Genetic analysis of grain yield conditioned on its component traits in rice (Oryza sativa L.)
G. F. Liu A B , J. Yang A , H. M. Xu A , Y. Hayat A and J. Zhu A CA Institute of Bioinformatics, College of Agriculture & Biotechnology, Zhejiang University, Hangzhou, Zhejiang 310029, P. R. China.
B College of Agriculture, South China Agricultural University, Guangzhou, Guangdong 510642, P. R. China.
C Corresponding author. Email: jzhu@zju.edu.cn
Australian Journal of Agricultural Research 59(2) 189-195 https://doi.org/10.1071/AR07163
Submitted: 20 April 2007 Accepted: 9 October 2007 Published: 19 February 2008
Abstract
Grain yield (GY) of rice is a complex trait consisting of several yield components. It is of great importance to reveal the genetic relationships between GY and its yield components at the QTL (quantitative trait loci) level for multi-trait improvement in rice. In the present study, GY per plant in rice and its 3 yield component traits, panicle number per plant (PN), grain number per panicle (GN), and 1000-grain weight (GW), were investigated using a doubled-haploid population derived from a cross of an indica variety IR64 and a japonica variety Azucena. The phenotypic values collected from 2 cropping seasons were analysed by QTLNetwork 2.0 for mapping QTLs with additive (a) and/or additive × environment interaction (ae) effects. Furthermore, conditional QTL analysis was conducted to detect QTLs for GY independent of yield components. The results showed that the general genetic variation in GY was largely influenced by GN with the contribution ratio of 29.2%, and PN and GN contributed 10.5% and 74.6% of the genotype × environment interaction variation in GY, respectively. Four QTLs were detected with additive and/or additive × environment interaction effects for GY by the unconditional mapping method. However, for GY conditioned on PN, GN, and GW, 6 additional loci were identified by the conditional mapping method. All of the detected QTLs affecting GY were associated with at least one of the 3 yield components. The results revealed that QTL expressions of GY were contributed differently by 3 yield component traits, and provide valuable information for effectively improving GY in rice.
Additional keywords: yield component traits, QTL, conditional mapping.
Acknowledgments
We thank Dr N. Huang for providing the research materials and molecular marker data. We also thank three anonymous reviewers for useful comments and suggestions on the earlier version of the manuscript.
Albert BSB,
Edwards MD, Stuber CW
(1991) Isoenzymatic identification of quantitative trait loci in crosses of elite maize inbreeds. Crop Science 31, 267–274.
Atchley WR, Zhu J
(1997) Developmental quantitative genetics, conditional epigenetic variability and growth in mice. Genetics 147, 765–776.
| PubMed |
Cao GQ,
Zhu J,
He CX,
Gao YM,
Yan JQ, Wu P
(2001) Impacts of epistasis and QTL × environment interaction for developmental behavior of plant height in rice (Oryza sativa L.). Theoretical and Applied Genetics 103, 153–160.
| Crossref | GoogleScholarGoogle Scholar |
Causse MA,
Fulton TM,
Cho YG,
Ahn SN, Chunwongse J , et al.
(1994) Saturated molecular map of the rice genome based on an interspecific backcross population. Genetics 138, 1251–1274.
| PubMed |
Champoux MC,
Wang G,
Sarkarung S,
Mackill DJ,
O’Toole JC,
Huang N, McCouch SR
(1995) Locating genes associated with root morphology and drought avoidance in rice via linkage to molecular markers. Theoretical and Applied Genetics 90, 969–981.
| Crossref | GoogleScholarGoogle Scholar |
Darvasi A, Pisanté-Shalom A
(2002) Complexities in the genetic dissection of quantitative trait loci. Trends in Genetics 18, 489–491.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Donald CM
(1968) The breeding of crop ideotypes. Euphytica 17, 385–403.
| Crossref | GoogleScholarGoogle Scholar |
Guiderdoni E,
Galinato E,
Luistro J, Vergara G
(1992) Anther culture of tropical japonica × indica hybrids of rice (Oryza sativa L.). Euphytica 62, 219–224.
| Crossref | GoogleScholarGoogle Scholar |
Guo LB,
Xing YZ,
Mei HW,
Xu CG,
Shi CH,
Wu P, Luo LJ
(2005) Dissection of component QTL expression in yield formation in rice. Plant Breeding 124, 127–132.
| Crossref | GoogleScholarGoogle Scholar |
Hittalmani S,
Huang N,
Courtois B,
Venuprasad R, Shashidhar HE , et al.
(2003) Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia. Theoretical and Applied Genetics 107, 679–690.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Huang N,
McCouch SR,
Mew T,
Parco A, Guiderdoni E
(1994) Development of an RFLP map from a doubled haploid population in rice. Rice Genetics Newsletter 11, 134–137.
