Crop genomics: advances and applications

Key Points

  • Reference genome sequences from many important crops and several model plant species are enabling a number of new applications of crop comparative genomics.

  • Compared with previous methods, comparative resequencing and high-density SNP genotyping permit much more detailed examination of crop evolutionary history and improve the potential to identify loci that are involved in plant domestication and improvement.

  • Genome-wide association studies and a new generation of genetic-mapping populations will improve assessment of the genetic basis of trait variation.

  • Deleterious mutations in individual genomes can be identified and selected against or even repaired.

  • Genomic selection or genome-wide marker-assisted selection can incorporate prior information on the effects of markers and accelerate plant breeding cycles.

Abstract

The completion of reference genome sequences for many important crops and the ability to perform high-throughput resequencing are providing opportunities for improving our understanding of the history of plant domestication and to accelerate crop improvement. Crop plant comparative genomics is being transformed by these data and a new generation of experimental and computational approaches. The future of crop improvement will be centred on comparisons of individual plant genomes, and some of the best opportunities may lie in using combinations of new genetic mapping strategies and evolutionary analyses to direct and optimize the discovery and use of genetic variation. Here we review such strategies and insights that are emerging.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Crop genome size.
Figure 2: Challenges of read mapping in plant genomes.
Figure 3: Mapping populations.

References

  1. 1

    Paterson, A. H., Freeling, M. & Sasaki, T. Grains of knowledge: genomics of model cereals. Genome Res. 15, 1643–1650 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2

    Brown, A. H. D. Enzyme polymorphism in plant populations. Theor. Popul. Biol. 15, 1–42 (1979).

    Google Scholar 

  3. 3

    Bowers, J. E. et al. A high-density genetic recombination map of sequence-tagged sites for Sorghum, as a framework for comparative structural and evolutionary genomics of tropical grains and grasses. Genetics 165, 367–386 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    Lewontin, R. C. & Krakauer, J. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74, 175–195 (1973).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5

    Nei, M. & Maruyama, T. Lewontin–Krakauer test for neutral genes — comment. Genetics 80, 395–395 (1975).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Schulte, D. et al. The International Barley Sequencing Consortium—at the threshold of efficient access to the barley genome. Plant Physiol. 149, 142–147 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Kaul, S. et al. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408, 796–815 (2000).

    CAS  Google Scholar 

  8. 8

    Initiative, T. I. B. Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature 463, 763–768 (2010).

    Google Scholar 

  9. 9

    Pool, J. E., Hellmann, I., Jensen, J. D. & Nielsen, R. Population genetic inference from genomic sequence variation. Genome Res. 20, 291–300 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10

    Metzker, M. L. Sequencing technologies — the next generation. Nature Rev. Genet. 11, 31–46 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Lockton, S. & Gaut, B. S. Plant conserved non-coding sequences and paralogue evolution. Trends Genet. 21, 60–65 (2005).

    CAS  PubMed  Google Scholar 

  12. 12

    Haun, W. J. et al. The composition and origins of genomic variation among individuals of the soybean reference cultivar Williams 82. Plant Physiol. 155, 645–655 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Velasco, R. et al. A high quality draft consensus sequence of the genome of a heterozygous grapevine variety. PLoS ONE 2, e1326 (2007).

    PubMed  PubMed Central  Google Scholar 

  14. 14

    Gore, M. A. et al. A first-generation haplotype map of maize. Science 326, 1115–1117 (2009).

    CAS  PubMed  Google Scholar 

  15. 15

    Young, N. D. et al. The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 16 Nov 2011(doi:1001038/nature10625).

  16. 16

    Shulaev, V. et al. The genome of woodland strawberry (Fragaria vesca). Nature Genet. 43, 109–116 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Xu, X. et al. Genome sequence and analysis of the tuber crop potato. Nature 475, 189–195 (2011). This is an excellent example of both the challenges and promise of comparative genomics in crop plant genomes. To overcome polyploidy and high levels of heterozygosity, the authors use a combination of traditional Sanger and next-generation methods to sequence and annotate the genome of a doubled-monoploid potato line.

