Single Nucleotide Polymorphisms Pairs Research Articles

A novel multiplex pyrosequencing assay for genotyping functionally relevant CTLA-4 polymorphisms: Potential applications in autoimmunity and cancer

CTLA-4 expression/function can be affected by single nucleotide polymorphisms (SNPs) of CTLA-4 gene, which have been widely associated with susceptibility or progression to autoimmune diseases and cancer development.In this study, we analyzed six CTLA-4 SNPs (−1661A>G, −1577G>A, −658C>T, −319C>T, +49A>G, CT60G>A) in 197 DNA samples from 43 B-lymphoblastoid cell lines (B-LCLs), 40 systemic sclerosis (SSc) patients, 14 pre-analyzed melanoma patients and 100 Italian healthy subjects.Genotyping of −1661A>G, −1577G>A, −658C>T and CT60G>A was performed by newly developed multiplex pyrosequencing (PSQ) assays, whereas −319C>T and +49A>G by T-ARMS PCR and direct sequencing. Genotype/allele frequency were analyzed using χ2 or Fisher exact test.Our study provides the first multiplex PSQ method that allows simultaneous genotyping of two CTLA-4 SNP pairs (i.e. −1661A>G/−658C>T and −1577G>A/CT60G>A) by two multiplex PSQ reactions. Herein, we show the CTLA-4 genotype distribution in the B-LCLs providing the first and best characterized cell line panel typed for functionally relevant CTLA-4 SNPs.We also report the significant association of the −1661A/G genotype, −1661 & −319 AC-GT diplotype and −319 & CT60 TG haplotype with susceptibility to SSc without Hashimoto’s thyroiditis occurrence. Furthermore, we confirmed previous genotyping data referred to melanoma patients and provided new genotyping data for Italian healthy subjects.

Association of IL33–IL-1 receptor–like 1 (IL1RL1) pathway polymorphisms with wheezing phenotypes and asthma in childhood

Genome-wide association studies identified IL33 and IL-1 receptor-like 1 (IL1RL1)/IL18R1 as asthma susceptibility loci. IL33 and IL1RL1 constitute a single ligand-receptor pathway. In 2 birth cohorts, the Prevalence and Incidence of Asthma and Mite Allergy (PIAMA) study and Avon Longitudinal Study of Parents and Children (ALSPAC), we analyzed associations of longitudinal wheezing phenotypes and asthma with single nucleotide polymorphisms (SNPs) of 8 genes encoding IL-33, IL1RL1, its coreceptor IL1RAcP, its adaptors myeloid differentiation primary response gene 88 (MyD88) and Toll-IL-11 receptor domain containing adaptor protein (TIRAP), and the downstream IL-1 receptor-associated kinase 1, IL-1 receptor-associated kinase 4, and TNF receptor-associated factor 6 (TRAF6). Furthermore, we investigated whether SNPs in this pathway show replicable evidence of gene-gene interaction. Ninety-four SNPs were investigated in 2007 children in the PIAMA study and 7247 children in ALSPAC. Associations with wheezing phenotypes and asthma at 8 years of age were analyzed in each cohort and subsequently meta-analyzed. Gene-gene interactions were assessed through model-based multifactor dimensionality reduction in the PIAMA study, and gene-gene interactions of 10 SNP pairs were further evaluated. Intermediate-onset wheeze was associated with SNPs in several genes in the IL33-IL1RL1 pathway after applying multiple testing correction in the meta-analysis: 2 IL33 SNPs (rs4742170 and rs7037276), 1 IL-1 receptor accessory protein (IL1RAP) SNP (rs10513854), and 1 TRAF6 SNP (rs5030411). Late-onset wheeze was associated with 2 IL1RL1 SNPs (rs10208293 and rs13424006), and persistent wheeze was associated with 1 IL33 SNP (rs1342326) and 1 IL1RAP SNP (rs9290936). IL33 and IL1RL1 SNPs were nominally associated with asthma. Three SNP pairs showed interaction for asthma in the PIAMA study but not in ALSPAC. IL33-IL1RL1 pathway polymorphisms are associated with asthma and specific wheezing phenotypes; that is, most SNPs are associated with intermediate-onset wheeze, a phenotype closely associated with sensitization. We speculate that IL33-IL1RL1 pathway polymorphisms affect development of wheeze and subsequent asthma through sensitization in early childhood.

The axis inhibition protein 2 polymorphisms and non‐syndromic orofacial clefts susceptibility in a Chinese Han population

The axis inhibition protein 2 (AXIN2) is an important regulator of β-catenin degradation in the Wnt pathway, which plays a key role in craniofacial morphogenesis. The goal of this study was to investigate the potential relationship between AXIN2 polymorphisms and the risks of non-syndromic orofacial clefts (NSOC) in a Chinese Han population. Four polymorphisms of AXIN2 (rs2240307, rs11867417, rs2240308, and rs7591) were selected to perform a case-control study with 599 NSOC cases and 602 healthy individuals from a Chinese Han population. The single nucleotide polymorphisms (SNPs) were genotyped on basis of double ligation and multiplex fluorescence PCR. Weak associations were found between these four SNPs and the risk of NSOC. Further stratified analysis showed that the overall genotype frequencies of rs2240307 were different between the cleft palate only (CPO) group and the control group (P = 0.048), and GG genotype markedly contributed to the susceptibility to CPO (OR = 3.22, 95% CI = 1.13-9.18). The similar effect was also observed on GA/AA genotype compared with GG homozygote (OR = 0.30, 95% CI = 0.11-0.84). The results of LD analysis between each pair of SNPs revealed that two SNPs (rs11867417 and rs7591) were in a LD block (r(2) > 0.8). But no statistically significant was found between cases and controls from haplotype analysis in these two loci. The borderline results gave us a hint that rs2240307 contributed to the susceptibility to CPO in a Chinese Han population, which was conductive to improving our awareness of the causes of NSOC.

Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data.

BackgroundHigh-throughput genotype (HTG) data has been used primarily in genome-wide association (GWA) studies; however, GWA results explain only a limited part of the complete genetic variation of traits. In systems genetics, network approaches have been shown to be able to identify pathways and their underlying causal genes to unravel the biological and genetic background of complex diseases and traits, e.g., the Weighted Gene Co-expression Network Analysis (WGCNA) method based on microarray gene expression data. The main objective of this study was to develop a scale-free weighted genetic interaction network method using whole genome HTG data in order to detect biologically relevant pathways and potential genetic biomarkers for complex diseases and traits.ResultsWe developed the Weighted Interaction SNP Hub (WISH) network method that uses HTG data to detect genome-wide interactions between single nucleotide polymorphism (SNPs) and its relationship with complex traits. Data dimensionality reduction was achieved by selecting SNPs based on its: 1) degree of genome-wide significance and 2) degree of genetic variation in a population. Network construction was based on pairwise Pearson's correlation between SNP genotypes or the epistatic interaction effect between SNP pairs. To identify modules the Topological Overlap Measure (TOM) was calculated, reflecting the degree of overlap in shared neighbours between SNP pairs. Modules, clusters of highly interconnected SNPs, were defined using a tree-cutting algorithm on the SNP dendrogram created from the dissimilarity TOM (1-TOM). Modules were selected for functional annotation based on their association with the trait of interest, defined by the Genome-wide Module Association Test (GMAT). We successfully tested the established WISH network method using simulated and real SNP interaction data and GWA study results for carcass weight in a pig resource population; this resulted in detecting modules and key functional and biological pathways related to carcass weight.ConclusionsWe developed the WISH network method which is a novel 'systems genetics' approach to study genetic networks underlying complex trait variation. The WISH network method reduces data dimensionality and statistical complexity in associating genotypes with phenotypes in GWA studies and enables researchers to identify biologically relevant pathways and potential genetic biomarkers for any complex trait of interest.

