Oryza sativa L. ssp. japonica and indica exhibit different sensitivity to photoinhibition and they show different stability of their core proteins D1 in the chloroplast photosystem Ⅱ. Using in situ hybridization, psb...Oryza sativa L. ssp. japonica and indica exhibit different sensitivity to photoinhibition and they show different stability of their core proteins D1 in the chloroplast photosystem Ⅱ. Using in situ hybridization, psbA, the gene encoding D1 protein of O. sativa ssp. japonica cv. 9516, and that of O. sativa ssp. indica cv. Shanyou 63 was cloned. As revealed by homology comparison of their sequences, the sequences are identical in the regions of promoter and 5′-UTR; differences are found in individual bases in the coding region all of which, being in the third position of respective codons, however, do not affect the amino acids coded finally; a difference is noted in the length of the oligo-U sequence in the region of 3′-UTR. It is thus apparent that, rather than a result of any difference in the amino acid sequences, the differences in the sensitivity to photoinhibition of D1 proteins between japonica and indica rice may be related to the upstream factors that regulate expression of psbA or to differences of photoprotective mechanisms.展开更多
Reverse_transcription Polymerase Chain Reaction (RT_PCR) was performed using cDNAs as templates from wheat_ Haynaldia villosa 6VS/6AL translocation line and 'Yangmai 5' induced with fungus Erysiphe gramin...Reverse_transcription Polymerase Chain Reaction (RT_PCR) was performed using cDNAs as templates from wheat_ Haynaldia villosa 6VS/6AL translocation line and 'Yangmai 5' induced with fungus Erysiphe graminis , and degenerate primers designed based on the conserved amino acid sequences of known plant disease_resistance genes. The cDNA sequences encoding cyclophilin_like and H +_ATPase_like genes were first isolated and characterized in wheat. The putative amino acid sequences of the two clones showed that they were highly homologous to those of cyclophilin proteins and H +_ATPases isolated from other plants. Thus they were designated as Ta_Cyp and Ta_MAH . The obvious expression differences could be observed between wheat_ H. villosa 6VS/6AL translocation line and susceptible wheat cultivar 'Yangmai 5', implying that the two genes may be related with the resistance of wheat_ H. villosa 6VS/6AL translocation line to disease. Southern blot indicated that the wheat genome contained 2-3 copies of Ta_Cyp gene and one copy of the Ta_MAH gene. Chinese Spring nulli_tetrasomic line analysis located the Ta_Cyp homologous genes on wheat chromosome 6A, 6B and 6D. Southern blot using Ta_Cyp clone as a probe showed that the polymorphic bands existed among the H. villosa , amphiploid of Triticum durum _ H. villosa , wheat_ H. villosa 6VS/6AL translocation line and 'Yangmai 5', suggesting that Ta_Cyp homologies exist in wheat genome as well as on the short arm of chromosome 6V in H. villosa .展开更多
The genetically modified high-oleic rapeseed （Brassica napus L.） line W-4 was obtained by transforming a binary vector which harbored an inverted repeat expression cassette of fad2 gene into the rapeseed cultivar We...The genetically modified high-oleic rapeseed （Brassica napus L.） line W-4 was obtained by transforming a binary vector which harbored an inverted repeat expression cassette of fad2 gene into the rapeseed cultivar Westar.The transformation was mediated by Agrobacterium.The flanking sequences to both the left and right borders of T-DNA insertion site were amplified by thermal asymmetric interlaced PCR （TAIL-PCR） from the genomic DNA of the transgenic rapeseed line W-4.The flanking sequences to the right border was 290 bp in length and the nucleotide composition was 31.27％ for G＋C content while 68.73％ for A＋T content.The flanking sequence to the left border was 365 bp in length and the G＋C content was 32.6％ and the A＋T