Identification Of Stable QTLs For Fiber Quality Traits Across Diverse Environments In Upland Cotton RIL Population

Cotton is an important industrial crop famous for its fiber. With revolutions in textile industry it become empirical for cotton breeders to produce and develop cotton verities with better fiber qualities. One way to improve fiber quality is by conventional breeding which is no doubt a good way but is laborious and time consuming. If we combine this conventional breeding with marker assisted selection(MAS) we can achieve our goals more quickly. In MAS we select markers which are tightly linked to some major quantitative trait loci(QTLs) of interest. To facilitate MAS, it is needed to identify stable QTLs with major effects and genetic map for a mapping population is a pre-requisite for QTL mapping. Many QTLs has been reported until now using different mapping population but QTLs identified in intraspecific cross have fewer obstacle in cotton breeding program through MAS.Cotton has four cultivated species including two diploid species Gossypium arboretum and G. herbecium and two tetraploid species including G. hirsutum and G. barbadense. Two diploid species G. arboretum(A genome) and G. raimondii(D genome) are potential donor of tetraploid cotton or upland cotton. In previous studies it has been observed that Dt sub-genome contained more QTLs related to fiber development than At sub-genome. So we selected G. raimondii(D genome) sequence based primers because of the importance of Dt sub-genome in fiber development.In this study a recombinant inbred line(RIL) population derived from a cross between two upland cotton cultivars s GK9708 and 0-153 has been used to construct a linkage map. We used 15203 markers including 12560 D genome sequence based SSR markers to find polymorphism between two parental lines(s GK9708 and 0-153). Then all selected polymorphic primer pairs were used to screen RIL population(contained 196 lines) along with two parents and F1. In total 505 primer pairs which produced 604 loci were used to construct a linkage map, among which 395 were successfully mapped into 60 linkage groups. The map covered a total distance of 2034.9c M, approximately 50% of upland cotton genome. This constructed linkage map was used to identify QTLs for fiber quality traits in eleven different environments. In total 115 QTLs were identified on 20 chromosomes, among which 33 QTLs were mapped on At sub-genome while 82 were mapped on Dt sub-genome. Three chromosomes c4, c14 and c25 contained more QTLs as compared to other chromosomes, while six chromosomes c2, c8, c9, c17, c18, and c26 have no QTL. Co-localization of QTLs or QTL clusters were identified on six chromosomes including c4, c7, c10, c14, c21 and c25. Seventy eight QTLs out of 115 were resided in these cluster regions. Twenty seven QTLs were identified as stable QTLs including 7 for fiber length, six for fiber strength, 4 for fiber elongation, 3 for fiber uniformity and 7 for fiber micronaire.Previously two genetic maps have been established by our research team which covers 30% of the genome. In second step we combined our SSR data with previous SSR data to construct a high density map and identify QTL for fiber quality traits. In total 997 loci has been used to construct a linkage map which covered a genetic distance of 4110 c M an average distance of 5.2c M between adjacent markers. This map covered almost 93.2% of upland cotton genome and was utilized to identify QTLs for fiber quality traits in eleven environments. In total 165 QTLs were identify among which 47 were declared as stable QTLs. Co-localization or QTL clustering was also observed and 103 QTLs were resided in 30 QTL cluster regions. These clusters were equally distributed among sub-genomes i.e. 16 cluster were mapped on At sub-genome while 14 clusters were identified on Dt sub-genome. QTLs were unequally distributed among sub-genome and more QTLs(107 QTLs) were identified on Dt sub-genome chromosomes than At sub-genome(58 QTL). Four chromosome were rich in QTLs clusters including c4, c7, c14 and c25. Biomercator v4.2 has been used to integrate QTL data of our RIL population and QTL data with previous studies to perform meta-analysis. Ninety QTLs were identified as common with previous reports while 75 QTLs were identified as novel ones. Meta-analysis revealed that c4, c7, c14 and c25 contained meta-clusters which means these chromosomes contained consistent QTL regions which can be utilized in MAS to improve fiber quality of upland cotton.Fiber quality data from eleven environments showed that these traits values were normally distributed. Broad sense heritability(H2B) estimates of these traits were range from low for fiber elongation(0.27) to high for fiber length(0.93), fiber strength(0.92), fiber micronaire(0.85), and fiber uniformity(0.80). High value of H2 B shows that QTLs identified in this population will be useful for future in cotton breeding program through MAS. Multi environmental evaluation and meta-analysis provide us opportunity to identify true and stable QTLs. Moreover population used in this report has been developed from intraspecific cross between two upland cotton cultivar, so QTLs identified in this population have few hindrance to use in MAS.