Downloads

1. Darwin, C. R. The effects of cross- and self-fertilization in the vegetable kingdom. (London: John Murray, 1876). 2. Comings, D. E. & MacMurray, J. P. Molecular heterosis: a review. Mol. Genet. Metab. 71, 19–31 (2000). 3. Chen, Z. J. Genomic and epigenetic insights into the molecular bases of heterosis. Nat. Rev. Genet. 14, 471–482 (2013). 4. Shull, G. H. The composition of a field of maize. J. Hered. 4, 296–301 (1908). 5. Virmani, S. S. Prospects of hybrid rice in tropics and sub-tropics in Hybrid rice technology: new developments and future prospects (ed. Virmani, S. S.) 7–20 (International Rice Research Institute Philippines, 1994). 6. Budak, H., Cesurer, L., Bölek, Y., Dokuyucu, T. & Akkaya, A. Understanding of heterosis. KSU J. Science and Engineering 5, 68–75 (2002). 7. Duvick, D. N. Heterosis: feeding people and protecting natural resources in The genetics and exploitation of heterosis in crops (ed. Coors, J. G. & Pandey, S.) 19–29 (Madison, 1999). 8. Sanghera, G. S. et al. The magic of heterosis: new tools and complexities. Nat. Sci. 9, 42–53 (2011). 9. Goff, A. S. & Zhang, Q. F. Heterosis in elite hybrid rice: speculation on the genetic and biochemical mechanisms. Curr. Opin. Plant Biol. 16, 221–227 (2013). 10. Davenport, C. B. Degeneration, albinism and inbreeding. Science 28, 454–455 (1908). 11. Bruce, A. B. The Mendelian theory of heredity and the augmentation of vigor. Science 32, 627–628 (1910). 12. Jones, D. F. Dominance of linked factors as a means of accounting for heterosis. Genetics 2, 466–479 (1917). 13. East, E. M. Heterosis. Genetics 21, 375–397 (1936). 14. Powers, L. An expansion of Jones’s theory for the explanation of heterosis. Am. Nat. 78, 275–280 (1944). 15. Williams, W. Heterosis and the genetics of complex characters. Nature 184, 527–530 (1959). 16. Xiao, J., Li, J., Yuan, L. & Tanksley, S. D. Dominance is the major genetic basis of heterosis in rice as revealed by QTL analysis using molecular markers. Genetics 140, 745–754 (1995). 17. Radoev, M., Becker, H. C. & Ecke, W. Genetic analysis of heterosis for yield and yield components in rapeseed (Brassica napus L.) by quantitative trait locus mapping. Genetics 179, 1547–1558 (2008). 18. Stuber, C. W., Lincoln, S. E., Wolff, D. W., Helentjaris, T. & Lander, E. S. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics 132, 823–839 (1992). 19. Li, Z. K. et al. Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice I. biomass and grain yield. Genetics 158, 1737–1753 (2001). 20. Luo, L. J. et al. Overdominant epistatic loci are the primary genetic basis of Inbreeding depression and heterosis in rice. II. Grain yield components. Genetics 158, 1755–1771 (2001). 21. Lu, H., Romero-Severson, J. & Bernardo, R. Genetic basis of heterosis explored by simple sequence repeat markers in a random-mated maize population. Theor. Appl. Genet. 107, 494–502 (2003). 22. Yu, S. B. et al. Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid. Proc. Natl. Acad. Sci. USA 94, 9226–9231 (1997). 23. Hua, J. P. et al. Single-locus heterotic effects and dominance-by-dominance interactions can adequately explain the genetic basis of heterosis in an elite rice hybrid. Proc. Natl. Acad. Sci. USA 100, 2574–2579 (2003). 24. Zhou, G. et al. Genetic composition of yield heterosis in an elite rice hybrid. Proc. Natl. Acad. Sci. USA 109, 15847–15852 (2012). 25. Hua, J. P. et al. Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance. Genetics 162, 1885–1895 (2002). 26. Yuan, Q. Q., Deng, Z. Y., Peng, T. & Tian, J. C. QTL-based analysis of heterosis for number of grains per spike in wheat using DH and immortalized F2 populations. Euphytica 188, 387–395 (2012). 27. Kusterer, B. et al. Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines. Genetics 177, 1839–1850 (2007). 