For the first time, a nodulin-like gene promoter was isolated from Gossypium hirsutum L. Guo Y 18 by means of inverse PCR. Three plant expression vectors were constructed for functional identification of the promoter....For the first time, a nodulin-like gene promoter was isolated from Gossypium hirsutum L. Guo Y 18 by means of inverse PCR. Three plant expression vectors were constructed for functional identification of the promoter. These vectors were different only in promoter regions; three truncations of the nodulinlike promoter took the place of the CaMV35S promoter in the pBI 121 plant expression vector. Then, the three vectors were introduced into cotton plants via the pollen tube pathway. The expression patterns of the gus gene driven by nodulin-like promoter truncations were investigated in the offspring of transgenic cotton plants. Histochemical GUS staining and fluorescence quantitative analysis were performed to achieve this goal. The results showed that the nodulin-like promoter was a strong, highly reproductive organspecific promoter, which demonstrated a much higher driver activity than the CaMV35S promoter did in cotton reproductive organs, but relatively lower activity in vegetation. Identification of the speciality and strength-determining regions of the nodulin-like promoter was also undertaken.展开更多
Motivation: Accurate identification and delineation of promoters/TSSs (transcription start sites) is important for improving genome annotation and devising experiments to study and understand transcriptional regulatio...Motivation: Accurate identification and delineation of promoters/TSSs (transcription start sites) is important for improving genome annotation and devising experiments to study and understand transcriptional regulation. Many promoter identifiers are developed for promoter identification. However, each promoter identifier has its own focuses and limitations, and we introduce an integration scheme to combine some identifiers together to gain a better prediction performance. Result: In this contribution, 8 promoter identifiers (Proscan, TSSG, TSSW, FirstEF, eponine, ProSOM, EP3, FPROM) are chosen for the investigation of integration. A feature selection method, called mRMR (Minimum Redundancy Maximum Relevance), is novelly transferred to promoter identifier selection by choosing a group of robust and complementing promoter identifiers. For comparison, four integration methods (SMV, WMV, SMV_IS, WMV_IS), from simple to complex, are developed to process a training dataset with 1400 se- quences and a testing dataset with 378 sequences. As a result, 5 identifiers (FPROM, FirstEF, TSSG, epo- nine, TSSW) are chosen by mRMR, and the integration of them achieves 70.08% and 67.83% correct prediction rates for a training dataset and a testing dataset respectively, which is better than any single identifier in which the best single one only achieves 59.32% and 61.78% for the training dataset and testing dataset respectively.展开更多
基金国家高技术研究发展计划(863计划)，the National Special Project for Cotton Development from Agricultural Department of the Chinese Government
文摘For the first time, a nodulin-like gene promoter was isolated from Gossypium hirsutum L. Guo Y 18 by means of inverse PCR. Three plant expression vectors were constructed for functional identification of the promoter. These vectors were different only in promoter regions; three truncations of the nodulinlike promoter took the place of the CaMV35S promoter in the pBI 121 plant expression vector. Then, the three vectors were introduced into cotton plants via the pollen tube pathway. The expression patterns of the gus gene driven by nodulin-like promoter truncations were investigated in the offspring of transgenic cotton plants. Histochemical GUS staining and fluorescence quantitative analysis were performed to achieve this goal. The results showed that the nodulin-like promoter was a strong, highly reproductive organspecific promoter, which demonstrated a much higher driver activity than the CaMV35S promoter did in cotton reproductive organs, but relatively lower activity in vegetation. Identification of the speciality and strength-determining regions of the nodulin-like promoter was also undertaken.
文摘Motivation: Accurate identification and delineation of promoters/TSSs (transcription start sites) is important for improving genome annotation and devising experiments to study and understand transcriptional regulation. Many promoter identifiers are developed for promoter identification. However, each promoter identifier has its own focuses and limitations, and we introduce an integration scheme to combine some identifiers together to gain a better prediction performance. Result: In this contribution, 8 promoter identifiers (Proscan, TSSG, TSSW, FirstEF, eponine, ProSOM, EP3, FPROM) are chosen for the investigation of integration. A feature selection method, called mRMR (Minimum Redundancy Maximum Relevance), is novelly transferred to promoter identifier selection by choosing a group of robust and complementing promoter identifiers. For comparison, four integration methods (SMV, WMV, SMV_IS, WMV_IS), from simple to complex, are developed to process a training dataset with 1400 se- quences and a testing dataset with 378 sequences. As a result, 5 identifiers (FPROM, FirstEF, TSSG, epo- nine, TSSW) are chosen by mRMR, and the integration of them achieves 70.08% and 67.83% correct prediction rates for a training dataset and a testing dataset respectively, which is better than any single identifier in which the best single one only achieves 59.32% and 61.78% for the training dataset and testing dataset respectively.
