为了研究ifitm基因的功能,本研究从猪肾PK15细胞中克隆了猪的3个ifitm c DNA序列,分析了猪ifitm1、ifitm2和ifitm3基因的染色体定位及其与其他物种基因序列的同源关系,并对不同ifitm在不同组织的表达进行分析和检测。结果显示,猪ifitm...为了研究ifitm基因的功能,本研究从猪肾PK15细胞中克隆了猪的3个ifitm c DNA序列,分析了猪ifitm1、ifitm2和ifitm3基因的染色体定位及其与其他物种基因序列的同源关系,并对不同ifitm在不同组织的表达进行分析和检测。结果显示,猪ifitm和人、鼠ifitm具有相同的基因和蛋白结构,进化上与牛ifitm高度同源,ifitm1和ifitm3在脾、肾、心、肝等组织中大量表达,而ifitm2只在脾和肾中检测到表达,在其他组织中的表达量相对较小。猪ifitm基因的克隆、生物信息学及组织表达分析为进一步研究其在猪细胞中的功能奠定了基础。展开更多
While it is widely accepted that genetic diversity determines the potential of adaptation,the role that gene expression variation plays in adaptation remains poorly known.Here we show that gene expression diversity co...While it is widely accepted that genetic diversity determines the potential of adaptation,the role that gene expression variation plays in adaptation remains poorly known.Here we show that gene expression diversity could have played a positive role in the adaptation of Miscanthus lutarioriparius.RNA-seq was conducted for 80 individuals of the species,with half planted in the energy crop domestication site and the other half planted in the control site near native habitats.A leaf reference transcriptome consisting of 18,503 high-quality transcripts was obtained using a pipeline developed for de novo assembling with population RNA-seq data.The population structure and genetic diversity of M.lutarioriparius were estimated based on 30,609 genic single nucleotide polymorphisms.Population expression（Ep） and expression diversity（Ed）were defined to measure the average level and the magnitude of variation of a gene expression in the population,respectively.It was found that expression diversity increased while genetic Resediversity decreased after the species was transplanted from the native habitats to the harsh domestication site,especially for genes involved in abiotic stress resistance,histone methylation,and biomass synthesis under water limitation.The increased expression diversity could have enriched phenotypic variation directly subject to selections in the new environment.展开更多
The face recognition with expression and occlusion variation becomes the greatest challenge in biometric applications to recognize people. The proposed work concentrates on recognizing occlusion and seven kinds of exp...The face recognition with expression and occlusion variation becomes the greatest challenge in biometric applications to recognize people. The proposed work concentrates on recognizing occlusion and seven kinds of expression variations such as neutral, surprise, happy, sad, fear, disgust and angry. During enrollment process, principle component analysis (PCA) detects facial regions on the input image. The detected facial region is converted into fuzzy domain data to make decision during recognition process. The Haar wavelet transform extracts features from the detected facial regions. The Nested Hidden markov model is employed to train these features and each feature of face image is considered as states in a Markov chain to perform learning among the features. The maximum likelihood for the input image was estimated by using Baum Welch algorithm and these features were kept on database. During recognition process, the expression and occlusion varied face image is taken as the test image and maximum likelihood for test image is found by following same procedure done in enrollment process. The matching score between maximum likelihood of input image and test image is computed and it is utilized by fuzzy rule based method to decide whether the test image belongs to authorized or unauthorized. The proposed work was tested among several expression varied and occluded face images of JAFFE and AR datasets respectively.展开更多
基金Supported by National High Technology Research and Development Program of China(863 Program,No.2003AA205090)985 Project Foundation of Peking University,China~~
文摘为了研究ifitm基因的功能,本研究从猪肾PK15细胞中克隆了猪的3个ifitm c DNA序列,分析了猪ifitm1、ifitm2和ifitm3基因的染色体定位及其与其他物种基因序列的同源关系,并对不同ifitm在不同组织的表达进行分析和检测。结果显示,猪ifitm和人、鼠ifitm具有相同的基因和蛋白结构,进化上与牛ifitm高度同源,ifitm1和ifitm3在脾、肾、心、肝等组织中大量表达,而ifitm2只在脾和肾中检测到表达,在其他组织中的表达量相对较小。猪ifitm基因的克隆、生物信息学及组织表达分析为进一步研究其在猪细胞中的功能奠定了基础。
基金supported by grants from the Key Program of the National Natural Science Foundation of China (No.91131902)the Knowledge Innovation Program of the Chinese Academy of Sciences (KSCX2-EX-QR-1)
文摘While it is widely accepted that genetic diversity determines the potential of adaptation,the role that gene expression variation plays in adaptation remains poorly known.Here we show that gene expression diversity could have played a positive role in the adaptation of Miscanthus lutarioriparius.RNA-seq was conducted for 80 individuals of the species,with half planted in the energy crop domestication site and the other half planted in the control site near native habitats.A leaf reference transcriptome consisting of 18,503 high-quality transcripts was obtained using a pipeline developed for de novo assembling with population RNA-seq data.The population structure and genetic diversity of M.lutarioriparius were estimated based on 30,609 genic single nucleotide polymorphisms.Population expression（Ep） and expression diversity（Ed）were defined to measure the average level and the magnitude of variation of a gene expression in the population,respectively.It was found that expression diversity increased while genetic Resediversity decreased after the species was transplanted from the native habitats to the harsh domestication site,especially for genes involved in abiotic stress resistance,histone methylation,and biomass synthesis under water limitation.The increased expression diversity could have enriched phenotypic variation directly subject to selections in the new environment.
文摘The face recognition with expression and occlusion variation becomes the greatest challenge in biometric applications to recognize people. The proposed work concentrates on recognizing occlusion and seven kinds of expression variations such as neutral, surprise, happy, sad, fear, disgust and angry. During enrollment process, principle component analysis (PCA) detects facial regions on the input image. The detected facial region is converted into fuzzy domain data to make decision during recognition process. The Haar wavelet transform extracts features from the detected facial regions. The Nested Hidden markov model is employed to train these features and each feature of face image is considered as states in a Markov chain to perform learning among the features. The maximum likelihood for the input image was estimated by using Baum Welch algorithm and these features were kept on database. During recognition process, the expression and occlusion varied face image is taken as the test image and maximum likelihood for test image is found by following same procedure done in enrollment process. The matching score between maximum likelihood of input image and test image is computed and it is utilized by fuzzy rule based method to decide whether the test image belongs to authorized or unauthorized. The proposed work was tested among several expression varied and occluded face images of JAFFE and AR datasets respectively.
