Modelos de covarianza residual heterocedásticos para mapeo de loci de caracteres cuantitativos.

ARROYO A; BALZARINI M.

Escuela de Biología y Matemática. Academia Nacional de Ciencias.

Tirao (Ed.) BIOMAT II

Lugar: Córdoba Argentina; Año: 2007; p. 129 - 140

SYNOPSISQuantitative and molecular genetics are being integrated rapidly with new advances in genome research. Particularly, quantitativetrait loci (QTL) analysis has changed the conventional view of polygenic inheritance and has led to the identification ofloci with quantitative effects of complex traits. QTL analysis implies statistical inference of QTL positions on genome and QTLeffects. Mapping QTL involves the simultaneous and iterative application of several statistical methods (e.g. single markeranalysis and interval mapping analysis). Under different methods, QTL positions and effects can be estimated by maximum likelihoodprocedures. But these traditional QTL mapping procedures assume independent data and homogeneous trait variances.However, plant breeding information usually comprises unbalanced and correlated data. Therefore, classical assumptions to mapQTL could be not met in practice. An alternative approach is QTL mapping via a mixed-model procedure to handle correlations.Our objective was to introduce applications of mixed-model theory for QTL mapping in plant populations. Utility of modelingresidual (co)variances structures in QTL mapping is demonstrated by a simulation study for the interval mapping framework inbackcross progenies under several scenario regarding heterogeneity of trait variances. The mixed-model procedure provides aunified QTL mapping approach in which we can analyze plant breeding data with complex (co)variances structures.