Molecular Epidemiology and Sequencing of the G-L Intergenic Region of Rabies Viruses Isolated in China

一组 25 个狂犬病病毒(RABV ) ，从 24 条狗和一个人的盒子恢复了，在在 2004 和 2006 之间的中国从各种各样的区域被收集。G-L intergenic 区域的基因、种系发生的分析在 25 街 RABV 被执行孤立， CTN 疫苗 7 拉紧代。学习基于 519 bp 核苷酸顺序的比较，包含 G-L intergenic 区域。中国街紧张的核苷酸顺序相同从 95.5% ～ 100% 。种系发生的分析证明中国的所有孤立清楚地在 Lyssavirus 遗传型 1 支持了所有中国病毒的放置，他们根据他们的地理起源是分布式的。所有仔细中国紧张被联系，但是他们能仍然被划分成二个组：一些街紧张和一些 CTN 紧张。这研究基于 G-L Intergenic 区域的序列关于狂犬病病毒的分子的传染病学介绍细节。关键词狂犬病病毒 - 分子的传染病学 - G-L intergenic 区域 - 中国 CLC 数字 R373.33 基础条款：第 10 国家 five-year-plan (2004BA718 b03 ) 的关键技术 R&D

Expressing activity of promoter elements of large intergenic region from cotton leaf curl virus in host plant

Cotton leaf curl virus (CLCuV) is a type of single-stranded DMA virus, belonging to geminivirus of subgroup Ⅲ. In order to determine the function of CLCuV large intergenic region (LIR), total DNA of CLCuV-infected cotton leaves was used as template, and fragment of LIR was obtained by PCR and inserted into clone vector. The fragment of LIR was fused with gus reporter gene and nos terminator in the orientation of transcription of virion sense and complementary sense respectively, and the plant expression vectors were constructed. GUS activity of Agrobacte-rium-mediated transgenic tobacco was measured. The result indicated that LIR showed strong promoter activity in complementary sense gene orientation. Average GUS activity of the complementary sense promoter was 5-6 times that of CaMV 35S promoter, and the highest GUS activity of individual plant was ten times of that of CaMV 35S promoter. Histochemical localization confirmed its activity in both mesophyll and vascular tissues. Activity of virion sense of LIR was rather low. Thus LIR isolated from CLCuV could be used as a novel strong promoter in plant genetic manipulation.

PsRNA:A Computing Engine for the Comparative Identification of Putative Small RNA Locations within Intergenic Regions

Small RNAs （sRNAs） are non-coding transcripts exerting their functions in the cells directly. Identification of sRNAs is a difficult task due to the lack of clear sequence and structural biases. Most sRNAs are identified within genus specific intergenic regions in related genomes. However, several of these regions remain un-annotated due to lack of sequence homology and/or potent statistical identification tools. A computational engine has been built to search within the intergenic regions to identify and roughly annotate new putative sRNA regions in Enterobacteriaceae genomes. It utilizes experimentally known sRNA data and their flanking genes/KEGG Orthology （KO） numbers as templates to identify similar sRNA regions in related query genomes. The search engine not only has the capability to locate putative intergenic regions for specific sRNAs, but also has the potency to locate conserved, shuffled or deleted gene clusters in query genomes. Because it uses the KO terms for locating functionally important regions such as sRNAs, any further KO number assignment to additional genes will increase the sensitivity. The PsRNA server is used for the identification of putative sRNA regions through the information retrieved from the sRNA of interest. The computing engine is available online at http：//bioserver 1 .physics.iisc.ernet.in/psrna/and http：//bicmku.in： 8081/psrna/.

Single Nucleotide Polymorphisms (SNPs) and Variable Number Tandem Repeats (VNTRs) in mtDNA D-loop and CO Ⅱ-tRNA^(Lys) Intergenic Region with PCOS

Objective To explore the relationships intergenic region in mtDNA with PCOS. of variations in D-loop and COH-tRNA^Lys Methods A total of 77 PCOS and 45 non-PCOS patients were enrolled, whose D-loop and COH-tRNA^Lys intergenic region in mtDNA were amplified and sequenced; sexual hormone assay, oral glucose tolerance test （OGTT） and insulin releasing test were carried out. Then variations found in mtDNA were compared between the two groups, the correlations between variations and clinical indexes were analyzed in all subjects. Results Nucleotide variations found in mtDNA were not different between the two groups, but the mutation of 16 094T/C was found associated with the serum levels ofT and fasting insulin; （303-317）CnTC, associated with the serum levels of A and LH; 195C/T with A level and 491T/C with LH level; （8 272-8 289）（ACCCCCTCT）, was associated with the serum level of 1 h glucose. Conclusion Noncoding region mutations in mtDNA perhaps associate with PCOS clinical symptoms and involve in PCOS development.

Identification of Streptococcus species and Haemophilus influenzae by direct sequencing of PCR products from 16S-23SrDNA intergenic spacer regions

Objective To set up a rapid and simple method for identificating bacteria by 16S 23SrDNA intergenic spacer regions (ISRs) Methods Polymorphic products of PCR from ISRs were selected on agarose gel and sequenced directly using purified fragments by excising the gel without cloning Nucleotide sequences were compared with GenBank databases and analyzed by DNAMAN program Results There was only a single product in streptococcus genus after PCR amplification of 16S 23SrDNA ISRs Five streptococcal species were obtained from 7 strains of streptococcus Two major amplicons were consistently generated for 8 strains of Haemophilus influenzae (H influenzae) The sequence data showed that they all belonged to H influenzae type b on GenBank databases Conclusion PCR and direct sequencing of 16S 23SrDNA ISRs were very successful methods for bacterial species identification

Junker: An Intergenic Explorer for Bacterial Genomes

In the past few decades, scientists from all over the world have taken a keen interest in novel functional units such as small regulatory RNAs, small open reading frames, pseudogenes, transposons, integrase binding attB/attP sites, repeat elements within the bacterial intergenic regions （IGRs） and in the analysis of those ＂junk＂ regions for ge- nomic complexity. Here we have developed a web server, named Junker, to facilitate the in-depth analysis of IGRs for examining their length distribution, four-quadrant plots, GC percentage and repeat details. Upon selection of a particular bacterial genome, the physical genome map is displayed as a multiple loci with options to view any loci of interest in detail. In addition, an IGR statistics module has been created and implemented in the web server to analyze the length distribution of the IGRs and to understand the disordered grouping of IGRs across the genome by generating the four-quadrant plots. The proposed web server is freely available at the URL http：//pranag.physics.iisc.ernet.in/junker/.