Genomic architecture of heterosis for yield traits in rice

Abstract

Increasing grain yield is a long-term goal in crop breeding to meet the demand for global food security. Heterosis, when a hybrid shows higher performance for a trait than both parents, offers an important strategy for crop breeding. To examine the genetic basis of heterosis for yield in rice, here we generate, sequence and record the phenotypes of 10,074 F2 lines from 17 representative hybrid rice crosses. We classify modern hybrid rice varieties into three groups, representing different hybrid breeding systems. Although we do not find any heterosis-associated loci shared across all lines, within each group, a small number of genomic loci from female parents explain a large proportion of the yield advantage of hybrids over their male parents. For some of these loci, we find support for partial dominance of heterozygous locus for yield-related traits and better-parent heterosis for overall performance when all of the grain-yield traits are considered together. These results inform on the genomic architecture of heterosis and rice hybrid breeding.

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Figure 1: Large-scale sequencing, genotyping and genetic mapping in 10,074 F2 lines.
Figure 2: Evaluation of dominance effects for all yield-related QTLs.
Figure 3: Two candidate genes hd3a and tac1 for heterosis for yield traits in type-A hybrids.
Figure 4: Combination of multiple beneficial alleles in type-C hybrids.

Accession codes

Primary accessions

European Nucleotide Archive

Data deposits

DNA sequencing data are deposited in the European Nucleotide Archive under the accession number PRJEB13735.

References

  1. 1

    Wang, Y., Xue, Y. & Li, J. Towards molecular breeding and improvement of rice in China. Trends Plant Sci. 10, 610–614 (2005)

  2. 2

    Cheng, S. H., Zhuang, J. Y., Fan, Y. Y., Du, J. H. & Cao, L. Y. Progress in research and development on hybrid rice: a super-domesticate in China. Ann. Bot. 100, 959–966 (2007)

  3. 3

    Li, S., Yang, D. & Zhu, Y. Characterization and use of male sterility in hybrid rice breeding. J. Integr. Plant Biol. 49, 791–804 (2007)

  4. 4

    Luo, D. et al. A detrimental mitochondrial-nuclear interaction causes cytoplasmic male sterility in rice. Nat. Genet. 45, 573–577 (2013)

  5. 5

    Krieger, U., Lippman, Z. B. & Zamir, D. The flowering gene SINGLE FLOWER TRUSS drives heterosis for yield in tomato. Nat. Genet. 42, 459–463 (2010)

  6. 6

    Li, X., Li, X., Fridman, E., Tesso, T. T. & Yu, J. Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis. Proc. Natl Acad. Sci. USA 112, 11823–11828 (2015)

  7. 7

    Hollick, J. B. & Chandler, V. L. Epigenetic allelic states of a maize transcriptional regulatory locus exhibit overdominant gene action. Genetics 150, 891–897 (1998)

  8. 8

    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)

  9. 9

    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)

  10. 10

    Zhou, G. et al. Genetic composition of yield heterosis in an elite rice hybrid. Proc. Natl Acad. Sci. USA 109, 15847–15852 (2012)

  11. 11

    Gao, Z.-Y. et al. Dissecting yield-associated loci in super hybrid rice by resequencing recombinant inbred lines and improving parental genome sequences. Proc. Natl Acad. Sci. USA 110, 14492–14497 (2013)

  12. 12

    Riedelsheimer, C. et al. Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44, 217–220 (2012)

  13. 13

    Huang, X. et al. Genomic analyses of complex traits reveal the genetic basis of heterosis in 1495 hybrid rice varieties. Nat. Commun. 6, 6258 (2015)

  14. 14

    Huang, X. et al. High-throughput genotyping by whole-genome resequencing. Genome Res. 19, 1068–1076 (2009)

  15. 15

    Kojima, S. et al. Hd3a, a rice ortholog of the Arabidopsis FT gene, promotes transition to flowering downstream of Hd1 under short-day conditions. Plant Cell Physiol. 43, 1096–1105 (2002)

  16. 16

    Yu, B. et al. TAC1, a major quantitative trait locus controlling tiller angle in rice. Plant J. 52, 891–898 (2007)

  17. 17

    Suresh, P. B. et al. Fine mapping of Rf3 and Rf4 fertility restorer loci of WA-CMS of rice (Oryza sativa L.) and validation of the developed marker system for identification of restorer lines. Euphytica 187, 421–435 (2012)

  18. 18

    Tang, H. et al. The rice restorer Rf4 for wild-abortive cytoplasmic male sterility encodes a mitochondrial-localized PPR protein that functions in reduction of WA352 transcripts. Mol. Plant 7, 1497–1500 (2014)

  19. 19

    Xue, W. et al. Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat. Genet. 40, 761–767 (2008)

  20. 20

    Komatsu, M., Maekawa, M., Shimamoto, K. & Kyozuka, J. The LAX1 and FRIZZY PANICLE 2 genes determine the inflorescence architecture of rice by controlling rachis-branch and spikelet development. Dev. Biol. 231, 364–373 (2001)

