Whole-genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2014 Feb 4

PMID 24489897

Citations 14

Authors

Anhui Huang

Shizhong Xu

Xiaodong Cai

Affiliations

Soon will be listed here.

Abstract

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F2 population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.

Citing Articles

Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome.

Id-Lahoucine S, Casellas J, Miglior F, Schenkel F, Canovas A Front Genet. 2023; 14:1132796.

PMID: 37091801 PMC: 10117652. DOI: 10.3389/fgene.2023.1132796.

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction.

Ahmadi N Methods Mol Biol. 2022; 2467:1-44.

PMID: 35451771 DOI: 10.1007/978-1-0716-2205-6_1.

Metabolomics for Crop Breeding: General Considerations.

Litvinov D, Karlov G, Divashuk M Genes (Basel). 2021; 12(10).

PMID: 34680996 PMC: 8535592. DOI: 10.3390/genes12101602.

MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.

Heinrich F, Ramzan F, Rajavel A, Schmitt A, Gultas M Biology (Basel). 2021; 10(9).

PMID: 34571798 PMC: 8469369. DOI: 10.3390/biology10090921.

Climate sensitivity of Cryptomeria japonica in two contrasting environments: Perspectives from QTL mapping.

Mori H, Yamashita K, Saiki S, Matsumoto A, Ujino-Ihara T PLoS One. 2020; 15(1):e0228278.

PMID: 31990959 PMC: 6986750. DOI: 10.1371/journal.pone.0228278.

References

Xue W, Xing Y, Weng X, Zhao Y, Tang W, Wang L . Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat Genet. 2008; 40(6):761-7. DOI: 10.1038/ng.143. View

Zhou G, Chen Y, Yao W, Zhang C, Xie W, Hua J . Genetic composition of yield heterosis in an elite rice hybrid. Proc Natl Acad Sci U S A. 2012; 109(39):15847-52. PMC: 3465387. DOI: 10.1073/pnas.1214141109. View

Tester M, Langridge P . Breeding technologies to increase crop production in a changing world. Science. 2010; 327(5967):818-22. DOI: 10.1126/science.1183700. View

Huang A, Xu S, Cai X . Empirical Bayesian LASSO-logistic regression for multiple binary trait locus mapping. BMC Genet. 2013; 14:5. PMC: 3771412. DOI: 10.1186/1471-2156-14-5. View

Segami S, Kono I, Ando T, Yano M, Kitano H, Miura K . Small and round seed 5 gene encodes alpha-tubulin regulating seed cell elongation in rice. Rice (N Y). 2014; 5(1):4. PMC: 3834490. DOI: 10.1186/1939-8433-5-4. View

Kitagawa K, Kurinami S, Oki K, Abe Y, Ando T, Kono I . A novel kinesin 13 protein regulating rice seed length. Plant Cell Physiol. 2010; 51(8):1315-29. DOI: 10.1093/pcp/pcq092. View

Hoggart C, Whittaker J, De Iorio M, Balding D . Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies. PLoS Genet. 2008; 4(7):e1000130. PMC: 2464715. DOI: 10.1371/journal.pgen.1000130. View

Wang E, Xu X, Zhang L, Zhang H, Lin L, Wang Q . Duplication and independent selection of cell-wall invertase genes GIF1 and OsCIN1 during rice evolution and domestication. BMC Evol Biol. 2010; 10:108. PMC: 2873416. DOI: 10.1186/1471-2148-10-108. View

Xie W, Feng Q, Yu H, Huang X, Zhao Q, Xing Y . Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing. Proc Natl Acad Sci U S A. 2010; 107(23):10578-83. PMC: 2890813. DOI: 10.1073/pnas.1005931107. View

10.

Zietkiewicz E, Rafalski A, Labuda D . Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics. 1994; 20(2):176-83. DOI: 10.1006/geno.1994.1151. View

11.

Wang S, Wu K, Yuan Q, Liu X, Liu Z, Lin X . Control of grain size, shape and quality by OsSPL16 in rice. Nat Genet. 2012; 44(8):950-4. DOI: 10.1038/ng.2327. View

12.

Li F, Liu W, Tang J, Chen J, Tong H, Hu B . Rice DENSE AND ERECT PANICLE 2 is essential for determining panicle outgrowth and elongation. Cell Res. 2010; 20(7):838-49. DOI: 10.1038/cr.2010.69. View

13.

Li X, Qian Q, Fu Z, Wang Y, Xiong G, Zeng D . Control of tillering in rice. Nature. 2003; 422(6932):618-21. DOI: 10.1038/nature01518. View

14.

Zha X, Luo X, Qian X, He G, Yang M, Li Y . Over-expression of the rice LRK1 gene improves quantitative yield components. Plant Biotechnol J. 2009; 7(7):611-20. DOI: 10.1111/j.1467-7652.2009.00428.x. View

15.

Heang D, Sassa H . Antagonistic actions of HLH/bHLH proteins are involved in grain length and weight in rice. PLoS One. 2012; 7(2):e31325. PMC: 3283642. DOI: 10.1371/journal.pone.0031325. View

16.

Xing Z, Tan F, Hua P, Sun L, Xu G, Zhang Q . Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor Appl Genet. 2003; 105(2-3):248-257. DOI: 10.1007/s00122-002-0952-y. View

17.

Minakuchi K, Kameoka H, Yasuno N, Umehara M, Luo L, Kobayashi K . FINE CULM1 (FC1) works downstream of strigolactones to inhibit the outgrowth of axillary buds in rice. Plant Cell Physiol. 2010; 51(7):1127-35. PMC: 2900823. DOI: 10.1093/pcp/pcq083. View

18.

Zhou X, Carbonetto P, Stephens M . Polygenic modeling with bayesian sparse linear mixed models. PLoS Genet. 2013; 9(2):e1003264. PMC: 3567190. DOI: 10.1371/journal.pgen.1003264. View

19.

Hua J, Xing Y, Wu W, Xu C, Sun X, Yu S . 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 U S A. 2003; 100(5):2574-9. PMC: 151382. DOI: 10.1073/pnas.0437907100. View

20.

Goff S, Ricke D, Lan T, Presting G, Wang R, Dunn M . A draft sequence of the rice genome (Oryza sativa L. ssp. japonica). Science. 2002; 296(5565):92-100. DOI: 10.1126/science.1068275. View