Ten upland cotton strains exhibiting 3 fiber quality traits and 8 yield traits,were grown for two years in an investigation of the correlation between grey relational analysis(GRA) and genetic identity in heterosis of...Ten upland cotton strains exhibiting 3 fiber quality traits and 8 yield traits,were grown for two years in an investigation of the correlation between grey relational analysis(GRA) and genetic identity in heterosis of cotton hybrid. The aim was to establish the optimal approach for heterosis prediction and parent selection. Plant traits data were collected and analyzed for GRA. In addition,72 simple sequence repeat(SSR) markers were examined and 148 polymorphisms were detected. Correlation analysis of GRA,genetic identity,F1 fiber quality and yield heterosis was conducted. Significant differences were observed between the two analytic methods,whereas comparable predictions were given for yield heterosis. GRA for yield exhibited slightly higher correlation than genetic identity analysis,with a correlation coefficient of 0.49. GRA and genetic analysis exhibited overlapping yet distinct advantages in heterosis prediction. Therefore,these analytical methods should be integrated to achieve the optimal heterosis prediction and parent selection.展开更多
A promising way to uncover the genetic architectures underlying complex traits may lie in the ability to recognize the genetic variants and expression transcripts that are responsible for the traits' inheritance.H...A promising way to uncover the genetic architectures underlying complex traits may lie in the ability to recognize the genetic variants and expression transcripts that are responsible for the traits' inheritance.However,statistical methods capable of investigating the association between the inheritance of a quantitative trait and expression transcripts are still limited.In this study,we described a two-step approach that we developed to evaluate the contribution of expression transcripts to the inheritance of a complex trait.First,a mixed linear model approach was applied to detect significant trait-associated differentially expressed transcripts.Then,conditional analysis were used to predict the contribution of the differentially expressed genes to a target trait.Diallel cross data of cotton was used to test the application of the approach.We proposed that the detected differentially expressed transcripts with a strong impact on the target trait could be used as intermediates for screening lines to improve the traits in plant and animal breeding programs.It can benefit the discovery of the genetic mechanisms underlying complex traits.展开更多
基金Hi-tech Research and Development Program of China(No.2012AA101108-02)National Science and Technology Pillar Program(No.2011BAD35B05)Modern Agro-industry Technology Research System(No.CARS-18-05)
文摘Ten upland cotton strains exhibiting 3 fiber quality traits and 8 yield traits,were grown for two years in an investigation of the correlation between grey relational analysis(GRA) and genetic identity in heterosis of cotton hybrid. The aim was to establish the optimal approach for heterosis prediction and parent selection. Plant traits data were collected and analyzed for GRA. In addition,72 simple sequence repeat(SSR) markers were examined and 148 polymorphisms were detected. Correlation analysis of GRA,genetic identity,F1 fiber quality and yield heterosis was conducted. Significant differences were observed between the two analytic methods,whereas comparable predictions were given for yield heterosis. GRA for yield exhibited slightly higher correlation than genetic identity analysis,with a correlation coefficient of 0.49. GRA and genetic analysis exhibited overlapping yet distinct advantages in heterosis prediction. Therefore,these analytical methods should be integrated to achieve the optimal heterosis prediction and parent selection.
基金supported by the National Basic Research Program of China(2011CB109306)the National High Technology Research and Development Program of China(2009ZX08009-004B,2011AA10A102)+2 种基金the CNTC(110200701023)the YNTC(08A05)the earmearked fund for Modern Agro-industry Technology Reasearch System(CARS-18-05)
文摘A promising way to uncover the genetic architectures underlying complex traits may lie in the ability to recognize the genetic variants and expression transcripts that are responsible for the traits' inheritance.However,statistical methods capable of investigating the association between the inheritance of a quantitative trait and expression transcripts are still limited.In this study,we described a two-step approach that we developed to evaluate the contribution of expression transcripts to the inheritance of a complex trait.First,a mixed linear model approach was applied to detect significant trait-associated differentially expressed transcripts.Then,conditional analysis were used to predict the contribution of the differentially expressed genes to a target trait.Diallel cross data of cotton was used to test the application of the approach.We proposed that the detected differentially expressed transcripts with a strong impact on the target trait could be used as intermediates for screening lines to improve the traits in plant and animal breeding programs.It can benefit the discovery of the genetic mechanisms underlying complex traits.