    CAS  PubMed  Google Scholar 

  18. 18

    Rafalski, A. & Morgante, M. Corn and humans: recombination and linkage disequilibrium in two genomes of similar size. Trends Genet. 20, 103–111 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Lijavetzky, D., Cabezas, J. A., Ibanez, A., Rodriguez, V. & Martinez-Zapater, J. M. High throughput SNP discovery and genotyping in grapevine (Vitis vinifera L.) by combining a re-sequencing approach and SNPlex technology. BMC Genomics 8, 424 (2007).

    PubMed  PubMed Central  Google Scholar 

  20. 20

    Caldwell, K. S., Russell, J., Langridge, P. & Powell, W. Extreme population-dependent linkage disequilibrium detected in an inbreeding plant species, Hordeum vulgare. Genetics 172, 557–567 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Gaut, B. S. & Ross-Ibarra, J. Selection on major components of angiosperm genomes. Science 320, 484–486 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22

    Tenaillon, M. I., Hollister, J. D. & Gaut, B. S. A triptych of the evolution of plant transposable elements. Trends Plant Sci. 15, 471–478 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23

    Nordborg, M. & Weigel, D. Next-generation genetics in plants. Nature 456, 720–723 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Jaillon, O. et al. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature 449, 463–467 (2007).

    CAS  PubMed  Google Scholar 

  25. 25

    Ross-Ibarra, J., Morrell, P. L. & Gaut, B. S. Colloquium papers: plant domestication, a unique opportunity to identify the genetic basis of adaptation. Proc. Natl Acad. Sci. USA 104 (Suppl. 1), 8641–8648 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26

    Brown, A. H. D. Variation under domestication in plants: 1859 and today. Phil. Trans. R. Soc. B 365, 2523–2530 (2010).

    PubMed  PubMed Central  Google Scholar 

  27. 27

    Harris, D. R. Vavilov's concept of centres of origin of cultivated plants: its genesis and its influence on the study of agricultural origins. Biol. J. Linn. Soc. 39, 7–16 (1990).

    Google Scholar 

  28. 28

    Rosenberg, N. A. & Nordborg, M. Genealogical trees, coalescent theory and the analysis of genetic polymorphisms. Nature Rev. Genet. 3, 380–390 (2002). This is a very accessible introduction to genealogical histories and coalescent theory that are pertinent to interpretation of sequence polymorphism data.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Gaut, B. S. & Clegg, M. T. Molecular evolution of the Adh1 locus in the genus Zea. Proc. Natl Acad. Sci. USA 90, 5095–5099 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Kim, M. Y. et al. Whole-genome sequencing and intensive analysis of the undomesticated soybean (Glycine soja Sieb. and Zucc.) genome. Proc. Natl Acad. Sci. USA 107, 22032–22037 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Eyre-Walker, A., Gaut, R. L., Hilton, H., Feldman, D. L. & Gaut, B. S. Investigation of the bottleneck leading to the domestication of maize. Proc. Natl Acad. Sci. USA 95, 4441–4446 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Haudry, A. et al. Grinding up wheat: a massive loss of nucleotide diversity since domestication. Mol. Biol. Evol. 24, 1506–1517 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33

    Wright, S. I. et al. The effects of artificial selection on the maize genome. Science 308, 1310–1314 (2005). This paper discusses a comparative resequencing study that used an original likelihood ratio test to model demography and selection. The paper was unique in providing an estimate of the proportion of loci in the genome involved in domestication and/or improvement.

    CAS  Google Scholar 

  34. 34

    Caicedo, A. L. et al. Genome-wide patterns of nucleotide polymorphism in domesticated rice. PLoS Genet. 3, 1745–1756 (2007).

    CAS  PubMed  Google Scholar 

  35. 35

    Molina, J. et al. Molecular evidence for a single evolutionary origin of domesticated rice. Proc. Natl Acad. Sci. USA 108, 8351–8356 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36

    Matsuoka, Y. et al. A single domestication for maize shown by multilocus microsatellite genotyping. Proc. Natl Acad. Sci. USA 99, 6080–6084 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Li, Y. H. et al. Genetic diversity in domesticated soybean (Glycine max) and its wild progenitor (Glycine soja) for simple sequence repeat and single-nucleotide polymorphism loci. New Phytol. 188, 242–253 (2010).

