02649naa a2200313 a 450000100080000000500110000800800410001902400310006010000190009124501890011026000090029950002220030852014270053065000100195765000210196765000090198865300290199765300240202665300400205065300350209070000180212570000170214370000230216070000160218370000210219970000140222070000190223477300820225310597862019-10-11       2019    bl uuuu     u00u1 u    #d7 a10.1534/g3.119.4000642DOI1 aMONTEVERDE, E.  aIntegrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in subtropical areas.h[electronic resource]  c2019  aArticle history: Manuscript received February 6, 2019 // Accepted for publication March 5, 2019// Published Early Online March 15, 2019. Supplemental material available at Figshare: https://doi.org/10.25387/g3.7685636  aUnderstanding the genetic and environmental basis of genotype · environment interaction (G·E) is of fundamental importance in plant breeding. If we consider G·E in the context of genotype · year interactions (G·Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G·E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in subtropical and temperate rice growing areas.  aARROZ  aFITOMEJORAMIENTO  aRICE  aENVIRONMENTAL COVARIATES  aGENOMIC PREDICTIONS  aGENOTYPE BY ENVIRONMENT INTERACTION  aQTL BY ENVIRONMENT INTERACTION1 aGUTIERREZ, L.1 aBLANCO, P.H.1 aPÉREZ DE VIDA, F.1 aROSAS, J.E.1 aBONNECARRERE, V.1 aQUERO, G.1 aMCCOUCH, SUSAN  tG3: GENES, GENOMES, GENETICS May 1, 2019gv.9 (5), p. 1519-1531. OPEN ACCESS.