Biomedical subjects

Xiang-Dong Ding

Publications and source records attributed to Xiang-Dong Ding.

3 recordsLinked to original sources

PubMed2005

[Sequences and their polymorphisms of swine MHC-DQB, DRB proximal promoter region].

The primers, RF/RR and QF1/QR,were designed based on the homologous region of swine MHC-DQB and DRB exon1 sequences and HLA-DQB and HLA-DRB sequences. The 5' proximal promoter region (URR) nucleotide sequences of swine MHC-DQB and DRB were firstly obtained by PCR, cloning and sequencing techniques. There exist highly conserved sequence motifs including W, X, Y, CCAAT, and TATA-like boxes in the obtained sequences,showing the same organization of the conserved regulatory elements as in other species. 12 DRB-URR and 14 DQB-URR alleles were found by PCR-SSCP in 313 pigs. The aligned results of these alleles showed that there exist abundant polymorphism sites in both Porcine MHC-DQB and DRB proximal promoter region.

Alleles↗

PubMed2005

[Methodology of mapping quantitative trait loci for discrete traits using maximum likelihood].

The maximum likelihood method was used to compare the efficiency of interval mapping with either the threshold model or the linear model. The irfluencing factors of quantitative trait loci (QTL) detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the number of segregating population was 500. The results showed that the threshold model was superior in terms of parameter estimation. It was a more efficient and accurate model of QTL mapping for discrete traits. In addition, the accuracy of QTL mapping depended on the effect of the putative QTL, the value of heritability and incidence directly. With an increase of QTL effect, heritability and incidence of categories, the accuracy of QTL mapping improved correspondingly.

Algorithms↗

PubMed2005

Methodology of mapping quantitative trait loci for ordinal traits of disease resistance in livestock.

Methodology of QTL mapping for ordinal traits of disease resistance based on the framework of a generalized linear model (GLM) was presented. The location and effect parameters of putative QTL were estimated using maximum likelihood method. The efficiency and power were compared with the linear model (LM). The factors influencing QTL detection efficiency (e.g. QTL effect and heritability) were simulated in our study too. Daughter design with multiple families was applied,and the number of segregating population was 500. Results showed that the threshold model has a certain advantage in location estimation and power of QTL mapping, and has efficiency and accuracy for ordinal traits. In addition,the accuracy of QTL mapping depends on the effect of putative quantitative trait loci and the value of heritability. With the increase of QTL effect and heritability, the accuracy of QTL mapping improves slightly.

Animals↗