    CAS  PubMed  Google Scholar 

  38. 38

    Chen, H., Morrell, P. L., Ashworth, V. E., de la Cruz, M. & Clegg, M. T. Tracing the geographic origins of major avocado cultivars. J. Hered. 100, 56–65 (2009).

    PubMed  PubMed Central  Google Scholar 

  39. 39

    Gepts, P. & Bliss, F. A. Phaseolin variability among wild and cultivated common beans (Phaseolus vulgaris) from Colombia. Econ. Bot. 40, 469–478 (1986).

    CAS  Google Scholar 

  40. 40

    Morrell, P. L. & Clegg, M. T. Genetic evidence for a second domestication of barley (Hordeum vulgare) east of the Fertile Crescent. Proc. Natl Acad. Sci. USA 104, 3289–3294 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Allaby, R. G., Fuller, D. Q. & Brown, T. A. The genetic expectations of a protracted model for the origins of domesticated crops. Proc. Natl Acad. Sci. USA 105, 13982–13986 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42

    Ross-Ibarra, J. & Gaut, B. S. Multiple domestications do not appear monophyletic. Proc. Natl Acad. Sci. USA 105, E105; author reply E106 (2008).

    PubMed  PubMed Central  Google Scholar 

  43. 43

    Kwak, M. & Gepts, P. Structure of genetic diversity in the two major gene pools of common bean (Phaseolus vulgaris L., Fabaceae). Theor. Appl. Genet. 118, 979–992 (2009).

    CAS  PubMed  Google Scholar 

  44. 44

    Myles, S. et al. Genetic structure and domestication history of the grape. Proc. Natl Acad. Sci. USA 108, 3530–3535 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    van Heerwaarden, J. et al. Genetic signals of origin, spread, and introgression in a large sample of maize landraces. Proc. Natl Acad. Sci. USA 108, 1088–1092 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    He, Z. et al. Two evolutionary histories in the genome of rice: the roles of domestication genes. PLoS Genet. 7, e1002100 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    Price, A. L. et al. Sensitive detection of chromosomal segments of distinct ancestry in admixed populations. PLoS Genet. 5, e1000519 (2009).

    PubMed  PubMed Central  Google Scholar 

  48. 48

    Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Darwin, C. The Variation of Animals and Plants under Domestication (Appleton, New York, 1876).

    Google Scholar 

  50. 50

    Hammer, K. Das Domestikationssyndrom. Kulturpflanze 32, 11–34 (1984).

    Google Scholar 

  51. 51

    Burger, J. C., Chapman, M. A. & Burke, J. M. Molecular insights into the evolution of crop plants. Am. J. Bot. 95, 113–122 (2008).

    PubMed  PubMed Central  Google Scholar 

  52. 52

    Vigouroux, Y. et al. Identifying genes of agronomic importance in maize by screening microsatellites for evidence of selection during domestication. Proc. Natl Acad. Sci. USA 99, 9650–9655 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Chapman, M. A. et al. A genomic scan for selection reveals candidates for genes involved in the evolution of cultivated sunflower (Helianthus annuus). Plant Cell 20, 2931–2945 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Lam, H. M. et al. Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nature Genet. 42, 1053–1059 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Hurwitz, B. L. et al. Rice structural variation: a comparative analysis of structural variation between rice and three of its closest relatives in the genus Oryza. Plant J. 63, 990–1003 (2010).

    CAS  Google Scholar 

  56. 56

    Swanson-Wagner, R. A. et al. Pervasive gene content variation and copy number variation in maize and its undomesticated progenitor. Genome Res. 20, 1689–1699 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Buckler, E. S. et al. The genetic architecture of maize flowering time. Science 325, 714–718 (2009). This study, using the NAM population, found that flowering time in maize provides a good fit to classic models of a quantitative trait and that a large number of loci contribute additively to the phenotype.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    Vielle-Calzada, J. P. et al. The Palomero genome suggests metal effects on domestication. Science 326, 1078–1078 (2009).

    CAS  Google Scholar 

  59. 59

    Sugimoto, K. et al. Molecular cloning of Sdr4, a regulator involved in seed dormancy and domestication of rice. Proc. Natl Acad. Sci. 107, 5792–5797 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Takahashi, R. The origin and evolution of cultivated barley. Adv. Genet. 7, 227–266 (1955).

