829.
124. Meuwissen T, Hayes B, Goddard M. 2016. Genomic selection: A paradigm shift in animal breeding. Animal Frontiers 6, 6-14.
125. Miao J, Guo D, Zhang J, Huang Q, Qin G, Zhang X, Wan J, Gu H, Qu LJ. 2013. Targeted mutagenesis in rice using CRISPR-Cas system. Cell Research 23, 1233-1236.
126. Myrold DD, Zeglin LH, Jansson JK. 2014. The potential of metagenomic approaches for understanding soil microbial processes. Soil Science Society of America Journal 78, 3-10.
127. Nachman MW. 2002. Variation in recombination rate across the genome: evidence and implications. Current Opinion in Genetics and Development 12, 657-663.
128. Neumann K, Verburg PH, Stehfest E, Müller C. 2010. The yield gap of global grain production: A spatial analysis. Agricultural Systems 103, 316-326.
129. Odegard J, Meuwissen TH. 2014. Identity-by-descent genomic selection using selective and sparse genotyping. Genetics, Selection, Evolution 46, 3.
130. Oakey H, Cullis B, Thompson R, Comadran J, Halpin C, Waugh R. 2016. Genomic selection in multi-environment crop trials. G3 (Bethesda, Md.) 6, 1313-1326.
131. Oury F-X, Godin C, Mailliard A, et al. 2012. A study of genetic progress due to selection reveals a negative effect of climate change on bread wheat yield in France. European Journal of Agronomy 40, 28-38.
132. Ow DW. 2016. The long road to recombinase-mediated plant transformation. Plant Biotechnology Journal 14, 441-447.
133. Palmer CE, Keller WA. 2005. Overview of haploidy. In: Palmer CE, Keller WA, Kasha KJ, eds. Biotechnology in agriculture and forestry, Vol. 56. Haploids in crop improvement II. Berlin: Springer-Verlag, 3-9.
134. Pardey PG, Beddow JM, Hurley TM, Beatty TKM, Ediman VR. 2014. A bounds analysis of world food futures: global agriculture through to 2050. Australian Journal of Agricultural and Resource Economics 58, 571-589.
135. Petolino JF, Kumar S. 2016. Transgenic trait deployment using designed nucleases. Plant Biotechnology Journal 14, 503-509.
136. Petolino JF, Srivastava V, Daniell H. 2016. Editing plant genomes: A new era of crop improvement. Plant Biotechnology Journal 14, 435-436.
137. Podlich DW, Winkler CR, Cooper M. 2004. Mapping as you go: an effective approach for marker-assisted selection of complex traits. Crop Science 44, 1560-1571.
138. Poland J, Endelman J, Dawson J, et al. 2012. Genomic selection in wheat breeding using genotyping-by-sequencing. Plant Genome 5, 103-113.
139. Poland JA, Brown PJ, Sorrells ME, Jannink JL. 2012. Development of high-density genetic maps for barley and wheat using a novel twoenzyme genotyping-by-sequencing approach. PLoS One 7, e32253.
140. Poland J, Rutkoski J. 2016. Advances and challenges in genomic selection for disease resistance. Annual Review of Phytopathology 54, 79-98.
141. Poorter H, Bühler J, van Dusschoten D, Climent J, Postma JA. 2012. Pot size matters: A meta-analysis of the effects of rooting volume on plant growth. Functional Plant Biology 39, 839-850.
142. Prasanna BM. 2016. Developing and deploying abiotic stress-tolerant maize varieties in the tropics: challenges and opportunities. In: Rajpal VR, Rao SR, Raina SN, eds. Molecular breeding for sustainable crop improvement, sustainable development and biodiversity. Switzerland: Springer International Publishing, 61-77.
143. Puchta H. 2017. Applying CRISPR/Cas for genome engineering in plants: The best is yet to come. Current Opinion in Plant Biology 36, 1-8.
