000 02553nam a22003017a 4500
001 G94606
003 MX-TxCIM
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040 _aMX-TxCIM
090 _aCIS-6161
100 1 _aDong Wang
_uPlant and Animal Genomes Conference, XVIII; San Diego, CA (USA); 9-13 Jan 2010. Abstracts of oral and poster presentations
245 0 0 _aAssociation analysis in structured plant populations, an adaptive mixed LASSO approach
260 _c2010
300 _a1 page
520 _aRecently, there has been heightened interest in performing association analysis in important crop species. The development of mixed linear models for plant association mapping has significantly advanced the statistical methodology in this field. However, the mixed linear model has been mostly limited to single marker analysis. On the other hand, the lack of knowledge on epistasis and GxE interactions has become one of the major impediments of utilizing genomic information for crop improvement. We report the development of the adaptive mixed LASSO method that can incorporate a large number of predictors while simultaneously accounting for the population structure. LASSO can deal with situations where the number of explanatory variables is much larger than the sample size, which is not feasible for traditional regression methods. By extending adaptive LASSO to include random effects for structured populations, we can readily apply our method to the setting of plant association mapping. Our results show that the adaptive mixed LASSO method is very promising in modeling multiple genetic effects (main QTL effects and epistasis) as well as modeling gene by environment interactions when a large number of markers are available and the population structure cannot be ignored. Since no equivalent method has been proposed in the setting of crop association analysis, it is expected to have a significant impact on the study of complex traits in important crop species. Applications to wheat breeding programs has been planned with the potential of influencing plant breeding practices.
536 _aGenetic Resources Program
546 _aEnglish
593 _aLucia Segura
594 _aINT2542|CCJL01
595 _aCSC
700 1 _aBaenziger, S.P.,
_ecoaut.
700 1 _aDweikat, I.,
_ecoaut.
700 1 _aEskridge, K.M.,
_ecoaut.
700 1 _9842
_aJiankang Wang
_gGenetic Resources Program
_8INT2542
_ecoaut.
700 1 _aCrossa, J.
_gGenetic Resources Program
_8CCJL01
_959
942 _cPRO
999 _c8011
_d8011