    Google Scholar 

  61. 61

    Morrell, P. L. & Clegg, M. T. in Wild Crop Relatives: Genomic and Breeding Resources: Cereals (ed. Kole, C.) 309–320 (Springer, Berlin, 2011).

    Google Scholar 

  62. 62

    Jones, H. et al. Population-based resequencing reveals that the flowering time adaptation of cultivated barley originated east of the Fertile Crescent. Mol. Biol. Evol. 25, 2211–2219 (2008).

    CAS  PubMed  Google Scholar 

  63. 63

    Bellon, M. R., Hodson, D. & Hellin, J. Assessing the vulnerability of traditional maize seed systems in Mexico to climate change. Proc. Natl Acad. Sci. USA 108, 13432–13437 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64

    Komatsuda, T. et al. Six-rowed barley originated from a mutation in a homeodomain-leucine zipper I-class homeobox gene. Proc. Natl Acad. Sci. USA 104, 1424–1429 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Purugganan, M. D., Boyles, A. L. & Suddith, J. I. Variation and selection at the CAULIFLOWER floral homeotic gene accompanying the evolution of domesticated Brassica oleracea. Genetics 155, 855–862 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Teshima, K. M., Coop, G. & Przeworski, M. How reliable are empirical genomic scans for selective sweeps? Genome Res. 16, 702–712 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Ralph, P. & Coop, G. Parallel adaptation: one or many waves of advance of an advantageous allele? Genetics 186, 647–668 (2010).

    PubMed  PubMed Central  Google Scholar 

  68. 68

    Paterson, A. H. et al. Convergent domestication of cereal crops by independent mutations at corresponding genetic loci. Science 269, 1714–1718 (1995).

    CAS  Google Scholar 

  69. 69

    Goff, S. A. A unifying theory for general multigenic heterosis: energy efficiency, protein metabolism, and implications for molecular breeding. New Phytol. 189, 923–937 (2011).

    CAS  Google Scholar 

  70. 70

    Mauricio, R. Mapping quantitative trait loci in plants: uses and caveats for evolutionary biology. Nature Rev. Genet. 2, 370–381 (2001).

    CAS  PubMed  Google Scholar 

  71. 71

    Risch, N. & Merikangas, K. The future of genetic studies of complex human diseases. Science 273, 1516–1517 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Myles, S. et al. Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21, 2194–2202 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Mackay, T. F., Stone, E. A. & Ayroles, J. F. The genetics of quantitative traits: challenges and prospects. Nature Rev. Genet. 10, 565–577 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Wurschum, T. et al. Genome-wide association mapping of agronomic traits in sugar beet. Theor. Appl. Genet. 123, 1121–1131 (2011).

    PubMed  PubMed Central  Google Scholar 

  75. 75

    Saidou, A. A. et al. Association studies identify natural variation at PHYC linked to flowering time and morphological variation in pearl millet. Genetics 182, 899–910 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. 76

    Huang, X. et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genet. 42, 961–967 (2010).

    CAS  Google Scholar 

  77. 77

    Atwell, S. et al. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465, 627–631 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. 78

    Hamblin, M. T., Buckler, E. S. & Jannink, J. L. Population genetics of genomics-based crop improvement methods. Trends Genet. 27, 98–106 (2011).

    CAS  PubMed  Google Scholar 

  79. 79

    Rockman, M. V. & Kruglyak, L. Breeding designs for recombinant inbred advanced intercross lines. Genetics 179, 1069–1078 (2008). This study provides an examination of breeding designs that maximize genetic resolution in intercross populations.

    PubMed  PubMed Central  Google Scholar 

  80. 80

    Macdonald, S. J. & Long, A. D. Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster. Genetics 176, 1261–1281 (2007). The authors of this paper provide a strong rationale for the development of next-generation populations. The study design permits estimation of QTL location, effect and frequency. Comparison of effect size of alleles contributed by founders of the population is particularly compelling.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. 81

    Yu, J. M., Holland, J. B., McMullen, M. D. & Buckler, E. S. Genetic design and statistical power of nested association mapping in maize. Genetics 178, 539–551 (2008).

