Cloning and characterization of a putative TAC1 ortholog associated with leaf angle in maize (Zea mays L.)

Background

Modifying plant architecture to increase photosynthesis efficiency and reduce shade avoidance response is very important for further yield improvement when crops are grown in high density. Identification of alleles controlling leaf angle in maize is needed to provide insight into molecular mechanism of leaf development and achieving ideal plant architecture to improve grain yield.

Methodology/Principal Findings

The gene cloning was done by using comparative genomics, and then performing real-time polymerase chain reaction (RT-PCR) analysis to assay gene expression. The gene function was validated by sequence dissimilarity analysis and QTL mapping using a functional cleaved amplified polymorphism (CAP).

Conclusions

The leaf angle is controlled by a major quantitative trait locus, ZmTAC1 (Zea mays L. Leaf Angle Control 1). ZmTAC1 has 4 exons encoding a protein with 263 amino acids, and its domains are the same as those of the rice OsTAC1 protein. ZmTAC1 was found to be located in the region of qLA2 by using the CAP marker and the F_2:3 families from the cross between Yu82 and Shen137. Real-time PCR analysis revealed ZmTAC1 expression was the highest in the leaf-sheath pulvinus, less in the leaf and shoot apical meristem, and the lowest in the root. A nucleotide difference in the 5′-untranslated region (UTR) between the compact inbred line Yu82 (“CTCC”) and the expanded inbred line Shen137 (“CCCC”) influences the expression level of ZmTAC1, further controlling the size of the leaf angle. Sequence verification of the change in the 5′-UTR revealed ZmTAC1 with “CTCC” was present in 13 compact inbred lines and ZmTAC1 with “CCCC” was present in 18 expanded inbred lines, indicating ZmTAC1 had been extensively utilized in breeding with regard to the improvement of the maize plant architecture.     

Using genome-wide associations to identify metabolic pathways involved in maize aflatoxin accumulation resistance

Background

Aflatoxin is a potent carcinogen that can contaminate grain infected with the fungus Aspergillus flavus. However, resistance to aflatoxin accumulation in maize is a complex trait with low heritability. Here, two complementary analyses were performed to better understand the mechanisms involved. The first coupled results of a genome-wide association study (GWAS) that accounted for linkage disequilibrium among single nucleotide polymorphisms (SNPs) with gene-set enrichment for a pathway-based approach. The rationale was that the cumulative effects of genes in a pathway would give insight into genetic differences that distinguish resistant from susceptible lines of maize. The second involved finding non-pathway genes close to the most significant SNP-trait associations with the greatest effect on reducing aflatoxin in multiple environments. Unlike conventional GWAS, the latter analysis emphasized multiple aspects of SNP-trait associations rather than just significance and was performed because of the high genotype x environment variability exhibited by this trait.

Results

The most significant metabolic pathway identified was jasmonic acid (JA) biosynthesis. Specifically, there was at least one allelic variant for each step in the JA biosynthesis pathway that conferred an incremental decrease to the level of aflatoxin observed among the inbred lines in the GWAS panel. Several non-pathway genes were also consistently associated with lowered aflatoxin levels. Those with predicted functions related to defense were: leucine-rich repeat protein kinase, expansin B3, reversion-to-ethylene sensitivity1, adaptor protein complex2, and a multidrug and toxic compound extrusion protein.

Conclusions

Our genetic analysis provided strong evidence for several genes that were associated with aflatoxin resistance. Inbred lines that exhibited lower levels of aflatoxin accumulation tended to share similar haplotypes for genes specifically in the pathway of JA biosynthesis, along with several non-pathway genes with putative defense-related functions. Knowledge gained from these two complementary analyses has improved our understanding of population differences in aflatoxin resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1874-9) contains supplementary material, which is available to authorized users.     

