Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/6/2003
Publication Date: 6/1/2003
Citation: KATAM, R., QURESHI, S.N., WU, J., SAHA, S., JENKINS, J.N., MCCARTY JR, J.C., REDDY, U.K., KANTETY, R.V., ZHU, J. EST-SSR: USEFUL MARKERS FOR MOLECLAR MAPPING IN COTTON. CD-ROM. Proceedings Beltwide Cotton Conference. 2003. p. 884.
Technical Abstract: Selection of suitable markers is one of the key factors for the success of marker assisted selection program (MAS) in cotton breeding. The primary limitations in the application of MAS are: the limited number of available informative molecular markers and information about the association of these markers with important traits. Here, we present a preliminary progress report on: (1) the identification of a set of EST-SSR markers and (2) developing a linkage map of agronomic and fiber traits with EST-SSR markers. We identified about 133 putative EST-SSR sequence data by mining Gossypium hirsutum EST databases. The intraspecies polymorphism rate of these EST-SSR markers among G. hirsutum cotton cultivars was 26% and interspecific polymorphism between G. hirsutum and G. barbadense was 49%. We also discovered about 1900 sequences containing an SSR motif of at least 18 bp length from G. arboreum EST database. In the past, SSRs have been developed in cotton based on isolating and sequencing clones containing putative SSR tracts, together with designing and testing flanking primers. These methods are typically costly, time-consuming and labor-intensive. Here we report a cost-effective, rapid and efficient strategy of developing EST-SSR markers in cotton by exploiting EST databases of GeneBank. We analyzed agronomic and fiber data of 192 Upland cotton recombinant inbred (RI) lines in replicated plots, over a two year period. Currently work is in progress in developing a linkage map of QTLs and EST-SSR markers using these RI lines. These markers will provide, for the first time, information about DNA markers that may give more direct estimates of diversity in functional genome and identify the relation of the transcribed region with important QTLs.