    PubMed  PubMed Central  Google Scholar 

  82. 82

    Brown, P. J. et al. Distinct genetic architectures for male and female inflorescence traits of maize. PLoS Genet. 7, e1002383 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. 83

    Kump, K. L. et al. Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nature Genet. 43, 163–168 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84

    Tian, F. et al. Genome-wide association study of leaf architecture in the maize nested association mapping population. Nature Genet. 43, 159–162 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85

    Cavanagh, C., Morell, M., Mackay, I. & Powell, W. From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants. Curr. Opin. Plant Biol. 11, 215–221 (2008).

    PubMed  Google Scholar 

  86. 86

    Kover, P. X. et al. A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet. 5, e1000551 (2009).

    PubMed  PubMed Central  Google Scholar 

  87. 87

    Harlan, H. V. & Martini, M. L. A composite hybrid mixture. J. Am. Soc. Agron. 487–490 (1929).

  88. 88

    Suneson, C. A. An evolutionary plant breeding method. Agron. J. 48, 188–191 (1956).

    Google Scholar 

  89. 89

    Allard, R. W., Kahler, A. L. & Weir, B. S. The effect of selection on esterase allozymes in a barley population. Genetics 72, 489–503 (1972).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Clegg, M. T., Allard, R. W. & Kahler, A. L. Is the gene the unit of selection? Evidence from two experimental plant populations. Proc. Natl Acad. Sci. USA 69, 2474–2478 (1972).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. 91

    Cargill, M. et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genet. 22, 231–238 (1999).

    CAS  PubMed  Google Scholar 

  92. 92

    Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93

    Johnson, T. & Barton, N. Theoretical models of selection and mutation on quantitative traits. Phil. Trans. R. Soc. Lond. B 360, 1411–1425 (2005).

    CAS  Google Scholar 

  94. 94

    Clark, A. G., Hubisz, M. J., Bustamante, C. D., Williamson, S. H. & Nielsen, R. Ascertainment bias in studies of human genome-wide polymorphism. Genome Res. 15, 1496–1502 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95

    Altshuler, D. L. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

    PubMed  PubMed Central  Google Scholar 

  96. 96

    Weigel, D. & Mott, R. The 1001 Genomes Project for Arabidopsis thaliana. Genome Biol. 10, 107 (2009).

    PubMed  PubMed Central  Google Scholar 

  97. 97

    Dickson, S. P., Wang, K., Krantz, I., Hakonarson, H. & Goldstein, D. B. Rare variants create synthetic genome-wide associations. PLoS Biol. 8, e1000294 (2010).

    PubMed  PubMed Central  Google Scholar 

  98. 98

    Hill, W. G. & Robertson, A. The effect of linkage on limits to artificial selection. Genet. Res. 8, 269–294 (1966).

    CAS  PubMed  Google Scholar 

  99. 99

    Huff, C. D. et al. Crohn's disease and genetic hitchhiking at IBD5. Mol. Biol. Evol. 4 Aug 2011 (doi:10.1093/molbev/msr151).

    PubMed  PubMed Central  Google Scholar 

  100. 100

    Clegg, M. T. Measuring plant mating systems. Bioscience 30, 814–818 (1980).

    Google Scholar 

  101. 101

    Nielsen, R. Molecular signatures of natural selection. Annu. Rev. Genet. 39, 197–218 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  102. 102

    Nielsen, R., Hellmann, I., Hubisz, M., Bustamante, C. & Clark, A. G. Recent and ongoing selection in the human genome. Nature Rev. Genet. 8, 857–868 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. 103

    Walsh, B. Using molecular markers for detecting domestication, improvement, and adaptation genes. Euphytica 161, 1–17 (2008).

    CAS  Google Scholar 

  104. 104

    Asano, K. et al. Artificial selection for a green revolution gene during japonica rice domestication. Proc. Natl Acad. Sci. USA 108, 11034–11039 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. 105

    Spielmeyer, W., Ellis, M. H. & Chandler, P. M. Semidwarf (sd-1), “green revolution” rice, contains a defective gibberellin 20-oxidase gene. Proc. Natl Acad. Sci. USA 99, 9043–9048 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. 106

    Fan, L. et al. Post-domestication selection in the maize starch pathway. PLoS ONE 4, e7612 (2009).