Genetic variants at newly identified lipid loci are associated with coronary heart disease in a Chinese Han population

Background

Recent genome-wide association studies (GWAS) have mapped several novel loci influencing blood lipid levels in Caucasians. We sought to explore whether the genetic variants at newly identified lipid-associated loci were associated with CHD susceptibility in a Chinese Han population.

Methodology/Principal Findings

We conducted a two-stage case-control study in a Chinese Han population. The first-stage, consisting of 1,376 CHD cases and 1,376 sex and age- frequency matched controls, examined 5 novel lipid-associated single-nucleotide polymorphisms (SNPs) identified from GWAS among Caucasians in relation to CHD risk in Chinese. We then validated significant SNPs in the second-stage, consisting of 1,269 cases and 2,745 controls. We also tested associations between SNPs within the five novel loci and blood lipid levels in 4,121 controls. We identified two novel SNPs (rs599839 in CELSR2-PSRC1-SORT1 and rs16996148 in NCAN-CILP2) that were significantly associated with reduced CHD risk in Chinese (odds ratios (95% confidence intervals) in the dominant model 0.76 (0.61-0.90; P = 0.001), 0.67 (0.57-0.77; P = 3.4×10⁻⁸), respectively). Multiple linear regression analyses using dominant model showed that rs599839 was significantly associated with decreased LDL levels (P = 0.022) and rs16996148 was significantly associated with increased LDL and HDL levels (P = 2.9×10⁻⁴ and 0.001, respectively).

Conclusions/Significance

We identified two novel SNPs (rs599839 and rs16996148) at newly identified lipid-associated loci that were significantly associated with CHD susceptibility in a Chinese Han population.     

Extent of height variability explained by known height-associated genetic variants in an isolated population of the Adriatic coast of Croatia

Background

Human height is a classical example of a polygenic quantitative trait. Recent large-scale genome-wide association studies (GWAS) have identified more than 200 height-associated loci, though these variants explain only 2∼10% of overall variability of normal height. The objective of this study was to investigate the variance explained by these loci in a relatively isolated population of European descent with limited admixture and homogeneous genetic background from the Adriatic coast of Croatia.

Methodology/Principal Findings

In a sample of 1304 individuals from the island population of Hvar, Croatia, we performed genome-wide SNP typing and assessed the variance explained by genetic scores constructed from different panels of height-associated SNPs extracted from five published studies. The combined information of the 180 SNPs reported by Lango Allen el al. explained 7.94% of phenotypic variation in our sample. Genetic scores based on 20∼50 SNPs reported by the remaining individual GWA studies explained 3∼5% of height variance. These percentages of variance explained were within ranges comparable to the original studies and heterogeneity tests did not detect significant differences in effect size estimates between our study and the original reports, if the estimates were obtained from populations of European descent.

Conclusions/Significance

We have evaluated the portability of height-associated loci and the overall fitting of estimated effect sizes reported in large cohorts to an isolated population. We found proportions of explained height variability were comparable to multiple reference GWAS in cohorts of European descent. These results indicate similar genetic architecture and comparable effect sizes of height loci among populations of European descent.     

Genetic variation on 9p22 is associated with abnormal ovarian ultrasound results in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

Background

A recent ovarian cancer genome-wide association study (GWAS) identified a locus on 9p22 associated with reduced ovarian cancer risk. The single nucleotide polymorphism (SNP) markers localize to the BNC2 gene, which has been associated with ovarian development.

Methods

We analyzed the association of 9p22 SNPs with transvaginal ultrasound (TVU) screening results and CA-125 blood levels from participants without ovarian cancer in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO); 1,106 women with adequate ultrasound screening results and available genotyping information were included in the study.

Results

We observed a significantly increased risk of abnormal suspicious TVU results for seven SNPs on 9p22, with odds ratios between 1.68 (95% CI: 1.04–2.72) for rs4961501 and 2.10 (95% CI: 1.31–3.38) for rs12379183. Associations were restricted to abnormal suspicious findings at the first TVU screen. We did not observe an association between 9p22 SNPs and CA-125 levels.

Conclusions

Our findings suggest that 9p22 SNPs, which were found to be associated with decreased risk of ovarian cancer in a recent GWAS, are associated with sonographically detectable ovarian abnormalities. Our results corroborate the relevance of the 9p22 locus for ovarian biology. Further studies are required to understand the complex relationship between screening abnormalities and ovarian carcinogenesis and to evaluate whether this locus can influence the risk stratification of ovarian cancer screening.     

Pooled sample-based GWAS: a cost-effective alternative for identifying colorectal and prostate cancer risk variants in the Polish population

Background

Prostate cancer (PCa) and colorectal cancer (CRC) are the most commonly diagnosed cancers and cancer-related causes of death in Poland. To date, numerous single nucleotide polymorphisms (SNPs) associated with susceptibility to both cancer types have been identified, but their effect on disease risk may differ among populations.

Methods

To identify new SNPs associated with PCa and CRC in the Polish population, a genome-wide association study (GWAS) was performed using DNA sample pools on Affymetrix Genome-Wide Human SNP 6.0 arrays. A total of 135 PCa patients and 270 healthy men (PCa sub-study) and 525 patients with adenoma (AD), 630 patients with CRC and 690 controls (AD/CRC sub-study) were included in the analysis. Allele frequency distributions were compared with t-tests and χ²-tests. Only those significantly associated SNPs with a proxy SNP (p<0.001; distance of 100 kb; r²>0.7) were selected. GWAS marker selection was conducted using PLINK. The study was replicated using extended cohorts of patients and controls. The association with previously reported PCa and CRC susceptibility variants was also examined. Individual patients were genotyped using TaqMan SNP Genotyping Assays.

Results

The GWAS selected six and 24 new candidate SNPs associated with PCa and CRC susceptibility, respectively. In the replication study, 17 of these associations were confirmed as significant in additive model of inheritance. Seven of them remained significant after correction for multiple hypothesis testing. Additionally, 17 previously reported risk variants have been identified, five of which remained significant after correction.

Conclusion

Pooled-DNA GWAS enabled the identification of new susceptibility loci for CRC in the Polish population. Previously reported CRC and PCa predisposition variants were also identified, validating the global nature of their associations. Further independent replication studies are required to confirm significance of the newly uncovered candidate susceptibility loci.     

Identification and validation of genomic regions influencing kernel zinc and iron in maize

Key message

Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize.

Abstract

Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world’s poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P?≤?5.03?×?10^?05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P?≤?1?×?10^?03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P?≤?0.01, R²?≥?0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

     

Genome-wide association study for flowering time,maturity dates and plant height in early maturing soybean (Glycine max) germplasm

Background

Soybean (Glycine max) is a photoperiod-sensitive and self-pollinated species. Days to flowering (DTF) and maturity (DTM), duration of flowering-to-maturity (DFTM) and plant height (PH) are crucial for soybean adaptability and yield. To dissect the genetic architecture of these agronomically important traits, a population consisting of 309 early maturity soybean germplasm accessions was genotyped with the Illumina Infinium SoySNP50K BeadChip and phenotyped in multiple environments. A genome-wide association study (GWAS) was conducted using a mixed linear model that involves both relative kinship and population structure.

Results

The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly.

Conclusions

This study identified multiple new loci and refined chromosomal regions of known loci associated with DTF, DTM, DFTM and/or PH in soybean. It demonstrates that GWAS is powerful in dissecting complex traits and identifying candidate genes although LD decayed slowly in soybean. The loci and trait-associated SNPs identified in this study can be used for soybean genetic improvement, especially the major-effect loci associated with PH could be used to improve soybean yield potential. The candidate genes may serve as promising targets for studies of molecular mechanisms underlying the related traits in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1441-4) contains supplementary material, which is available to authorized users.     

Comprehensive genotyping of the USA national maize inbred seed bank

Background

Genotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world.

