High Degree Of Linkage Disequilibrium Research Articles

Identifying Relationships between Glutathione S-Transferase-2 Single Nucleotide Polymorphisms and Hypoxia Tolerance and Growth Traits in Macrobrachium nipponense.

Investigating hypoxia tolerance and growth trait single nucleotide polymorphisms (SNPs) in Macrobrachium nipponense is conducive to cultivating prawns with hypoxia tolerance and good growth characteristics. The glutathione S-transferase-2 gene (GST-2) has been shown to regulate hypoxia responses in M. nipponense. In this study, we identified a single GST-2 SNP in M. nipponense, and analyzed its regulatory relationship with hypoxia tolerance and growth. The GST-2 sequence was amplified with a polymerase chain reaction from 197 "Taihu Lake No. 3", "Taihu Lake No. 2", and Pearl River population samples to identify SNP loci. The full-length Mn-GST2 sequence was 2317 bp, including three exons and two introns. In total, 38 candidate SNP loci were identified from GST-2 using Mega11.0 comparisons, with most loci moderately polymorphic in terms of genetic diversity. Locus genotypes were also analyzed, and basic genetic parameters for loci were calculated using Popgene32 and PIC_CALC. The expected heterozygosity of the 38 SNP loci ranged from 0.2334 to 0.4997, with an average of 0.4107, while observed heterozygosity ranged from 0.1929 to 0.4721, with an average of 0.3401. The polymorphic information content ranged from 0.21 to 0.37. From SPSS analyses, the G+256A locus was significantly correlated with hypoxia tolerance across all three M. nipponense populations, while the SNP loci A+261C, C+898T, A+1370C, and G+1373T were significantly associated with growth traits. Further analyses revealed that the T+2017C locus was significantly correlated with hypoxia tolerance in "Taihu Lake No. 2" populations, G+256A, A+808T, C+1032T, and A+1530G loci were significantly correlated with hypoxia tolerance in "Taihu Lake No. 3" populations, while no SNP loci were correlated with hypoxia tolerance in Pearl River populations. A+1370C and G+1373T loci, which were associated with growth traits, exhibited a high degree of linkage disequilibrium (r2 = 0.89 and r2 > 0.8), suggesting potential genetic linkage. Our data suggest associations between hypoxia tolerance and growth trait SNP loci in M. nipponense, and provide valuable evidence for the genetic improvement of growth and hypoxia tolerance in this prawn species.

The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOE [Formula: see text]4-negative Japanese adults.

Late-onset Alzheimer's disease (LOAD) is the most common cause of dementia among those older than 65 years. The onset of LOAD is influenced by neuroinflammation. The human leukocyte antigen (HLA) system is involved in regulating inflammatory responses. Numerous HLA alleles and their haplotypes have shown varying associations with LOAD in diverse populations, yet their impact on the Japanese population remains to be elucidated. Here, we conducted a comprehensive investigation into the associations between LOAD and HLA alleles within the Japanese population. Using whole-genome sequencing (WGS) data from 303 LOAD patients and 1717 cognitively normal (CN) controls, we identified four-digit HLA class I alleles (A, B, and C) and class II alleles (DRB1, DQB1, and DPB1). We found a significant association between the HLA-DRB1*09:01-DQB1*03:03 haplotype and LOAD risk in APOE [Formula: see text]4-negative samples (odds ratio = 1.81, 95% confidence interval = 1.38-2.38, P = 2.03[Formula: see text]). These alleles not only showed distinctive frequencies specific to East Asians but demonstrated a high degree of linkage disequilibrium in APOE [Formula: see text]4-negative samples (r2 = 0.88). Because HLA class II molecules interact with T-cell receptors (TCRs), we explored potential disparities in the diversities of TCR α chain (TRA) and β chain (TRB) repertoires between APOE [Formula: see text]4-negative LOAD and CN samples. Lower diversity of TRA repertoires was associated with LOAD in APOE [Formula: see text]4-negative samples, irrespective of the HLA DRB1*09:01-DQB1*03:03 haplotype. Our study enhances the understanding of the etiology of LOAD in the Japanese population and provides new insights into the underlying mechanisms of its pathogenesis.

Identification of potential genetic causal variants for obesity-related traits using statistical fine mapping.

