Analysis Of Sea Island Cotton F_2:5 Population Of The Yield And Fusarium Wilt Genetic For QTL Mapping

In this research, a RIL population with107lines from the sea island cotton cross06-146and xinhai14.These lines adopted two areas two years of data were used to analysis the correlation between yield andFusarium wilt related traits; in this study, genetic linkage map was constructed with the polymorphic SSRmarkers.Based on the map, the QTLs for Fusarium wilt and resistance to Fusarium wilt were identifiedwith Composite Interval Mapping （CIM） method. Using marker assisted-selection which is closely linkedwith cotton Fusarium wilt Resistance QTLs, and this could provide scientific basis and methods in themolecular marker assisted selection （MAS） breeding programs.（1） F_2:5groups phenotypic variation in Env1, Env2, Env3, Env4conditions:in Env1, Env2, Env4environment:the variation coefficient of effective number is the maximum,the second is the variationcoefficient of effective branch number, variation coefficient of single boll weight is the minimum;however,variation coefficient of effective number is the maximum, lint variation coefficient is the minimum, theresults have a deviation value with the other three environment in the Env3environment.Increasing theeffective number and the number of branch in breeding can improve the cotton production;some smallervariation coefficient of yield traits, however, is not conducive to varieties breeding.（2） Gossypium barbadense yield correlation analysis show that:the phenotypic correlation between yieldand the bell number, boll weight, lint yield, seed index, fiber index, boll number and lint, boll weight andseed index, fiber index, seed index and fiber index achieved at a positive and significant level; while thephenotypic correlation between disease level and the number of section in the beginning, beginning sectionhigh, branch number, bell number, lint, yield is negative, which shows that the more serious blight diseaseis, the more damage to some agronomic traits and yield traits of sea island cotton.（3） Menstruation results show that the sea island cotton yield components for the relative importance offactors of production: the bell number> single boll weight>fiber index> seed index.Thus, it’s an importantaspect of the production to improve variety adaptability, resistance and boll number per plant at the sametime to increase single boll weight, fiber index and seed index gradually.（4） Correlation analysis results show that the sea island cotton yield is a comprehensive traits by manyfactors such as bell number, boll weight, lint, etc.Yield components restrict each other, among them the bellis the dominant factor restricting the number of branch, branch number and plant height is the dominantfactor of restricting the bell, Seed index is the dominant factor to single boll weight, fiber index is thedominant factor to lint, single boll weight and seed index is the dominant factor to fiber index, single boll weight is the dominant factor to seed index, and change any production form factors can change theoutput.Therefore, we should not pursuit the one-sided single factor in breeding selection, and should beoptimize the combination of yield components and yield structure, seek the maximum yield potential.（5） The principal component analysis shows that: the first factor is mainly composed of single bollweight, fiber index, seed index, effective branch number and effective boll number; the second factors ismainly decided by the high beginning section, the third factors mainly decided by the section number in thebeginning, the forth factor mainly is decided by lint, the fifth factor mainly is decided by plant height.（6） We selected32blight resistant strains from two years experiment in F_2:5 groups, the highest yield isthe result of the achievement of the best balance between various yield components and considering thevariety effect, varieties×location effect and varieties×breeds three effect value:Comprehensive evaluationfor the best strain are10852,10868; Followed by10840,10892; good strains are10826,10729,10777,10846,10832,10846,10832,10774,10750,10749,10858,10727,10858,10727; general strains are10816,10904,10747,10825,10902,10873,10846,10719,10726,10890,10893,10890; poor strain are10787,10710.（7） This study use Mapmaker3.0and JoinMap4.0software make linkage analysis about240pairspolymorphism SSR markers loci, adopt the Kosambi function, LOD values set to3.0. Preliminaryconstructed15linkage group, this graph contains240polymorphism marker, total length is3962.56cM,the genetic map genome coverage rate of the built the integration is about79.25%, average distancebetween markers is16.65cM, covered15cotton genome chromosome.（8） This study used WinQTLCartV2.0and MapQTL5.0software, composite interval mapping method isadopted to improve the disease resistance QTL mapping, LOD values is3.0,12possible QTLs weredetected, respectively located in Chr1,Chr3,Chr8, Chr12, Chr16, Chr26. In the Evn1, Evn3, Evn4environment can detect qFw8-1, qFw3-1, qFw26-1-1, qFw1-1QTL, focus on chromosome8,3,26,1, andthe chromosome control the hot section of disease characters, and extremely stable, the gene controlledblight probably exists in the quantitative traits of seat.