为准确评价高油酸花生种质资源的遗传多样性,本研究以34个阜花系列高油酸花生进行农艺性状及SSR位点分析。结果表明,所有花生品种间主茎高、侧枝长、结果枝数、百果质量、百仁质量差异显著,但是出米率差异较小,稳定在(70.34±0.78)...为准确评价高油酸花生种质资源的遗传多样性,本研究以34个阜花系列高油酸花生进行农艺性状及SSR位点分析。结果表明,所有花生品种间主茎高、侧枝长、结果枝数、百果质量、百仁质量差异显著,但是出米率差异较小,稳定在(70.34±0.78)%之间;采用56对引物对34个阜花系列高油酸花生品种(系)进行多态性分析,筛选出18对引物在这些种质间存在多态性,平均等位位点数为2.89个,Shannon’s信息指数分布在0.06~3.06之间,平均值为1.2,多态性信息含量(polymorphism information content, PIC)指数分布在0.33~0.91之间,平均值为0.66;34个高油酸花生相似系数分布在0.346~0.885之间,平均值为0.661;UPGMA(unweighted pair-group method with arithmetic means)聚类分析表明,所有阜花系列高油酸花生品种(系)分布在不同分枝上,遗传多样性程度较高。研究结果提高了SSR分子标记筛选的效率,也为阜花系列高油酸花生遗传多样性提供参考,为今后高油酸花生种质创制提供依据。展开更多
This study was conducted to analyze the variation of soil multifunctionality(SMF)along elevation and the driving factors in the Altun Shan.Soil samples(0–10 cm)were collected from 15 sites(H01 to H15)at every 200 m e...This study was conducted to analyze the variation of soil multifunctionality(SMF)along elevation and the driving factors in the Altun Shan.Soil samples(0–10 cm)were collected from 15 sites(H01 to H15)at every 200 m elevation interval,covering a total range from 900 m to 3500 m above mean sea level.We investigated climate factors(mean annual temperature,MAT;mean annual precipitation,MAP),soil environment(soil water content,electrical conductance,and pH),vegetation factors,and elevation to determine which of them are the main driving factors of the spatial variability of SMF in the Altun Shan.We explored the best-fit model of SMF along the changes in elevation using a structural equation model,performed variance partitioning analysis(VPA)on SMF with the“varpart”function to explain the relative contribution of various environmental factors to SMF changes,and used a random forest model for relative importance analysis.The results showed that SMF in the Altun Shan significantly increased with elevation in a linear trend.The main driver of changes in SMF was found to be MAP.Although the rise in elevation did not have a significant direct effect on changes in SMF,it could indirectly affect SMF by significantly influencing MAP,p H,MAT,and normalized difference vegetation index(NDVI).When considering climate,soil environment,and vegetation factors together,they explained 76%of the variation in SMF.The largest contribution to the variation in SMF was attributed to the independent effect of climate(0.31)and its interactive effect with soil(0.30).The relative importance of MAP on SMF changes was found to be the greatest.It is indicated that changes in SMF are caused by the combined effect of multiple environmental conditions.These findings are essential for understanding the spatial variability and drivers of SMF in dryland mountain ecosystems,especially concerning the function of mountain ecosystems in the context of global climatic changes.展开更多
文摘为准确评价高油酸花生种质资源的遗传多样性,本研究以34个阜花系列高油酸花生进行农艺性状及SSR位点分析。结果表明,所有花生品种间主茎高、侧枝长、结果枝数、百果质量、百仁质量差异显著,但是出米率差异较小,稳定在(70.34±0.78)%之间;采用56对引物对34个阜花系列高油酸花生品种(系)进行多态性分析,筛选出18对引物在这些种质间存在多态性,平均等位位点数为2.89个,Shannon’s信息指数分布在0.06~3.06之间,平均值为1.2,多态性信息含量(polymorphism information content, PIC)指数分布在0.33~0.91之间,平均值为0.66;34个高油酸花生相似系数分布在0.346~0.885之间,平均值为0.661;UPGMA(unweighted pair-group method with arithmetic means)聚类分析表明,所有阜花系列高油酸花生品种(系)分布在不同分枝上,遗传多样性程度较高。研究结果提高了SSR分子标记筛选的效率,也为阜花系列高油酸花生遗传多样性提供参考,为今后高油酸花生种质创制提供依据。
基金the Tianshan Talent Plan(2022TSYCCX0001)Natural Science Foundation of Xinjiang(2022D01D083)+1 种基金the National Natural Science Foundation of China(U2003214 and 41977099)the Ecological Processes and Biological Adaptation team for financial and experimental instrumentation help。
文摘This study was conducted to analyze the variation of soil multifunctionality(SMF)along elevation and the driving factors in the Altun Shan.Soil samples(0–10 cm)were collected from 15 sites(H01 to H15)at every 200 m elevation interval,covering a total range from 900 m to 3500 m above mean sea level.We investigated climate factors(mean annual temperature,MAT;mean annual precipitation,MAP),soil environment(soil water content,electrical conductance,and pH),vegetation factors,and elevation to determine which of them are the main driving factors of the spatial variability of SMF in the Altun Shan.We explored the best-fit model of SMF along the changes in elevation using a structural equation model,performed variance partitioning analysis(VPA)on SMF with the“varpart”function to explain the relative contribution of various environmental factors to SMF changes,and used a random forest model for relative importance analysis.The results showed that SMF in the Altun Shan significantly increased with elevation in a linear trend.The main driver of changes in SMF was found to be MAP.Although the rise in elevation did not have a significant direct effect on changes in SMF,it could indirectly affect SMF by significantly influencing MAP,p H,MAT,and normalized difference vegetation index(NDVI).When considering climate,soil environment,and vegetation factors together,they explained 76%of the variation in SMF.The largest contribution to the variation in SMF was attributed to the independent effect of climate(0.31)and its interactive effect with soil(0.30).The relative importance of MAP on SMF changes was found to be the greatest.It is indicated that changes in SMF are caused by the combined effect of multiple environmental conditions.These findings are essential for understanding the spatial variability and drivers of SMF in dryland mountain ecosystems,especially concerning the function of mountain ecosystems in the context of global climatic changes.
