Background:Genetic improvement in fiber quality is one of the main challenges for cotton breeders.Quantitative trait loci(QTL)mapping provides a powerful approach to dissect the molecular mechanism in fiber quality tr...Background:Genetic improvement in fiber quality is one of the main challenges for cotton breeders.Quantitative trait loci(QTL)mapping provides a powerful approach to dissect the molecular mechanism in fiber quality traits.In present study,F14 recombinant inbred line(RIL)population was backcrossed to paternal parent for a paternal backcross(BC/P)population,deriving from one upland cotton hybrid.Three repetitive BC/P field trials and one maternal backcross(BC/M)field trial were performed including both two BC populations and the original RIL population.Results:In total,24 novel QTLs are detected for fiber quality traits and among which 13 QTLs validated previous results.Thirty-five QTLs in BC/P populations explain 5.01%–22.09%of phenotype variation(PV).Among the 35 QTLs,23 QTLs are detected in BC/P population alone.Present study provides novel alleles of male parent for fiber quality traits with positive genetic effects.Particularly,qFS-Chr3–1 explains 22.09%of PV in BC/P population,which increaseds 0.48 cN·tex−1 for fiber strength.A total of 7,2,8,2 and 6 QTLs explain over 10.00%of PV for fiber length,fiber uniformity,fiber strength,fiber elongation and fiber micronaire,respectively.In RIL population,six common QTLs are detected in more than one environment:qFL-Chr1–2,qFS-Chr5–1,qFS-Chr9–1,qFS-Chr21–1,qFM-Chr9–1 and qFM-Chr9–2.Two common QTLs of qFE-Chr2–2(TMB2386-SWU12343)and qFM-Chr9–1(NAU2873-CGR6771)explain 22.42%and 21.91%of PV.The region between NAU4034 and TMB1296 harbor 30 genes(379 kb)in A05 and 42 genes(49 kb)in D05 for fiber length along the QTL qFL-Chr5–1 in BC/P population,respectively.In addition,a total of 142 and 46 epistatic QTLs and QTL×environments(E-QTLs and QQEs)are identified in recombinant inbred lines in paternal backcross(RIL-P)and paternal backcross(BC/P)populations,respectively.Conclusions:The present studies provide informative basis for improving cotton fiber quality in different populations.展开更多
One-bit compressed sensing （CS） technology reconstructs the sparse signal when the available measurements are reduced to only their sign-bit. It is well known that CS reconstruction should know the measurement matri...One-bit compressed sensing （CS） technology reconstructs the sparse signal when the available measurements are reduced to only their sign-bit. It is well known that CS reconstruction should know the measurement matrix exactly to obtain a correct result. However, the measurement matrix is probably perturbed in many practical scenarios. An iterative algorithm called perturbed binary iterative hard thresholding （PBIHT） is proposed to reconstruct the sparse signal from the binary measurements （sign measurements） where the measurement matrix experiences a general perturbation. The proposed algorithm can reconstruct the original data without any prior knowledge about the perturbation. Specifically, using the ideas of the gradient descent, PBIHT iteratively estimates signal and perturbation until the estimation converges. Simulation results demonstrate that, under certain conditions, PBIHT improves the performance of signal reconstruction in the perturbation scenario.展开更多
基金the National Key R&D Program for Crop Breeding(2016YFD0101407)to Hua JP.
文摘Background:Genetic improvement in fiber quality is one of the main challenges for cotton breeders.Quantitative trait loci(QTL)mapping provides a powerful approach to dissect the molecular mechanism in fiber quality traits.In present study,F14 recombinant inbred line(RIL)population was backcrossed to paternal parent for a paternal backcross(BC/P)population,deriving from one upland cotton hybrid.Three repetitive BC/P field trials and one maternal backcross(BC/M)field trial were performed including both two BC populations and the original RIL population.Results:In total,24 novel QTLs are detected for fiber quality traits and among which 13 QTLs validated previous results.Thirty-five QTLs in BC/P populations explain 5.01%–22.09%of phenotype variation(PV).Among the 35 QTLs,23 QTLs are detected in BC/P population alone.Present study provides novel alleles of male parent for fiber quality traits with positive genetic effects.Particularly,qFS-Chr3–1 explains 22.09%of PV in BC/P population,which increaseds 0.48 cN·tex−1 for fiber strength.A total of 7,2,8,2 and 6 QTLs explain over 10.00%of PV for fiber length,fiber uniformity,fiber strength,fiber elongation and fiber micronaire,respectively.In RIL population,six common QTLs are detected in more than one environment:qFL-Chr1–2,qFS-Chr5–1,qFS-Chr9–1,qFS-Chr21–1,qFM-Chr9–1 and qFM-Chr9–2.Two common QTLs of qFE-Chr2–2(TMB2386-SWU12343)and qFM-Chr9–1(NAU2873-CGR6771)explain 22.42%and 21.91%of PV.The region between NAU4034 and TMB1296 harbor 30 genes(379 kb)in A05 and 42 genes(49 kb)in D05 for fiber length along the QTL qFL-Chr5–1 in BC/P population,respectively.In addition,a total of 142 and 46 epistatic QTLs and QTL×environments(E-QTLs and QQEs)are identified in recombinant inbred lines in paternal backcross(RIL-P)and paternal backcross(BC/P)populations,respectively.Conclusions:The present studies provide informative basis for improving cotton fiber quality in different populations.
文摘结构刚度、振动及开口处强度影响开口甲板服役寿命。针对开口甲板型式,以多项式惩罚模型(Polynomial penalization model,PPM)为理论依据并辅以三段式延拓(Three-stage continuation,TSC)法,提出一种基于折衷规划法(Compromise programming method,CPM)和改进博弈论四重组合赋权法(Improved fourfold combination weighting model of game theory,IFCWGT)的强度-刚度-振动多目标拓扑优化(Topology optimization,TO)综合策略。为缓解传统变密度法收敛至局部最优解及局部模态问题,将应用TSC技术的PPM引入至开口甲板多目标概念设计领域。建立结合CPM和PPM-TSC的最大单元应力最小化、静态多应变能最小化、动态多频率最大化的多目标TO模型并应用β法以获取Pareto妥协解。提出利用博弈论思想无偏好耦合层次分析(Analytic hierarchy process,AHP)法、熵权法(Entropy weight method,EWM)、基于层间相关性(Criteria importance through intercriteria correlation,CRITIC)法及变异系数法(Coefficient of variation method,CVM)的IFCWGT策略,以得到兼具设计决策者主观价值和数据客观性的子目标综合权重因子。研究表明,所提出的融合四种主客观赋权法的IFCWGT技术在子目标权重分配及开口甲板拓扑性能、拓扑布局方面更具先进性。
基金supported by the National Natural Science Foundation of China ( 61302084,61771066)
文摘One-bit compressed sensing （CS） technology reconstructs the sparse signal when the available measurements are reduced to only their sign-bit. It is well known that CS reconstruction should know the measurement matrix exactly to obtain a correct result. However, the measurement matrix is probably perturbed in many practical scenarios. An iterative algorithm called perturbed binary iterative hard thresholding （PBIHT） is proposed to reconstruct the sparse signal from the binary measurements （sign measurements） where the measurement matrix experiences a general perturbation. The proposed algorithm can reconstruct the original data without any prior knowledge about the perturbation. Specifically, using the ideas of the gradient descent, PBIHT iteratively estimates signal and perturbation until the estimation converges. Simulation results demonstrate that, under certain conditions, PBIHT improves the performance of signal reconstruction in the perturbation scenario.