A genome-wide association study of immune response traits in Canadian Holstein cattle

BackgroundBreeding for enhanced immune response (IR) has been suggested as a tool to improve inherent animal health. Dairy cows with superior antibody-mediated (AMIR) and cell-mediated immune responses (CMIR) have been demonstrated to have a lower occurrence of many diseases including mastitis. Adaptive immune response traits are heritable, and it is, therefore, possible to breed for improved IR, decreasing the occurrence of disease. The objective of this study was to perform genome-wide association studies to determine differences in genetic profiles among Holstein cows classified as High or Low for AMIR and CMIR. From a total of 680 cows with immune response phenotypes, 163 cows for AMIR (81 High and 82 Low) and 140 for CMIR (75 High and 65 Low) were selectively genotyped using the Illumina Bovine SNP50 BeadChip. Results were validated using an unrelated population of 164 Holstein bulls IR phenotyped for AMIR and 146 for CMIR.ResultsA generalized quasi likelihood score method was used to determine single nucleotide polymorphisms (SNP) and chromosomal regions associated with immune response. After applying a 5% chromosomal false discovery rate, 186 SNPs were significantly associated with AMIR. The majority (93%) of significant markers were on chromosome 23, with a similar peak found in the bull population. For CMIR, 21 SNP markers remained significant. Candidate genes within 250,000 base pairs of significant SNPs were identified to determine biological pathways associated with AMIR and CMIR. Various pathways were identified, including the antigen processing and presentation pathway, important in host defense. Candidate genes included those within the bovine Major Histocompatability Complex such as BoLA-DQ, BoLA-DR and the non-classical BoLA-NC1 for AMIR and BoLA-DQ for CMIR, the complement system including C2 and C4 for AMIR and C1q for CMIR, and cytokines including IL-17A, IL17F for AMIR and IL-17RA for CMIR and tumor necrosis factor for both AMIR and CMIR. Additional genes associated with CMIR included galectins 1, 2 and 3, BCL2 and β-defensin.ConclusionsThe significant genetic variation associated with AMIR and CMIR in this study may imply feasibility to include immune response in genomic breeding indices as an approach to improve inherent animal health.

How genome-wide SNP-SNP interactions relate to nasopharyngeal carcinoma susceptibility.

This study is the first to use genome-wide association study (GWAS) data to evaluate the multidimensional genetic architecture underlying nasopharyngeal cancer. Since analysis of data from GWAS confirms a close and consistent association between elevated risk for nasopharyngeal carcinoma (NPC) and major histocompatibility complex class 1 genes, our goal here was to explore lesser effects of gene-gene interactions. We conducted an exhaustive genome-wide analysis of GWAS data of NPC, revealing two-locus interactions occurring between single nucleotide polymorphisms (SNPs), and identified a number of suggestive interaction loci which were missed by traditional GWAS analyses. Although none of the interaction pairs we identified passed the genome-wide Bonferroni-adjusted threshold for significance, using independent GWAS data from the same population (Stage 2), we selected 66 SNP pairs in 39 clusters with P<0.01. We identified that in several chromosome regions, multiple suggestive interactions group to form a block-like signal, effectively reducing the rate of false discovery. The strongest cluster of interactions involved the CREB5 gene and a SNP rs1607979 on chromosome 17q22 (P = 9.86×10−11) which also show trans-expression quantitative loci (eQTL) association in Chinese population. We then detected a complicated cis-interaction pattern around the NPC-associated HLA-B locus, which is immediately adjacent to copy-number variations implicated in male susceptibility for NPC. While it remains to be seen exactly how and to what degree SNP-SNP interactions such as these affect susceptibility for nasopharyngeal cancer, future research on these questions holds great promise for increasing our understanding of this disease’s genetic etiology, and possibly also that of other gene-related cancers.

Long Range Linkage Disequilibrium across the Human Genome

Long-range linkage disequilibria (LRLD) between sites that are widely separated on chromosomes may suggest that population admixture, epistatic selection, or other evolutionary forces are at work. We quantified patterns of LRLD on a chromosome-wide level in the YRI population of the HapMap dataset of single nucleotide polymorphisms (SNPs). We calculated the disequilibrium between all pairs of SNPs on each chromosome (a total of >2×1011 values) and evaluated significance of overall disequilibrium using randomization. The results show an excess of associations between pairs of distant sites (separated by >0.25 cM) on all of the 22 autosomes. We discuss possible explanations for this observation.

Epistatic Effects on Abdominal Fat Content in Chickens: Results from a Genome-Wide SNP-SNP Interaction Analysis

We performed a pairwise epistatic interaction test using the chicken 60 K single nucleotide polymorphism (SNP) chip for the 11th generation of the Northeast Agricultural University broiler lines divergently selected for abdominal fat content. A linear mixed model was used to test two dimensions of SNP interactions affecting abdominal fat weight. With a threshold of P<1.2×10−11 by a Bonferroni 5% correction, 52 pairs of SNPs were detected, comprising 45 pairs showing an Additive×Additive and seven pairs showing an Additive×Dominance epistatic effect. The contribution rates of significant epistatic interactive SNPs ranged from 0.62% to 1.54%, with 47 pairs contributing more than 1%. The SNP-SNP network affecting abdominal fat weight constructed using the significant SNP pairs was analyzed, estimated and annotated. On the basis of the network’s features, SNPs Gga_rs14303341 and Gga_rs14988623 at the center of the subnet should be important nodes, and an interaction between GGAZ and GGA8 was suggested. Twenty-two quantitative trait loci, 97 genes (including nine non-coding genes), and 50 pathways were annotated on the epistatic interactive SNP-SNP network. The results of the present study provide insights into the genetic architecture underlying broiler chicken abdominal fat weight.

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46 450 cases and 42 461 controls from the breast cancer association consortium

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Genetic consequences of breaking migratory traditions in barnacle geese Branta leucopsis

Cultural transmission of migratory traditions enables species to deal with their environment based on experiences from earlier generations. Also, it allows a more adequate and rapid response to rapidly changing environments. When individuals break with their migratory traditions, new population structures can emerge that may affect gene flow. Recently, the migratory traditions of the Barnacle Goose Branta leucopsis changed, and new populations differing in migratory distance emerged. Here, we investigate the population genetic structure of the Barnacle Goose to evaluate the consequences of altered migratory traditions. We used a set of 358 single nucleotide polymorphism (SNP) markers to genotype 418 individuals from breeding populations in Greenland, Spitsbergen, Russia, Sweden and the Netherlands, the latter two being newly emerged populations. We used discriminant analysis of principal components, FST , linkage disequilibrium and a comparison of geneflow models using migrate-n to show that there is significant population structure, but that relatively many pairs of SNPs are in linkage disequilibrium, suggesting recent admixture between these populations. Despite the assumed traditions of migration within populations, we also show that genetic exchange occurs between all populations. The newly established nonmigratory population in the Netherlands is characterized by high emigration into other populations, which suggests more exploratory behaviour, possibly as a result of shortened parental care. These results suggest that migratory traditions in populations are subject to change in geese and that such changes have population genetic consequences. We argue that the emergence of nonmigration probably resulted from developmental plasticity.

Corrigendum of ‘High throughput analysis of epistasis in genome-wide association studies with BiForce’

Abstract Contact: Wenhua.Wei@igmm.ed.ac.uk

Random Forests approach for identifying additive and epistatic single nucleotide polymorphisms associated with residual feed intake in dairy cattle