144. Rawat N, Pumphrey MO, Liu S, et al. 2016. Wheat Fhb1 encodes a chimeric lectin with agglutinin domains and a pore-forming toxin-like domain conferring resistance to Fusarium head blight. Nature Genetics 48, 1576-1580.
145. Rebetzke GJ, Chenu K, Biddulph B, Moeller C, Deery DM, Rattey AR, Bennett D, Barrett-Lennard EG, Mayer JE. 2013. A multisite managed environment facility for targeted trait and germplasm phenotyping. Functional Plant Biology 40, 1-13.
146. Renaut S, Rieseberg LH. 2015. The accumulation of deleterious mutations as a consequence of domestication and improvement in sunflowers and other compositae crops. Molecular Biology and Evolution 32, 2273-2283.
147. Resende MF Jr, Muñoz P, Resende MD, Garrick DJ, Fernando RL, Davis JM, Jokela EJ, Martin TA, Peter GF, Kirst M. 2012. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190, 1503-1510.
148. Reynolds MP, Pask AJD, Mullan DM (eds). 2012. Physiological breeding I: interdisciplinary approaches to improve crop adaptation. CIMMYT.
149. Robbins K, Buckler ES, Jannink J-L, et al. 2016. The genomic & open-source breeding informatics initiative. Plant and Animal Genome Conference 24, W440.
150. Romay MC, Millard MJ, Glaubitz JC, et al. 2013. Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biology 14, R55.
151. Ronceret A, Doutriaux MP, Golubovskaya IN, Pawlowski WP. 2009. PHS1 regulates meiotic recombination and homologous chromosome pairing by controlling the transport of RAD50 to the nucleus. Proceedings of the National Academy of Sciences, USA 106, 20121-20126.
152. Ruiter R. 2017. Crop improvement through targeted genome optimization requires more than scissors. Plant and Animal Genome Conference 25, W697.
153. Rupp R, Mucha S, Larroque H, McEwan J, Conington J. 2016. Genomic application in sheep and goat breeding. Animal Frontiers 6, 39-44.
154. Rutkoski J. 2016. Using big data and global partnerships to accelerate rates of genetic gain in wheat. AAAS 2016 Annual Meeting, February 11-15, 2016, Washington, DC.
155. Rutkoski JE, Heffner EL, Sorrells ME. 2011. Genomic selection for durable stem rust resistance in wheat. Euphytica 179, 161-173.
156. Rutkoski JE, Poland JA, Singh RP, Huerta-Espino J, Bhavani S, Barbier H, Rouse MN, Jannink JL, Sorrells ME. 2014. Genomic selection for quantitative adult plant stem rust resistance in wheat. Plant Genome 7, doi: 10.3835/plantgenome2014.02.0006.
157. Sadhu MJ, Bloom JS, Day L, Kruglyak L. 2016. CRISPR-directed mitotic recombination enables genetic mapping without crosses. Science 352, 1113-1116.
158. Saidou AA, Thuillet AC, Couderc M, Mariac C, Vigouroux Y. 2014. Association studies including genotype by environment interactions: prospects and limits. BMC Genetics 15, 3.
159. Sallam AH, Endelman JB, Jannink J-L, Smith KP. 2015. Assessing genomic selection prediction accuracy in a dynamic barley breeding population. Plant Genome 8, 1-15.
160. Salvi S, Tuberosa R. 2005. To clone or not to clone plant QTLs: present and future challenges. Trends in Plant Science 10, 297-304.
161. Salvi S, Tuberosa R. 2007. Cloning QTLs in plants. In: Varshney RK, Tuberosa R, eds. Genomics-assisted crop improvement. Dordrecht: Springer, 207-225.