Results

The method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits.

Conclusions

The genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.     

Genomic consequences of selection and genome-wide association mapping in soybean

Background

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

Results

To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

Conclusions

These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1872-y) contains supplementary material, which is available to authorized users.     

Common variants in CDKN2B-AS1 associated with optic-nerve vulnerability of glaucoma identified by genome-wide association studies in Japanese

Background

To date, only a small portion of the genetic variation for primary open-angle glaucoma (POAG), the major type of glaucoma, has been elucidated.

Methods and Principal Findings

We examined our two data sets of the genome-wide association studies (GWAS) derived from a total of 2,219 Japanese subjects. First, we performed a GWAS by analyzing 653,519 autosomal common single-nucleotide polymorphisms (SNPs) in 833 POAG patients and 686 controls. As a result, five variants that passed the Bonferroni correction were identified in CDKN2B-AS1 on chromosome 9p21.3, which was already reported to be a significant locus in the Caucasian population. Moreover, we combined the data set with our previous GWAS data set derived from 411 POAG patients and 289 controls by the Mantel-Haenszel test, and all of the combined variants showed stronger association with POAG (P<5.8×10⁻¹⁰). We then subdivided the case groups into two subtypes based on the value of intraocular pressure (IOP)—POAG with high IOP (high pressure glaucoma, HPG) and that with normal IOP (normal pressure glaucoma, NPG)—and performed the GWAS using the two data sets, as the prevalence of NPG in Japanese is much higher than in Caucasians. The results suggested that the variants from the same CDKN2B-AS1 locus were likely to be significant for NPG patients.

Conclusions and Significance

In this study, we successfully identified POAG-associated variants in the CDKN2B-AS1 locus using a Japanese population, i.e., variants originally reported as being associated with the Caucasian population. Although we cannot rule out that the significance could be due to the differences in sample size between HPG and NPG, the variants could be associated specifically with the vulnerability of the optic nerve to IOP, which is useful for investigating the etiology of glaucoma.     

Limits on the reproducibility of marker associations with southern leaf blight resistance in the maize nested association mapping population

Background

A previous study reported a comprehensive quantitative trait locus (QTL) and genome wide association study (GWAS) of southern leaf blight (SLB) resistance in the maize Nested Association Mapping (NAM) panel. Since that time, the genomic resources available for such analyses have improved substantially. An updated NAM genetic linkage map has a nearly six-fold greater marker density than the previous map and the combined SNPs and read-depth variants (RDVs) from maize HapMaps 1 and 2 provided 28.5 M genomic variants for association analysis, 17 fold more than HapMap 1. In addition, phenotypic values of the NAM RILs were re-estimated to account for environment-specific flowering time covariates and a small proportion of lines were dropped due to genotypic data quality problems. Comparisons of original and updated QTL and GWAS results confound the effects of linkage map density, GWAS marker density, population sample size, and phenotype estimates. Therefore, we evaluated the effects of changing each of these parameters individually and in combination to determine their relative impact on marker-trait associations in original and updated analyses.

Results

Of the four parameters varied, map density caused the largest changes in QTL and GWAS results. The updated QTL model had better cross-validation prediction accuracy than the previous model. Whereas joint linkage QTL positions were relatively stable to input changes, the residual values derived from those QTL models (used as inputs to GWAS) were more sensitive, resulting in substantial differences between GWAS results. The updated NAM GWAS identified several candidate genes consistent with previous QTL fine-mapping results.

Conclusions

The highly polygenic nature of resistance to SLB complicates the identification of causal genes. Joint linkage QTL are relatively stable to perturbations of data inputs, but their resolution is generally on the order of tens or more Mbp. GWAS associations have higher resolution, but lower power due to stringent thresholds designed to minimize false positive associations, resulting in variability of detection across studies. The updated higher density linkage map improves QTL estimation and, along with a much denser SNP HapMap, greatly increases the likelihood of detecting SNPs in linkage with causal variants. We recommend use of the updated genetic resources and results but emphasize the limited repeatability of small-effect associations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1068) contains supplementary material, which is available to authorized users.     