Feed efficiency is an economically important trait in the beef and dairy cattle industries. Residual feed intake (RFI) is a measure of partial efficiency that is independent of production level per unit of body weight. The objective of this study was to identify significant associations between single nucleotide polymorphism (SNP) markers and RFI in dairy cattle using the Random Forests (RF) algorithm. Genomic data included 42,275 SNP genotypes for 395 Holstein cows, whereas phenotypic measurements were daily RFI from 50 to 150d postpartum. Residual feed intake was defined as the difference between an animal’s feed intake and the average intake of its cohort, after adjustment for year and season of calving, year and season of measurement, age at calving nested within parity, days in milk, milk yield, body weight, and body weight change. Random Forests is a widely used machine-learning algorithm that has been applied to classification and regression problems. By analyzing the tree structures produced within RF, the 25 most frequent pairwise SNP interactions were reported as possible epistatic interactions. The importance scores that are generated by RF take into account both main effects of variables and interactions between variables, and the most negative value of all importance scores can be used as the cutoff level for declaring SNP effects as significant. Ranking by importance scores, 188 SNP surpassed the threshold, among which 38 SNP were mapped to RFI quantitative trait loci (QTL) regions reported in a previous study in beef cattle, and 2 SNP were also detected by a genome-wide association study in beef cattle. The ratio of number of SNP located in RFI QTL to the total number of SNP in the top 188 SNP chosen by RF was significantly higher than in all 42,275 whole-genome markers. Pathway analysis indicated that many of the top 188 SNP are in genomic regions that contain annotated genes with biological functions that may influence RFI. Frequently occurring ancestor-descendant SNP pairs can be explored as possible epistatic effects for further study. The importance scores generated by RF can be used effectively to identify large additive or epistatic SNP and informative QTL. The consistency in results of our study and previous studies in beef cattle indicates that the genetic architecture of RFI in dairy cattle might be similar to that of beef cattle.

Nucleotide sequence analysis of two lignin genes in Acacia auriculiformis × Acacia mangium hybrid for enhancement of wood pulp quality

There is large potential in the establishment of Acacia auriculiformis × Acacia mangium hybrid plantations through selection of high quality parents especially with characteristics favourable for some end products like pulp and fibre. Trees altered in their lignin profile with reduced amounts of lignin or increased extractable syringyl are desirable in the pulp and paper industry. Cinnamoyl-CoA reductase (CCR) and caffeic acid O-methyltransferase (COMT) are two enzymes likely to regulate lignin content and composition in the syringyl (S)- and guaiacyl (G)-related monolignols at specific branches of the lignin biosynthetic pathway. A goal of this study was to discover the genetic variation in CCR and COMT genes in Acacia species using single nucleotide polymorphisms (SNPs). In this study, two lignin genes, CCR (3,317 bp) and COMT (2,764 bp), were isolated from the Acacia hybrid, sequenced and analysed in silico. Southern blot analysis suggested that there are one to two copies of genes encoding CCR and COMT in the Acacia hybrid. Upon genotyping 480 individuals from natural populations of A. auriculiformis and A. mangium, six CCR SNPs were found in A. auriculiformis and five CCR SNPs in A. mangium. Three COMT SNPs were found in A. auriculiformis and one COMT SNP in A. mangium. A pair of CCR SNPs showed high linkage disequlibrium (LD) with r2 value of 0.870 in an A. mangium population from Papua New Guinea. The SNPs will be further exploited through the candidate gene-based LD mapping to identify QTLs for the Acacia marker-assisted breeding. This is the first documentation of the isolation, cloning and re-sequencing of CCR and COMT genes in the Acacia hybrid and the natural populations of A. auriculiformis and A. mangium.

Efficient Two‐Step Testing of Gene‐Gene Interactions in Genome‐Wide Association Studies

Exhaustive testing of all possible SNP pairs in a genome-wide association study (GWAS) generally yields low power to detect gene-gene (G × G) interactions because of small effect sizes and stringent requirements for multiple-testing correction. We introduce a new two-step procedure for testing G × G interactions in case-control GWAS to detect interacting single nucleotide polymorphisms (SNPs) regardless of their marginal effects. In an initial screening step, all SNP pairs are tested for gene-gene association in the combined sample of cases and controls. In the second step, the pairs that pass the screening are followed up with a traditional test for G × G interaction. We show that the two-step method is substantially more powerful to detect G × G interactions than the exhaustive testing approach. For example, with 2,000 cases and 2,000 controls, the two-step method can have more than 90% power to detect an interaction odds ratio of 2.0 compared to less than 50% power for the exhaustive testing approach. Moreover, we show that a hybrid two-step approach that combines our newly proposed two-step test and the two-step test that screens for marginal effects retains the best power properties of both. The two-step procedures we introduce have the potential to uncover genetic signals that have not been previously identified in an initial single-SNP GWAS. We demonstrate the computational feasibility of the two-step G × G procedure by performing a G × G scan in the asthma GWAS of the University of Southern California Children's Health Study.