Obesity is highly influenced by heritability and variant effects. While previous genome-wide association studies (GWASs) have successfully identified numerous genetic loci associated with obesity-related traits [body mass index (BMI) and waist-to-hip ratio (WHR)], most causal variants remain unidentified. The high degree of linkage disequilibrium (LD) throughout the genome makes it extremely difficult to distinguish the GWAS-associated SNPs that exert a true biological effect. This study was to identify the potential causal variants having a biological effect on obesity-related traits. We used Probabilistic Annotation INTegratOR, a Bayesian fine-mapping method, which incorporated genetic association data (GWAS summary statistics), LD structure, and functional annotations to calculate a posterior probability of causality for SNPs across all loci of interest. Moreover, we performed gene expression analysis using the available public transcriptomic data to validate the corresponding genes of the potential causal SNPs partially. We identified 96 SNPs for BMI and 43 SNPs for WHR with a high posterior probability of causality (> 99%), including 49 BMI SNPs and 24 WHR SNPs which did not reach genome-wide significance in the original GWAS. Finally, we partially validated some genes corresponding to the potential causal SNPs. Using a statistical fine-mapping approach, we identified a set of potential causal variants to be prioritized for future functional validation and also detected some novel trait-associated variants. These results provided novel insight into our understanding of the genetics of obesity and also demonstrated that fine mapping may improve upon the results identified by the original GWASs.

Correlations of IL-18 and IL-6 gene polymorphisms and expression levels with onset of glioma.

The aim of this study was to explore the correlations of interleukin (IL)-18 and IL-6 gene polymorphisms and expression levels with the onset of glioma. The differences in the expression levels of IL-18 and IL-6 between glioma patients and normal people in the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were analyzed. A total of 200 glioma patients and 200 healthy people were taken as the research subjects. Peripheral blood was collected to extract deoxyribonucleic acids (DNAs). IL-18 and IL-6 gene polymorphisms were detected and analyzed combined with haplotype analysis and gene expression levels of IL-18 and IL-6, as well as their levels in serum. Both IL-18 and IL-6 were highly expressed in tumor tissues of glioma patients, whereas they were lowly expressed in normal cerebral tissues, with statistically significant differences (p<0.05). Statistically significant differences in the allele distributions of IL-18 gene polymorphisms rs371411440 (p=0.041) and rs371828055 (p=0.002) and IL-6 gene polymorphisms rs201211345 (p=0.000) and rs201439472 (p=0.003) were observed between disease group and control group (p<0.05). Genotype distributions of IL-18 gene polymorphism rs371828055 (p=0.005) and IL-6 gene polymorphisms rs201211345 (p=0.000) and rs201439472 (p=0.019) in disease group were significantly different from those in control group (p<0.05). Disease group exhibited significantly higher frequencies of genotype GG of IL-18 gene polymorphism rs371828055, genotype AA of IL-6 gene polymorphism rs201211345 and genotype TT of IL-6 gene polymorphism rs201439472 than control group (p<0.05). There were statistically significant differences in the distributions of the dominant model AA+AC of IL-6 gene polymorphism rs201211345 (p=0.016) and the recessive model GT+TT of IL-18 gene polymorphism rs371828055 (p=0.010) between the two groups (p<0.05). Differences in the distributions of haplotypes CC (p=0.001) and GT (p=0.027) of IL-18 gene polymorphisms rs371411440 and rs371828055 and haplotypes AC (p=0.009), AT (p=0.000) and CT (p=0.000) of IL-6 gene polymorphisms rs201211345 and rs201439472 were observed between disease group and control group (p<0.05). In addition, a high degree of linkage disequilibrium was detected between IL-6 gene polymorphisms rs201211345 and rs201439472 (D'=0.583). The genotypes of IL-18 gene polymorphism rs371828055 were evidently correlated with the gene expression of IL-18 (p=0.000). Meanwhile, patients with genotype GT had a distinctly lower expression level of IL-18 (p<0.05). The genotypes of IL-6 gene polymorphism rs201211345 were obviously associated with the expression of IL-6 (p=0.002). The expression of IL-6 was markedly down-regulated in patients carrying genotype AA (p<0.05). Consistent with the expression levels of IL-18 and IL-6, the genotypes of IL-18 gene polymorphism rs371828055 were associated with the content of serum IL-18 (p<0.05). Moreover, patients carrying genotype GT had distinctly lower content of serum IL-18 (p<0.05). Additionally, the genotypes of IL-6 gene polymorphism rs201211345 were evidently correlated with the content of serum IL-6 (p<0.05), and the content of serum IL-6 declined distinctly in patients with genotype AA (p<0.05). IL-18 and IL-6 gene polymorphisms and expression levels are significantly correlated with the onset of glioma.

