As important yield-related traits,thousand-grain weight(TGW),grain number per spike(GNS)and grain weight per spike(GWS)are crucial components of wheat production.To dissect their underlying genetic basis,a double hapl...As important yield-related traits,thousand-grain weight(TGW),grain number per spike(GNS)and grain weight per spike(GWS)are crucial components of wheat production.To dissect their underlying genetic basis,a double haploid(DH)population comprised of 198 lines derived from 8762/Keyi 5214 was constructed.We then used genechip to genotype the DH population and integrated the yield-related traits TGW,GNS and GWS for QTL mapping.Finally,we obtained a total of 18942 polymorphic SNP markers and identified 41 crucial QTLs for these traits.Three stable QTLs for TGW were identified on chromosomes 2D(QTgw-2D.3 and QTgw-2D.4)and 6A(QTgw-6A.1),with additive alleles all from the parent 8762,explaining 4.81–18.67%of the phenotypic variations.Five stable QTLs for GNS on chromosomes 3D,5B,5D and 6A were identified.QGns-5D.1 was from parent 8762,while the other four QTLs were from parent Keyi 5214,explaining 5.89–7.08%of the GNS phenotypic variations.In addition,a stable GWS genetic locus QGws-4A.3 was detected from the parent 8762,which explained 6.08–6.14%of the phenotypic variations.To utilize the identified QTLs,we developed STARP markers for four important QTLs,Tgw2D.3-2,Tgw2D.4-1,Tgw6A.1 and Gns3D.1.Our results provide important basic resources and references for the identification and cloning of genes related to TGW,GNS and GWS in wheat.展开更多
无人机三维路径规划是一个比较复杂的全局优化问题,其目标是在考虑威胁和约束的条件下,获得最优或接近最优的飞行路径。针对鲸鱼算法在进行无人机三维航迹规划时,存在容易陷入局部最优、收敛速度较慢、收敛精度不够高等问题,提出了一种...无人机三维路径规划是一个比较复杂的全局优化问题,其目标是在考虑威胁和约束的条件下,获得最优或接近最优的飞行路径。针对鲸鱼算法在进行无人机三维航迹规划时,存在容易陷入局部最优、收敛速度较慢、收敛精度不够高等问题,提出了一种基于莱维飞行(Lévy flight)的鲸鱼优化算法(Levy Flight Based on Whale Optimization Algorithm, LWOA),用于解决无人机三维路径规划问题。该算法在迭代过程中加入了Levy飞行对最优解进行随机扰动;引入了信息交流机制,通过当前全局最优解和个体记忆最优解以及邻域最优解来更新个体的位置,能够更好地权衡局部收敛和全局开发。仿真结果表明,所提路径规划算法可以有效避开威胁区,收敛速度更快,收敛精度更高,且更不易陷入局部最优解。当迭代次数为300次、种群个数为50时,LWOA算法求得的成本函数值是PSO算法的91.1%,是GWO算法的92.1%,是WOA算法的95.9%,航迹代价更小。展开更多
解析小麦抗倒伏遗传机制,发掘抗倒伏位点,选育抗倒伏品种,对于保障我国粮食生产安全具有重要意义。周8425B是我国黄淮麦区重要的小麦骨干亲本,农艺性状优良,其衍生品种具有较好的抗倒伏特性。本研究对周8425B及其衍生品种等62份材料的8...解析小麦抗倒伏遗传机制,发掘抗倒伏位点,选育抗倒伏品种,对于保障我国粮食生产安全具有重要意义。周8425B是我国黄淮麦区重要的小麦骨干亲本,农艺性状优良,其衍生品种具有较好的抗倒伏特性。本研究对周8425B及其衍生品种等62份材料的8个抗倒伏相关性状进行评价,并结合50K SNP芯片数据进行全基因组关联分析(GWAS,genome-wide association analysis)。共计检测到226个显著关联SNP标记,分布于21条染色体的42个位点上,分别解释7.0%~18.8%的表型变异。其中,14个位点与已报道的位点一致,其他28个位点为新的位点。另外,还鉴定到3个候选基因(TraesCS5B01G555800、TraesCS3A01G496400和TraesCS6B01G225400),分别编码E3-泛素蛋白连接酶、纤维素合酶和细胞分裂蛋白酶。本研究对于小麦品种抗倒伏性状改良具有参考价值。展开更多