    PubMed  PubMed Central  Google Scholar 

  107. 107

    Stumpf, M. P. & McVean, G. A. Estimating recombination rates from population-genetic data. Nature Rev. Genet. 4, 959–968 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. 108

    Paterson, A. H. et al. The Sorghum bicolour genome and the diversification of grasses. Nature 457, 551–556 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. 109

    McMullen, M. D. et al. Genetic properties of the maize nested association mapping population. Science 325, 737–740 (2009).

    CAS  PubMed  Google Scholar 

  110. 110

    Schon, C. C., Dhillon, B. S., Utz, H. F. & Melchinger, A. E. High congruency of QTL positions for heterosis of grain yield in three crosses of maize. Theor. Appl. Genet. 120, 321–332 (2010).

    PubMed  PubMed Central  Google Scholar 

  111. 111

    Allard, R. W. History of plant population genetics. Annu. Rev. Genet. 33, 1–27 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. 112

    Nordborg, M. Linkage disequilibrium, gene trees and selfing: an ancestral recombination graph with partial self-fertilization. Genetics 154, 923–929 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. 113

    Morrell, P. L., Toleno, D. M., Lundy, K. E. & Clegg, M. T. Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp. spontaneum) despite high rates of self-fertilization. Proc. Natl Acad. Sci. USA 102, 2442–2447 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  114. 114

    Morrell, P. L., Toleno, D. M., Lundy, K. E. & Clegg, M. T. Estimating the contribution of mutation, recombination and gene conversion in the generation of haplotypic diversity. Genetics 173, 1705–1723 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  115. 115

    Charlesworth, D. Effects of inbreeding on the genetic diversity of populations. Phil. Trans. R. Soc. Lond. B 358, 1051–1070 (2003).

    CAS  Google Scholar 

  116. 116

    Zhao, K. Y. et al. An Arabidopsis example of association mapping in structured samples. PLoS Genet. 3, e4 (2007).

    PubMed  PubMed Central  Google Scholar 

  117. 117

    Turner, A., Beales, J., Faure, S., Dunford, R. P. & Laurie, D. A. The pseudo-response regulator Ppd-H1 provides adaptation to photoperiod in barley. Science 310, 1031–1034 (2005).

    CAS  Google Scholar 

  118. 118

    Yano, M. et al. Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map. Theor. Appl. Genet. 95, 1025–1032 (1997).

    CAS  Google Scholar 

  119. 119

    Lin, Y. R., Schertz, K. F. & Paterson, A. H. Comparative analysis of QTLs affecting plant height and maturity across the Poaceae, in reference to an interspecific Sorghum population. Genetics 141, 391–411 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. 120

    Gan, X. et al. Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature 477, 419–423 (2011). De novo sequencing and annotation along with trascriptome sequencing of 18 reference genomes from the founders of a next-generation population are discussed in this paper. Re-annotation of individual genes suggests that many genes that appear to have lost function in simple comparisons with the original A. thaliana reference genome contain compensatory mutations that restore function at the locus.

    CAS  PubMed  PubMed Central  Google Scholar 

  121. 121

    Muller, H. J. Our load of mutations. Am. J. Hum. Genet. 2, 111–176 (1950).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. 122

    Ng, S. B. et al. Exome sequencing identifies the cause of a Mendelian disorder. Nature Genet. 42, 30–35 (2010).

    CAS  Google Scholar 

  123. 123

    Gossmann, T. I. et al. Genome wide analyses reveal little evidence for adaptive evolution in many plant species. Mol. Biol. Evol. 27, 1822–1832 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. 124

    Lai, J. S. et al. Genome-wide patterns of genetic variation among elite maize inbred lines. Nature Genet. 42, 1027–1030 (2010).

    CAS  Google Scholar 

  125. 125

    Gunther, T. & Schmid, K. J. Deleterious amino acid polymorphisms in Arabidopsis thaliana and rice. Theor. Appl. Genet. 121, 157–168 (2010).