  21. 21

    Wang, Z. Y. et al. The amylose content in rice endosperm is related to the post-transcriptional regulation of the waxy gene. Plant J. 7, 613–622 (1995)

  22. 22

    Gao, Z. et al. Map-based cloning of the ALK gene, which controls the gelatinization temperature of rice. Sci. China C Life Sci. 46, 661–668 (2003)

  23. 23

    Liu, G., Lu, G., Zeng, L. & Wang, G. L. Two broad-spectrum blast resistance genes, Pi9(t) and Pi2(t), are physically linked on rice chromosome 6. Mol. Genet. Genomics 267, 472–480 (2002)

  24. 24

    Yang, J. et al. A killer-protector system regulates both hybrid sterility and segregation distortion in rice. Science 337, 1336–1340 (2012)

  25. 25

    Zhou, H. et al. RNase Z(S1) processes Ub L40 mRNAs and controls thermosensitive genic male sterility in rice. Nat. Commun. 5, 4884 (2014)

  26. 26

    Ding, J. et al. A long noncoding RNA regulates photoperiod-sensitive male sterility, an essential component of hybrid rice. Proc. Natl Acad. Sci. USA 109, 2654–2659 (2012)

  27. 27

    Yan, W.-H. et al. A major QTL, Ghd8, plays pleiotropic roles in regulating grain productivity, plant height, and heading date in rice. Mol. Plant 4, 319–330 (2011)

  28. 28

    Kim, S. L., Lee, S., Kim, H. J., Nam, H. G. & An, G. OsMADS51 is a short-day flowering promoter that functions upstream of Ehd1, OsMADS14, and Hd3a. Plant Physiol. 145, 1484–1494 (2007)

  29. 29

    Fujita, D. et al. NAL1 allele from a rice landrace greatly increases yield in modern indica cultivars. Proc. Natl Acad. Sci. USA 110, 20431–20436 (2013)

  30. 30

    Yano, M. et al. Hd1, a major photoperiod sensitivity quantitative trait locus in rice, is closely related to the Arabidopsis flowering time gene CONSTANS. Plant Cell 12, 2473–2484 (2000)

  31. 31

    Sasaki, A. et al. Green revolution: a mutant gibberellin-synthesis gene in rice. Nature 416, 701–702 (2002)

  32. 32

    Sun, H. et al. Heterotrimeric G proteins regulate nitrogen-use efficiency in rice. Nat. Genet. 46, 652–656 (2014)

  33. 33

    Song, X. J. et al. Rare allele of a previously unidentified histone H4 acetyltransferase enhances grain weight, yield, and plant biomass in rice. Proc. Natl Acad. Sci. USA 112, 76–81 (2015)

  34. 34

    Izawa, T. et al. Os-GIGANTEA confers robust diurnal rhythms on the global transcriptome of rice in the field. Plant Cell 23, 1741–1755 (2011)

  35. 35

    Jiao, Y. et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat. Genet. 42, 541–544 (2010)

  36. 36

    Miura, K. et al. OsSPL14 promotes panicle branching and higher grain productivity in rice. Nat. Genet. 42, 545–549 (2010)

  37. 37

    Yao, H., Dogra Gray, A., Auger, D. L. & Birchler, J. A. Genomic dosage effects on heterosis in triploid maize. Proc. Natl Acad. Sci. USA 110, 2665–2669 (2013)

  38. 38

    Birchler, J. A., Johnson, A. F. & Veitia, R. A. Kinetics genetics: Incorporating the concept of genomic balance into an understanding of quantitative traits. Plant Sci. 245, 128–134 (2016)

  39. 39

    Picelli, S. et al. Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Res. 24, 2033–2040 (2014)

  40. 40

    Wang, S., Basten, C. J. & Zeng, Z. B. Windows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh. http://statgen.ncsu.edu/qtlcart/WQTLCart.htm (2007)

  41. 41

    Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006)

  42. 42

    Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348–354 (2010)

  43. 43

    Huang, X. et al. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat. Genet. 44, 32–39 (2011)

  44. 44

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

  45. 45

    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011)

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Acknowledgements

This work was supported by the Chinese Academy of Sciences (XDA08020101) and the National Natural Science Foundation of China (31322028, 91535202, 31421093 and 31301302).

Author information

Affiliations

Authors

Contributions

B.H. conceived the project and its components. X.H. and B.H. designed studies and contributed to the original concept of the project. S.Y. and J.G. contributed the generation of the genetic populations. J.G., Qil.Z., B.C., J.X., N.C. and S.Y. contributed in phenotyping for grain yield traits. W.L., Y.L. J.C., C.Z., D.F., Q.W. and Q.F. performed the genome sequencing. X.H., Qia.Z., Y.Z., L.Z. and T.H. performed genome data analysis and genetic analysis. X.H. and B.H. analysed whole data and wrote the paper.

Corresponding authors

Correspondence to Xuehui Huang or Bin Han.

Additional information

Reviewer Information

Nature thanks J. Ross-Ibarra, D. Weigel and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 The experimental design and analysis procedure used in the study.