162. Salvi S, Tuberosa R. 2015. The crop QTLome comes of age. Current Opinion in Biotechnology 32, 179-185.
163. Samayoa LF, Malvar RA, Olukolu BA, Holland JB, Butrón A. 2015. Genome-wide association study reveals a set of genes associated with resistance to the Mediterranean corn borer (Sesamia nonagrioides L.) in a maize diversity panel. BMC Plant Biology 15, 35.
164. Sauer NJ, Mozoruk J, Miller RB, Warburg ZJ, Walker KA, Beetham PR, Schöpke CR, Gocal GF. 2016. Oligonucleotide-directed mutagenesis for precision gene editing. Plant Biotechnology Journal 14, 496-502.
165. Schatz MC, Maron LG, Stein JC, et al. 2014. Whole genome de novo assemblies of three divergent strains of rice, Oryza sativa, document novel gene space of aus and indica. Genome Biology 15, 506.
166. Schlötterer C, Tobler R, Kofler R, Nolte V. 2014. Sequencing pools of individuals-mining genome-wide polymorphism data without big funding. Nature Reviews Genetics 15, 749-763.
167. Schopp P, Riedelsheimer C, Utz HF, Schön CC, Melchinger AE. 2015. Forecasting the accuracy of genomic prediction with different selection targets in the training and prediction set as well as truncation selection. Theoretical and Applied Genetics 128, 2189-2201.
168. Semagn K, Beyene J, Babu R, et al. 2015. Quantitative trait loci mapping and molecular breeding for developing stress resilient maize for sub-Saharan Africa. Crop Science 55, 1449-1459.
169. Servin B, Martin OC, Mézard M, Hospital F. 2004. Toward a theory of marker-assisted gene pyramiding. Genetics 168, 513-523.
170. Shan Q, Wang Y, Li J, Gao C. 2014. Genome editing in rice and wheat using the CRISPR/Cas system. Nature Protocols 9, 2395-2410.
171. Shen X, Liu ZQ, Mocoeur A, Xia Y, Jing HC. 2015. PAV markers in Sorghum bicolour: genome pattern, affected genes and pathways, and genetic linkage map construction. Theoretical and Applied Genetics 128, 623-637.
172. Sikora P, Chawade A, Larsson M, Olsson J, Olsson O. 2011. Mutagenesis as a tool in plant genetics, functional genomics, and breeding. International Journal of Plant Genomics 2011, 314829.
173. Singh A, Ganapathysubramanian B, Singh AK, Sarkar S. 2016. Machine learning for high-throughput stress phenotyping in plants. Trends in Plant Science 21, 110-124.
174. Snowdon RJ, Abbadi A, Kox T, Schmutzer T, Leckband G. 2015. Heterotic haplotype capture: precision breeding for hybrid performance. Trends in Plant Science 20, 410-413.
175. Spindel JE, Begum H, Akdemir D, Collard B, Redoña E, Jannink JL, McCouch S. 2016. Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement. Heredity 116, 395-408.
176. Spindel J, Begum H, Akdemir D, Virk P, Collard B, Redoña E, Atlin G, Jannink JL, McCouch SR. 2015. Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS Genetics 11, e1004982.
177. Springer NM, Ying K, Fu Y, et al. 2009. Maize inbreds exhibit high levels of copy number variation (CNV) and presence/absence variation (PAV) in genome content. PLoS Genetics 5, e1000734.
178. Srivastava V, Thomson J. 2016. Gene stacking by recombinases. Plant Biotechnology Journal 14, 471-482.
179. Sun X, Hu Z, Chen R, Jiang Q, Song G, Zhang H, Xi Y. 2015. Targeted mutagenesis in soybean using the CRISPR-Cas9 system. Scientific Reports 5, 10342.
180. Sun Y, Wang J, Crouch JH, Xu Y. 2010. Efficiency of selective genotyping for genetic analysis of complex traits and potential applications in crop improvement. Molecular Breeding 26, 493-511.
