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Utility Assessment of Published Microsatellite Markers for Fiber Length and Bundle Strength QTL in a Cotton Breeding Program

Kari L. HugieTexas A&M Univ. Dep. of Soil and Crop Sciences 2474 TAMU College Station TX 77843‐2474David D. FangUSDA–ARS Southern Regional Research Center 1100 Robert E. Lee Blvd. New Orleans LA 70124‐4305C. Wayne SmithTexas A&M Univ. Dep. of Soil and Crop Sciences 2474 TAMU College Station TX 77843‐2474Ping LiUSDA–ARS Southern Regional Research Center 1100 Robert E. Lee Blvd. New Orleans LA 70124‐4305Lori L. HinzeUSDA–ARS Southern Plains Agricultural Research Center 2881 F&B Rd. College Station TX 77845‐4988Steve HagueTexas A&M Univ. Dep. of Soil and Crop Sciences 2474 TAMU College Station TX 77843‐2474D. C. JonesCotton Incorporated 6399 Weston Pkwy. Cary NC 27513‐2314
2016en
ABI

Abstract

Numerous DNA markers associated with quantitative trait loci (QTL) for cotton ( Gossypium spp.) fiber quality traits have been identified in the literature, but there are still significant challenges regarding the use of these QTL in marker‐assisted selection. While one of the primary limitations to the application of marker‐assisted selection for fiber quality traits has been the inconsistency of marker–trait associations, more recent studies have reported numerous marker–trait associations and colocating of QTL in different genetic backgrounds and environments. The objectives of this study were to assess the published microsatellite markers linked to upper‐half mean fiber length (UHML) and fiber bundle strength (Str) QTL in different genetic backgrounds and to characterize the utility of stable marker–trait associations in selection for improved fiber quality within the context of an applied breeding program. Using the results of 32 published QTL mapping studies, six stable marker–trait associations each for UHML and Str were detected. For each trait, the mean of F 3:4 progeny rows that were grouped based on the six marker genotypes was compared with the mean of F 3:4 progeny rows that were grouped based on phenotype. In all but one case, the mean UHML and Str of F 3:4 progeny rows with the majority of alleles (i.e., four to six alleles) in the desirable state was similar to the mean of F 3:4 progeny rows derived from F 3 plants in the top 20% for UHML and Str. Our results indicate that, after proper validation, published QTL for UHML and Str could be utilized in selection for improved fiber quality.

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