content was 67.4％,indicating that the T-DNA was integrated in the A/T-rich region.Further more,sequence alignment analysis showed a deletion of 62 bp including the right border of pCNFIRnos and the integration of the whole left border except a change of G to A.That was to say,the integration of the T-DNA in the transgenic line W-4 not involved in the vector sequences.Based on both flanking sequences as well as the left and right borders of the T-DNA sequences,two pairs of specific primers TLF/TLR and TRF/TRR were designed.Using the primers the event-specific PCR detection method for transgenic rapeseed line W-4 was established.By the PCR,two fragments of 485 and 405 bp were amplified from the W-4 genomic DNA as expected,while no products were amplified from the genomic DNA of other transgenic rapeseed lines and non-transgenic rapeseed line.And by the PCR it is possible to detect the W-4 genomic DNA from a mixed sample of genomic DNA.The limit of the detection for the qualitative PCR assay was 0.1％.The method developed in this work is highly specific,sensitive and suitable for event-specific detection of the transgenic rapeseed line W-4.展开更多
The discovery of novel cancer genes is one of the main goals in cancer research.Bioinformatics methods can be used to accelerate cancer gene discovery,which may help in the understanding of cancer and the development ...The discovery of novel cancer genes is one of the main goals in cancer research.Bioinformatics methods can be used to accelerate cancer gene discovery,which may help in the understanding of cancer and the development of drug targets.In this paper,we describe a classifier to predict potential cancer genes that we have developed by integrating multiple biological evidence,including protein-protein interaction network properties,and sequence and functional features.We detected 55 features that were significantly different between cancer genes and non-cancer genes.Fourteen cancer-associated features were chosen to train the classifier.Four machine learning methods,logistic regression,support vector machines(SVMs),BayesNet and decision tree,were explored in the classifier models to distinguish cancer genes from non-cancer genes.The prediction power of the different models was evaluated by 5-fold cross-validation.The area under the receiver operating characteristic curve for logistic regression,SVM,Baysnet and J48 tree models was 0.834,0.740,0.800 and 0.782,respectively.Finally,the logistic regression classifier with multiple biological features was applied to the genes in the Entrez database,and 1976 cancer gene candidates were identified.We found that the integrated prediction model performed much better than the models based on the individual biological evidence,and the network and functional features had stronger powers than the sequence features in predicting cancer genes.展开更多
文摘Oryza sativa L. ssp. japonica and indica exhibit different sensitivity to photoinhibition and they show different stability of their core proteins D1 in the chloroplast photosystem Ⅱ. Using in situ hybridization, psbA, the gene encoding D1 protein of O. sativa ssp. japonica cv. 9516, and that of O. sativa ssp. indica cv. Shanyou 63 was cloned. As revealed by homology comparison of their sequences, the sequences are identical in the regions of promoter and 5′-UTR; differences are found in individual bases in the coding region all of which, being in the third position of respective codons, however, do not affect the amino acids coded finally; a difference is noted in the length of the oligo-U sequence in the region of 3′-UTR. It is thus apparent that, rather than a result of any difference in the amino acid sequences, the differences in the sensitivity to photoinhibition of D1 proteins between japonica and indica rice may be related to the upstream factors that regulate expression of psbA or to differences of photoprotective mechanisms.
