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Articles by J Guan
Total Records ( 3 ) for J Guan
  Y Gan , J Guan and S. Zhou
 

Motivation: Identification of core promoters is a key clue in understanding gene regulations. However, due to the diverse nature of promoter sequences, the accuracy of existing prediction approaches for non-CpG island (simply CGI)-related promoters is not as high as that for CGI-related promoters. This consequently leads to a low genome-wide promoter prediction accuracy.

Results: In this article, we first systematically analyze the similarities and differences between the two types of promoters (CGI- and non-CGI-related) from a novel structural perspective, and then devise a unified framework, called PNNP (Pattern-based Nearest Neighbor search for Promoter), to predict both CGI- and non-CGI-related promoters based on their structural features. Our comparative analysis on the structural characteristics of promoters reveals two interesting facts: (i) the structural values of CGI- and non-CGI-related promoters are quite different, but they exhibit nearly similar structural patterns; (ii) the structural patterns of promoters are obviously different from that of non-promoter sequences though the sequences have almost similar structural values. Extensive experiments demonstrate that the proposed PNNP approach is effective in capturing the structural patterns of promoters, and can significantly improve genome-wide performance of promoters prediction, especially non-CGI-related promoters prediction.

  X Huang , Q Feng , Q Qian , Q Zhao , L Wang , A Wang , J Guan , D Fan , Q Weng , T Huang , G Dong , T Sang and B. Han
 

The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was ~20x faster in data collection and 35x more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.

  J Guan , H. L Zhao , L Baum , Y Sui , L He , H Wong , F. M. M Lai , P. C. Y Tong and J. C. N. Chan
 

Background. Diabetic nephropathy represents a heterogeneous group of renal pathologies that may be associated with genetic susceptibility. There have been clinical reports on the risk association of diabetic nephropathy with an apolipoprotein E (ApoE) exon 4 polymorphism although its correlations with renal histopathological changes have not been explored.

Methods. A total of 213 adult autopsies with type 2 diabetes and 111 non-diabetic control cases were analysed. Genomic DNA samples were obtained from spleen tissues. The ApoE genotype was determined by PCR-LDR analysis. Histopathological examination of kidney sections was performed in a subset of 51 diabetic and 111 control cases. ApoE protein expression in diabetic carriers with similar clinical status was examined by immunohistochemical staining.

Results. In type 2 diabetes, 2 carriers (P = 0.04; odds ratio = 5.42; 95% CI: 1.10–26.8) and 3/4 (P = 0.04; odds ratio = 22.5; 95% CI: 1.11–454.90) genotype carriers were more likely to have glomerular hypertrophy than were 3/3 carriers. The 2 carriers showed an increase in glomerular ApoE protein expression. A correlation between ApoE genotype and nodular glomerulosclerosis was not found.

Conclusions. Our findings confirm the risk association of the ApoE polymorphism with diabetic nephropathy in clinical studies and is the first study demonstrating the correlations between ApoE genotypes, protein expression and structural changes in diabetic nephropathy.

 
 
 
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