28. Melchinger, A. E. et al. Genetic basis of heterosis for growth related traits in Arabidopsis investigated by testcross progenies of nearisogenic lines reveals a significant role of epistasis. Genetics 177, 1827–1837 (2007). 29. Garcia, A. A. F., Wang, S., Melchinger, A. E. & Zeng, Z. B. Quantitative trait loci mapping and the genetic basis of heterosis in maize and rice. Genetics 180, 1707–1724 (2008). 30. Li, L. Z. et al. Dominance, overdominance and epistasis condition the heterosis in two heterotic rice Hybrids. Genetics 180, 1725–1742 (2008). 31. Reif, J. C. et al. Unraveling epistasis with triple testcross progenies of near-isogenic lines. Genetics 181, 247–251 (2009). 32. He, X. H. & Zhang, Y. M. A complete solution for dissecting pure main and epistatic effects of QTL in triple testcross design. PLoS ONE 6, e24575 (2011). 33. He, X. H., Hu, Z. L. & Zhang, Y. M. Genome-wide mapping of QTL associated with heterosis in the RIL-based NCIII design. Chinese Sci. Bull. 57, 2655–2665 (2012). 34. Qu, Z. et al. QTL Mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses. PLoS ONE 7, e28463 (2012). 35. Hu, W. M., Xu, Y., Zhang, E. Y. & Xu, C. W. Study on the genetic basis of general combining ability with QTL mapping strategy. Scientia Agricultura Sinica 46, 3305–3313 (2013) (in Chinese). 36. Qi, H. H. et al. Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines. Theor. Appl. Genet. 126, 369–377 (2013). 37. Huang, J. et al. General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines. Genetica 141, 453–461 (2013). 38. Li, L. Z. et al. QTL mapping for combining ability in different population-based NCII designs by a simulation study. J. Genet. 92, 529–543 (2013). 39. Cai, X., Huang, A. & Xu, S. Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping. BMC Bioinformatics 12, 211 (2011). 40. Huang, A. H., Xu, S. & Cai, X. Empirical Bayesian elastic net for multiple quantitative trait locus mapping. Heredity 114, 107–115 (2015). 41. Bhullar, K. S., Gill, K. S. & Khehra, A. S. Combining ability analysis over F1-F5 generations in diallel crosses of bread wheat. Theor. Appl. Genet. 55, 77–80 (1979). 42. Singh, O., Gowda, C. L. L., Sethi, S. C., Dasgupta, T. & Smithson, J. B. Genetic analysis of agronomic characters in chickpea. I. Estimates of genetic variances from diallel designs. Theor. Appl. Genet. 83, 956–962 (1992). 43. Cho, Y. K. & Scott, R. A. Combining ability of seed vigor and seed yield in soybean. Euphytica 112, 145–150 (2000). 44. Shukla, S. K. & Pandey, M. P. Combining ability and heterosis over environments for yield and yield components in two-line hybrids involving thermosensitive genic male sterile lines in rice (Oryza sativa L.). Plant Breeding 127, 28–32 (2008). 45. Cui, Y., Zhang, F., Xu, J., Li, Z. & Xu, S. Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach. Heredity, online, doi: 10.1038/hdy.2015.56 (2015). 46. Zhang, Y. M. & Xu, S. A penalized maximum likelihood method for estimating epistatic effects of QTL. Heredity 95, 96–104 (2005). 47. Yi, N. & Xu, S. Bayesian Lasso for quantitative trait loci mapping. Genetics 179, 1045–1055 (2008). 48. Park, T. & Casella, G. The Bayesian Lasso. J. Am. Stat. Assoc. 103, 681–686 (2008). 49. Yi, N. & Banerjee, S. Hierarchical generalized linear models for multiple quantitative trait locus mapping. Genetics 181, 1101–1113 (2009). 50. Feng, J. Y. et al. An efficient hierarchical generalized linear mixed model for mapping QTL of ordinal traits in crop cultivars. PLoS ONE 8, e59541 (2013). 51. Xu, S. An expectation–maximization algorithm for the Lasso estimation of quantitative trait locus effects. Heredity 105, 483–494 (2010). 52. Lü, H. Y., Liu, X. F., Wei, S. P. & Zhang, Y. M. Epistatic association mapping in homozygous crop cultivars. PLoS ONE 6, e17773 (2011). 53. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).