文摘Reverse_transcription Polymerase Chain Reaction (RT_PCR) was performed using cDNAs as templates from wheat_ Haynaldia villosa 6VS/6AL translocation line and 'Yangmai 5' induced with fungus Erysiphe graminis , and degenerate primers designed based on the conserved amino acid sequences of known plant disease_resistance genes. The cDNA sequences encoding cyclophilin_like and H +_ATPase_like genes were first isolated and characterized in wheat. The putative amino acid sequences of the two clones showed that they were highly homologous to those of cyclophilin proteins and H +_ATPases isolated from other plants. Thus they were designated as Ta_Cyp and Ta_MAH . The obvious expression differences could be observed between wheat_ H. villosa 6VS/6AL translocation line and susceptible wheat cultivar 'Yangmai 5', implying that the two genes may be related with the resistance of wheat_ H. villosa 6VS/6AL translocation line to disease. Southern blot indicated that the wheat genome contained 2-3 copies of Ta_Cyp gene and one copy of the Ta_MAH gene. Chinese Spring nulli_tetrasomic line analysis located the Ta_Cyp homologous genes on wheat chromosome 6A, 6B and 6D. Southern blot using Ta_Cyp clone as a probe showed that the polymorphic bands existed among the H. villosa , amphiploid of Triticum durum _ H. villosa , wheat_ H. villosa 6VS/6AL translocation line and 'Yangmai 5', suggesting that Ta_Cyp homologies exist in wheat genome as well as on the short arm of chromosome 6V in H. villosa .
基金Supported by Key Agricultural Technology Research and Development Program of Jiangsu Province(BE2009304)Fund for National Rapeseed Research System(CARS13)~~
文摘The genetically modified high-oleic rapeseed （Brassica napus L.） line W-4 was obtained by transforming a binary vector which harbored an inverted repeat expression cassette of fad2 gene into the rapeseed cultivar Westar.The transformation was mediated by Agrobacterium.The flanking sequences to both the left and right borders of T-DNA insertion site were amplified by thermal asymmetric interlaced PCR （TAIL-PCR） from the genomic DNA of the transgenic rapeseed line W-4.The flanking sequences to the right border was 290 bp in length and the nucleotide composition was 31.27％ for G＋C content while 68.73％ for A＋T content.The flanking sequence to the left border was 365 bp in length and the G＋C content was 32.6％ and the A＋T content was 67.4％,indicating that the T-DNA was integrated in the A/T-rich region.Further more,sequence alignment analysis showed a deletion of 62 bp including the right border of pCNFIRnos and the integration of the whole left border except a change of G to A.That was to say,the integration of the T-DNA in the transgenic line W-4 not involved in the vector sequences.Based on both flanking sequences as well as the left and right borders of the T-DNA sequences,two pairs of specific primers TLF/TLR and TRF/TRR were designed.Using the primers the event-specific PCR detection method for transgenic rapeseed line W-4 was established.By the PCR,two fragments of 485 and 405 bp were amplified from the W-4 genomic DNA as expected,while no products were amplified from the genomic DNA of other transgenic rapeseed lines and non-transgenic rapeseed line.And by the PCR it is possible to detect the W-4 genomic DNA from a mixed sample of genomic DNA.The limit of the detection for the qualitative PCR assay was 0.1％.The method developed in this work is highly specific,sensitive and suitable for event-specific detection of the transgenic rapeseed line W-4.
基金supported by the National Natural Science Foundation of China (31000591,31000587,31171266)
文摘The discovery of novel cancer genes is one of the main goals in cancer research.Bioinformatics methods can be used to accelerate cancer gene discovery,which may help in the understanding of cancer and the development of drug targets.In this paper,we describe a classifier to predict potential cancer genes that we have developed by integrating multiple biological evidence,including protein-protein interaction network properties,and sequence and functional features.We detected 55 features that were significantly different between cancer genes and non-cancer genes.Fourteen cancer-associated features were chosen to train the classifier.Four machine learning methods,logistic regression,support vector machines(SVMs),BayesNet and decision tree,were explored in the classifier models to distinguish cancer genes from non-cancer genes.The prediction power of the different models was evaluated by 5-fold cross-validation.The area under the receiver operating characteristic curve for logistic regression,SVM,Baysnet and J48 tree models was 0.834,0.740,0.800 and 0.782,respectively.Finally,the logistic regression classifier with multiple biological features was applied to the genes in the Entrez database,and 1976 cancer gene candidates were identified.We found that the integrated prediction model performed much better than the models based on the individual biological evidence,and the network and functional features had stronger powers than the sequence features in predicting cancer genes.