    PubMed  PubMed Central  Google Scholar 

  126. 126

    Lu, J. et al. The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication. Trends Genet. 22, 126–131 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  127. 127

    Tang, H. B., Sezen, U. & Paterson, A. H. Domestication and plant genomes. Curr. Opin. Plant Biol. 13, 160–166 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  128. 128

    Chun, S. & Fay, J. C. Evidence for hitchhiking of deleterious mutations within the human genome. PLoS Genet. 7, e1002240 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. 129

    Lande, R. & Schemske, D. W. The evolution of self-fertilization and inbreeding depression in plants. I. Genetic models. Evolution 39, 24–40 (1985).

    PubMed  PubMed Central  Google Scholar 

  130. 130

    Charlesworth, D. & Willis, J. H. The genetics of inbreeding depression. Nature Rev. Genet. 10, 783–796 (2009).

    CAS  Google Scholar 

  131. 131

    Felsenstein, J. The evolutionary advantage of recombination. Genetics 78, 737–756 (1974).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. 132

    Lynch, M., Conery, J. & Burger, R. Mutational meltdowns in sexual populations. Evolution 49, 1067–1080 (1995).

    PubMed  Google Scholar 

  133. 133

    Meuwissen, T. H., Hayes, B. J. & Goddard, M. E. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  134. 134

    Heffner, E. L., Sorrells, M. E. & Jannink, J. L. Genomic selection for crop improvement. Crop Sci. 49, 1–12 (2009).

    CAS  Google Scholar 

  135. 135

    Andolfatto, P. et al. Multiplexed shotgun genotyping for rapid and efficient genetic mapping. Genome Res. 21, 610–617 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  136. 136

    Elshire, R. J. et al. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6, e19379 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. 137

    Heffner, E. L., Jannink, J.-L. & Sorrells, M. E. Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Gen. 4, 65–75 (2011).

    Google Scholar 

  138. 138

    Salome, P. A. et al. Genetic architecture of flowering-time variation in Arabidopsis thaliana. Genetics 188, 421–433 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  139. 139

    Troyer, A. F. Adaptedness and heterosis in corn and mule hybrids. Crop Sci. 46, 528–543 (2006).

    Google Scholar 

  140. 140

    Duvick, D. N. The contribution of breeding to yield advances in maize (Zea mays L.). Adv. Agron. 86, 83–145 (2005).

    Google Scholar 

  141. 141

    Bernardo, R. Molecular markers and selection for complex traits in plants: Learning from the last 20 years. Crop Sci. 48, 1649–1664 (2008).

    Google Scholar 

  142. 142

    Weinthal, D., Tovkach, A., Zeevi, V. & Tzfira, T. Genome editing in plant cells by zinc finger nucleases. Trends Plant Sci. 15, 308–321 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  143. 143

    Bogdanove, A. J. & Voytas, D. F. TAL effectors: customizable proteins for DNA targeting. Science 333, 1843–1846 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  144. 144

    Shukla, V. K. et al. Precise genome modification in the crop species Zea mays using zinc-finger nucleases. Nature 459, 437–441 (2009). This paper is an impressive demonstration of the potential power of targeted genomic editing. The authors use a custom zinc finger nuclease to modify two traits in maize and show that the method is sufficiently precise to target only one of the two paralogues of the enzyme of interest.

    CAS  PubMed  PubMed Central  Google Scholar 

  145. 145

    Morbitzer, R., Romer, P., Boch, J. & Lahaye, T. Regulation of selected genome loci using de novo-engineered transcription activator-like effector (TALE)-type transcription factors. Proc. Natl Acad. Sci. USA 107, 21617–21622 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  146. 146

    Century, K., Reuber, T. L. & Ratcliffe, O. J. Regulating the regulators: the future prospects for transcription-factor-based agricultural biotechnology products. Plant Physiol. 147, 20–29 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  147. 147

    Presgraves, D. C. The molecular evolutionary basis of species formation. Nature Rev. Genet. 11, 175–180 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  148. 148

    Gepts, P. A comparison between crop domestication, classical plant breeding, and genetic engineering. Crop Sci. 42, 1780–1790 (2002).

    Google Scholar 

  149. 149

    Ming, R. et al. The draft genome of the transgenic tropical fruit tree papaya (Carica papaya Linnaeus). Nature 452, 991–996 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. 150

    Argout, X. et al. The genome of Theobroma cacao. Nature Genet. 43, 101–108 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. 151

    Goff, S. A. et al. A draft sequence of the rice genome (Oryza sativa L. ssp. japonica). Science 296, 92–100 (2002).