ATP2B1 gene rs71454161, rs73196661 and rs73196675 polymorphisms in eclampsia.

We aimed to explore the associations of the ATP2B1 gene polymorphisms with eclampsia. A total of 150 patients with eclampsia (disease group) and 150 healthy pregnant women (control group) were taken as the subjects of study. The peripheral blood of the two groups of subjects was collected to extract deoxyribonucleic acids (DNAs), and the ATP2B1 gene rs71454161, rs73196661 and rs73196675 polymorphisms were detected by sequencing the Polymerase Chain Reaction (PCR) products, and then, analyzed combined with gene expression determined via Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) and clinical indicators, such as 24-h urine protein, platelets, and LDH. A difference was observed in the allele distribution of ATP2B1 gene rs71454161 (p=0.000) and rs73196661 (p=0.011) between the disease group and control group. Disease group exhibited higher frequencies of allele G of rs71454161 and allele T of rs73196661 than control group. Besides, there was a difference in the genotype distribution of ATP2B1 gene rs71454161 (p=0.000), rs73196661 (p=0.000) and rs73196675 (p=0.000) between disease group and control group. Disease group exhibited higher frequencies of genotype GG of rs71454161, genotype TT of rs73196661 and genotype CG of rs73196675 than control group. Moreover, a difference in the distributions of ATP2B1 gene rs71454161 (p=0.000) and rs73196661 (p=0.014) was found between the two groups in the dominant model. Disease group exhibited lower frequencies of AA+AG of rs71454161 and CC+CT of rs73196661 than control group in the dominant model. Differences in the distributions of haplotypes ACC (p=0.000), ATC (p=0.047) and GTC (p=0.000) of ATP2B1 gene rs71454161, rs73196661 and rs73196675 were observed between disease group and control group. Furthermore, a high degree of linkage disequilibrium was detected between rs71454161 and rs73196661 (D'=0.329). The ATP2B1 gene rs73196675 polymorphism was evidently correlated with the gene expression of ATP2B1 (p<0.05), and the patients with genotype GG had a lower expression level of ATP2B1. The ATP2B1 gene rs71454161 was evidently correlated with the 24-h urinary protein in eclampsia patients (p=0.021), and the patients with genotype AG had a higher level of 24-h urinary proteins. The rs73196661 polymorphism was significantly correlated with LDH (p=0.000), and the patients with genotype CC had a higher level of LDH. The ATP2B1 gene polymorphism was significantly correlated with the occurrence and progression of eclampsia.

Integration of Transcriptome and Exome Genotyping Identifies Significant Variants with Autism Spectrum Disorder.

Autism is a complex disease with genetic predisposition factors. Real factors for treatment and early diagnosis are yet to be defined. This study integrated transcriptome and exome genotyping for identifying functional variants associated with autism spectrum disorder and their impact on gene expression to find significant variations. More than 1800 patients were screened, and 70 (47 male/23 female) with an average age of 7.56 ± 3.68 years fulfilled the DSM-5 criteria for autism. Analysis revealed 682 SNPs of 589 genes significantly (p < 0.001) associated with autism among the putative functional exonic variants (n = 243,345) studied. Olfactory receptor genes on chromosome 6 were significant after Bonferroni correction (α = 0.05/243345 = 2.05 × 10−7) with a high degree of linkage disequilibrium on 6p22.1 (p = 6.71 × 10−9). The differentially expressed gene analysis of autistic patients compared to controls in whole RNA sequencing identified significantly upregulated (foldchange ≥0.8 and p-value ≤ 0.05; n = 125) and downregulated (foldchange ≤−0.8 and p-value ≤ 0.05; n = 117) genes. The integration of significantly up- and downregulated genes and genes of significant SNPs identified regulatory variants (rs6657480, rs3130780, and rs1940475) associated with the up- (ITGB3BP) and downregulation (DDR1 and MMP8) of genes in autism spectrum disorder in people of Arab ancestries. The significant variants could be a biomarker of interest for identifying early autism among Arabs and helping to characterize the genes involved in the susceptibility mechanisms for autistic subjects.

A statistical approach to fine-mapping for the identification of potential causal variants related to human intelligence.

