Qtl Mapping For Traits Related To Boll Weight In Upland Cotton(Gossypium Hirsutum L.)

Cotton plays an important role in the development of China’s economic. Boll weight is one of the most important yielding components. In the recent years, many researches focused on QTL mapping for cotton agronomic traits but less for boll especially for the boll weight-related traits such as boll width, boll length, locule number of boll and boll coat weight. In this study, F2individuals and F2:3families were constructed using two parents with significant differences on boll weight-related traits. QTL mapping were performed using SSR molecular markers, and it will lay the foundation for marker-assisted selection to improve cotton yielding.1. Construction of genetic linkage mapAbout8200SSR markers were employed to screen polymorphisms between two parents, AQ and08-10604, approximately3.22%(264/8200) of SSR primers showed polymorphic. Using these polymorphic primers to genotype F2individuals, two hundred and eighty-four loci yielded, of which155loci were codominant, one hundred and twenty-nine loci dominant. There were45loci (17.31%) showed segregation distortion and37loci were mapped.Two hundred and thirty loci were assigned onto16chromosomes of cotton genome using JoinMap3.0software at a LOD>4, including28linkage groups. The total length of the map was1417.28cM, and the average distance between adjacent loci was6.53cM. At length was699.115cM, Dt length718.755cM, and unknown group of chain length120.702cM.2. QTL mappingThe results of correlation analysis showed that the highest positive correlation was between seed yield and boll number per plant and boll weight has higher positive correlation to boll width, boll length and lint weight per boll, which may be associated with the photosynthesis of boll.Totally,73QTLs were mapped for12traits related to boll weight with WinQTLCart2.0by composite interval mapping method in F2individuals and F2:3family, 44QTLs were significant, including12QTLs for boll width,8QTLs for boll length,3QTLs for seed-index,9QTLs for boll coat weight,5QTLs for boll weight,2QTLs for lint percentage,2QTLs for locule number of boll,1QTL for lint weight per boll.1QTL for lint weight and1QTL for seed yield. Using jiont analysis method,32QTLs for traits related to boll weight were mapped and only19QTLs were significant, including6QTLs for boll width,4QTLs for boll length,1QTL for seed-index,3QTLs for boll weight,1QTL for lint percentage,2QTLs for locule number of boll,2QTLs for lint weight per boll.28QTLs were located for5fiber traits in F2and F2:3and12QTLs were significant, including2QTLs for fiber length,2QTLs for fiber strength,4QTLs for Micronaire,3QTLs for Fiber uniformity ratio. Using jiont analysis method,14QTLs for fiber quality were detected,5QTLs were significant, including3QTLs for fiber length,1QTL for fiber strength,1QTL for Micronaire.More QTLs about boll width and boll length were detected.4and1significant QTLs for boll weight from AQ were found in F2and F2:3respectively, explaining2.1%-10.6%of POV. Only a few of QTLs about boll width were found in the same or neighbored position on A10、Dl and D5, and one same QTL about boll length was found in the same or neighbored position on A13with higher percentage of POV. It can be speculated that boll width and boll length are more stable.