A HapMap harvest of insights into the genetics of common disease

Comprehension and Data-Sharing Behavior of Direct-To-Consumer Genetic Test Customers

AIM

The aim of this study was to evaluate current direct-to-consumer (DTC) genetic customers' ability to interpret and comprehend test results and to determine if honest brokers are needed.

METHOD

One hundred and twenty-two customers of the DTC genetic testing company 23andMe were polled in an online survey. The subjects were asked about their personal test results and to interpret the results of two mock test cases (type 2 diabetes and multiple sclerosis), where results were translated into disease probability for an individual compared to the public.

RESULTS

When asked to evaluate the risk, 72.1% correctly assessed the first case and 77% were correct on the second case. Only 23.8% of those surveyed were able to interpret both cases correctly. x03C7;2 and logistic regression were used to interpret the results. Participants who took the time to read the DTC test-provided supplemental material were 3.93 times (p = 0.040) more likely to correctly interpret the test results than those who did not. The odds for correctly interpreting the test cases were 3.289 times (p = 0.011) higher for those who made more than USD 50,000 than those who made less. Survey results were compared to the Health Information National Trends Survey (HINTS) phase 4 cycle 3 data to evaluate national trends.

CONCLUSIONS

Most of the subjects were able to correctly interpret the test cases, yet a majority did not share their results with a health-care professional. As the market for DTC genetic testing grows, test comprehension will become more critical. Involving more health professionals in this process may be necessary to ensure proper interpretations.

Analytical Complexity in Detection of Gene Variant-by-Environment Exposure Interactions in High-Throughput Genomic and Exposomic Research

It seems intuitive that disease risk is influenced by the interaction between inherited genetic variants and environmental exposure factors; however, we have few documented interactions between variants and exposures. Advances in technology may enable the simultaneous measurement (i.e., on the same individuals in an epidemiological study) of millions of genome variants with thousands of environmental "exposome" factors, significantly increasing the number of possible factor pairs available for testing for the presence of interactions. The burden of analytic complexity, or sheer number of genetic and exposure factors measured, poses a considerable challenge for discovery of interactions in population-scale data. Advances in analytic approaches, large sample sizes, less conservative methods to mitigate multiple testing, and strong biological priors will be required to prune the search space to find reproducible and robust gene-by-environment interactions in observational data.

Genome-wide Association Studies Identify Genetic Loci Associated With Albuminuria in Diabetes

Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and are associated with an increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (P = 2.4 × 10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. Single nucleotide polymorphisms at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in the average UACR per minor allele was 21% for HS6ST1 (P = 6.3 × 10(-7)) and 13% for RAB38/CTSC (P = 5.8 × 10(-7)). Experiments using streptozotocin-induced diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout versus control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared with control subjects. The loci identified here confirm known pathways and highlight novel pathways influencing albuminuria.

Decoding DNA, RNA and peptides with quantum tunnelling

Drugs and treatments could be precisely tailored to an individual patient by extracting their cellular- and molecular-level information. For this approach to be feasible on a global scale, however, information on complete genomes (DNA), transcriptomes (RNA) and proteomes (all proteins) needs to be obtained quickly and at low cost. Quantum mechanical phenomena could potentially be of value here, because the biological information needs to be decoded at an atomic level and quantum tunnelling has recently been shown to be able to differentiate single nucleobases and amino acids in short sequences. Here, we review the different approaches to using quantum tunnelling for sequencing, highlighting the theoretical background to the method and the experimental capabilities demonstrated to date. We also explore the potential advantages of the approach and the technical challenges that must be addressed to deliver practical quantum sequencing devices.

Genome-wide association study reveals a locus for nasal carriage of Staphylococcus aureus in Danish crossbred pigs

Background

Staphylococcus aureus is an important human opportunistic pathogen residing on skin and mucosae of healthy people. Pigs have been identified as a source of human colonization and infection with methicillin-resistant Staphylococcus aureus (MRSA) and novel measures are needed to control zoonotic transmission. A recent longitudinal study indicated that a minority of pigs characterized by high nasal load and stable carriage may be responsible for the maintenance of S. aureus within farms. The primary objective of the present study was to detect genetic loci associated with nasal carriage of S. aureus in Danish crossbred pigs (Danish Landrace/Yorkshire/Duroc).

