Fusarium oxysporum and Geotrichum candidum, which are among important pathogens of Solanum lycopersicum L. (Tomato), are sometimes misidentified during morphological misidentification. The study was carried out to eva...Fusarium oxysporum and Geotrichum candidum, which are among important pathogens of Solanum lycopersicum L. (Tomato), are sometimes misidentified during morphological misidentification. The study was carried out to evaluate molecular diversity of F. oxysporum and G. candidum isolated from two tomato varieties obtained from Akure, Ilorin and Ibadan, Nigeria. The tomato samples were collected and brought back to the laboratory for fungal isolation. Isolation of the pathogens were done following standard procedures. DNA extraction from pure cultures of the pathogens was done at the Centre Laboratory of University of Ibadan. Genetic relationships among the organisms were also estimated by constructing a Dendrogram through UPGMA using the Mega6 Software and genetic distance was computed also using the Mega6 Software. Five strains of F. oxysporum and seven strains of G. candidum were identified. Percentage similarity of the pathogens with those in GenBank was 99.17% - 100.00% for F. oxysporum and 98.48% - 100.00% for G. candidum. The T-01 marker showed the lowest major allele frequency of 0.0833, while T-10 marker has the highest value for major allele frequency of 0.6667 and an average value of 0.3958. Evolutionary relationship showed that the two strains of G. candidum (MN650247 and MN650250) were similar. The three strains of F. oxysporum (MN650246 and MN650248, MN650245 and MN650253) were also similar. Genetic distances among pairs of the fungal strains ranged from 0.12 to 6.30 in pairwise fashion, with an average of 1.32. Evolutionary relationship or closeness among strains of a fungal species can thus be said not to depend on location.展开更多
Although several methods are available to study the extent of isolation by distance （IBD） among natural populations, comparatively few exist to detect the presence of sharp genetic breaks in genetic distance dataset...Although several methods are available to study the extent of isolation by distance （IBD） among natural populations, comparatively few exist to detect the presence of sharp genetic breaks in genetic distance datasets. In recent years, Monmonier＇s maximum-difference algorithm has been increasingly used by population geneticists. However, this method does not provide means to measure the statistical significance of such barriers, nor to determine their relative contribution to population differentiation with respect to IBD. Here, we propose an approach to assess the significance of genetic boundaries. The method is based on the calculation of a multiple regression from distance matrices, where binary matrices represent putative genetic barriers to test, in addition to geographic and genetic distances. Simulation results suggest that this method reliably detects the presence of genetic barriers, even in situations where IBD is also significant. We also illustrate the methodology by analyzing previously published datasets. Conclusions about the importance of genetic barriers can be misleading if one does not take into consideration their relative contribution to the overall genetic structure of species.展开更多
基金The National Natural Science Foundation of China(No.31101637,No.31172068,No.31471980)the project of Chongqing Science&Technology Commission(No.CSTC,2010CA1010,No.cstc2014jcyjA80008)the Science Research Foundation of the Education Committee of Chongqing(No.KJ1400530)
文摘Fusarium oxysporum and Geotrichum candidum, which are among important pathogens of Solanum lycopersicum L. (Tomato), are sometimes misidentified during morphological misidentification. The study was carried out to evaluate molecular diversity of F. oxysporum and G. candidum isolated from two tomato varieties obtained from Akure, Ilorin and Ibadan, Nigeria. The tomato samples were collected and brought back to the laboratory for fungal isolation. Isolation of the pathogens were done following standard procedures. DNA extraction from pure cultures of the pathogens was done at the Centre Laboratory of University of Ibadan. Genetic relationships among the organisms were also estimated by constructing a Dendrogram through UPGMA using the Mega6 Software and genetic distance was computed also using the Mega6 Software. Five strains of F. oxysporum and seven strains of G. candidum were identified. Percentage similarity of the pathogens with those in GenBank was 99.17% - 100.00% for F. oxysporum and 98.48% - 100.00% for G. candidum. The T-01 marker showed the lowest major allele frequency of 0.0833, while T-10 marker has the highest value for major allele frequency of 0.6667 and an average value of 0.3958. Evolutionary relationship showed that the two strains of G. candidum (MN650247 and MN650250) were similar. The three strains of F. oxysporum (MN650246 and MN650248, MN650245 and MN650253) were also similar. Genetic distances among pairs of the fungal strains ranged from 0.12 to 6.30 in pairwise fashion, with an average of 1.32. Evolutionary relationship or closeness among strains of a fungal species can thus be said not to depend on location.
基金supported by a Natural Sciences and Engineering Research Council of Canada scholarship and a Fonds Québécois de la Recherche sur la Nature et les Technologies scholarship to S.R.P.a Natural Sciences and Engineering Research Council of Canada grant to F.-J.L.
文摘Although several methods are available to study the extent of isolation by distance （IBD） among natural populations, comparatively few exist to detect the presence of sharp genetic breaks in genetic distance datasets. In recent years, Monmonier＇s maximum-difference algorithm has been increasingly used by population geneticists. However, this method does not provide means to measure the statistical significance of such barriers, nor to determine their relative contribution to population differentiation with respect to IBD. Here, we propose an approach to assess the significance of genetic boundaries. The method is based on the calculation of a multiple regression from distance matrices, where binary matrices represent putative genetic barriers to test, in addition to geographic and genetic distances. Simulation results suggest that this method reliably detects the presence of genetic barriers, even in situations where IBD is also significant. We also illustrate the methodology by analyzing previously published datasets. Conclusions about the importance of genetic barriers can be misleading if one does not take into consideration their relative contribution to the overall genetic structure of species.
