A set of novel multi‐allelic SNPs for forensic application developed through massively parallel sequencing and its examples of population genetic studies

Association of VEGFA polymorphisms with chronic obstructive pulmonary disease in Chinese Han and Mongolian populations

NEW FINDINGS

What is the central question of this study? Vascular endothelial growth factor A (VEGFA) is an important growth factor involved in changes in the bronchial microvascular and airway inflammation in chronic obstructive pulmonary disease (COPD) progression. What is the association of single nucleotide polymorphisms (SNPs) in VEGFA with the risk of COPD in the Chinese Han and Mongolian populations? What is the main finding and its importance? The effect of five SNPs in the VEGFA gene was analysed and compared between the Chinese Han and Mongolian populations. A contribution of risk alleles rs833068, rs833070 and rs3024997 to COPD was detected in the Chinese Mongolian population only. The study provided data from different populations to validate the role of VEGFA polymorphisms in COPD and provided reliable SNPs to predict the risk of COPD.

ABSTRACT

We attempted to define the associations between single nucleotide polymorphisms (SNPs) in the vascular endothelial growth factor A (VEGFA) gene and chronic obstructive pulmonary disease (COPD) in Chinese Han and Mongolian cohorts. Five SNPs were genotyped in cohorts of 684 COPD patients (350 Mongolian and 334 Han) and 784 healthy controls (350 Mongolian and 434 Han) using SNPscan multiplex PCR. SNP frequencies, genetic models and haplotypes were analysed using the chi-square test. The associations of SNPs with COPD and linkage disequilibrium were analysed using logistic regression and HaploView, respectively. We found that only rs833068G>A, rs833070T>C and rs3024997G>A were significantly associated with the risk of COPD in the Mongolian population (rs833068: P < 0.001, rs833070: P < 0.001, rs3024997: P = 0.002). In the analysis of genotype distributions, the A/A and G/A genotypes in rs833068 (A/A: odds ratio (OR) = 0.313, P < 0.001; G/A: OR = 0.724, P < 0.001) and rs3024997 (A/A: OR = 0.513, P = 0.008; G/A: OR = 0.671, P = 0.008) and the C/C and T/C genotypes in rs833070 (C/C: OR = 0.435, P = 0.007; T/C: OR = 0.593, P = 0.007) were associated with protection against COPD in the Mongolian population. The haplotype frequencies of GCCAT and GTCGC were significantly different between the patients and controls (GCCAT: P = 0.001; GTCGC: P < 0.001) in the Mongolian population. Our findings indicate that five SNPs in the VEGFA gene play divergent roles in the Han and Mongolian populations. rs833068A, rs833070C and rs3024997A were observed to be associated with the risk of COPD in the Mongolian population.

A digital coding combination analysis for mutational genotyping using pyrosequencing

In the present study, we developed a novel digital coding combination analysis (DCCA) to analyze the gene mutation based on the sample combination principle. The principle is that any numerically named sample is divided into two groups, any two samples are not grouped in the same two groups, and any sample can be tested within the detection limit. Therefore, we proposed a specific combination that N samples were divided into M groups. Then N samples were analyzed, which could obtain the mutation results of M mixed groups. If only two groups showed positive (mutant type) signals, the same sample number from two positive signal groups would be the positive sample, and the remaining samples were negative (wild type). If three groups or more exhibited positive results, the same sample number from three positive signal groups would be the positive sample. If some samples remained uncertain, individual samples could be analyzed on a small scale. In the present study, we used the two genotypes of a mutation site (A5301G) to verify whether it was a useful and promising method. The results showed that we could quantitatively detect mutations and demonstrate 100% consistent results against a panel of defined mixtures with the detection limit using pyrosequencing. This method was suitable, sensitive, and reproducible for screening and analyzing low-frequency mutation samples, which could reduce reagent consumption and cost by approximately 70-80% compared with conventional clinical methods.