Nitrogen(N), phosphorus(P), and potassium(K) are essential macronutrients that are crucial not only for maize growth and development, but also for crop yield and quality. The genetic basis of macronutrient dynamics an...Nitrogen(N), phosphorus(P), and potassium(K) are essential macronutrients that are crucial not only for maize growth and development, but also for crop yield and quality. The genetic basis of macronutrient dynamics and accumulation during grain filling in maize remains largely unknown. In this study, we evaluated grain N, P, and K concentrations in 206 recombinant inbred lines generated from a cross of DH1M and T877 at six time points after pollination. We then calculated conditional phenotypic values at different time intervals to explore the dynamic characteristics of the N, P, and K concentrations. Abundant phenotypic variations were observed in the concentrations and net changes of these nutrients. Unconditional quantitative trait locus(QTL) mapping revealed 41 non-redundant QTLs, including 17, 16, and 14 for the N, P, and K concentrations, respectively. Conditional QTL mapping uncovered 39 non-redundant QTLs related to net changes in the N, P, and K concentrations. By combining QTL, gene expression, co-expression analysis, and comparative genomic data, we identified 44, 36, and 44 candidate genes for the N, P, and K concentrations, respectively, including GRMZM2G371058 encoding a Doftype zinc finger DNA-binding family protein, which was associated with the N concentration, and GRMZM2G113967encoding a CBL-interacting protein kinase, which was related to the K concentration. The results deepen our understanding of the genetic factors controlling N, P, and K accumulation during maize grain development and provide valuable genes for the genetic improvement of nutrient concentrations in maize.展开更多
This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expan...This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.展开更多
基金supported by the Seed Industry Revitalization Project of Jiangsu Province,China(JBGS[2021]009)the National Natural Science Foundation of China(32061143030 and 31972487)+3 种基金the Jiangsu Province University Basic Science Research Project,China(21KJA210002)the Key Research and Development Program of Jiangsu Province,China(BE2022343)the Innovative Research Team of Universities in Jiangsu Province,China,the High-end Talent Project of Yangzhou University,China,the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD),Chinathe Qing Lan Project of Jiangsu Province,China。
文摘Nitrogen(N), phosphorus(P), and potassium(K) are essential macronutrients that are crucial not only for maize growth and development, but also for crop yield and quality. The genetic basis of macronutrient dynamics and accumulation during grain filling in maize remains largely unknown. In this study, we evaluated grain N, P, and K concentrations in 206 recombinant inbred lines generated from a cross of DH1M and T877 at six time points after pollination. We then calculated conditional phenotypic values at different time intervals to explore the dynamic characteristics of the N, P, and K concentrations. Abundant phenotypic variations were observed in the concentrations and net changes of these nutrients. Unconditional quantitative trait locus(QTL) mapping revealed 41 non-redundant QTLs, including 17, 16, and 14 for the N, P, and K concentrations, respectively. Conditional QTL mapping uncovered 39 non-redundant QTLs related to net changes in the N, P, and K concentrations. By combining QTL, gene expression, co-expression analysis, and comparative genomic data, we identified 44, 36, and 44 candidate genes for the N, P, and K concentrations, respectively, including GRMZM2G371058 encoding a Doftype zinc finger DNA-binding family protein, which was associated with the N concentration, and GRMZM2G113967encoding a CBL-interacting protein kinase, which was related to the K concentration. The results deepen our understanding of the genetic factors controlling N, P, and K accumulation during maize grain development and provide valuable genes for the genetic improvement of nutrient concentrations in maize.
基金Under the auspices of Chinese National Funding of Social Sciences (No.17AGL005)Institute of Socialism with Chinese Characteristics of Southeast University (No.DDZTZK2021C11)。
文摘This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.