基金the Henan Modern Agricultural Industrial Technology System Construction,China(HARS-22-1-Z7)。
文摘As important yield-related traits,thousand-grain weight(TGW),grain number per spike(GNS)and grain weight per spike(GWS)are crucial components of wheat production.To dissect their underlying genetic basis,a double haploid(DH)population comprised of 198 lines derived from 8762/Keyi 5214 was constructed.We then used genechip to genotype the DH population and integrated the yield-related traits TGW,GNS and GWS for QTL mapping.Finally,we obtained a total of 18942 polymorphic SNP markers and identified 41 crucial QTLs for these traits.Three stable QTLs for TGW were identified on chromosomes 2D(QTgw-2D.3 and QTgw-2D.4)and 6A(QTgw-6A.1),with additive alleles all from the parent 8762,explaining 4.81–18.67%of the phenotypic variations.Five stable QTLs for GNS on chromosomes 3D,5B,5D and 6A were identified.QGns-5D.1 was from parent 8762,while the other four QTLs were from parent Keyi 5214,explaining 5.89–7.08%of the GNS phenotypic variations.In addition,a stable GWS genetic locus QGws-4A.3 was detected from the parent 8762,which explained 6.08–6.14%of the phenotypic variations.To utilize the identified QTLs,we developed STARP markers for four important QTLs,Tgw2D.3-2,Tgw2D.4-1,Tgw6A.1 and Gns3D.1.Our results provide important basic resources and references for the identification and cloning of genes related to TGW,GNS and GWS in wheat.
文摘无人机三维路径规划是一个比较复杂的全局优化问题,其目标是在考虑威胁和约束的条件下,获得最优或接近最优的飞行路径。针对鲸鱼算法在进行无人机三维航迹规划时,存在容易陷入局部最优、收敛速度较慢、收敛精度不够高等问题,提出了一种基于莱维飞行(Lévy flight)的鲸鱼优化算法(Levy Flight Based on Whale Optimization Algorithm, LWOA),用于解决无人机三维路径规划问题。该算法在迭代过程中加入了Levy飞行对最优解进行随机扰动;引入了信息交流机制,通过当前全局最优解和个体记忆最优解以及邻域最优解来更新个体的位置,能够更好地权衡局部收敛和全局开发。仿真结果表明,所提路径规划算法可以有效避开威胁区,收敛速度更快,收敛精度更高,且更不易陷入局部最优解。当迭代次数为300次、种群个数为50时,LWOA算法求得的成本函数值是PSO算法的91.1%,是GWO算法的92.1%,是WOA算法的95.9%,航迹代价更小。
文摘解析小麦抗倒伏遗传机制,发掘抗倒伏位点,选育抗倒伏品种,对于保障我国粮食生产安全具有重要意义。周8425B是我国黄淮麦区重要的小麦骨干亲本,农艺性状优良,其衍生品种具有较好的抗倒伏特性。本研究对周8425B及其衍生品种等62份材料的8个抗倒伏相关性状进行评价,并结合50K SNP芯片数据进行全基因组关联分析(GWAS,genome-wide association analysis)。共计检测到226个显著关联SNP标记,分布于21条染色体的42个位点上,分别解释7.0%~18.8%的表型变异。其中,14个位点与已报道的位点一致,其他28个位点为新的位点。另外,还鉴定到3个候选基因(TraesCS5B01G555800、TraesCS3A01G496400和TraesCS6B01G225400),分别编码E3-泛素蛋白连接酶、纤维素合酶和细胞分裂蛋白酶。本研究对于小麦品种抗倒伏性状改良具有参考价值。