Genome-wide association studies (GWASs) have identified >20 genetic loci associated with human intelligence. However, due to correlations between the trait-associated SNPs, only a few of the loci are confirmed to have a true biological effect. In order to distinguish the SNPs that have a causal effect on human intelligence, we must eliminate the noise from the high degree of linkage disequilibrium that persists throughout the genome. In this study, we apply a novel PAINTOR fine-mapping method, which uses a Bayesian approach to determine the SNPs with the highest probability of causality. This technique incorporates the GWAS summary statistics, linkage disequilibrium structure, and functional annotations to compute the posterior probability of causality for all SNPs in the GWAS-associated regions. We found five SNPs (rs6002620, rs41352752, rs6568547, rs138592330, and rs28371699) with a high probability of causality, three of which have posterior probabilities >0.60. The SNP rs6002620 (NDUFA6), which is involved in mitochondrial function, has the highest likelihood of causality. These findings provide important insight into the genetic determinants contributing to human intelligence.

HOTAIR lncRNA SNPs rs920778 and rs1899663 are associated with smoking, male gender, and squamous cell carcinoma in a Chinese lung cancer population.

The abnormal expression of the long noncoding RNA (lncRNA) HOX transcript intergenic antisense RNA (HOTAIR) plays an important role in the development of various cancers; however, single nucleotide polymorphisms (SNPs) in HOTAIR and their association with primary lung cancer susceptibility have not yet been reported. Here, we performed a case-control study including 262 primary lung cancer patients and 451 cancer-free control individuals to investigate the association between four haplotype-tagging SNPs (rs920778, rs12826786, rs4759314, and rs1899663) in the HOTAIR lncRNA and the risk of developing primary lung cancer. We found a significant association between the SNPs rs920778 and rs1899663 in the HOTAIR and primary lung cancer susceptibility (P < 0.05). Moreover, homozygous C/T (C/T + TT) for rs920778 (C > T) sites was significantly associated with gender, smoking history, and pathological type. In addition, linkage disequilibrium and haplotype analysis of HOTAIR gene polymorphisms for susceptibility to lung cancer revealed a high degree of linkage disequilibrium between the rs920778 and rs1899663 loci (D' = 0.86, r2 = 0.52). The population of rs920778, rs1899663, and rs4759314 had a significantly increased risk of lung cancer (P < 0.001). In summary, the present study provides persuasive evidence that SNP rs920778 is closely correlated with susceptibility to primary lung cancer. Future studies are warranted to validate and expand these findings, and to further dissect the importance of these SNPs in the development of primary lung cancer.

An unsupervised machine learning method for discovering patient clusters based on genetic signatures

IntroductionMany chronic disorders have genomic etiology, disease progression, clinical presentation, and response to treatment that vary on a patient-to-patient basis. Such variability creates a need to identify characteristics within patient populations that have clinically relevant predictive value in order to advance personalized medicine. Unsupervised machine learning methods are suitable to address this type of problem, in which no a priori class label information is available to guide this search. However, it is challenging for existing methods to identify cluster memberships that are not just a result of natural sampling variation. Moreover, most of the current methods require researchers to provide specific input parameters a priori. MethodThis work presents an unsupervised machine learning method to cluster patients based on their genomic makeup without providing input parameters a priori. The method implements internal validity metrics to algorithmically identify the number of clusters, as well as statistical analyses to test for the significance of the results. Furthermore, the method takes advantage of the high degree of linkage disequilibrium between single nucleotide polymorphisms. Finally, a gene pathway analysis is performed to identify potential relationships between the clusters in the context of known biological knowledge. Datasets and resultsThe method is tested with a cluster validation and a genomic dataset previously used in the literature. Benchmark results indicate that the proposed method provides the greatest performance out of the methods tested. Furthermore, the method is implemented on a sample genome-wide study dataset of 191 multiple sclerosis patients. The results indicate that the method was able to identify genetically distinct patient clusters without the need to select parameters a priori. Additionally, variants identified as significantly different between clusters are shown to be enriched for protein-protein interactions, especially in immune processes and cell adhesion pathways, via Gene Ontology term analysis. ConclusionOnce links are drawn between clusters and clinically relevant outcomes, Immunochip data can be used to classify high-risk and newly diagnosed chronic disease patients into known clusters for predictive value. Further investigation can extend beyond pathway analysis to evaluate these clusters for clinical significance of genetically related characteristics such as age of onset, disease course, heritability, and response to treatment.

Genetic identification and expression profiling of drought responsive genes in sorghum

Drought is the most important yield limiting abiotic stress worldwide and could have negative effects on food security. This study was conducted to map yield and yield-contributing trait QTLs under drought stress by association mapping, and to in silico identify drought responsive genes and assay their expression profile. Association analysis was conducted using 181 SSR markers and nine phenotypic traits collected from a structured sorghum population consisting of 96 accessions evaluated under optimum and drought stressed conditions at Assiut University Experimental Farm, Assiut, Egypt. Genomic regions associated with major drought tolerance QTLs were annotated with NCBI and sorghum databases to identify drought responsive genes, which were further transcriptionally analyzed. Significant differences between optimum irrigation and drought-stressed conditions were observed in all measured phenotypic traits. Association analysis revealed 93 marker-trait associations between 71 SSR markers and the nine phenotypic traits with an R2 value ranging from 6.56 to 42.64%. A high degree of linkage disequilibrium (>52%) was identified among markers on different chromosomes, suggesting epistatic interaction. BLASTP annotation of QTL genomic sequences identified 86 gene homologs, from which fifteen genes are drought responsive. All fifteen genes were differentially expressed in drought tolerant and susceptible accessions and their expression levels were highly induced in response to drought stress. The results provide a powerful approach coupling association and in silico analyses to identify gene clusters having a common expression profile with similar function, pointing to an evolutionary mechanism to initiate a quantitative drought stress tolerance mechanism.

Genome-wide association mapping of resistance to a Brazilian isolate of Sclerotinia sclerotiorum in soybean genotypes mostly from Brazil

BackgroundSclerotinia Stem Rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is ubiquitous in cooler climates where soybean crops are grown. Breeding for resistance to SSR remains challenging in crops like soybean, where no single gene provides strong resistance, but instead, multiple genes work together to provide partial resistance. In this study, a genome-wide association study (GWAS) was performed to dissect the complex genetic architecture of soybean quantitative resistance to SSR and to provide effective molecular markers that could be used in breeding programs. A collection of 420 soybean genotypes were selected based on either reports of resistance, or from one of three different breeding programs in Brazil, two commercial, one public. Plant genotype sensitivity to SSR was evaluated by the cut stem inoculation method, and lesion lengths were measured at 4 days post inoculation.ResultsGenotyping-by-sequencing was conducted to genotype the 420 soybean lines. The TASSEL 5 GBSv2 pipeline was used to call SNPs under optimized parameters, and with the extra step of trimming adapter sequences. After filtering missing data, heterozygosity, and minor allele frequency, a total of 11,811 SNPs and 275 soybean genotypes were obtained for association analyses. Using a threshold of FDR-adjusted p-values <0.1, the Compressed Mixed Linear Model (CMLM) with Genome Association and Prediction Integrated Tool (GAPIT), and the Fixed and Random Model Circulating Probability Unification (FarmCPU) methods, both approaches identified SNPs with significant association to disease response on chromosomes 1, 11, and 18. The CMLM also found significance on chromosome 19, whereas FarmCPU also identified significance on chromosomes 4, 9, and 16.ConclusionsThese similar and yet different results show that the computational methods used can impact SNP associations in soybean, a plant with a high degree of linkage disequilibrium, and in SSR resistance, a trait that has a complex genetic basis. A total of 125 genes were located within linkage disequilibrium of the three loci shared between the two models. Their annotations and gene expressions in previous studies of soybean infected with S. sclerotiorum were examined to narrow down the candidates.

Effect of Genetic Variability in the CYP4F2, CYP4F11, and CYP4F12 Genes on Liver mRNA Levels and Warfarin Response

