为了对黄河鲤体质量性状进行全基因组关联分析及全基因组选择模型的预测准确性比较,采用鲤250K高密度SNP芯片对613尾黄河鲤(Cyprinus carpio)进行基因分型,并通过测定其体质量性状的表型信息进行全基因组关联分析,以及基于体质量性状、...为了对黄河鲤体质量性状进行全基因组关联分析及全基因组选择模型的预测准确性比较,采用鲤250K高密度SNP芯片对613尾黄河鲤(Cyprinus carpio)进行基因分型,并通过测定其体质量性状的表型信息进行全基因组关联分析,以及基于体质量性状、全基因组关联分析(genome-wide association study,GWAS)的不同变异数据集对GBLUP、贝叶斯、RKHS和机器学习模型等10种全基因组选择模型的预测准确性进行比较,以筛选出适用于黄河鲤体质量性状的全基因组选择模型。结果表明:通过GWAS定位到与体质量性状相关的5个SNP,位于1号和21号染色体上,进一步筛选关联SNP所在区域的基因,定位到WBP1L、GPM6B、TIMMDC1、RCAN1、EOGT基因;当选取与黄河鲤体质量性状表型相关的前100个SNP作为数据集,分析全基因组选择模型预测准确性时,机器学习模型XGBoost的预测准确性最高,为0.26,当SNP的数量分别为500、1000、3000、5000、20000时,GBLUP模型的准确性均最高,分别为0.3084、0.3444、0.4393、0.4526、0.4007,而XGBoost、LightGBM和GBLUP模型的变异系数则较低,说明模型预测的稳定性相对可靠。研究表明,本研究中共鉴定到5个与黄河鲤体质量性状相关的候选基因,分别为WBP1L、GPM6B、TIMMDC1、RCAN1、EOGT,10种全基因组选择模型中GBLUP模型的预测准确性最高,可用于黄河鲤体质量性状的基因组选育。展开更多
In recent years,smart textiles have attracted the attention of scholars from all walks of life,but there is an imbalance between functionality and usability,which affects their marketization process.Firstly,five repre...In recent years,smart textiles have attracted the attention of scholars from all walks of life,but there is an imbalance between functionality and usability,which affects their marketization process.Firstly,five representative smart textiles are introduced and their respective wearability is described around preparation methods.Secondly,it is concluded that the preparation methods of smart textiles can be divided into two categories:fiber methods and finishing methods.The fiber methods refer to making smart fibers into smart textiles.Textiles made by fiber methods are breathable and feel good in the hand,but the mechanical properties are influenced by the production equipment,and the process cost is high.The finishing methods refer to the functional finishing of ordinary textiles.Although the finishing method is simple and convenient,it may reduce the comfort of the textile.Finally,applications and new research in various fields of smart textiles are presented with promising prospects.It is anticipated that this review will serve as a theoretical basis for future research and development of smart textiles.Researchers are expected to create new technologies to overcome the tension between functionality and usability,as well as to increase user comfort and convenience.展开更多
文摘为了对黄河鲤体质量性状进行全基因组关联分析及全基因组选择模型的预测准确性比较,采用鲤250K高密度SNP芯片对613尾黄河鲤(Cyprinus carpio)进行基因分型,并通过测定其体质量性状的表型信息进行全基因组关联分析,以及基于体质量性状、全基因组关联分析(genome-wide association study,GWAS)的不同变异数据集对GBLUP、贝叶斯、RKHS和机器学习模型等10种全基因组选择模型的预测准确性进行比较,以筛选出适用于黄河鲤体质量性状的全基因组选择模型。结果表明:通过GWAS定位到与体质量性状相关的5个SNP,位于1号和21号染色体上,进一步筛选关联SNP所在区域的基因,定位到WBP1L、GPM6B、TIMMDC1、RCAN1、EOGT基因;当选取与黄河鲤体质量性状表型相关的前100个SNP作为数据集,分析全基因组选择模型预测准确性时,机器学习模型XGBoost的预测准确性最高,为0.26,当SNP的数量分别为500、1000、3000、5000、20000时,GBLUP模型的准确性均最高,分别为0.3084、0.3444、0.4393、0.4526、0.4007,而XGBoost、LightGBM和GBLUP模型的变异系数则较低,说明模型预测的稳定性相对可靠。研究表明,本研究中共鉴定到5个与黄河鲤体质量性状相关的候选基因,分别为WBP1L、GPM6B、TIMMDC1、RCAN1、EOGT,10种全基因组选择模型中GBLUP模型的预测准确性最高,可用于黄河鲤体质量性状的基因组选育。
基金Innovation Team Building Program of Beijing Institute of Fashion Technology,China。
文摘In recent years,smart textiles have attracted the attention of scholars from all walks of life,but there is an imbalance between functionality and usability,which affects their marketization process.Firstly,five representative smart textiles are introduced and their respective wearability is described around preparation methods.Secondly,it is concluded that the preparation methods of smart textiles can be divided into two categories:fiber methods and finishing methods.The fiber methods refer to making smart fibers into smart textiles.Textiles made by fiber methods are breathable and feel good in the hand,but the mechanical properties are influenced by the production equipment,and the process cost is high.The finishing methods refer to the functional finishing of ordinary textiles.Although the finishing method is simple and convenient,it may reduce the comfort of the textile.Finally,applications and new research in various fields of smart textiles are presented with promising prospects.It is anticipated that this review will serve as a theoretical basis for future research and development of smart textiles.Researchers are expected to create new technologies to overcome the tension between functionality and usability,as well as to increase user comfort and convenience.
