Discovering possible context dependences around SNP sites in human genes with Bayesian network learning

Objective To investigate the relationship between NINJ2 gene polymorphism and stroke, and the differences of serum levels of tumor necrosis factor-αt (TNF-α), NGF, interleukin-6 (IL-6)and P-Selectin in healthy controls and patients under recovery stage. Methods Fifty-two patients with large-artery atherosclerosis (LAA) infarction, 85 patients with small-artery occlusion lacunar (SAO)infarction, 50 patients with intracerebral hemorrhage (ICH) and 66 healthy controls were included in this study. Genotypes of the 2 single nucleotide polymorphism (SNP) sites (rs12425791 and rs11833579) in NINJ2 gene were examined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RLFP) method. The differences of genotypes and alleles frequencies of the 2 SNP sites between each 2 different groups were analyzed and compared. Multinomial logistic regression was used to calculate the odds ratio (OR) of genotypes in each patient group, and 95% confidential interval (95% CI)was given. The serum levels ofTNF-α, NGF, IL-6 and P-Selectin were tested by ELISA method, and compared between groups and within group classified by genotypes. Results In regard to rs12425791 site, the frequencies of AG and AA+AG genotypes in LAA and SAO groups were significantly higher than those in control group (P＜0.05), while this difference was not found between the ICH group and control group (P＞0.05); the frequency of A allele in the SAO group was significantly higher than that in the control group (P＜0.05), while this difference was not found between the control group and both the LAA and ICH groups (P＞0.05). In regard to rs11833579 site, no significant differences in the genotypes and alleles were noted between all the patient groups and control group (P＞0.05). After adjusting the influence of other risk factors, the multinomial logistic regression analysis showed that the onset of stroke was still significantly associated with the AG genotype at rs12425791 site in the LAA group (OR=4.298,95%CI=1.430-12.922) and AG, AG+AA genotypes at rs12425791 site in the SAO group (OR=3.923 and 2.937, 95%CI= 1.417- 10.860 and 1.119-7.710). Neither genotypes in rs 11833579 site were significantly associated with the onset of stroke. No significant differences of serum levels of TNF-α, NGF, IL-6 and P-Selectin were noted between each patient group under recovery stage and control group (P＞0.05); in regard to rs12425791 site, the serum level of TNF in LAA group with different genotypes was significantly different (P＜0.05) and the serum level of P-Selectin in ICH group with different genotypes was significantly different (P＜0.05); in regard to rs11833579 site, the serum level of NGF in LAA group with different genotypes was statistically different (P＜0.05). Conclusion This SNP site (rs12425791)is significantly associated with ischemia stroke and the A allele increases the risk of being susceptible to this disease in Chinese Han population. That SNP site (rs1 1833579) is not significantly associated with stroke. No significant differences of TNF-α, NGF, IL-6, P-Selectin serum levels are noted between patients under recovery stage and controls. Key words: NINJ2 gene; Polymorphism; single nucleotide; Stroke; Tumor necrosis factor-α; NGF; Interleukin-6; P-Selectin

The present study aimed at identifying single-nucleotide polymorphic (SNP) sites in different coding and non-coding regions of lactoferrin gene in Indian riverine buffaloes. A total of 102 animals from six different river buffalo breeds were screened at six bubaline lactoferrin gene loci. Single-strand conformation polymorphism (SSCP) analysis revealed monomorphic patterns at three loci LtfE2, LtfE11, and LtfE14 while a total of eight distinct patterns were observed in the other three loci viz. LtfE5, LtfE10, and LtfE16 which correspond to respective exons and their flanking regions. Sequence analysis of different SSCP variants revealed the presence of two SNP sites within the coding (exon 16) region and five SNP sites in flanking non-coding regions (intron 4 and intron 9). Both SNPs within exon 16 were found to be synonymous. The SNPs and haplotypes identified in the present study could serve as potential markers for association with susceptibility/resistance to mastitis in buffaloes.

Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS.Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whether or not a SNP carries any additional information about the phenotype beyond that available by all the other SNPs. This rules out spurious correlations between phenotypes and SNPs that can arise from marginal methods because the ‘spuriously correlated’ SNP merely happens to be correlated with the ‘truly causal’ SNP. In addition, the method offers a data driven approach to identifying and refining groups of SNPs that jointly contain informative signals about the phenotype. We demonstrate the value of our method by applying it to the seven diseases analyzed by the Wellcome Trust Case Control Consortium (WTCCC). We show, in particular, that our method is also capable of finding significant SNPs that were not identified in the original WTCCC study, but were replicated in other independent studies.Availability and implementation: Reproducibility of our research is supported by the open-source Bioconductor package hierGWAS.Contact:peter.buehlmann@stat.math.ethz.chSupplementary information:Supplementary data are available at Bioinformatics online.

