Optimizing Multiplex PCR for a Set of Malay Ancestry Informative Marker-Single Nucleotide Polymorphisms (AIM-SNPs) and Preliminary Analysis of Genotypes Between Malay and non-Malay Population.

Background: Inference of genetic ancestry is of great interest in many fields and one of the markers in these analyses is ancestry informative marker single nucleotide polymorphisms (AIMSNPs). The Malay population is an ethnic group located mainly in South East Asia and comprises the largest ethnicity in Malaysia. Objectives: To determine Malay ancestry, Yahya et al, 2017 selected 37,487 SNPs from the genotyping data collected by the Malaysian Node of the Human Variome Project and Singapore Genome Variation Project and referenced them against the data from the International HapMap Project Phase 3. The SNPs determined to be informative for ancestry were compiled into AIM-SNP panels, and from these a few SNPs were selected for optimization in preparation for single base extension reaction multiplexing. Methodology: The chosen AIMSNPs were optimized and validated on Malay and non-Malay populations. Genotyping was carried out on participants of self-reported Malay and non-Malay ancestry respectively and the data were compared for Malay and non-Malay population to investigate for significant differences in the genotype between Malay and non-Malay participants. Findings: The results showed great similarities between the Malay and non-Malay population, which may arise from many factors, and further optimization of more SNPs and genotyping is required to definitively conclude the validity of the AIM-SNP panels for Malay population Conclusion: Knowledge of ancestry is important to minimise spurious association. This pilot study gives a brief account of the optimization process and offers an insight into how this may be done in South East Asian populations.

Transcriptional similarity in couples reveals the impact of shared environment and lifestyle on gene regulation through modified cytosines

Gene expression is a complex and quantitative trait that is influenced by both genetic and non-genetic regulators including environmental factors. Evaluating the contribution of environment to gene expression regulation and identifying which genes are more likely to be influenced by environmental factors are important for understanding human complex traits. We hypothesize that by living together as couples, there can be commonly co-regulated genes that may reflect the shared living environment (e.g., diet, indoor air pollutants, behavioral lifestyle). The lymphoblastoid cell lines (LCLs) derived from unrelated couples of African ancestry (YRI, Yoruba people from Ibadan, Nigeria) from the International HapMap Project provided a unique model for us to characterize gene expression pattern in couples by comparing gene expression levels between husbands and wives. Strikingly, 778 genes were found to show much smaller variances in couples than random pairs of individuals at a false discovery rate (FDR) of 5%. Since genetic variation between unrelated family members in a general population is expected to be the same assuming a random-mating society, non-genetic factors (e.g., epigenetic systems) are more likely to be the mediators for the observed transcriptional similarity in couples. We thus evaluated the contribution of modified cytosines to those genes showing transcriptional similarity in couples as well as the relationships these CpG sites with other gene regulatory elements, such as transcription factor binding sites (TFBS). Our findings suggested that transcriptional similarity in couples likely reflected shared common environment partially mediated through cytosine modifications.

A-MBED: Adaptive Markov Blanket Method for Epitasis Detection in Genome-Wide Association Studies

With the completion of the international HapMap project and the development of high-throughput technologies, designing more effective epistasis detection algorithm for genome-wide data poses a significant challenge. This paper proposes a new method based on the Markov blanket to solve the limitations of the existing algorithm, such as a large false-positive proportion and low accuracy. The algorithm uses G2 to judge the strength of correlation between variables of self-adaptive remove strategy and SNP matching method; to effectively eliminate variables that are unrelated to the target, as well as weak correlation between variables; to significantly reduce the search space and time; to prevent unnecessary retrieval analysis; and to improve the accuracy of the detection algorithm to a certain extent.

A FAST AND ACCURATE ALGORITHM FOR DIPLOID INDIVIDUAL HAPLOTYPE RECONSTRUCTION

Haplotypes can provide significant information in many research fields, including molecular biology and medical therapy. However, haplotyping is much more difficult than genotyping by using only biological techniques. With the development of sequencing technologies, it becomes possible to obtain haplotypes by combining sequence fragments. The haplotype reconstruction problem of diploid individual has received considerable attention in recent years. It assembles the two haplotypes for a chromosome given the collection of fragments coming from the two haplotypes. Fragment errors significantly increase the difficulty of the problem, and which has been shown to be NP-hard. In this paper, a fast and accurate algorithm, named FAHR, is proposed for haplotyping a single diploid individual. Algorithm FAHR reconstructs the SNP sites of a pair of haplotypes one after another. The SNP fragments that cover some SNP site are partitioned into two groups according to the alleles of the corresponding SNP site, and the SNP values of the pair of haplotypes are ascertained by using the fragments in the group that contains more SNP fragments. The experimental comparisons were conducted among the FAHR, the Fast Hare and the DGS algorithms by using the haplotypes on chromosome 1 of 60 individuals in CEPH samples, which were released by the International HapMap Project. Experimental results under different parameter settings indicate that the reconstruction rate of the FAHR algorithm is higher than those of the Fast Hare and the DGS algorithms, and the running time of the FAHR algorithm is shorter than those of the Fast Hare and the DGS algorithms. Moreover, the FAHR algorithm has high efficiency even for the reconstruction of long haplotypes and is very practical for realistic applications.

Lack of association of genetic variations of deoxycytidine kinase with toxicity or survival of non-small cell lung cancer patients treated with gemcitabine plus cisplatin.

e13065 Background: To determine whether tagging polymorphisms (tSNPs) of deoxycytidine kinase (DCK) have an effect on toxicity or prognosis in patients with non–small-cell lung cancer (NSCLC) treated with gemcitabine plus cisplatin. Methods: Three tSNPs (−201 C>T, rs2306744; IVS2+9846 G>A, rs12648166; IVS6+1392 T>C, rs4694362) were chosen using two databases, the international HapMap Project and Japanese Single-Nucleotide Polymorphisms. Genotyping was performed using the Genome Lab SNPstream Genotyping System and SNaPShot assay kit. We evaluated the associations of the tSNPs with hematologic toxicity or overall survival of 139 NSCLC patients at stages IIIA/IIIB (59) and IV (80). Results: The median survival time of the patients was 11.9 months. Hematologic toxicity such as neutropenia, thrombocytopenia and anemia were not different by the three tSNPs or haplotypes (CGT, CAT and CAC) of DCK. The genetic variations did not affect on survival of the patients (log-rank P: 0.248 for −201 C>T, 0.571 for IVS2+9846 G>A, 0.686 for IVS6+1392 T>C, 0,556 for CGT, 0.453 for CAT and 0.845 for CAC). In Cox model, these tSNPs and haplotypes did not reveal prognostic relevance (aHR and 95%CI: 0.954 and 0.611 to 1.489 for −201 C>T; 1.193 and 0.719 to 1.979 for IVS2+9846 G>A; 1.072 and 0.674 to 1.706 for IVS6+1392 T>C, 0,668 and 0.205 to 2.175 for CGT, 1.043 and 0.713 to 1.525 for CAT and1.043 and 0.701 to 1.550 for CAC). Conclusions: This is the first study to focus on the association of tSNPs and their haplotypes of DCK with toxicity and survival in NSCLC patients. This suggests that genetic variations of DCK have no effect on the outcomes in the patients treated with gemcitabine-based chemotherapy.

SCANNING AND ANALYSIS OF MISMATCH DISTRIBUTION ON HUMAN GENOME

The mismatch distribution is a good descriptive summary statistic that describes the phenomena of population genetics. This article scanned mismatch distribution on human genome with single nucleotide polymorphism (SNP) data from the International HapMap Project. It is found that the abnormal mismatch distribution could imply some special segments on some chromosomes. One of the segments, on chromosome 8, was proved as an inversion. Other special segments may also imply some special structure on chromosomes, such as duplication. The conjectures of other segments still need further research.

The Genetic Diversity and Structure of Linkage Disequilibrium of the MTHFR Gene in Populations of Northern Eurasia

The structure of the haplotypes and linkage disequilibrium (LD) of the methylenetetrahydrofolate reductase gene (MTHFR) in 9 population groups from Northern Eurasia and populations of the international HapMap project was investigated in the present study. The data suggest that the architecture of LD in the human genome is largely determined by the evolutionary history of populations; however, the results of phylogenetic and haplotype analyses seems to suggest that in fact there may be a common old mechanism for the formation of certain patterns of LD. Variability in the structure of LD and the level of diversity of MTHFR haplotypes cause a certain set of tagSNPs with an established prognostic significance for each population. In our opinion, the results obtained in the present study are of considerable interest for understanding multiple genetic phenomena: namely, the association of interpopulation differences in the patterns of LD with structures possessing a genetic susceptibility to complex diseases, and the functional significance of the pleiotropic MTHFR gene effect. Summarizing the results of this study, a conclusion can be made that the genetic variability analysis with emphasis on the structure of LD in human populations is a powerful tool that can make a significant contribution to such areas of biomedical science as human evolutionary biology, functional genomics, genetics of complex diseases, and pharmacogenomics.