Genetic polymorphisms in the gene encoding cytochrome P450 (CYP) 4F2, a vitamin K oxidase, affect stable warfarin dose requirements and time to therapeutic INR. CYP4F2 is part of the CYP4F gene cluster, which is highly polymorphic and exhibits a high degree of linkage disequilibrium, making it difficult to define causal variants. Our objective was to examine the effect of genetic variability in the CYP4F gene cluster on expression of the individual CYP4F genes and warfarin response. mRNA levels of the CYP4F gene cluster were quantified in human liver samples (n = 149) obtained from a well-characterized liver bank and fine mapping of the CYP4F gene cluster encompassing CYP4F2, CYP4F11, and CYP4F12 was performed. Genome-wide association study (GWAS) data from a prospective cohort of warfarin-treated patients (n = 711) was also analyzed for genetic variations across the CYP4F gene cluster. In addition, SNP-gene expression in human liver tissues and interactions between CYP4F genes were explored in silico using publicly available data repositories. We found that SNPs in CYP4F2, CYP4F11, and CYP4F12 were associated with mRNA expression in the CYP4F gene cluster. In particular, CYP4F2 rs2108622 was associated with increased CYP4F2 expression while CYP4F11 rs1060467 was associated with decreased CYP4F2 expression. Interestingly, these CYP4F2 and CYP4F11 SNPs showed similar effects with warfarin stable dose where CYP4F11 rs1060467 was associated with a reduction in daily warfarin dose requirement (∼1 mg/day, Pc = 0.017), an effect opposite to that previously reported with CYP4F2 (rs2108622). However, inclusion of either or both of these SNPs in a pharmacogenetic algorithm consisting of age, body mass index (BMI), gender, baseline clotting factor II level, CYP2C9∗2 rs1799853, CYP2C9∗3 rs1057910, and VKORC1 rs9923231 improved warfarin dose variability only by 0.5–0.7% with an improvement in dose prediction accuracy of ∼1–2%. Although there is complex regulation across the CYP4F gene cluster, the opposing effects between the two SNPs in the CYP4F gene cluster appear to compensate for each other and their effect on warfarin dose requirement is unlikely to be clinically significant.

A Statistical Approach to Fine Mapping for the Identification of Potential Causal Variants Related to Bone Mineral Density.

Although genomewide association studies (GWASs) have been able to successfully identify dozens of genetic loci associated with bone mineral density (BMD) and osteoporosis-related traits, very few of these loci have been confirmed to be causal. This is because in a given genetic region there may exist many trait-associated SNPs that are highly correlated. Although this correlation is useful for discovering novel associations, the high degree of linkage disequilibrium that persists throughout the genome presents a major challenge to discern which among these correlated variants has a direct effect on the trait. In this study we apply a recently developed Bayesian fine-mapping method, PAINTOR, to determine the SNPs that have the highest probability of causality for femoral neck (FNK) BMD and lumbar spine (LS) BMD. The advantage of this method is that it allows for the incorporation of information about GWAS summary statistics, linkage disequilibrium, and functional annotations to calculate a posterior probability of causality for SNPs across all loci of interest. We present a list of the top 10 candidate SNPs for each BMD trait to be followed up in future functional validation experiments. The SNPs rs2566752 (WLS) and rs436792 (ZNF621 and CTNNB1) are particularly noteworthy because they have more than 90% probability to be causal for both FNK and LS BMD. Using this statistical fine-mapping approach we expect to gain a better understanding of the genetic determinants contributing to BMD at multiple skeletal sites. © 2017 American Society for Bone and Mineral Research.

Association of GABAA receptor α2 subunit gene (GABRA2) with alcohol dependence-related aggressive behavior.

Alcohol dependence is a common chronic disorder precipitated by the complex interaction between biological, genetic and environmental risk factors. Recent studies have demonstrated that polymorphisms of the gene encoding the GABAA receptor α2 subunit (GABRA2) are associated with alcohol dependence in different populations of European ancestry. As aggression often occurs in the context of alcohol dependence, the aim of this study was to examine the allelic and haplotypic association of GABRA2 gene with alcohol dependence and related aggressive behavior in subjects of Eastern European (Croatian) origin. Genotyping of the 3 single nucleotide polymorphisms (SNPs) across the GABRA2 gene (rs567926, rs279858 and rs9291283) was performed in patients with alcohol dependence (N=654) and healthy control subjects (N=574). Alcohol-dependent participants were additionally subdivided according to the presence/absence of aggressive behavior and type of alcohol dependence according to the Cloninger's classification. The association of rs279858 with alcohol dependence yielded nominal significance level. Haplotype analysis revealed a high degree of linkage disequilibrium (LD) for rs567926 and rs279858, but not for rs9291283 polymorphism in the GABRA2 gene. In patients with alcohol dependence, the A-C (rs567926 and rs279858) haplotype carriers were more likely to demonstrate aggressive behavior. The same haplotype (present only in 1.6% of all subjects) was significantly more often present in patients with a combination of early onset alcohol abuse and aggression, corresponding to the Cloninger's type II alcoholism subgroup. These findings support the involvement of GABRA2 gene in alcohol dependence-related aggressive behavior.

Investigation of FOXP3 genetic variations at positions -2383 C/T and IVS9+459 T/C in southern Iranian patients with lung carcinoma.

FOXP3 gene is an X-linked gene that encodes FOXP3 protein, an essential transcription factor in CD4+CD25+FOXP3+ regulatory T (Treg) cells. We aimed, in the present study, to investigate the association of two FOXP3 polymorphisms, -2383 C/T (rs3761549) and IVS9+459 T/C (rs2280883), with lung cancer. In a case-control study we analyzed genotypes and alleles frequencies at -2383 C/T and IVS9+459 T/C positions in 156 patients with lung cancer and 156 age and sex matched healthy controls in Southern Iranian population, using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) methods. The data were verified by direct automated DNA sequencing. The frequency of -2383 T allele was significantly higher in the patients than in the control group (11.8% versus 5.9%, P-value=0.04, OR=2.13, 95%CI=1.04-4.54). T allele frequency at IVS9+459 T/C position was higher, compared to the controls, in the patients who presented the disease over 55 years old (69.9% versus 59.1%, P-value=0.04, OR=1.61, 95%CI=1.01-2.55) and also in SCLC patients (77.8% versus 59.1%, P-value=0.03, OR=2.42, 95%CI=1.05-5.59). No significant differences were found in the genotypes and haplotypes distributions between the cases and controls. A high degree of linkage disequilibrium was observed between two polymorphisms. As the first study dealing with -2383 C/T and IVS9+459 T/C in lung cancer, our data conclusively suggest the association of -2383 T allele with susceptibility to lung cancer in Iranian population. The association of IVS9+459 T allele with susceptibility to lung cancer in old patients suggests the age-dependent effects of FOXP3 gene on cancer occurrence.

Detection of SNPs in the TBC1D1 gene and their association with carcass traits in chicken.

TBC1D1 plays an important role in numerous fundamental physiological processes including muscle metabolism, regulation of whole body energy homeostasis and lipid metabolism. The objective of the present study was to identify single nucleotide polymorphisms (SNPs) in chicken TBC1D1 using 128 Erlang mountainous chickens and to determine if these SNPs are associated with carcass traits. The approach consisted of sequencing TBC1D1 using a panel of DNA from different individuals, revealing twenty-two SNPs. Among these SNPs, two polymorphisms (g.69307744C>T and g.69307608T>G) of block 1, four polymorphisms (g.69322320C>T, g.69322314G>A, g.69317290A>G and g.69317276T>C) of block 2 and four polymorphisms of block 3 (g.69349746G>A, g.69349736C>G, g.69349727C>T and g.69349694C>T) exhibited a high degree of linkage disequilibrium in all test populations. An association analysis was performed between the twenty-two SNPs and seven performance traits. SNPs g.69307744C>T, g.69340192G>A and g.69355665T>C were demonstrated to have a strong effect on liveweight (BW), carcass weight (CW), semi-eviscerated weight (SEW) and eviscerated weight (EW) and g.69340070C>T polymorphism was related to BW, SEW and BMW in chicken populations. However, for the other SNPs, there were no significant correlations between different genotypes and carcass traits. Meanwhile, haplotype CT-TG of block 1 and combined genotype AG-TT-AC-CT of block 3 were significantly associated with BW, CW, SEW and EW. Overall, our results provide evidence that polymorphisms in TBC1D1 are associated with carcass traits and would be a useful candidate gene in selection programs for improving carcass traits.

SIRT1 gene polymorphisms are associated with growth traits in Nanyang cattle

Growth is under complex genetic control and uncovering the molecular mechanisms how the genes and polymorphisms affect economic growth traits, are important for successful marker-assisted selection and more efficient management strategies in commercial cattle populations. SIRT1 is a NAD+-dependent deacetylase that belongs to the class III histone deacetylases. It plays an important role in numerous fundamental cellular processes including gene silencing, DNA repair, and metabolic regulation. In addition, SIRT1 acts as an inhibitor of adipogenesis and has been associated with body weight regulation. The objective of the present study was to identify single nucleotide polymorphisms (SNPs) of bovine SIRT1 using 1255 animals representing the five main Chinese breeds and to determine if these SNPs are associated with economically important traits in Nanyang cattle. The approach consisted of resequencing SIRT1 using a panel of DNA from unrelated animals of five different breeds and the process revealed five novel SNPs. SNPs g.17324T>C and g.17491G>A exhibited a high degree of linkage disequilibrium in all tested breeds. Seven major haplotypes accounting for 91.2% of the alleles were observed and the haplotype ‘GCCGA’ was the most common haplotype in NY, QC, LX and JX breeds. An association analysis was performed between the five SNPs and six performance traits. SNP g.-274C>G was demonstrated to have a strong effect on 24-months-old body weight and g.17379A>G polymorphism was related to 6 and 12-months-old body weight in NY population, although these effects did not remained significant after the Bonferroni correction. Our results provide evidence that polymorphisms in SIRT1 are associated with growth efficiency traits, and may be used for marker-assisted selection and management in feedlot cattle.

Impulsiveness mediates the association between GABRA2 SNPs and lifetime alcohol problems

Genetic variants in GABRA2 have previously been shown to be associated with alcohol measures, electroencephalography (EEG) β waves and impulsiveness-related traits. Impulsiveness is a behavioral risk factor for alcohol and other substance abuse. Here, we tested association between 11 variants in GABRA2 with NEO-impulsiveness and problem drinking. Our sample of 295 unrelated adult subjects was from a community of families with at least one male with DSM-IV alcohol use diagnosis, and from a socioeconomically comparable control group. Ten GABRA2 SNPs (single-nucleotide polymorphisms) were associated with the NEO-impulsiveness (P < 0.03). The alleles associated with higher impulsiveness correspond to the minor alleles identified in previous alcohol dependence studies. All ten SNPs are in linkage disequilibrium (LD) with each other and represent one effect on impulsiveness. Four SNPs and the corresponding haplotype from intron 3 to intron 4 were also associated with Lifetime Alcohol Problems Score (LAPS, P < 0.03) (not corrected for multiple testing). Impulsiveness partially mediates (22.6% average) this relation between GABRA2 and LAPS. Our results suggest that GABRA2 variation in the region between introns 3 and 4 is associated with impulsiveness and this effect partially influences the development of alcohol problems, but a direct effect of GABRA2 on problem drinking remains. A potential functional SNP rs279827, located next to a splice site, is located in the most significant region for both impulsiveness and LAPS. The high degree of LD among nine of these SNPs and the conditional analyses we have performed suggest that all variants represent one signal.

Linkage Disequilibrium in a Diversity and Stress Adaptation Rice Panel for Association Mapping

Estimated of linkage disequilibrium (LD) are important as an indication of how useful LD-base association genetics approaches can be when compared with other available mapping methods. The success of association mapping efforts depends on the possibilities of separating LD due to linkage from LD due to other causes. In an attempt to associate markers with drought tolerance at vegetative stage, we examined the pattern of LD in a diversity and stress adaptation rice panel containing 184 rice germplasm accessions with 141 polymorphic SSR markers that were nearly evenly distributed at 3 mb bin on the 12 rice chromosomes. Significant LD was detected across the genome of the 184 rice genotypes and the extent of LD varied with different chromosomes, selfing in O. sativa species and existing of population structure in the rice panel might be the major factors of creating high LD. No genetic linkage was detected except for two pairs of SSR markers RM288 and RM464 (11.98758 Mb), RM215 and RM464 (14.61396 Mb), which were located on chromosome 9 at a relatively far distance but showed significantly higher correlation. The high degree of LD and fast decay of LD detected in this experiment indicating the 141 SSR markers used in the experiment could be feasible to carry out the whole-genome scan association studies with a relatively high resolution.

Novel genomic approaches unravel genetic architecture of complex traits in apple

BackgroundUnderstanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated.ResultsA high degree of LD even at longer distances between markers was observed, and the patterns of LD decay were similar across successive generations. Genomic regions were identified, some of which coincided with known candidate genes, with significant effects on various traits. Phenotypic variation explained by the loci identified through a whole-genome scan ranged from 3% to 25% across different traits, while fitting all markers simultaneously generally provided heritability estimates close to those from pedigree-based analysis. Results from ‘Q+K’ and ‘K’ models were very similar, suggesting that the SNP-based kinship matrix captures most of the underlying population structure. Correlations between allele substitution effects obtained from single-marker and all-marker analyses were about 0.90 for all traits. Use of SNP-derived realized relationships in linear mixed models provided a better goodness-of-fit than pedigree-based expected relationships. Genomic regions with probable pleiotropic effects were supported by the corresponding higher linkage group (LG) level estimated genetic correlations.ConclusionsThe accuracy of artificial selection in plants species can be increased by using more precise marker-derived estimates of realized coefficients of relationships. All-marker analyses that indirectly account for population- and pedigree structure will be a credible alternative to single-SNP analyses in GWAS. This study revealed large differences in the genetic architecture of apple fruit traits, and the marker-trait associations identified here will help develop genome-based breeding methods for apple cultivar development.