Results

Fifty-six persistent carriers and 65 non-carriers selected from 15 farms surveyed in the previous longitudinal study were genotyped using Illumina’s Porcine SNP60 beadchip. In addition, spa typing was performed on 126 S. aureus isolates from 37 pigs to investigate possible relationships between host and S. aureus genotypes. A single SNP (MARC0099960) on chromosome 12 was found to be associated with nasal carriage of S. aureus at a genome-wide level after permutation testing (p = 0.0497) whereas the association of a neighboring SNP was found to be borderline (p = 0.114). Typing of S. aureus isolates led to detection of 11 spa types belonging to the three main S. aureus clonal complexes (CC) previously described in pigs (CC9, CC30 and CC398). Individual carriers often harbored multiple S. aureus genotypes and the host-pathogen interaction seems to be independent of S. aureus genotype.

Conclusion

Our results suggest it may be possible to select pigs genetically resistant to S. aureus nasal colonization as a tool to control transmission of livestock-associated MRSA to humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-015-0599-y) contains supplementary material, which is available to authorized users.

Measurement of Systemic Mitochondrial Function in Advanced Primary Open-Angle Glaucoma and Leber Hereditary Optic Neuropathy

Primary Open Angle Glaucoma (POAG) is a common neurodegenerative disease characterized by the selective and gradual loss of retinal ganglion cells (RGCs). Aging and increased intraocular pressure (IOP) are glaucoma risk factors; nevertheless patients deteriorate at all levels of IOP, implying other causative factors. Recent evidence presents mitochondrial oxidative phosphorylation (OXPHOS) complex-I impairments in POAG. Leber Hereditary Optic Neuropathy (LHON) patients suffer specific and rapid loss of RGCs, predominantly in young adult males, due to complex-I mutations in the mitochondrial genome. This study directly compares the degree of OXPHOS impairment in POAG and LHON patients, testing the hypothesis that the milder clinical disease in POAG is due to a milder complex-I impairment. To assess overall mitochondrial capacity, cells can be forced to produce ATP primarily from mitochondrial OXPHOS by switching the media carbon source to galactose. Under these conditions POAG lymphoblasts grew 1.47 times slower than controls, whilst LHON lymphoblasts demonstrated a greater degree of growth impairment (2.35 times slower). Complex-I enzyme specific activity was reduced by 18% in POAG lymphoblasts and by 29% in LHON lymphoblasts. We also assessed complex-I ATP synthesis, which was 19% decreased in POAG patients and 17% decreased in LHON patients. This study demonstrates both POAG and LHON lymphoblasts have impaired complex-I, and in the majority of aspects the functional defects in POAG were milder than LHON, which could reflect the milder disease development of POAG. This new evidence places POAG in the spectrum of mitochondrial optic neuropathies and raises the possibility for new therapeutic targets aimed at improving mitochondrial function.

Associating Multivariate Quantitative Phenotypes with Genetic Variants in Family Samples with a Novel Kernel Machine Regression Method

The recent development of sequencing technology allows identification of association between the whole spectrum of genetic variants and complex diseases. Over the past few years, a number of association tests for rare variants have been developed. Jointly testing for association between genetic variants and multiple correlated phenotypes may increase the power to detect causal genes in family-based studies, but familial correlation needs to be appropriately handled to avoid an inflated type I error rate. Here we propose a novel approach for multivariate family data using kernel machine regression (denoted as MF-KM) that is based on a linear mixed-model framework and can be applied to a large range of studies with different types of traits. In our simulation studies, the usual kernel machine test has inflated type I error rates when applied directly to familial data, while our proposed MF-KM method preserves the expected type I error rates. Moreover, the MF-KM method has increased power compared to methods that either analyze each phenotype separately while considering family structure or use only unrelated founders from the families. Finally, we illustrate our proposed methodology by analyzing whole-genome genotyping data from a lung function study.