Extended Data Figure 2 Selection of 17 representative hybrid combinations from 1,495 hybrids.

a, Plots of the first two principal components of 1,495 hybrids. The 17 representative hybrids are coloured in red. b, Plots of the principal component 3 and the principal component 4 of 1,495 hybrids. c, Plots of heading date and plant height of 1,495 hybrids. d, Plots of grain number and seed-setting rate of 1,495 hybrids.

Extended Data Figure 3 High-resolution genotyping of F2 lines by whole-genome sequencing.

a, Aligned recombination maps of 1,105 lines from a cross between Fuhui676 and Guangzhan63-4S. Three genotypes were indicated by blue, red and yellow, respectively (blue, Fuhui676/Fuhui676; red, Guangzhan63-4S/Guangzhan63-4S; yellow, Fuhui676/Guangzhan63-4S). b, The recombination map of a single F2 line from a cross between Fuhui676 × Guangzhan63-4S. The genomic DNA of the line was sequenced in the HiSeq2500 system, and genotyped through the SEG-Map computational algorithm. Detected SNP genotypes in this line were indicated along chromosomes according to their physical locations. A sliding window approach was used for genotype calling, recombination breakpoint determination and map construction. There were several IBS (identity by state) segments shared by both parents (for example, the regions on the chromosomes 10 and 11), which are indicated by the grey boxes.

Extended Data Figure 4 Analysis of flowering time in type-A hybrids.

a, Flowering-time modelling using the genotypes of four genes (Hd3a, Ghd7, Hd2 and Ehd1) known to regulate flowering time. We used the data in one type-A population (Guanghui998 × Tianfeng) for experimentation, and evaluated the accuracy of the modelling in the other eight populations. b, The estimates of the genetic effects of three genotypes of the four genes, in which the flowering time of the homozygous genotypes of male parents was set to be 90 days according to the average performance of restorer lines. The arrows indicated the flowering time for the genotypes Hd3a/hd3a and hd3a/hd3a.

Extended Data Figure 5 The linkage drag around the hd3a locus.

The allelic combinations of six candidate genes on the short arm of chromosome 6 and their frequencies in 1,063 indica CMS lines.

Extended Data Figure 6 QTL for heterosis for yield traits in type-B hybrids.

a, Plots of the dominance effects of three traits at the Tms5 locus in the four type-B hybrids. b, Plots of the dominance effects of three traits at the Ghd8 locus in the four type-B hybrids. c, The yield advantages in the hybrid LYP9 by two QTLs LAX1 and SS3p10 from PA64S (**P < 0.001, two-tailed t-test). The male (M) and heterozygous (H) genotypes are indicated. d, The yield advantages in the hybrid Liangyou676 by two QTLs at the ‘ghd8’ locus and PN3q23 from Guangzhan63-4S (**P < 0.001, two-tailed t-test).

Extended Data Figure 7 Support for pseudo-overdominance at the Tms5 locus.

a, The linkage mapping of fertility in one population of type B. LOD values are plotted against the physical positions, and the threshold (3.5) is indicated by a horizontal dashed line. b, The linkage mapping of panicle number in one population of type A. c, The linkage mapping of yield per plant in the population of type A. d, Gene structure and causal variation site between Tms5 and tms5 alleles in the hybrids of type B. e, No mutations are detected at the Tms5 gene between both parents (Fuhui838 and II32A) of the type-A population.

Extended Data Figure 8 Performances of two QTLs LAX1 and SS3p10 in type-B hybrid LYP9.

a, The linkage mapping of seed-setting rate in the population of type-B hybrid LYP9. LOD values are plotted against the physical positions, and the threshold (3.5) is indicated by a horizontal dashed line. b, The performances of seed-setting rate for three genotypes of the SS3p10 locus in the population of type-B hybrid LYP9. c, The linkage mapping of grain weight in the population of type-B hybrid LYP9. d, The performances of grain weight for three genotypes of the LAX1 locus in the population of type-B hybrid LYP9.

Extended Data Figure 9 Performances of two QTLs, GW3p6 and PN3q23, in type-B hybrid Liangyou676.

a, The linkage mapping of grain weight in the population of type-B hybrid Liangyou676. b, The performances of grain weight for three genotypes of the GW3p6 locus in the population of type-B hybrid Liangyou676. c, The linkage mapping of panicle number in the population of type-B hybrid Liangyou676. d, The performances of panicle number for three genotypes of the PN3q23 locus in the population of type-B hybrid Liangyou676.

Extended Data Figure 10 Partial positive dominance effect of IPA1 for the yield components.

a, The performances of grain number per panicle for three genotypes of the IPA1 gene. b, The performances of panicle number for three genotypes of the IPA1 gene. c, The performances of seed-setting rate for three genotypes of the IPA1 gene.

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Huang, X., Yang, S., Gong, J. et al. Genomic architecture of heterosis for yield traits in rice. Nature 537, 629–633 (2016). https://doi.org/10.1038/nature19760

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