181. Svitashev S, Young JK, Schwartz C, Gao H, Falco SC, Cigan AM. 2015. Targeted mutagenesis, precise gene editing, and site-specific gene insertion in maize using Cas9 and guide RNA. Plant Physiology 169, 931-945.
182. Swanson-Wagner RA, Eichten SR, Kumari S, Tiffin P, Stein JC, Ware D, Springer NM. 2010. Pervasive gene content variation and copy number variation in maize and its undomesticated progenitor. Genome Research 20, 1689-1699.
183. Takagi H, Abe A, Yoshida K, et al. 2013. QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. The Plant Journal 74, 174-183.
184. Tanksley SD, McCouch SR. 1997. Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277, 1063-1066.
185. Tanksley SD, Young ND, Paterson AH, Bonierbale MW. 1989. RFLP mapping in plant breeding: new tools for an old science. Nature Biotechnology 7, 257-263.
186. Taylor DR, Ingvarsson PK. 2003. Common features of segregation distortion in plants and animals. Genetica 117, 27-35.
187. Technow F, Messina CD, Totir LR, Cooper M. 2015. Integrating crop growth models with whole genome prediction through approximate Bayesian computation. PLoS One 10, e0130855.
188. Till BJ, Comai L, Henikoff S. 2007. Tilling and ecotilling for crop improvement. In: Varshney RK, Tuberosa R, eds. Genomics-assisted crop improvement. Dordrecht, The Netherlands: Springer, 333-349.
189. Till BJ, Reynolds SH, Greene EA, et al. 2003. Large-scale discovery of induced point mutations with high-throughput TILLING. Genome Research 13, 524-530.
190. Tilman D, Balzer C, Hill J, Beforta BL. 2011. Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences, USA 108, 20260-20264.
191. Uauy C, Krasileva K, Bailey PC, Buffalo V, Phillips AL, Ayling S, Dubcovsky J. 2013. An in-silico functional genomics resource: targeted re-sequencing of wheat TILLING mutant populations. Plant and Animal Genome XXI Conference. https://pag.confex.com/pag/xxi/webprogram/ Paper6334.html, last accessed on April 26, 2017.
192. Uga Y, Sugimoto K, Ogawa S, et al. 2013. Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nature Genetics 45, 1097-1102.
193. USDA-National Agricultural Statistics Service. 2013. Field crops statistics. USDA-NASS.
194. van Ittersum MK, Cassman KG, Grassini P, Wolf J, Tittonell P, Hochman Z. 2013. Yield gap analysis with local to global relevance-A review. Field Crops Research 143, 4-17.
195. Varshney RK, Singh VK, Hickey JM, Xu X, Marshall DF, Wang J, Edwards D, Ribaut JM. 2016. Analytical and decision support tools for genomics-assisted breeding. Trends in Plant Science 21, 354-363.
196. Visscher PM. 2008. Sizing up human height variation. Nature Genetics 40, 489-490.
197. Vivek BS, Krishna GK, Vengadessan V, et al. 2017. Use of genomic estimated breeding values results in rapid genetic gains for drought tolerance in maize. Plant Genome 10 doi: 10.3835/ plantgenome2016.07.0070.
198. Voss-Fels K, Snowdon RJ. 2016. Understanding and utilizing crop genome diversity via high-resolution genotyping. Plant Biotechnology Journal 14, 1086-1094.
199. Wang TL, Uauy C, Robson F, Till B. 2012. TILLING in extremis. Plant Biotechnology Journal 10, 761-772.
200. Wang Y, Cheng X, Shan Q, Zhang Y, Liu J, Gao C, Qiu JL. 2014. Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nature Biotechnology 32, 947-951.
201. Wang ZP, Xing HL, Dong L, Zhang HY, Han CY, Wang XC, Chen QJ. 2015. Egg cell-specific promoter-controlled CRISPR/Cas9 efficiently generates homozygous mutants for multiple target genes in Arabidopsis in a single generation. Genome Biology 16, 144.
