[Genetic polymorphisms of 21 non-combined of DNA index system short tandem repeat loci in Hainan Li population].

OBJECTIVE: To investigate the genetic polymorphisms of 21 non-combined DNA index system short tandem repeat (STR) loci in Hainan Li population. METHODS: DNA samples from 339 unrelated healthy individuals of Li population from Hainan Province were extracted and amplified with fluorescence labeled multiplex PCR system. PCR products were electrophoresed on an ABI3130 Genetic Analyzer following the manufacturer's instructions. Allele designation was performed with a GeneMapper ID-X by comparison with the allele ladder provided by the corresponding kit. RESULTS: A total of 173 alleles and 489 genotypes were observed for the 21 STR loci, respectively. The frequencies of alleles and genotypes were 0.0010-0.5434 and 0.0020-0.3274, respectively. The heterozygosity varied from 0.639 to 0.833. Discrimination power (DP) was 0.803-0.948, power of exclusion for trio-paternity was 0.416-0.584, power of exclusion for duo-paternity was 0.140-0.238, the polymorphism information content(PIC) was 0.57-0.81, respectively. The total discrimination power (TDP), cumulative probability of exclusion for trio-paternity testing(CPE-trio) and cumulative probability of exclusion for duo-paternity testing (CPE-duo) were 0.999 999 999 999 99, 0.999 999 883 211 752, and 0.987 266, respectively. CONCLUSION: The 21 STR loci are highly polymorphic and informative in the studied population and can be employed as supplementary loci in duo-paternity testing or cases with variant circumstances.

Bioinformatics analysis for hepatocellular carcinoma genes based on the data of expression profile chip. / åŸºäºŽè¡¨è¾¾è°±èŠ¯ç‰‡æ•°æ®çš„è‚ç»†èƒžç™ŒåŸºå› çš„ç”Ÿç‰©ä¿¡æ¯å­¦åˆ†æž.

OBJECTIVES: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, especially in Asia and Africa. However, the underlying mechanism is still unclear. Consequently, it is important to explore its key genes and prognosis-related genes via bioinformatics. This study aimed to explore the molecular mechanism of HCC by using bioinformatics analysis for HCC gene chip data. METHODS: Microarray data of HCC genes were downloaded from public GEO database and screened for differentially expressed genes (DEGs) by GEO2R analysis. Then DAVID online tool was used for GO annotation and KEGG pathway enrichment analysis. STRING-DB online database and Cytoscape software were used for protein interaction network analysis.GEPIA and Ualcan were applied to evaluate prognosis and promoter methylation level. RESULTS: A total of 87 DEGs of HCC were screened, of which 15 genes were up-regulated and 72 genes were down-regulated. GO annotation indicated that most of the genes were involved in oxidation reduction,cellular amino acid derivative metabolic process, carboxylic acid catabolic process, and response to wounding. KEGG pathways were enriched in linoleic acid metabolism, retinol metabolism, complement and coagulation cascades,steroid hormone biosynthesis, drug metabolism, and other pathways. Two key modules and key genes AURKA and SPP2 were obtained by protein interaction network analysis. Prognostic analysis showed that the 2 genes were significantly correlated with the total survival time of patients with HCC. There was no significant difference in the methylation level of AURKA promoter between the primary tumor group and the normal group (P=0.296) and the methylation level of SPP2 promoter was significantly lower in the primary tumor group than that in the normal group (P<0.001). CONCLUSIONS: HCC-relevant AURKA and SPP2 are obtained via bioinformatics analysis, which are closely related to the prognosis of patients with HCC. Gene promoter methylation is not the main factor for AURKA and SPP2 expression levels.

[Sequencing of a large off-ladder allele at Penta E locus].