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

Molecular authentication of Panax ginseng and ginseng products using robust SNP markers in ribosomal external transcribed spacer region

This study investigated the possible association between single nucleotide polymorphism (SNP) sites on a genome wide level and the presence of polycystic ovary syndrome (PCOS) in a local population. Patients treated for PCOS in the outpatient clinic of the reproductive medicine center of Changzhou Maternal and Child Health Care Hospital (affiliated to Nanjing Medical University) from January of 2010 to December 2012 were selected. Female patients affected by infertility due to simple oviduct reasons or male factors, during the same period, were enrolled for the control group. A genome-wide association study was performed. Specific experimental steps included extraction of the total human DNA and optimization of PCR amplification of target genes; flight mass spectrometry for genotyping; and statistical analyses of sequencing results. By primary selection and secondary verification at two stages in the experiment, three SNP sites were found to contain significantly different allele frequencies between the patient and control groups (P<0.05): rs346795081 on THADA, rs346803513 on DENND1A and rs346999236 on TOX3. The average expression levels at the three discovered SNPs sites were significantly different between the patient and the control groups, indicating their correlation with PCOS, and the possible role of their corresponding genes on the pathogenesis of the disease.

Single nucleotide polymorphisms (SNPs) is subtle variation in a genomic DNA sequence of individuals of the same species. It plays a key role in the pharmaceutical industry to understand variations in drug treatment responses between individuals at the molecular level. Discovering patterns around SNPs loci is very important for better understanding the possible origin of SNPs in evolution. Bayesian network has been applied to this problem and got promising results. Since Bayesian network based SNPs pattern analysis demonstrates high computational complexity, we parallelized this workload on Intel Xeon SMP systems. SNPs' task level parallelism is exploited. Experiment results show that memory is bottleneck: on 8-way Xeon SMP hyper-threading enabled system, system memory bandwidth is fully saturated and memory load access latency is roughly 50% longer than on single processor system. Another interesting result is that Intel's hyper-threading technology helps improve the multithreaded workload's performance by 1.6X speedup. Workload profiling shows that parallel SNPs' data sharing nature matches hyper-threading's cache sharing mechanism, and thus greatly reduces cache coherency protocol traffic on shared front side bus. Scalability analysis shows that imbalance and locks are two major factors that may limit the parallel workload speedup on more processor platforms.

Insights into the relative contributions of locus specific and genome-wide effects on population genetic diversity can be gained through separation of their resulting genetic signals. Here we explore patterns of adaptive and neutral genetic diversity in the disjunct natural populations of Pinus radiata (D. Don) from mainland California. A first-generation common garden of 447 individuals revealed significant differentiation of wood phenotypes among populations (P ST), possibly reflecting local adaptation in response to environment. We subsequently screened all trees for genetic diversity at 149 candidate gene single nucleotide polymorphism (SNP) loci for signatures of adaptation. Ten loci were identified as being possible targets of diversifying selection following F ST outlier tests. Multivariate canonical correlation performed on a data set of 444 individuals identified significant covariance between environment, adaptive phenotypes and outlier SNP diversity, lending support to the case for local adaptation suggested from F ST and P ST tests. Covariation among discrete sets of outlier SNPs and adaptive phenotypes (inferred from multivariate loadings) with environment are supported by existing studies of candidate gene function and genotype–phenotype association. Canonical analyses failed to detect significant correlations between environment and 139 non-outlier SNP loci, which were applied to estimate neutral patterns of genetic differentiation among populations (F ST 4.3 %). Using this data set, significant hierarchical structure was detected, indicating three populations on the mainland. The hierarchical relationships based on neutral SNP markers (and SSR) were in contrast with those inferred from putatively adaptive loci, potentially highlighting the independent action of selection and demography in shaping genetic structure in this species.

The tumor necrosis factor and TNF receptor (TNF-TNFR) superfamily plays very important roles in the pathogenesis of many immune-mediated diseases. Regulation of TNF-TNFR superfamily gene expression influences many aspects of the pathology associated with these diseases. In order to investigate genetic variations in the regulatory regions of the TNF-TNFR superfamily genes, promoter regions were screened by sequencing DNA samples from 24 unrelated Korean individuals. We identified a total of 68 single-nucleotide polymorphisms (SNPs) in the regulatory regions of the known TNF-TNFR superfamily genes, including 50 SNPs in the promoter regions, 16 SNPs in the 5'-UTR regions, and two SNPs in the coding regions of these genes. Among the 68 SNPs identified in this study, 25 SNPs were novel SNPs. Interestingly, the sequence alteration created by 11 SNPs completely abolished putative transcription factor binding sites in these alleles. These results suggest that these SNP sites can regulate gene expression by controlling the binding of transcription factors. The identification of function-altering SNPs in the promoter regions of the TNF-TNFR superfamily will facilitate efforts to understand the association of TNF-TNFR superfamily genes with several immune-mediated human diseases.

Objective To investigate the relationship between the single nucleotide polymorphisms （SNP） in HEX gene and biliary duct abnormality. Methods One hundred and seventeen patients with biliary atresia （BA） were recruited in this study including 72 males and 45 females. Among BA patients, 12 patients aged 1-2 months old, 42 aged 2-3 months old and 63 older than 3 months. Thirty two patients with choledochal cysts （CBD） were enrolled in this study including 6 males and 26 females. The CBD patients aged from 1 month to 13 years old. The control group included 34 males and 17 females without any abnormality. Genome DNA of peripheral blood was extracted, and HEX gene was amplified by PCR. The production of PCR was sequenced. Results Two SNPs sites were found. One SNP site was 24 Co-A transversion of SNP located at Exon 1, which was found in 24 cases including 19 BA patients, 3 CBD patients, and 2 controls. Four of the 19 BA patients had AA homozygote allele. The 3 CBD patients and 2 controls had GA heterozygote allele. The other SNP site was 26 T-G transversion of SNP locating at the upstream of Exon 3, which was found in lg cases including 12 BA patients, 2 CBD patients, and 4 controls. The 24 G-A transversion of SNPs was correlated with the morbidity of BA （OR = 4. 75, 95% CI 1. 0632-21. 2207）. Conclusions 24 G/A polymorphisms of Exon 1 in HEX gene is associated with the morbidity of BA. Key words: Biliary atresia; Choledochal cysts; Polymorphism, single nucleotide

Polymerase chain reaction-amplified product length polymorphism (PCR-APLP) is one of the most convenient and reliable methods for single nucleotide polymorphism (SNP) analysis. This method is based on PCR, but uses allele-specific primers containing SNP sites at the 3′-terminus of each primer. To use this method at least two allele-specific primers and one “counter-primer”, which serves as a common forward or reverse primer of the allele-specific primers, are required. The allele-specific primers have SNP sites at the 3′-terminus, and another primer should have a few non-complementary flaps at the 5′-terminus to detect SNPs by determining the difference of amplicon length by PCR and subsequent electrophoresis. A major disadvantage of the addition of a non-complementary flap is the non-specific annealing of the primer with non-complementary flaps. However, a design principle for avoiding this undesired annealing has not been fully established, therefore, it is often difficult to design effective APLP primers. Here, we report allele-specific primers with an inosine chain at the 5′-terminus for PCR-APLP analysis. This unique design improves the competitiveness of allele-specific primers and the reliability of SNP analysis when using the PCR-APLP method.

A recent genome-wide association study for diabetic nephropathy in European type 1 diabetes identified 3 candidate loci for diabetic nephropathy. In this study, we examined the association of the 3 single nucleotide polymorphism (SNP) loci with susceptibility to diabetic nephropathy in Japanese subjects with type 2 diabetes. We genotyped 3 SNPs, rs7583877 in AFF3, rs12437854 in the RGMA-MCTP2 locus and rs7588550 in ERBB4, for 2,300 Japanese patients with type 2 diabetes [initial study, 1,055 nephropathy cases with overt proteinuria or with end-stage renal disease (ESRD) and 1,245 control patients with normoalbuminuria]. The association of these SNPs with diabetic nephropathy was examined by using a logistic regression analysis. We observed a significant association of rs7588550 in ERBB4 with diabetic nephropathy in the Japanese patients with type 2 diabetes, although the effect direction was not consistent with that in the European study [p=0.0126, odds ratio (OR)=0.79, 95% confidence interval (CI): 0.65-0.95]. We further examined the association of rs7588550 with diabetic nephropathy in an independent Japanese cohort (596 nephropathy cases and 311 controls) and observed the same trend of the association with the initial study. We did not observe any association of the remaining 2 SNP loci with diabetic nephropathy in the present Japanese sample. The association of SNP loci derived from GWAS in European type 1 diabetes with diabetic nephropathy was not replicated in the Japanese patients with type 2 diabetes, although the ERBB4 locus may have some effect also in Japanese type 2 diabetes.