    CAS  Google Scholar 

  152. 152

    Varshney, R. K. et al. Draft genome sequence of pigeonpea (Cajanus cajan), an orphan legume crop of resource-poor farmers. Nature Biotech. 6 Nov 2011 (doi:10.1038/nbt.2022).

    PubMed  PubMed Central  Google Scholar 

  153. 153

    Schmutz, J. et al. Genome sequence of the palaeopolyploid soybean. Nature 463, 178–183 (2010).

    CAS  PubMed  Google Scholar 

  154. 154

    Schnable, P. S. et al. The B73 maize genome: complexity, diversity, and dynamics. Science 326, 1112–1115 (2009).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the US Department of Agriculture (USDA)–US National Institute for Food and Agriculture (NIFA) (2011-68002-30029) for partial support for P.L.M., USDA–NIFA (2009-01864) for J.R.-I. and the USDA Agriculture Research Service and the National Science Foundation (NSF)–Plant Genome Research (0820691) and NSF–Division of Biological Infrastructure (0965342) for support to E.S.B. The authors are grateful to J. Gerke, A. Gonzales, M. Hufford, D. Segal, R. Stupar and three anonymous referees for comments on the manuscript.

Author information

Affiliations

Authors

Corresponding authors

Correspondence to Peter L. Morrell or Jeffrey Ross-Ibarra.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Peter L. Morrell's homepage

Edward S. Buckler's homepage

Jeffrey Ross-Ibarra's homepage

1000 Genomes Project (in humans)

1001 Genomes Project (in A. thaliana)

Drosophila Genetic Reference Panel

Gramene

International Barley Sequencing Consortium

International Tomato Genome Sequencing Project

International Wheat Genome Sequencing Consortium

Phytozome

US Department of Agriculture (USDA) National Agricultural Statistics Service

Glossary

Genome-wide association studies

(GWASs). Studies that search for a statistical association between a phenotype and a particular allele by screening loci (most commonly by genotyping SNPs) across the entire genome.

Paralogy

Unlike orthologous genes, which trace their common origin to a locus in an ancestral species, paralogous loci consist of gene copies that trace their common origin to a duplication event within a genome.

Linkage disequilibrium

(LD). Nonrandom association of alleles at two or more loci. The pattern and extent of LD in a genomic region is affected by mutation, recombination, genetic drift, natural selection and demographic history.

Bottleneck

A temporary marked reduction in population size.

Site frequency spectrum

The distribution of allele frequencies in a population: essentially a count of the number of alleles in a population at a given frequency.

Genetic drift

Fluctuations in allele frequencies that are due to the effects of random sampling.

Admixture

The mixing of two or more genetically differentiated populations.

Introgression

The incorporation of genetic material from one population or species into another by hybridization and backcrossing.

Haplotype

The combination of alleles or genetic markers found on a single chromosome of an individual.

Selective sweeps

Increases in frequency of an allele and closely linked chromosomal segments that are due to positive selection. Sweeps initially reduce variation and subsequently lead to a local excess of rare alleles as new unique mutations accumulate.

Standing variation

Variation for a locus or trait that is polymorphic in a population.

Heterosis

Otherwise known as 'hybrid vigour', heterosis is the phenomenon whereby progeny of a cross between genetically distinct parents have greater fitness than either of the parental types.

Purifying selection

Selection against a deleterious allele.

Ascertainment bias

Sampling bias that arises from how SNPs are chosen for inclusion on SNP arrays; SNPs that are known to be polymorphic in a particular population will have frequencies that are higher than would be expected by random sampling alone.

Hill–Robertson effect

The reduction in efficacy of selection at a locus owing to selection at linked loci.

Dobzhansky–Muller effects

Intrinsic reductions in viability or fertility resulting from epistatic interactions between multiple substitutions, typically observed in the offspring of a cross between individuals from genetically distinct populations.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Morrell, P., Buckler, E. & Ross-Ibarra, J. Crop genomics: advances and applications. Nat Rev Genet 13, 85–96 (2012). https://doi.org/10.1038/nrg3097

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing