目的应用Affymetrix SNP 6.0芯片技术筛选先天性小耳畸形的候选致病基因。方法对3例小耳畸形患者血液基因组进行Affymetrix SNP 6.0芯片分析,采用Birdseed软件分析样本的芯片数据,通过Minor Allele Frequency对在患者和汉族人参考样本...目的应用Affymetrix SNP 6.0芯片技术筛选先天性小耳畸形的候选致病基因。方法对3例小耳畸形患者血液基因组进行Affymetrix SNP 6.0芯片分析,采用Birdseed软件分析样本的芯片数据,通过Minor Allele Frequency对在患者和汉族人参考样本中有显著差异的单核苷酸多态性(SNP)进行筛选。结果得到SNP相关基因4 180个,根据已知文献收集和耳部发育相关并被SNP 6.0注释的基因共5个,包括MSX1,MSX2,GSC,HOXA2和PRKRA。结论应用Affymetrix SNP 6.0芯片技术筛选出5个先天性小耳畸形的候选致病基因,分别是MSX1,MSX2,GSC,HOXA2和PRKRA。展开更多
Soybean cyst nematode （SCN） is one of the most devastating pathogen for soybean. Therefore, identiifcation of resistant germplasm resources and resistant genes is needed to improve SCN resistance for soybean. Soybea...Soybean cyst nematode （SCN） is one of the most devastating pathogen for soybean. Therefore, identiifcation of resistant germplasm resources and resistant genes is needed to improve SCN resistance for soybean. Soybean varieties Huipizhiheidou and Wuzhaiheidou were distributed in China and exhibited broad spectrums of resistance to various SCN races. In this study, these two resistant varieties, combined with standard susceptible varieties （Lee and Essex）, were utilized to identify the differentially expressed transcripts after infection with SCN race 4 between resistant and susceptible reactions by using the Affymetrix Soybean Genome GeneChip. Comparative analyses indicated that 21 common genes changed signiifcantly in the resistant group, of which 16 increased and 5 decreased. However, 12 common genes changed signiifcantly in the susceptible group, of which 9 increased and 3 decreased. Additionally, 27 genes were found in common between resistant and susceptible reactions. The 21 signiifcantly changed genes in resistant reaction were associated with disease and defense, cell structure, transcription, metabolism, and signal transduction. The fold induction of 4 from the 21 genes was conifrmed by quantitative RT-PCR （qRT-PCR） analysis. Moreover, the gene ontology （GO） enrichment analyses demonstrated the serine family amino acid metabolic process and arginine metabolic process may play important roles in SCN resistance. This study provided a new insight on the genetic basis of soybean resistance to SCN race 4, and the identiifed resistant or resistant-related genes are potentially useful for SCN-resistance breeding in soybean.展开更多
The pathogenesis of acne has been linked to multiple factors such as increased sebum production, inflammation, follicular hyperkeratinization, and the action of Propionibacterium acnes within the follicle. In an attem...The pathogenesis of acne has been linked to multiple factors such as increased sebum production, inflammation, follicular hyperkeratinization, and the action of Propionibacterium acnes within the follicle. In an attempt to understand the specific genes involved in inflammatory acne, we performed gene expression profiling in acne patients. Skin biopsies were obtained from an inflammatory papule and from normal skin in six patients with acne. Biopsies were also taken from normal skin of six subjects without acne. Gene array expression profiling was conducted using Affymetrix HG-U133A 2.0 arrays comparing lesional to nonlesional skin in acne patients and comparing nonlesional skin from acne patients to skin from normal subjects. Within the acne patients, 211 genes are upregulated in lesional skin compared to nonlesional skin. A significant proportion of these genes are involved in pathways that regulate inflammation and extracellular matrix remodeling, and they include matrix metalloproteinases 1 and 3, IL- 8, human β defensin 4, and granzyme B. These data indicate a prominent role of matrix metalloproteinases, inflammatory cytokines, and antimicrobial peptides in acne lesions. These studies are the first describing the comprehensive changes in gene expression in inflammatory acne lesions and are valuable in identifying potential therapeutic targets in inflammatory acne.展开更多
RiceDB, a web-based integrated database to annotate rice microarray in various biological contexts was developed. It is composed of eight modules. RiceMap module archives the process of Affymetrix probe sets mapping t...RiceDB, a web-based integrated database to annotate rice microarray in various biological contexts was developed. It is composed of eight modules. RiceMap module archives the process of Affymetrix probe sets mapping to different databases about rice, and aims to the genes represented by a microarray set by retrieving annotation information via the identifier or accession number of every database; RiceGO module indicates the association between a microarray set and gene ontology （GO） categories; RiceKO module is used to annotate a microarray set based on the KEGG biochemical pathways; RiceDO module indicates the information of domain associated with a microarray set; RiceUP module is used to obtain promoter sequences for all genes represented by a microarray set; RiceMR module lists potential microRNA which regulated the genes represented by a microarray set; RiceCD and RiceGF are used to annotate the genes represented by a microarray set in the context of chromosome distribution and rice paralogous family distribution. The results of automatic annotation are mostly consistent with manual annotation. Biological interpretation of the microarray data is quickened by the help of RiceDB.展开更多
文摘目的 应用Affymetrix全基因组芯片结合荧光定量PCR（quantitative real-timePCR，qPCR）技术，进行致病性DNA拷贝数变异的精细定位研究。方法以一个定位于染色体7q36的中国人遗传性三节拇指多并指综合征伴随Ⅳ型并指家系中的一例患者为研究对象。收集外周血标本，常规提取基因组DNA。应用Affymetrix Genome-Wide Human SNP Array6．0芯片，将基因组DNA纯化，经过酶切、连接、扩增、标记、杂交、染色和扫描等步骤后得到原始数据，应用Affymetrix Genotyping Console3．0软件进行拷贝数分析。在经芯片分析所确定的重复范围内设计引物，采用qPCR方法进行验证，并进一步缩小断端范周、精确重复区域范围。结果将患者重复区域两断端范围由原来的113kb和33kb分别缩小到5．4kb和1．8kb，致病性DNA重复范围由原来的291～437kb精确至379～387kb。结论应用Affymetrix全基因组芯片联合qPCR技术可以实现对DNA拷贝数突变的精确、可靠的检测。
文摘目的应用Affymetrix SNP 6.0芯片技术筛选先天性小耳畸形的候选致病基因。方法对3例小耳畸形患者血液基因组进行Affymetrix SNP 6.0芯片分析,采用Birdseed软件分析样本的芯片数据,通过Minor Allele Frequency对在患者和汉族人参考样本中有显著差异的单核苷酸多态性(SNP)进行筛选。结果得到SNP相关基因4 180个,根据已知文献收集和耳部发育相关并被SNP 6.0注释的基因共5个,包括MSX1,MSX2,GSC,HOXA2和PRKRA。结论应用Affymetrix SNP 6.0芯片技术筛选出5个先天性小耳畸形的候选致病基因,分别是MSX1,MSX2,GSC,HOXA2和PRKRA。
基金supported by the National Nature Science Foundation of China (31301345 and 31171576)the CAAS Innovation Project, the Genetically Modified Organisms Breeding Major Projects, China (2009ZX08004-003B and 2011ZX08004-003)the Key Technologies R&D Program of China during the 12th Five-Year Plan period (2011BAD35B06-3)
文摘Soybean cyst nematode （SCN） is one of the most devastating pathogen for soybean. Therefore, identiifcation of resistant germplasm resources and resistant genes is needed to improve SCN resistance for soybean. Soybean varieties Huipizhiheidou and Wuzhaiheidou were distributed in China and exhibited broad spectrums of resistance to various SCN races. In this study, these two resistant varieties, combined with standard susceptible varieties （Lee and Essex）, were utilized to identify the differentially expressed transcripts after infection with SCN race 4 between resistant and susceptible reactions by using the Affymetrix Soybean Genome GeneChip. Comparative analyses indicated that 21 common genes changed signiifcantly in the resistant group, of which 16 increased and 5 decreased. However, 12 common genes changed signiifcantly in the susceptible group, of which 9 increased and 3 decreased. Additionally, 27 genes were found in common between resistant and susceptible reactions. The 21 signiifcantly changed genes in resistant reaction were associated with disease and defense, cell structure, transcription, metabolism, and signal transduction. The fold induction of 4 from the 21 genes was conifrmed by quantitative RT-PCR （qRT-PCR） analysis. Moreover, the gene ontology （GO） enrichment analyses demonstrated the serine family amino acid metabolic process and arginine metabolic process may play important roles in SCN resistance. This study provided a new insight on the genetic basis of soybean resistance to SCN race 4, and the identiifed resistant or resistant-related genes are potentially useful for SCN-resistance breeding in soybean.
文摘The pathogenesis of acne has been linked to multiple factors such as increased sebum production, inflammation, follicular hyperkeratinization, and the action of Propionibacterium acnes within the follicle. In an attempt to understand the specific genes involved in inflammatory acne, we performed gene expression profiling in acne patients. Skin biopsies were obtained from an inflammatory papule and from normal skin in six patients with acne. Biopsies were also taken from normal skin of six subjects without acne. Gene array expression profiling was conducted using Affymetrix HG-U133A 2.0 arrays comparing lesional to nonlesional skin in acne patients and comparing nonlesional skin from acne patients to skin from normal subjects. Within the acne patients, 211 genes are upregulated in lesional skin compared to nonlesional skin. A significant proportion of these genes are involved in pathways that regulate inflammation and extracellular matrix remodeling, and they include matrix metalloproteinases 1 and 3, IL- 8, human β defensin 4, and granzyme B. These data indicate a prominent role of matrix metalloproteinases, inflammatory cytokines, and antimicrobial peptides in acne lesions. These studies are the first describing the comprehensive changes in gene expression in inflammatory acne lesions and are valuable in identifying potential therapeutic targets in inflammatory acne.
基金supported by the National Key Basic Research and Development Program of China(Grant No.2005CB120900)the National Natural Science Foundation of China(Grant No.30500106)the Scientific Research Foundation for Returned Overseas Chinese Scholars,Ministry of Education,and the Department of Science and Technology of Zhejiang Province,China(Grant No.2007C22025).
文摘RiceDB, a web-based integrated database to annotate rice microarray in various biological contexts was developed. It is composed of eight modules. RiceMap module archives the process of Affymetrix probe sets mapping to different databases about rice, and aims to the genes represented by a microarray set by retrieving annotation information via the identifier or accession number of every database; RiceGO module indicates the association between a microarray set and gene ontology （GO） categories; RiceKO module is used to annotate a microarray set based on the KEGG biochemical pathways; RiceDO module indicates the information of domain associated with a microarray set; RiceUP module is used to obtain promoter sequences for all genes represented by a microarray set; RiceMR module lists potential microRNA which regulated the genes represented by a microarray set; RiceCD and RiceGF are used to annotate the genes represented by a microarray set in the context of chromosome distribution and rice paralogous family distribution. The results of automatic annotation are mostly consistent with manual annotation. Biological interpretation of the microarray data is quickened by the help of RiceDB.