Bivariate genome-wide association analyses of femoral neck bone geometry and appendicular lean mass

Objective

Femoral neck geometric parameters (FNGPs), such as periosteal diameter (W), cross-sectional area (CSA), cortical thickness (CT), buckling ratio (BR), and section modulus (Z), are highly genetically correlated with body lean mass. However, the specific SNPs/genes shared by these phenotypes are largely unknown.

Methods

To identify the specific SNPs/genes shared between FNGPs and appendicular lean mass (ALM), we performed an initial bivariate genome-wide association study (GWAS) by scanning ∼690,000 SNPs in 1,627 unrelated Han Chinese adults (802 males and 825 females) and a follow-up replicate study in 2,286 unrelated US Caucasians.

Results

We identified 13 interesting SNPs that may be important for both FNGPs and ALM. Two SNPs, rs681900 located in the HK2 (hexokinase 2) gene and rs11859916 in the UMOD (uromodulin) gene, were bivariately associated with FNGPs and ALM (p = 7.58×10⁻⁶ for ALM-BR and p = 2.93×10⁻⁶ for ALM-W, respectively). The associations were then replicated in Caucasians, with corresponding p values of 0.024 for rs681900 and 0.047 for rs11859916. Meta-analyses yielded combined p values of 3.05×10⁻⁶ and 2.31×10⁻⁶ for rs681900 and rs11859916, respectively. Our findings are consistent with previous biological studies that implicated HK2 and UMOD in both FNGPs and ALM. Our study also identified a group of 11 contiguous SNPs, which spanned a region of ∼130 kb, were bivariately associated with FNGPs and ALM, with p values ranging from 3.06×10⁻⁷ to 4.60×10⁻⁶ for ALM-BR. The region contained two neighboring miRNA coding genes, MIR873 (MicroRNA873) and MIR876 (MicroRNA876).

Conclusion

Our study implicated HK2, UMOD, MIR873 and MIR876, as pleiotropic genes underlying variation of both FNGPs and ALM, thus suggesting their important functional roles in co-regulating both FNGPs and ALM.     

Characterization of genome-wide association-identified variants for atrial fibrillation in African Americans

Background

Despite a greater burden of risk factors, atrial fibrillation (AF) is less common among African Americans than European-descent populations. Genome-wide association studies (GWAS) for AF in European-descent populations have identified three predominant genomic regions associated with increased risk (1q21, 4q25, and 16q22). The contribution of these loci to AF risk in African American is unknown.

Methodology/Principal Findings

We studied 73 African Americans with AF from the Vanderbilt-Meharry AF registry and 71 African American controls, with no history of AF including after cardiac surgery. Tests of association were performed for 148 SNPs across the three regions associated with AF, and 22 SNPs were significantly associated with AF (P<0.05). The SNPs with the strongest associations in African Americans were both different from the index SNPs identified in European-descent populations and independent from the index European-descent population SNPs (r²<0.40 in HapMap CEU): 1q21 rs4845396 (odds ratio [OR] 0.30, 95% confidence interval [CI] 0.13–0.67, P = 0.003), 4q25 rs4631108 (OR 3.43, 95% CI 1.59–7.42, P = 0.002), and 16q22 rs16971547 (OR 8.1, 95% CI 1.46–45.4, P = 0.016). Estimates of European ancestry were similar among cases (23.6%) and controls (23.8%). Accordingly, the probability of having two copies of the European derived chromosomes at each region did not differ between cases and controls.

Conclusions/Significance

Variable European admixture at known AF loci does not explain decreased AF susceptibility in African Americans. These data support the role of 1q21, 4q25, and 16q22 variants in AF risk for African Americans, although the index SNPs differ from those identified in European-descent populations.     