OBJECTIVE: To identify a rare large off ladder (OL) allele at the Penta E locus. METHODS: Chelex-100 was used to extract DNAs from the blood samples. The PCR fragments were purified, extracted, and subjected to TA cloning and sequencing. RESULTS: An OL allele was identified by the PowerPlex™ 21 at the Penta E locus, which was postulated as allele 26 based on assigned size. The OL allele was verified as a novel fragment containing 26 full AAAGA repeats. CONCLUSION: OL alleles and microvariants should be verified by direct sequencing. Typing of OL alleles has significance for both daily work and forensic genetics.

[Genetic polymorphisms of 23 autosomal short tandem repeat loci among ethnic Han Chinese from southern China].

OBJECTIVE: To study genetic polymorphisms of 23 autosomal short tandem repeat (STR) loci among ethnic Han Chinese from southern China. METHODS: The 23 autosomal STR loci among 331 unrelated healthy Han Chinese from southern China were genotyped with fluorescent multiplex amplification and capillary electrophoresis. Genetic parameters were subjected to statistical analysis. RESULTS: In total 265 alleles and 890 genotypes were detected for the 23 STR loci. The numbers of alleles were 5-22, allelic frequency was 0.0015-0.5483, heterozygosity was 0.5891-0.9124, power of discrimination was 0.7818-0.9831, polymorphic information content was 0.5425-0.9031, probability of exclusion for trio-paternity testing was 0.2780-0.8208, and probability of exclusion for duo-paternity testing was 0.193-0.693. The combined power of discrimination was over 0.999 999 999 999 99, the combined probability of exclusion for trio-paternity identification was 0.999 999 999 729 813, and the combined probability of exclusion for duo-paternity identification was 0.999 999 207 508 474, respectively. The 23 STR loci showed no significant deviation from Hardy-Weinberg disequilibrium after Bonferroni correction (P> 0.05). CONCLUSION: The 23 autosomal STR loci were highly polymorphic among ethnic Han Chinese from southern China, which showed a high efficiency for paternity testing, personal identification and population genetics.

[Research progress in DEAD-box family protein in cancer].

DEAD-box family protein is a kind of ATP dependent RNA helicase, which plays a critical role in RNA metabolism. The DEAD-box family proteins can affect cell proliferation, differentiation, and apoptosis through regulating the expression of oncogenes, tumor suppressor genes and tumor related signaling pathways. It plays the role in promoting or suppressing cancer.

Transcriptome profiling of a multiple recurrent muscle-invasive urothelial carcinoma of the bladder by deep sequencing.

Urothelial carcinoma of the bladder (UCB) is one of the commonly diagnosed cancers in the world. The UCB has the highest rate of recurrence of any malignancy. A genome-wide screening of transcriptome dysregulation between cancer and normal tissue would provide insight into the molecular basis of UCB recurrence and is a key step to discovering biomarkers for diagnosis and therapeutic targets. Compared with microarray technology, which is commonly used to identify expression level changes, the recently developed RNA-seq technique has the ability to detect other abnormal regulations in the cancer transcriptome, such as alternative splicing. In this study, we performed high-throughput transcriptome sequencing at ∼50× coverage on a recurrent muscle-invasive cisplatin-resistance UCB tissue and the adjacent non-tumor tissue. The results revealed cancer-specific differentially expressed genes between the tumor and non-tumor tissue enriched in the cell adhesion molecules, focal adhesion and ECM-receptor interaction pathway. Five dysregulated genes, including CDH1, VEGFA, PTPRF, CLDN7, and MMP2 were confirmed by Real time qPCR in the sequencing samples and the additional eleven samples. Our data revealed that more than three hundred genes showed differential splicing patterns between tumor tissue and non-tumor tissue. Among these genes, we filtered 24 cancer-associated alternative splicing genes with differential exon usage. The findings from RNA-Seq were validated by Real time qPCR for CD44, PDGFA, NUMB, and LPHN2. This study provides a comprehensive survey of the UCB transcriptome, which provides better insight into the complexity of regulatory changes during recurrence and metastasis.