Abstract 2567: Genetic risk stratification for breast cancer based on a polygenic risk score and family history.

Abstract Background: Breast cancer is the most common cancer among Western women. Risk stratification of women can aid surveillance for and prevention of breast cancer. However, the value of genetic profiling in risk stratification has been widely debated. Early studies were based on risk profiles generated from only a few genetic variants, while recent genome-wide association studies (GWAS) have led to the identification of many more loci. We investigated the value of using 77 single nucleotide polymorphisms (SNPs) in breast cancer susceptibility loci identified to date for risk stratification of women both with and without a family history of breast cancer. Methods: We tested for all possible pair-wise multiplicative SNP interactions between 77 SNPs using 46,450 cases and 42,599 controls of European origin in the Breast Cancer Association Consortium (BCAC) using logistic regression analyses. A subset of 33,673 cases and 33,381 controls from studies not selected for family history was used to construct a polygenic risk score (PRS) based on the 77 SNPs. Estimates of the relative risk for breast cancer by levels of the PRS and population-based breast cancer incidence and mortality rates were used to derive absolute risks of developing breast cancer for percentiles of the PRS. Results: There was no strong evidence for multiplicative interaction between any particular SNP pair, but there was a suggestion of a larger number of observed significant interactions over those expected by chance. Women in the highest 1% of the PRS score had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (40-60thpctile)(OR=3.36 95%CI:2.95-3.83). The corresponding relative risks for PRSs derived separately for ER-positive and ER-negative disease were 3.73 95%CI:3.24-4.30 and 2.80 95%CI: 2.26-3.46, respectively. The OR for family history (1 or more first degree relatives with breast cancer) was slightly attenuated, from 1.85 to 1.74, after adjusting for the PRS, consistent with the estimated fraction (∼14%) of the familial relative risk explained by the 77 SNPs under a multiplicative polygenetic model of inheritance. The combined effects of PRS and family history of breast cancer were consistent with a multiplicative model (P-interaction=0.34). The 10-year absolute risk of breast cancer for a 50 year old woman without family history of breast cancer ranged from 0.70 % for women in the lowest 1% of the PRS, 2.4% for the middle quintile, to 7.1 % for the highest 1% of the PRS. For a 50 year old woman with a family history, the corresponding risk ranged from 1.2%, 4.0% and 11.2%, respectively. Conclusion: The PRS provides good discrimination of breast cancer risk across women without a family history of breast cancer, and can also be used to further refine the genetic risk among women with a family history. The observed level of risk discrimination could be useful to inform targeted screening or prevention strategies. Citation Format: Nasim Mavaddat, Paul Pharoah, Per Hall, Douglas Easton, Montserrat Garcia-Closas, for the Breast Cancer Association Consortium. Genetic risk stratification for breast cancer based on a polygenic risk score and family history. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2567. doi:10.1158/1538-7445.AM2013-2567 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

SNP-SNP Interaction Network in Angiogenesis Genes Associated with Prostate Cancer Aggressiveness

Angiogenesis has been shown to be associated with prostate cancer development. The majority of prostate cancer studies focused on individual single nucleotide polymorphisms (SNPs) while SNP-SNP interactions are suggested having a great impact on unveiling the underlying mechanism of complex disease. Using 1,151 prostate cancer patients in the Cancer Genetic Markers of Susceptibility (CGEMS) dataset, 2,651 SNPs in the angiogenesis genes associated with prostate cancer aggressiveness were evaluated. SNP-SNP interactions were primarily assessed using the two-stage Random Forests plus Multivariate Adaptive Regression Splines (TRM) approach in the CGEMS group, and were then re-evaluated in the Moffitt group with 1,040 patients. For the identified gene pairs, cross-evaluation was applied to evaluate SNP interactions in both study groups. Five SNP-SNP interactions in three gene pairs (MMP16+ ROBO1, MMP16+ CSF1, and MMP16+ EGFR) were identified to be associated with aggressive prostate cancer in both groups. Three pairs of SNPs (rs1477908+ rs1387665, rs1467251+ rs7625555, and rs1824717+ rs7625555) were in MMP16 and ROBO1, one pair (rs2176771+ rs333970) in MMP16 and CSF1, and one pair (rs1401862+ rs6964705) in MMP16 and EGFR. The results suggest that MMP16 may play an important role in prostate cancer aggressiveness. By integrating our novel findings and available biomedical literature, a hypothetical gene interaction network was proposed. This network demonstrates that our identified SNP-SNP interactions are biologically relevant and shows that EGFR may be the hub for the interactions. The findings provide valuable information to identify genotype combinations at risk of developing aggressive prostate cancer and improve understanding on the genetic etiology of angiogenesis associated with prostate cancer aggressiveness.

Evaluation of 16 SNPs allele-specific to quantify post hSCT chimerism by SYBR green-based qRT-PCR

The importance of monitoring post haematopoietic stem cell transplantation (hSCT) chimerism has been defined in numerous publications. Single-nucleotide polymorphisms (SNPs) are molecular markers that vary significantly among different populations. Allied...

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection

BackgroundThe silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters.ResultsA total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes.ConclusionsThis high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-14-810) contains supplementary material, which is available to authorized users.

SNP와 양적 표현형의 연관성 분석을 위한 분류기

인간 유전체 정보와 관련된 기술이 발전함으로 인하여 이를 이용한 질환 또는 질병에 대한 연관성을 분석하여 그 위험도나 치료 예후 등에 대한 예측하기 위한 연구가 활발히 진행되고 있다. 이러한 연구의 대부분은 대표적인 질적 표현형을 대상으로 하는 환자-대조군 연구(case-control study) 방법을 이용하고 있으며 양적 표현형에 대해서는 개별 단일 염기 변이의 연관성을 회기 분석 방법을 이용하여 규명하는 연구가 주로 수행되고 있다. 특히 복합 질병(complex disease)에 대한 위험도를 예측하기 위한 연구의 경우 흔한 변이 흔한 질환(common variants common disease)의 가정아래 주로 각각의 단일 염기 변이가 보이는 연관성 정보를 기반으로 진행되고 있으며 여러 변이의 상호 작용에 의한 영향을 분석한 결과는 상대적으로 미비하다. 이 논문에서는 양적 표현형에 대한 SNP의 연관성을 분석하고 그 결과로 발견된 SNP을 이용하여 대상 표현형의 값을 예측하기 위한 분류기를 구성하고 그 성능을 평가하였으며 분류기의 단일 염기 변이의 선택에 있어서 각각의 단일 염기 변이의 연관성을 고려할 때와 단일 염기 변이의 쌍이 보이는 연관성을 고려할 때의 분류 성능을 비교하였다. The advance of technologies for human genome makes it possible that the analysis of association between genetic variants and diseases and the application of the results to predict risk or susceptibility to them. Many of those studies carried out in case-control study. For quantitative traits, statistical analysis methods are applied to find single nucleotide polymorphisms (SNP) relevant to the diseases and consider them one by one. In this study, we presented methods to select informative single nucleotide polymorphisms and predict risk for quantitative traits and compared their performance. We adopted two SNP selection methods: one considering single SNP only and the other of all possible pairs of SNPs.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 August 2012 – 30 September 2012

This article documents the addition of 83 microsatellite marker loci and 96 pairs of single-nucleotide polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Bembidion lampros, Inimicus japonicus, Lymnaea stagnalis, Panopea abbreviata, Pentadesma butyracea, Sycoscapter hirticola and Thanatephorus cucumeris (anamorph: Rhizoctonia solani). These loci were cross-tested on the following species: Pentadesma grandifolia and Pentadesma reyndersii. This article also documents the addition of 96 sequencing primer pairs and 88 allele-specific primers or probes for Plutella xylostella.