Pooled genome-wide analysis to identify novel risk loci for pediatric allergic asthma

Background

Genome-wide association studies of pooled DNA samples were shown to be a valuable tool to identify candidate SNPs associated to a phenotype. No such study was up to now applied to childhood allergic asthma, even if the very high complexity of asthma genetics is an appropriate field to explore the potential of pooled GWAS approach.

Methodology/Principal Findings

We performed a pooled GWAS and individual genotyping in 269 children with allergic respiratory diseases comparing allergic children with and without asthma. We used a modular approach to identify the most significant loci associated with asthma by combining silhouette statistics and physical distance method with cluster-adapted thresholding. We found 97% concordance between pooled GWAS and individual genotyping, with 36 out of 37 top-scoring SNPs significant at individual genotyping level. The most significant SNP is located inside the coding sequence of C5, an already identified asthma susceptibility gene, while the other loci regulate functions that are relevant to bronchial physiopathology, as immune- or inflammation-mediated mechanisms and airway smooth muscle contraction. Integration with gene expression data showed that almost half of the putative susceptibility genes are differentially expressed in experimental asthma mouse models.

Conclusion/Significance

Combined silhouette statistics and cluster-adapted physical distance threshold analysis of pooled GWAS data is an efficient method to identify candidate SNP associated to asthma development in an allergic pediatric population.     

Genome-wide association study combined with biological context can reveal more disease-related SNPs altering microRNA target seed sites

Background

Emerging studies demonstrate that single nucleotide polymorphisms (SNPs) resided in the microRNA recognition element seed sites (MRESSs) in 3′UTR of mRNAs are putative biomarkers for human diseases and cancers. However, exhaustively experimental validation for the causality of MRESS SNPs is impractical. Therefore bioinformatics have been introduced to predict causal MRESS SNPs. Genome-wide association study (GWAS) provides a way to detect susceptibility of millions of SNPs simultaneously by taking linkage disequilibrium (LD) into account, but the multiple-testing corrections implemented to suppress false positive rate always sacrificed the sensitivity. In our study, we proposed a method to identify candidate causal MRESS SNPs from 12 GWAS datasets without performing multiple-testing corrections. Alternatively, we used biological context to ensure credibility of the selected SNPs.

Results

In 11 out of the 12 GWAS datasets, MRESS SNPs were over-represented in SNPs with p-value ≤ 0.05 (odds ratio (OR) ranged from 1.1 to 2.4). Moreover, host genes of susceptible MRESS SNPs in each of the 11 GWAS dataset shared biological context with reported causal genes. There were 286 MRESS SNPs identified by our method, while only 13 SNPs were identified by multiple-testing corrections with a given threshold of 1 × 10⁻⁵, which is a common cutoff used in GWAS. 27 out of the 286 candidate SNPs have been reported to be deleterious while only 2 out of 13 multiple-testing corrected SNPs were documented in PubMed. MicroRNA-mRNA interactions affected by the 286 candidate SNPs were likely to present negatively correlated expression. These SNPs introduced greater alternation of binding free energy than other MRESS SNPs, especially when grouping by haplotypes (4210 vs. 4105 cal/mol by mean, 9781 vs. 8521 cal/mol by mean, respectively).

Conclusions

MRESS SNPs are promising disease biomarkers in multiple GWAS datasets. The method of integrating GWAS p-value and biological context is stable and effective for selecting candidate causal MRESS SNPs, it reduces the loss of sensitivity compared to multiple-testing corrections. The 286 candidate causal MRESS SNPs provide researchers a credible source to initialize their design of experimental validations in the future.

Electronic supplementary material

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Educational attainment: a genome wide association study in 9538 Australians

Background

Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ.

Methodology

In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of ∼2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores.

Results

The best SNP fell short of having a genome-wide significant p-value (p = 9.77×10⁻⁷). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r²<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing - rs7106258 (p = 9.7*10⁻⁴) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample.

Conclusion

While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA.