Statistical models for the detection of genes controlling quantitative trait loci expression
Many important traits in plant breeding exhibit continuous variation (yield, maturity, biotic and abiotic stress tolerance, etc.). The genetic principles underlying their inheritance are basically the same as those affecting Mendelian or qualitative traits, but since the segregation of the genes con...
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
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International Center for Tropical Agriculture
1995
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/82010 |
| _version_ | 1855523487815303168 |
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| author | Carbonell, Emilio A. |
| author_browse | Carbonell, Emilio A. |
| author_facet | Carbonell, Emilio A. |
| author_sort | Carbonell, Emilio A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Many important traits in plant breeding exhibit continuous variation (yield, maturity, biotic and abiotic stress tolerance, etc.). The genetic principles underlying their inheritance are basically the same as those affecting Mendelian or qualitative traits, but since the segregation of the genes concerned could be followed individually, new methods and concepts had to be developed. In this presentation, the task of searching for genes affecting quantitative, or continuous, traits will be considered. The immediate hope is the possibility of identifying specific portions of the genome involved in the variation of these traits (called QTLs) in order to enhance breeding programs. Moreover, the long term hope is finding the location of these genes to characterize and manipulate them to our advantage. Therefore, we will try to discuss the different statistical models used for QTL analysis and the power of different approaches. QTL analysis have been approached using different statistical strategies depending on the number of markers involved in the analysis. Early studies considered the relationship between a marker and a QTL; later, models considered a pair of markers flanking the QTL and studied the association between the QTL and the interval defined by the flanking markers. More recently, statistical methodologies focus their attention to consider the whole linkage group considering all markers of the group as being associated with the QTL. Although any type of classification of statistical approaches is always incomplete and biased, we will try to describe the current statistical models organized according to the number of markers studied and by the basic statistical methodology being employed. The practical implications of the approach will be discussed presenting a study on genotype by environment interactions for 15 traits in almonds investigated during 2-3 years by means of isozymatic markers. |
| format | Book Chapter |
| id | CGSpace82010 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 1995 |
| publishDateRange | 1995 |
| publishDateSort | 1995 |
| publisher | International Center for Tropical Agriculture |
| publisherStr | International Center for Tropical Agriculture |
| record_format | dspace |
| spelling | CGSpace820102025-11-05T16:58:10Z Statistical models for the detection of genes controlling quantitative trait loci expression Carbonell, Emilio A. linear models genetic markers genetic variation genotype environment interaction modelos lineales marcadores genéticos variación genética interacción genotipo ambiente Many important traits in plant breeding exhibit continuous variation (yield, maturity, biotic and abiotic stress tolerance, etc.). The genetic principles underlying their inheritance are basically the same as those affecting Mendelian or qualitative traits, but since the segregation of the genes concerned could be followed individually, new methods and concepts had to be developed. In this presentation, the task of searching for genes affecting quantitative, or continuous, traits will be considered. The immediate hope is the possibility of identifying specific portions of the genome involved in the variation of these traits (called QTLs) in order to enhance breeding programs. Moreover, the long term hope is finding the location of these genes to characterize and manipulate them to our advantage. Therefore, we will try to discuss the different statistical models used for QTL analysis and the power of different approaches. QTL analysis have been approached using different statistical strategies depending on the number of markers involved in the analysis. Early studies considered the relationship between a marker and a QTL; later, models considered a pair of markers flanking the QTL and studied the association between the QTL and the interval defined by the flanking markers. More recently, statistical methodologies focus their attention to consider the whole linkage group considering all markers of the group as being associated with the QTL. Although any type of classification of statistical approaches is always incomplete and biased, we will try to describe the current statistical models organized according to the number of markers studied and by the basic statistical methodology being employed. The practical implications of the approach will be discussed presenting a study on genotype by environment interactions for 15 traits in almonds investigated during 2-3 years by means of isozymatic markers. Muchos caracteres de interés agronómico muestran variación continua (rendimiento, precocidad, tolerancia a stress biótico y abiótico, etc.). Los principios genéticos que regulan su herencia son, básicamente, los mismos que afectan a los caracteres Mendelianos o cualitativos; sin embargo, dado que no se podía efectuar de forma individual la segregación de los genes responsables de su variación, ha sido necesario desarrollar nuevos métodos y conceptos. En esta conferencia, consideraremos el tema de la búsqueda de genes que afectan a los caracteres cuantitativos. El objetivo a corto plazo es la posibilidad de identificar regiones específicas del genoma involucradas en la variación de estos caracteres (o QTLs) para ser utilizados en programas de mejoramiento genético. A largo plazo, se espera llegar a localizar más finamente estos genes para caracterizarlos y manejarlos en nuestro beneficio. Discutiremos los diferentes modelos estadísticos empleados en el análisis de QTLs y la potencia de los diferentes enfoques. Los análisis de QTLs se han efectuado siguiendo diferentes estrategias según el número de marcadores que se estudia simultáneamente. Los primeros estudios implicaban a un único marcador; posteriormente, se consideraron parejas de marcadores y se estudiaba la presencia de un QTL dentro del intervalo que definen. Más recientemente, los métodos estadísticos centran su atención en considerar todo el grupo de ligamiento, e incluso todo el genoma, y estudian las asociación de todos los marcadores simultáneamente. Aunque cualquier tipo de clasificación es incompleta y sesgada, describiremos los métodos existentes de acuerdo a número de marcadores que estudian y la técnica estadística que emplean. Las implicaciones prácticas del enfoque del análisis de QTLs se discutirá presentando un estudio mediante marcadores isoenzimáticos sobre la interacción genotipo-medio en 15 caracteres de almendro evaluados durante 2-3 años 1995 2017-06-20T09:00:28Z 2017-06-20T09:00:28Z Book Chapter https://hdl.handle.net/10568/82010 en Open Access application/pdf International Center for Tropical Agriculture Carbonell, Emilio A.. 1995. Statistical models for the detection of genes controlling quantitative trait loci expression . In: Simposio Internacional de Estadística en Agricultura y Medio Ambiente (1995, Palmira, Valle del Cauca, Colombia). Memorias. Conferencia satélite . Centro Internacional de Agricultura Tropical (CIAT), Cali, CO. p. 91-121. |
| spellingShingle | linear models genetic markers genetic variation genotype environment interaction modelos lineales marcadores genéticos variación genética interacción genotipo ambiente Carbonell, Emilio A. Statistical models for the detection of genes controlling quantitative trait loci expression |
| title | Statistical models for the detection of genes controlling quantitative trait loci expression |
| title_full | Statistical models for the detection of genes controlling quantitative trait loci expression |
| title_fullStr | Statistical models for the detection of genes controlling quantitative trait loci expression |
| title_full_unstemmed | Statistical models for the detection of genes controlling quantitative trait loci expression |
| title_short | Statistical models for the detection of genes controlling quantitative trait loci expression |
| title_sort | statistical models for the detection of genes controlling quantitative trait loci expression |
| topic | linear models genetic markers genetic variation genotype environment interaction modelos lineales marcadores genéticos variación genética interacción genotipo ambiente |
| url | https://hdl.handle.net/10568/82010 |
| work_keys_str_mv | AT carbonellemilioa statisticalmodelsforthedetectionofgenescontrollingquantitativetraitlociexpression |