Multi-trait Multi-environment Quantitative Trait Loci Mapping for a Sugarcane Commercial Cross Provides Insights on the Inheritance of Important Traits

Overview

Journal Mol Breed

Specialties Biotechnology
Molecular Biology

Date 2015 Aug 15

PMID 26273212

Citations 7

Authors

G R A Margarido

M M Pastina

A P Souza

A A F Garcia

Affiliations

Soon will be listed here.

Abstract

Breeding trials typically consist of phenotypic observations for various traits evaluated in multiple environments. For sugarcane in particular, repeated measures are obtained for plant crop and one or more ratoons, such that joint analysis through mixed models for modeling heterogeneous genetic (co)variances between traits, locations and harvests is appropriate. This modeling approach also enables us to include molecular marker information, aiding in understanding the genetic architecture of quantitative traits. Our work aims at detecting QTL and QTL by environment interactions by fitting mixed models with multiple QTLs, with appropriate modeling of multi-trait multi-environment data for outcrossing species. We evaluated 100 individuals from a biparental cross at two locations and three years for fiber content, sugar content (POL) and tonnes of cane per hectare (TCH). We detected 13 QTLs exhibiting QTL by location, QTL by harvest or the three-way interaction. Overall, 11 of the 13 effects presented some degree of pleiotropy, affecting at least two traits. Furthermore, these QTLs always affected fiber and TCH in the same direction, whereas POL was affected in the opposite way. There was no evidence in favor of the linked QTL over the pleiotropic QTL hypothesis for any detected genome position. These results provide valuable insights into the genetic basis of quantitative variation in sugarcane and the genetic relation between traits.

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References

Zeng Z, Kao C, Basten C . Estimating the genetic architecture of quantitative traits. Genet Res. 2000; 74(3):279-89. DOI: 10.1017/s0016672399004255. View

Alimi N, Bink M, Dieleman J, Magan J, Wubs A, Palloix A . Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper. Theor Appl Genet. 2013; 126(10):2597-625. DOI: 10.1007/s00122-013-2160-3. View

Sukhwinder-Singh , Hernandez M, Crossa J, Singh P, Bains N, Singh K . Multi-trait and multi-environment QTL analyses for resistance to wheat diseases. PLoS One. 2012; 7(6):e38008. PMC: 3367963. DOI: 10.1371/journal.pone.0038008. View

Margarido G, Souza A, Garcia A . OneMap: software for genetic mapping in outcrossing species. Hereditas. 2007; 144(3):78-9. DOI: 10.1111/j.2007.0018-0661.02000.x. View

Jordan D, Casu R, Besse P, Carroll B, Berding N, McIntyre C . Markers associated with stalk number and suckering in sugarcane colocate with tillering and rhizomatousness QTLs in sorghum. Genome. 2004; 47(5):988-93. DOI: 10.1139/g04-040. View

Phillips P . Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet. 2008; 9(11):855-67. PMC: 2689140. DOI: 10.1038/nrg2452. View

Broman K . Review of statistical methods for QTL mapping in experimental crosses. Lab Anim (NY). 2001; 30(7):44-52. View

Pastina M, Malosetti M, Gazaffi R, Mollinari M, Margarido G, Oliveira K . A mixed model QTL analysis for sugarcane multiple-harvest-location trial data. Theor Appl Genet. 2011; 124(5):835-49. PMC: 3284670. DOI: 10.1007/s00122-011-1748-8. View

Serang O, Mollinari M, Garcia A . Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids. PLoS One. 2012; 7(2):e30906. PMC: 3281906. DOI: 10.1371/journal.pone.0030906. View

10.

Garcia A, Kido E, Meza A, Souza H, Pinto L, Pastina M . Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases. Theor Appl Genet. 2005; 112(2):298-314. DOI: 10.1007/s00122-005-0129-6. View

11.

Lander E, Botstein D . Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics. 1989; 121(1):185-99. PMC: 1203601. DOI: 10.1093/genetics/121.1.185. View

12.

Boer M, Wright D, Feng L, Podlich D, Luo L, Cooper M . A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. Genetics. 2007; 177(3):1801-13. PMC: 2147942. DOI: 10.1534/genetics.107.071068. View

13.

Jiang C, Zeng Z . Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics. 1995; 140(3):1111-27. PMC: 1206666. DOI: 10.1093/genetics/140.3.1111. View

14.

Collard B, Mackill D . Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc Lond B Biol Sci. 2007; 363(1491):557-72. PMC: 2610170. DOI: 10.1098/rstb.2007.2170. View

15.

Lin M, Lou X, Chang M, Wu R . A general statistical framework for mapping quantitative trait loci in nonmodel systems: issue for characterizing linkage phases. Genetics. 2003; 165(2):901-13. PMC: 1462782. DOI: 10.1093/genetics/165.2.901. View

16.

Freeman J, Potts B, Downes G, Pilbeam D, Thavamanikumar S, Vaillancourt R . Stability of quantitative trait loci for growth and wood properties across multiple pedigrees and environments in Eucalyptus globulus. New Phytol. 2013; 198(4):1121-1134. DOI: 10.1111/nph.12237. View

17.

Evans D . The power of multivariate quantitative-trait loci linkage analysis is influenced by the correlation between variables. Am J Hum Genet. 2002; 70(6):1599-602. PMC: 379151. DOI: 10.1086/340850. View

18.

Aitken K, Hermann S, Karno K, Bonnett G, McIntyre L, Jackson P . Genetic control of yield related stalk traits in sugarcane. Theor Appl Genet. 2008; 117(7):1191-203. DOI: 10.1007/s00122-008-0856-6. View

19.

Haley C, Knott S . A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity (Edinb). 1992; 69(4):315-24. DOI: 10.1038/hdy.1992.131. View

20.

Zeng Z . Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc Natl Acad Sci U S A. 1993; 90(23):10972-6. PMC: 47903. DOI: 10.1073/pnas.90.23.10972. View