202. Warr A, Robert C, Hume D, Archibald A, Deeb N, Watson M. 2015. Exome sequencing: current and future perspectives. G3 (Bethesda, Md.) 5, 1543-1550.
203. Weeks DP, Spalding MH, Yang B. 2016. Use of designer nucleases for targeted gene and genome editing in plants. Plant Biotechnology Journal 14, 483-495.
204. Weil CF. 2009. TILLING in grass species. Plant Physiology 149, 158-164.
205. Wenzel P. 2014. Large-scale application of GbS in the Seeds of Discovery (SeeD) project: 'rightsizing' of methods and initial results. 4th International Workshop on Next Generation Genomics and Integrated Breeding for Crop Improvement, February 19-21, 2014, Patancheru, India: ICRISAT.
206. Whelan B, Taylor J. 2013. Precision agriculture for grain production systems. Collingwood, Australia: CSIRO Publishing.
207. Wilde HD, Chen Y, Jiang P, Bhattacharya A. 2012. Targeted mutation breeding of horticultural plants. Emirates Journal of Food and Agriculture 24, 31-41.
208. Windhausen VS, Atlin GN, Hickey JM, et al. 2012. Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments. G3 (Bethesda, Md.) 2, 1427-1436.
209. Wong CK, Bernardo R. 2008. Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theoretical and Applied Genetics 116, 815-824.
210. Woolliams JA, Berg P, Dagnachew BS, Meuwissen TH. 2015. Genetic contributions and their optimization. Journal of Animal Breeding and Genetics 132, 89-99.
211. Xia Z, Watanabe S, Yamada T, et al. 2012. Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering. Proceedings of the National Academy of Sciences, USA 109, E2155-E2164.
212. Xie K, Minkenberg B, Yang Y. 2015. Boosting CRISPR/Cas9 multiplex editing capability with the endogenous tRNA-processing system. Proceedings of the National Academy of Sciences, USA 112, 3570-3575.
213. Xing HL, Dong L, Wang ZP, Zhang HY, Han CY, Liu B, Wang XC, Chen QJ. 2014. A CRISPR/Cas9 toolkit for multiplex genome editing in plants. BMC Plant Biology 14, 327.
214. Xu K, Xu X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM, Bailey-Serres J, Ronald PC, Mackill DJ. 2006. Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442, 705-708.
215. Xu R, Li H, Qin R, Wang L, Li L, Wei P, Yang J. 2014. Gene targeting using the Agrobacterium tumefaciens-mediated CRISPR-Cas system in rice. Rice 7, 5.
216. Xu RF, Li H, Qin RY, Li J, Qiu CH, Yang YC, Ma H, Li L, Wei PC, Yang JB. 2015. Generation of inheritable and 'transgene clean' targeted genome-modified rice in later generations using the CRISPR/Cas9 system. Scientific Reports 5, 11491.
217. Xu Y. 2010. Molecular plant breeding. Wallingford, UK: CABI Publishing.
218. Xu Y. 2011. From line to space: A 3-D profile of molecular plant breeding. In: The first congress of cereal biotechnology and breeding, May 23-27, 2011, Szeged, Hungary.
219. Xu Y. 2012. Environmental assaying or e-typing as a key component for integrated plant breeding platform. In: Marker-assisted selection workshop, 6th international crop science congress, August 6-10, 2012, Bento Goncalves, RS, Brazil.
220. Xu Y. 2014. Whole genome strategies for marker-assisted plant breeding. In: 4th International Workshop on Next Generation Genomics and Integrated Breeding for Crop Improvement, February 19-21, 2014, Patancheru, India: ICRISAT.
221. Xu Y. 2016. Envirotyping for deciphering environmental impacts on crop plants. Theoretical and Applied Genetics 129, 653-673.
222. Xu Y, Crouch JH. 2008. Marker-assisted selection in plant breeding: from publications to practice. Crop Science 48, 391-407.