Julier B,
Huguet T,
Chardon F,
Ayadi R,
Pierre JB,
Prosperi JM,
Barre P, Huyghe C
(2007) Identification of quantitative trait loci influencing aerial morphogenesis in the model legume Medicago truncatula. Theoretical and Applied Genetics 114, 1391–1406.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Lander ES, Botstein D
(1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199.
| PubMed |
Lehmensiek A,
Eckermann PJ,
Verbyla AP,
Appels R,
Sutherland MW,
Martin D, Daggard GE
(2006) Flour yield QTLs in three Australian doubled haploid wheat populations. Australian Journal of Agricultural Research 57, 1115–1122.
| Crossref | GoogleScholarGoogle Scholar |
Li ZK,
Pinson SRM,
Stansel JW, Paterson AH
(1998) Genetic dissection of the source-sink relationship affecting fecundity and yield in rice. Molecular Breeding 4, 419–426.
| Crossref | GoogleScholarGoogle Scholar |
Lin HX,
Qian HR,
Zhuang JY,
Min SK,
Xiong ZM,
Huang N, Zheng KL
(1996) RFLP mapping of QTLs for yield and related characters in rice. Theoretical and Applied Genetics 92, 920–927.
| Crossref | GoogleScholarGoogle Scholar |
Miller RG
(1974) The Jackknife: a review. Biometrika 61, 1–15.
Musial JM,
Lowe KF,
Mackie JM,
Aitken KS, Irwin JAG
(2006) DNA markers linked to yield, yield components, and morphological traits in autotetraploid lucerne (Medicago sativa L.). Australian Journal of Agricultural Research 57, 801–810.
| Crossref | GoogleScholarGoogle Scholar |
Paterson AH,
Deverna JW,
Lanini B, Tanksley SD
(1991) Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments. Genetics 127, 181–197.
| PubMed |
Risch NJ
(2000) Searching for genetic determinants in the new millennium. Nature 405, 847–856.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Wang DL,
Zhu J,
Li ZK, Paterson AH
(1999) Mapping QTLs with epistatic effects and QTLs by environment interaction by mixed linear model approaches. Theoretical and Applied Genetics 99, 1255–1264.
| Crossref | GoogleScholarGoogle Scholar |
Wen YX, Zhu J
(2005) Multivariable conditional analysis for complex trait and its components. Acta Genetica Sinica 82, 289–296.
Wu JX,
Jenkins JN,
McCarty JC, Zhu J
(2004) Genetic association of yield with its component traits in a recombinant inbred line population of cotton. Euphytica 140, 171–179.
| Crossref | GoogleScholarGoogle Scholar |
Xing Y,
Tan YF,
Hua JP,
Sun XL,
Xu CG, Zhang QF
(2002) Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theoretical and Applied Genetics 105, 248–257.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Yan JQ,
Zhu J,
He C,
Benmoussa M, Wu P
(1999) Molecular marker-assisted dissection of genotype × environment interaction for plant type traits in rice (Oryza sativa L.). Crop Science 39, 538–544.
Yan JQ,
Zhu J,
He CX,
Benmoussa M, Wu P
(1998a) Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.). Genetics 150, 1257–1265.
| PubMed |
Yan JQ,
Zhu J,
He CX,
Benmoussa M, Wu P
(1998b) Quantitative trait loci analysis for the developmental behavior of tiller number in rice (Oryza sativa L.). Theoretical and Applied Genetics 97, 267–274.
| Crossref | GoogleScholarGoogle Scholar |
Yan W,
Hunt LA,
Johnson P,
Stewart G, Lu X
(2002) On-farm strip trials vs replicated performance trials for cultivar evaluation. Crop Science 42, 385–392.
Yang J,
Zhu J, Williams RW
(2007) Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics 23, 1527–1536.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Yano M, Sasaki T
(1997) Genetic and molecular dissection of quantitative traits in rice. Plant Molecular Biology 35, 145–153.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Zeng ZB
(1994) Precision mapping of quantitative trait loci. Genetics 136, 1457–1468.
| PubMed |
Zeng ZB
(2005) QTL mapping and the genetic basis of adaptation: recent developments. Genetica 123, 25–37.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Zeng ZB, Weir BS
(1996) Statistical methods for mapping quantitative trait loci. Acta Agronomica Sinica 22, 535–549.
Zhao JY,
Becker HC, Zhang DQ
(2006) Conditional QTL mapping of oil content in rapseed with respect to protein content and traits related to plant development and grain yield. Theoretical and Applied Genetics 113, 33–38.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Zhu J
(1994) General genetic models and new analysis methods for quantitative traits (Chinese). Journal of Zhejiang Agricultural University 20, 551–559.
Zhu J
(1995) Analysis of conditional genetic effects and variance components in developmental genetics. Genetics 141, 1633–1639.
| PubMed |
Zhu J
(1999) Mixed model approaches of mapping genes for complex quantitative traits. Journal of Zhejiang University (Natural Science) 33, 327–335.
Zhuang JY,
Lin HX,
Lu J,
Qian HR,
Hittalmani S,
Huang N, Zheng KL
(1997) Analysis of QTL × environment interaction for yield components and plant height in rice. Theoretical and Applied Genetics 95, 799–808.
| Crossref | GoogleScholarGoogle Scholar |