BackgroundThe utilization of long reads for single nucleotide polymorphism (SNP) phasing has become popular, providing substantial support for research on human diseases and genetic studies in animals and plants. However, due to the complexity of the linkage relationships between SNP loci and sequencing errors in the reads, the recent methods still cannot yield satisfactory results.ResultsIn this study, we present a graph-based algorithm, GCphase, which utilizes the minimum cut algorithm to perform phasing. First, based on alignment between long reads and the reference genome, GCphase filters out ambiguous SNP sites and useless read information. Second, GCphase constructs a graph in which a vertex represents alleles of an SNP locus and each edge represents the presence of read support; moreover, GCphase adopts a graph minimum-cut algorithm to phase the SNPs. Next, GCpahse uses two error correction steps to refine the phasing results obtained from the previous step, effectively reducing the error rate. Finally, GCphase obtains the phase block. GCphase was compared to three other methods, WhatsHap, HapCUT2, and LongPhase, on the Nanopore and PacBio long-read datasets. The code is available from https://github.com/baimawjy/GCphase.ConclusionsExperimental results show that GCphase under different sequencing depths of different data has the least number of switch errors and the highest accuracy compared with other methods.

Background MicroRNAs (miRNAs) are af amily of endogenous small non-coding RNAs involved in various developmental and physiological processes by negatively regulating gene expression. Single nucleotide polymorphisms (SNPs) are important variations for the diversity among individuals, as well as leading to phenotypes, traits, and diseases. What will happen when SNPs meet miRNAs? To date, a number of studies have demonstrated that SNPs in target sites or miRNA genes were associated with diseases [1-3]. Our aim is to characterize these functional miRNA related SNPs comprehensively. Results Through mapping SNPs onto miRNAs, we totally identified 757 SNPs (including indel polymorphisms) in 440 human pre-miRNAs, 218 SNPs in pre-miRNAs of other 8 species and thousands of SNPs in pre-miRNAs flanking regions. Of them, 50 SNPs are in the seed regions of 41 human miRNAs. Two different methods (TargetScan and miRanda) were used to predict the target sites for the wild type miRNAs and SNP-miRNAs. By comparing the targets of wild type miRNA with that of SNP-miRNA, we obtained the potential miRNA targets loss and gain. We found about half of the targets will be changed by SNP in miRNA seed region. In addition, we experimentally confirmed seven loss of-function SNPs and one gain-of-function SNP by luciferase report assay. We also mapped SNPs onto gene 3’ untranslated region (3’UTR) and identified tens of thousands of SNPs in 3’UTRs which would affect the miRNA/gene interaction, either destroy a real target or create an illegal target. Among these miRNA related SNPs, we think the SNPs with relatively high minor allele frequencies (MAF), high MAF difference between populations and undergoing positive selection pressure will be important candidates for population phonotype research and complex trait studies. All useful data were compiled into miRNASNP, a user-friendly free online database (http://www.bioguo. org/miRNASNP/).

BackgroundThe fidelity of DNA replication serves as the nidus for both genetic evolution and genomic instability fostering disease. Single nucleotide polymorphisms (SNPs) constitute greater than 80% of the genetic variation between individuals. A new theory regarding DNA replication fidelity has emerged in which selectivity is governed by base-pair geometry through interactions between the selected nucleotide, the complementary strand, and the polymerase active site. We hypothesize that specific nucleotide combinations in the flanking regions of SNP fragments are associated with mutation.ResultsWe modeled the relationship between DNA sequence and observed polymorphisms using the novel multifactor dimensionality reduction (MDR) approach. MDR was originally developed to detect synergistic interactions between multiple SNPs that are predictive of disease susceptibility. We initially assembled data from the Broad Institute as a pilot test for the hypothesis that flanking region patterns associate with mutagenesis (n = 2194). We then confirmed and expanded our inquiry with human SNPs within coding regions and their flanking sequences collected from the National Center for Biotechnology Information (NCBI) database (n = 29967) and a control set of sequences (coding region) not associated with SNP sites randomly selected from the NCBI database (n = 29967). We discovered seven flanking region pattern associations in the Broad dataset which reached a minimum significance level of p ≤ 0.05. Significant models (p << 0.001) were detected for each SNP type examined in the larger NCBI dataset. Importantly, the flanking region models were elongated or truncated depending on the nucleotide change. Additionally, nucleotide distributions differed significantly at motif sites relative to the type of variation observed. The MDR approach effectively discerned specific sites within the flanking regions of observed SNPs and their respective identities, supporting the collective contribution of these sites to SNP genesis.ConclusionThe present study represents the first use of this computational methodology for modeling nonlinear patterns in molecular genetics. MDR was able to identify distinct nucleotide patterning around sites of mutations dependent upon the observed nucleotide change. We discovered one flanking region set that included five nucleotides clustered around a specific type of SNP site. Based on the strongly associated patterns identified in this study, it may become possible to scan genomic databases for such clustering of nucleotides in order to predict likely sites of future SNPs, and even the type of polymorphism most likely to occur.