Genetic Analysis And Mapping Of Major QTL On Yield And Fiber Quality Related Traits In Cotton Chromosome Segment Substitution Lines

Cotton（Gossypium spp.） is one of the most important cash crops and the leading fiber resource for the textile industry worldwide. Most global cotton production involves two cultivated species, G. hirsutum and G. barbadense. G. hirsutum, also known as Upland cotton, represents 95% of global cotton fiber production. G. barbadense, another important tetraploid cultivated species, has excellent fiber quality and disease resistance compared to Upland cotton, which exhibits high yield but only moderate fiber quality. The narrow genetic base and limited genetic diversity of Upland cotton has become a serious concern for genetic improvement of lint yield and fiber quality in cotton breeding. Interspecific introgression can be used to transfer valuable alien genes from G. barbadense germplasm for the improvement of upland cotton species.Chromosome segment substitution lines（CSSLs, often referred to as introgression lines）, which include near-isogenic lines covering the entire genome of a crop, can be developed by crossing donor and recipient parents, backcrossing to the recipient parent and using molecular marker-assisted selection（MAS）. In this process, one or a few homozygous chromosome segments are derived from the donor parent and the rest of the genome is the same as that of the recipient parent. These lines serve as ideal tools for quantitative genetics, utilization of heterosis and gene pyramiding breeding.In this study, we used two sets of CSSLs, Pop36（CCRI 36 × Hai1 BC5F3:5） and Pop45（CCRI 45 × Hai1 BC4F3:5）, as parents for hybridization. Two sets of population of F₁ hybrids were produced according to two methods, partial diallel mating design and random mating design. We measured and analyzed the genetic effects and heterosis of yield and fiber quality related traits via the additive-dominance genetic model. These materials were planted in 6 environments to evaluate the lint yield and fiber quality traits using the correlation and path analysis. For genotyping, SSR markers have been used for QTL detection, identifying number and size of island chromosome intrograssion fragment. The objectives of this study were to（1） determine the genetic mechanism underlying yield and fiber quality traits of the CSSLs;（2） study the relations among yield and fiber quality traits in CSSLs and clarify the main direction of yield breeding of CSSLs;（3） identify the major QTLs related to yield and fiber quality traits for fine QTL mapping and the marker assisted selection. The main study results were indicated as follows:（1）The heterosis analysis showed that similar expressions of heterosis were detected in two CSSL populations with different genetic backgrounds（Pop36 and Pop45）. Compared to lint percentage, seed index, length, micronaire and strength, average population mid-parent heterosis（MP） of boll weight, boll number, seedcotton yield and lint yield were relatively high. The differences of MP between two CSSL populations were detected for plant height, number of fruiting branches, elongation and uniformity. Compared to lint percentage, the average population better-parent heterosis（HP） of boll weight, seedcotton yield and lint yield were relatively large. HP heterosis was not obvious or negative for other yield and fiber quality traits.（2）In this study, we detected a similar genetic mechanism for yield and fiber quality traits in two CSSL populations with different genetic backgrounds（Pop36 and Pop45）. We found that all yield and fiber quality traits of the CSSLs examined were controlled by genetic effects and their interaction with environment. Lint percentage and seed index were primarily controlled by additive effects and boll weight, boll number, seedcotton yield and lint yield were mainly controlled by dominance effects. Plant height and number of fruiting branches were greatly influenced by environment. Micronaire and uniformity were primarily controlled by genetic effects. Length, strength and elongation were primarily controlled by the interaction between genetic effects and environment. General heritability in the narrow sense for lint percentage and seed index were high, indicating that early generation selection was effective. Boll weight, seedcotton yield and lint yield were greatly influenced by environment, indicating that direct selection is less reliable. Interaction heritability in the broad sense for plant height, boll number, seedcotton yield and lint yield were relatively large, indicating that heterosis can be used in specific environments. In addition, general heritability both in the narrow sense and broad sense for length, micronaire and strength were relatively high, indicating that early generation selection was effective.（3）The results indicated that there were abundant genetic variations both in CSSLs and F₁ hybrids, and some of them had good lint yield and fiber quality. In addition, significant positive heterosis was detected for all traits in both populations（Pop36 and Pop45）, especially for the yield related traits and there were no difference among environments. The results also showed the broad prospect for utilization of heterosis and gene pyramiding breeding of CSSLs in cotton.（4）The correlation analysis showed that no significant correlation between yield and fiber quality traits were detected in F₁ hybrids and CSSLs and slightly different result existed due to different background and type of materials. The results indicated that it was relatively feasible to improve yield and fiber quality simultaneously using CSSLs. Path analysis illustrated that the relations between lint yield and yield components, and the effects of yield components on lint yield were significantly controlled by the background and type of materials and environment.（5）In Pop36, total of 162 QTLs were identified with 101 QTLs for yield related traits, explaining 7.04%¹6.39% of phenotypic variation respectively, in which 12 QTLs were identified in at least 2 environments. We identified 61 QTL for fiber quality, which explained 7.02%³5.48% of the phenotypic variation respectively, in which 22 QTLs were identified in at least 2 environments. In Pop45, total of 150 QTLs were identified with 82 QTLs for yield related traits, explaining 6.31%¹5.29% of phenotypic variation respectively, in which 20 QTLs were identified in at least 2 environments. We identified 68 QTL for fiber quality, which explained 6.68%²3.44% of the phenotypic variation respectively, in which 16 QTLs were identified in at least 2 environments. In addition, all QTLs identified were mapped on 26 chromosomes both in Pop36 and Pop45.（6）In Pop36, 34 QTLs were identified in more than 2 environments, 1 QTL（q FS-20-14） was detected in five environments; 4 QTLs（q FS-7-9, q FS-14-17, q FS-22-1, q FL-7-9） were detected in four environments; 5 QTLs（q FL-7-5, q FL-13-6, q FL-22-1, q FM-14-9, q SI-14-17） were detected in three environments; 24 QTLs were detected in two environments. The number of QTLs for length, strength, boll number, micronaire and elongation was relatively large and more than three. In Pop45, 36 QTLs were identified in more than 2 environments, 9 QTLs（q BN-2-3, q BN-2-7, q BN-19-8, q SY-21-21, q LY-21-21, q FL-15-3, q FM-5-13, q FM-15-5, q FU-11-21） was detected in three environments; 27 QTLs were detected in two environments. The number of QTLs for length, micronaire, boll number, seedcotton yield and lint yield elongation was relatively large and more than four. These stable QTLs are useful for the marker assisted selection.（7）In Pop36, QTL favorable allele of yield related traits was mainly come from CCRI 36, account for 63.4%, and QTL favorable allele of fiber quality was mainly come from Hai 1, account for 59.0%. In Pop45, QTL favorable allele of yield related traits and fiber quality was come from CCRI 36 and Hai 1, respectively, in which had the same proportion.（8）Several QTL clusters or co-localization QTLs were observed in CSSLs, a phenomenon that has been previously reported in cotton. In Pop36, there are 79 makers linkaged to 162 QTLs, and three makers（NAU1085, HAU0883 a, TMB1125） linkaged to more than 8 QTLs, respectively. In Pop36, there are 79 makers linkaged to 162 QTLs, and four makers（BNL1434, DPL0444, GH132, HAU1980b） linkaged to more than 5 QTLs, respectively.（9）In Pop36, more than half of QTLs（91 of 162） affecting yield and fiber quality traits were found to be located on the same chromosomes through a comparative analysis with the previous studies. There are 47 QTLs affecting yield traits and 44 QTLs affecting fiber quality traits. In Pop45, nearly half of QTLs（71 of 150） affecting yield and fiber quality traits were found to be located on the same chromosomes through a comparative analysis with the previous studies. There were 33 QTLs affecting yield traits and 38 QTLs affecting fiber quality traits. In addition, there were 71 QTLs in Pop36 and 79 QTLs in Pop45, which was first detected in our study.