223. Xu Y, Lu Y, Xie C, Gao S, Wan J, Prasanna BM. 2012. Whole-genome strategies for marker-assisted plant breeding. Molecular Breeding 29, 833-854.
224. Xu Y, Xie C, Wan J, He Z, Prasanna BM. 2013. Marker-assisted selection in cereals: platforms, strategies and examples. In: Gupta PK, Varshney RK, eds. Cereal genomics II. Dordrecht: Springer Science+Business Media, 375-411.
225. Xu Y, Zhu L, Xiao J, Huang N, McCouch SR. 1997. Chromosomal regions associated with segregation distortion of molecular markers in F2, backcross, doubled haploid, and recombinant inbred populations in rice (Oryza sativa L.). Molecular and General Genetics 253, 535-545.
226. Yang J, Jiang H, Yeh CT, Yu J, Jeddeloh JA, Nettleton D, Schnable PS. 2015. Extreme-phenotype genome-wide association study (XP-GWAS): A method for identifying trait-associated variants by sequencing pools of individuals selected from a diversity panel. The Plant Journal 84, 587-596.
227. Yang S, Fresnedo-Ramírez J, Wang M, et al. 2016. A next-generation marker genotyping platform (AmpSeq) in heterozygous crops: A case study for marker-assisted selection in grapevine. Horticulture Research 3, 16002.
228. Yin Y, König S. 2016. Genomics for phenotype prediction and management purposes. Animal Frontiers 6, 65-72.
229. Yu X, Li X, Guo T, et al. 2016. Genomic prediction contributing to a promising global strategy to turbocharge gene banks. Nature Plants 2, 16150.
230. Zeng D, Tian Z, Rao Y, et al. 2017. Rational design of high-yield and superior-quality rice. Nature Plants 3, 17031.
231. Zetsche B, Gootenberg JS, Abudayyeh OO, et al. 2015. Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell 163, 759-771.
232. Zhang H, Zhang J, Wei P, et al. 2014. The CRISPR/Cas9 system produces specific and homozygous targeted gene editing in rice in one generation. Plant Biotechnology Journal 12, 797-807.
233. Zhang X, Pérez-Rodríguez P, Semagn K, et al. 2015. Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs. Heredity 114, 291-299.
234. Zhang J, Song Q, Cregan PB, Jiang GL. 2016. Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max). Theoretical and Applied Genetics 129, 117-130.
235. Zhang Y, Liang Z, Zong Y, Wang Y, Liu J, Chen K, Qiu JL, Gao C. 2016. Efficient and transgene-free genome editing in wheat through transient expression of CRISPR/Cas9 DNA or RNA. Nature Communications 7, 12617.
236. Zhao Y, Zhang C, Liu W, et al. 2016. An alternative strategy for targeted gene replacement in plants using a dual-sgRNA/Cas9 design. Scientific Reports 6, 23890.
237. Zhou H, Liu B, Weeks DP, Spalding MH, Yang B. 2014. Large chromosomal deletions and heritable small genetic changes induced by CRISPR/Cas9 in rice. Nucleic Acids Research 42, 10903-10914.
238. Zhu XG, Long SP, Ort DR. 2010. Improving photosynthetic efficiency for greater yield. Annual Review of Plant Biology 61, 235-261.
239. Zivy M, Devaux P, Blaisonneau J, Jean R, Thiellement H. 1992. Segregation distortion and linkage studies in microspore-derived double haploid lines of Hordeum vulgare L. Theoretical and Applied Genetics 83, 919-924.
240. Zou C, Wang P, Xu Y. 2016. Bulked sample analysis in genetics, genomics and crop improvement. Plant Biotechnology Journal 14, 1941-1955.
241. Zuo W, Chao Q, Zhang N, et al. 2015. A maize wall-associated kinase confers quantitative resistance to head smut. Nature Genetics 47, 151-157.