Genetic susceptibility to Barrett's oesophagus: Lessons from early studies

Barrett’s oesophagus (BO) is a common condition, predisposing strongly to the development of oesophageal adenocarcinoma (OAC). Consequently, there has been considerable effort to determine the processes involved in the development of BO metaplasia, and ultimately develop markers of patients at risk. Whilst a number of robust acquired risk factors have been identified, a genetic component to these and the apparent increased susceptibility of certain individuals has long been suspected. This has been evidenced in part by linkage studies, but subsequently two recent genome-wide association studies (GWAS) have suggested mechanisms underlying the heritability of BO, as well as providing the first direct evidence at modern levels of statistical significance. This review discusses BO heritability, in addition to that of individual variants and genes reported to be associated with BO to date. Through this, we identify a number of plausible associations, although often tempered by issues of methodology, and discuss the priorities and need for future research.

Effect of IL28B genotype on hepatitis B and C virus infection

Genetic factors play a major role for treatment response and disease progression of chronic hepatitis B (HBV) and C virus (HCV) infection. In 2009 a genome-wide association study (GWAS) identified a single nucleotide polymorphism near the IL28B gene that was associated with treatment-induced viral clearance in chronic HCV infection treated with pegylated interferon-α (PEG-IFN) and ribavirin (RBV). Further, another GWAS found an association between IL28B genotype and spontaneous viral clearance in acute HCV infection. The effect on sustained viral response (SVR) could also be observed in patients receiving a triple-therapy with a direct antiviral agent (DAA) combined with PEG-IFN/RBV. In the era of all-oral interferon-free treatment regimens with the combination of different DAAs-with SVR rates exceeding 90%-the effect of IL28B was blunt. In contrast, in HBV several retrospective studies yielded conflicting results of the association of IL28B with PEG-IFN-induced treatment response.

Genome-wide association of drought-related and biomass traits with HapMap SNPs in Medicago truncatula

Improving drought tolerance of crop plants is a major goal of plant breeders. In this study, we characterized biomass and drought-related traits of 220 Medicago truncatula HapMap accessions. Characterized traits included shoot biomass, maximum leaf size, specific leaf weight, stomatal density, trichome density and shoot carbon-13 isotope discrimination (δ(13) C) of well-watered M. truncatula plants, and leaf performance in vitro under dehydration stress. Genome-wide association analyses were carried out using the general linear model (GLM), the standard mixed linear model (MLM) and compressed MLM (CMLM) in TASSEL, which revealed significant overestimation of P-values by CMLM. For each trait, candidate genes and chromosome regions containing SNP markers were found that are in significant association with the trait. For plant biomass, a 0.5 Mbp region on chromosome 2 harbouring a plasma membrane intrinsic protein, PIP2, was discovered that could potentially be targeted to increase dry matter yield. A protein disulfide isomerase-like protein was found to be tightly associated with both shoot biomass and leaf size. A glutamate-cysteine ligase and an aldehyde dehydrogenase family protein with Arabidopsis homologs strongly expressed in the guard cells were two of the top genes identified by stomata density genome-wide association studies analysis.

Genetic Susceptibility to Rhodococcus equi

Rhodococcus equi pneumonia is a major cause of morbidity and mortality in neonatal foals. Much effort has been made to identify preventative measures and new treatments for R. equi with limited success. With a growing focus in the medical community on understanding the genetic basis of disease susceptibility, investigators have begun to evaluate the interaction of the genetics of the foal with R. equi. This review describes past efforts to understand the genetic basis underlying R. equi susceptibility and tolerance. It also highlights the genetic technology available to study horses and describes the use of this technology in investigating R. equi. This review provides readers with a foundational understanding of candidate gene approaches, single nucleotide polymorphism‐based, and copy number variant‐based genome‐wide association studies, and next generation sequencing (both DNA and RNA).

Genomic medicine: health care issues and the unresolved ethical and social dilemmas

Our perception of the mechanism by which single genes can cause disease is evolving. This has led to the understanding of the pathophysiological basis of common diseases. Genomic Medicine continues to contribute to the understanding of the molecular basis of disease. Medicine has strived to achieve the goal of tailoring interventions to individual variations in risk and treatment response and advances in medical genomics will facilitate this process. Relevant to present-day practice is the use of genomic information to classify individuals according to disease susceptibility or expected responsiveness to a pharmacologic treatment and to provide targeted interventions. By investigating the genetic profile of individuals, medical professionals are able to select patients and use the information obtained to plan out a course of treatment that is much more in step with the way their body works. However, society is concerned about the effect genetic knowledge will have on ethnic or racial groups. Currently, the Health Insurance Portability and Accountability Act prohibits discrimination based on genetics. There is a need to increase the understanding of the social and ethical challenges that genomics information may pose to clinicians and scientists. This review is not meant to be exhaustive; rather, clinically relevant examples are used to illustrate how genomic medicine can facilitate the provision of molecular diagnostic methods that improve drug therapy. Finally, the rapid pace of change in genomics may likely make my conclusions today obsolete tomorrow.

Genomewide association study identifies HAS2 as a novel susceptibility gene for adult asthma in a Japanese population

BACKGROUND

It is increasingly clear that asthma is not a single disease, but a disorder with vast heterogeneity in pathogenesis, severity, and treatment response. To date, 30 genomewide association studies (GWASs) of asthma have been performed, including by our group. However, most gene variants identified so far confer relatively small increments in risk and explain only a small proportion of familial clustering.

OBJECTIVE

To identify additional genetic determinants of susceptibility to asthma using a selected Japanese population with reduced tobacco smoking exposure.

METHODS

We performed a GWAS by genotyping a total of 480 098 single-nucleotide polymorphisms (SNPs) for a Japanese cohort consisting of 734 healthy controls and 240 patients with asthma who had smoked for no more than 10 pack-years. The SNP with the strongest association was genotyped in two other independent Japanese cohorts consisting of a total of 531 healthy controls and 418 patients with asthma who had smoked for no more than 10 pack-years. For the hyaluronan synthase 2 (HAS2) gene, we investigated SNP-gene associations using an expression quantitative trait loci (eQTL) database and also analysed its gene expression profiles in 13 different normal tissues.

RESULTS

In the discovery GWAS, a SNP located upstream of HAS2, rs7846389, showed the strongest statistical significance (P = 1.43 × 10(-7) ). In the two independent replication cohorts, rs7846389 was consistently associated with asthma (nominal P = 0.0152 and 0.0478 in the first and second replication cohorts, respectively). In the meta-analysis, association of rs7846389 with susceptibility to asthma reached the level of genomewide significance (P = 7.92 × 10(-9) ). This variant was strongly correlated with HAS2 mRNA expression. The strongest expression of the gene was detected in the lung.

CONCLUSIONS

Our study identified HAS2 as a novel candidate gene for susceptibility to adult asthma.

Genome-wide Association Study on Platinum-induced Hepatotoxicity in Non-Small Cell Lung Cancer Patients

Platinum-based chemotherapy has been shown to improve the survival of advanced non-small cell lung cancer (NSCLC) patients; the platinum-induced toxicity severely impedes the success of chemotherapy. Genetic variations, such as single nucleotide polymorphisms (SNPs), may contribute to patients’ responses to the platinum-based chemotherapy. To identify SNPs that modify the risk of hepatotoxicity in NSCLC patients receiving platinum-based chemotherapy, we performed a genome-wide association scan in 334 subjects followed by a replication study among 375 subjects. Consistent associations with platinum-induced hepatotoxicity risk was identified for SNP rs2838566 located at 21q22.3, as the minor A allele could significantly increase the risk of liver injury (OR = 3.78, 95%CI = 1.99–7.19, P = 4.90 × 10⁻⁵ for GWAS scan, OR = 1.89, 95%CI = 1.03–3.46, P = 0.039 for replication, and OR = 2.56, 95%CI = 1.65–3.95, P = 2.55 × 10⁻⁵ for pooled population). These results suggested that genetic variants at 21q22.3 may contribute to the susceptibility of platinum-induced hepatotoxicity in NSCLC patients.

How do SNP ascertainment schemes and population demographics affect inferences about population history?

Background

The selection of variable sites for inclusion in genomic analyses can influence results, especially when exemplar populations are used to determine polymorphic sites. We tested the impact of ascertainment bias on the inference of population genetic parameters using empirical and simulated data representing the three major continental groups of cattle: European, African, and Indian. We simulated data under three demographic models. Each simulated data set was subjected to three ascertainment schemes: (I) random selection; (II) geographically biased selection; and (III) selection biased toward loci polymorphic in multiple groups. Empirical data comprised samples of 25 individuals representing each continental group. These cattle were genotyped for 47,506 loci from the bovine 50 K SNP panel. We compared the inference of population histories for the empirical and simulated data sets across different ascertainment conditions using F_ST and principal components analysis (PCA).

Results

Bias toward shared polymorphism across continental groups is apparent in the empirical SNP data. Bias toward uneven levels of within-group polymorphism decreases estimates of F_ST between groups. Subpopulation-biased selection of SNPs changes the weighting of principal component axes and can affect inferences about proportions of admixture and population histories using PCA. PCA-based inferences of population relationships are largely congruent across types of ascertainment bias, even when ascertainment bias is strong.

Conclusions

Analyses of ascertainment bias in genomic data have largely been conducted on human data. As genomic analyses are being applied to non-model organisms, and across taxa with deeper divergences, care must be taken to consider the potential for bias in ascertainment of variation to affect inferences. Estimates of F_ST, time of separation, and population divergence as estimated by principal components analysis can be misleading if this bias is not taken into account.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1469-5) contains supplementary material, which is available to authorized users.

A genome-wide pleiotropy scan for prostate cancer risk

BACKGROUND

No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).

OBJECTIVE

To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.

RESULTS AND LIMITATIONS

A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.

CONCLUSIONS

We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.

PATIENT SUMMARY

We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.

Genome-wide association study of myelosuppression in non-small-cell lung cancer patients with platinum-based chemotherapy

Platinum-induced myelosuppression severely impedes successful chemotherapy in non-small-cell lung cancer (NSCLC) patients. Hence, it is clinically important to identify the patients who are at high risk for severe toxicity to certain chemotherapy. We first carried out a genome-wide scan of 906 703 single-nucleotide polymorphisms (SNPs) to identify genetic variants associated with platinum-induced myelosuppression risk in 333 NSCLC patients with chemotherapy. Then, we replicated 24 SNPs that had P<1 × 10(-4) in another independent cohort of 876 NSCLC patients. With P<0.05 as the criterion of statistical significance, we found that rs13014982 at 2q24.3 and rs9909179 at 17p12 exhibited consistently significant associations with myelosuppression risk in both the genome-wide association studies (GWAS) scan and the replication stage (rs13014982: odds ratio (OR)=0.55, 95% confidence intervals (CIs): 0.41-0.74, P=7.29 × 10(-5) for GWAS scan and OR=0.77, 95% CI: 0.65-0.93, P=0.006 for replication stage; rs9909179: OR=0.51, 95% CI: 0.37-0.70, P=4.60 × 10(-5) for GWAS scan and OR=0.82, 95% CI: 0.68-0.99, P=0.040 for replication stage; both in additive model). In combined samples of genome-wide scan and replication samples, the minor alleles of rs13014982 and rs9909179 remained significant associations with the decreased risk of myelosuppression (rs13014982: OR=0.71, 95% CI: 0.61-0.83, P =1.36 × 10(-5); rs9909179: OR=0.76, 95% CI: 0.65-0.89, P=0.001). Rs13014982 at 2q24.3 and rs9909179 at 17p12 might be independent susceptibility markers for platinum-induced myelosuppression risk in NSCLC patients.

The genomic load of deleterious mutations: relevance to death in infancy and childhood

The human diploid genome has approximately 40,000 functioning conserved genes distributed within 6 billion base pairs of DNA. Most individuals carry a few heterozygous deleterious mutations and this leads to an increased risk of recessive disease in the offspring of cousin unions. Rare recessive disease is more common in the children of cousin marriages than in the general population, even though <1% of marriages in the Western World are between first cousins. But more than 90% of the children of cousin marriages do not have recessive disease and are as healthy as the rest of the population. A mathematical model based on these observations generates simultaneous equations linking the mean number of deleterious mutations in the genome of adults (M), the mean number of new deleterious mutations arising in gametogenesis and passed to the next generation (N) and the number of genes in the human diploid genome (L). The best estimates are that M is <7 and N is approximately 1. The nature of meiosis indicates that deleterious mutations in zygotes will have a Poisson distribution with a mean of M + N. There must be strong selective pressure against zygotes at the upper end of the Poisson distribution otherwise the value of M would rise with each generation. It is suggested that this selection is based on synergistic interaction of heterozygous deleterious mutations acting in large complex highly redundant and robust genetic networks. To maintain the value of M in single figures over many thousands of generations means that the zygote loss must be of the order of 30%. Most of this loss will occur soon after conception but some will occur later; during fetal development, in infancy and even in childhood. Selection means genetic death and this is caused by disease to which the deleterious mutations predispose. In view of this genome sequencing should be undertaken in all infant deaths in which the cause of death is not ascertained by standard techniques.

A Sequence Kernel Association Test for Dichotomous Traits in Family Samples under a Generalized Linear Mixed Model

OBJECTIVE

The existing methods for identifying multiple rare variants underlying complex diseases in family samples are underpowered. Therefore, we aim to develop a new set-based method for an association study of dichotomous traits in family samples.

METHODS

We introduce a framework for testing the association of genetic variants with diseases in family samples based on a generalized linear mixed model. Our proposed method is based on a kernel machine regression and can be viewed as an extension of the sequence kernel association test (SKAT and famSKAT) for application to family data with dichotomous traits (F-SKAT).

RESULTS

Our simulation studies show that the original SKAT has inflated type I error rates when applied directly to family data. By contrast, our proposed F-SKAT has the correct type I error rate. Furthermore, in all of the considered scenarios, F-SKAT, which uses all family data, has higher power than both SKAT, which uses only unrelated individuals from the family data, and another method, which uses all family data.

CONCLUSION

We propose a set-based association test that can be used to analyze family data with dichotomous phenotypes while handling genetic variants with the same or opposite directions of effects as well as any types of family relationships.

[Genetic predisposition and Pediatric Acute Respiratory Distress Syndrome: New tools for genetic study]

Acute respiratory distress syndrome (ARDS) is the most severe form of respiratory failure. Theoretically, any acute lung condition can lead to ARDS, but only a small percentage of individuals actually develop the disease. On this basis, genetic factors have been implicated in the risk of developing ARDS. Based on the pathophysiology of this disease, many candidate genes have been evaluated as potential modifiers in patient, as well as in animal models, of ARDS. Recent experimental data and clinical studies suggest that variations of genes involved in key processes of tissue, cellular and molecular lung damage may influence susceptibility and prognosis of ARDS. However, the pathogenesis of pediatric ARDS is complex, and therefore, it can be expected that many genes might contribute. Genetic variations such as single nucleotide polymorphisms and copy-number variations are likely associated with susceptibility to ARDS in children with primary lung injury. Genome-wide association (GWA) studies can objectively examine these variations, and help identify important new genes and pathogenetic pathways for future analysis. This approach might also have diagnostic and therapeutic implications, such as predicting patient risk or developing a personalized therapeutic approach to this serious syndrome.

Guidelines for the tetra-primer ARMS-PCR technique development

The tetra-primer amplification refractory mutation system-polymerase chain (ARMS-PCR) reaction is a simple and economical method to genotype single-nucleotide polymorphisms (SNPs). It uses four primers in a single PCR and is followed just by gel electrophoresis. However, the optimization step can be very hardworking and time-consuming. Hence, we propose to demonstrate and discuss critical steps for its development, in a way to provide useful information. Two SNPs that provided different amplification conditions were selected. DNA extraction methods, annealing temperatures, PCR cycles protocols, reagents, and primers concentration were also analyzed. The use of tetra-primer ARMS-PCR could be impaired for SNPs in DNA regions rich in cytosine and guanine and for samples with DNA not purified. The melting temperature was considered the factor of greater interference. However, small changes in the reagents concentration significantly affect the PCR, especially MgCl2. Balancing the inner primers band is also a key step. So, in order to balance the inner primers band, intensity is important to observe which one has the weakest band and promote its band by increasing its concentration. The use of tetra-primer ARMS-PCR attends the expectations of modern genomic research and allows the study of SNPs in a fast, reliable, and low-cost way.

A common genetic variation of melanoma inhibitory activity-2 labels a subtype of pancreatic adenocarcinoma with high endoplasmic reticulum stress levels

HNF1 homeobox A (HNF1A)-mediated gene expression constitutes an essential component of the secretory pathway in the exocrine pancreas. Melanoma inhibitory activity 2 (MIA2), a protein facilitating protein secretion, is an HNF1A target. Protein secretion is precisely coordinated by the endoplasmic reticulum (ER) stress/unfolded protein response (UPR) system. Here, we demonstrate that HNFA and MIA2 are expressed in a subset of human PDAC tissues and that HNF1A induced MIA2 in vitro. We identified a common germline variant of MIA2 (c.A617G: p.I141M) associated with a secretory defect of the MIA2 protein in PDAC cells. Patients carrying MIA2^I141M survived longer after tumor resection but the survival benefit was restricted to those patients who received adjuvant chemotherapy. The MIA2^I141M variant was associated with high expression of ER stress/UPR genes – in particular those of the ERN1/XBP arm – in human PDAC samples. Accordingly, PDAC cell lines expressing the MIA2^I141M variant expressed high levels of ERN1 and were more sensitive to gemcitabine. These findings define an interaction between the common MIA2^I141M variant and the ER stress/UPR system and specify a subgroup of PDAC patients who are more likely to benefit from adjuvant chemotherapy.

Effectiveness of shrinkage and variable selection methods for the prediction of complex human traits using data from distantly related individuals

Genome‐wide association studies (GWAS) have detected large numbers of variants associated with complex human traits and diseases. However, the proportion of variance explained by GWAS‐significant single nucleotide polymorphisms has been usually small. This brought interest in the use of whole‐genome regression (WGR) methods. However, there has been limited research on the factors that affect prediction accuracy (PA) of WGRs when applied to human data of distantly related individuals. Here, we examine, using real human genotypes and simulated phenotypes, how trait complexity, marker‐quantitative trait loci (QTL) linkage disequilibrium (LD), and the model used affect the performance of WGRs. Our results indicated that the estimated rate of missing heritability is dependent on the extent of marker‐QTL LD. However, this parameter was not greatly affected by trait complexity. Regarding PA our results indicated that: (a) under perfect marker‐QTL LD WGR can achieve moderately high prediction accuracy, and with simple genetic architectures variable selection methods outperform shrinkage procedures and (b) under imperfect marker‐QTL LD, variable selection methods can achieved reasonably good PA with simple or moderately complex genetic architectures; however, the PA of these methods deteriorated as trait complexity increases and with highly complex traits variable selection and shrinkage methods both performed poorly. This was confirmed with an analysis of human height.

Next-generation sequencing of nine atrial fibrillation candidate genes identified novel de novo mutations in patients with extreme trait of atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Genome-wide association studies (GWAS) have identified common variants in nine genomic regions associated with AF (KCNN3, PRRX1, PITX2, WNT8A, CAV1, C9orf3, SYNE2, HCN4 and ZFHX3 genes); however, the genetic variability of these risk variants does not explain the entire genetic susceptibility to AF. Rare variants missed by GWAS may also contribute to genetic risk of AF.

METHODS

We used an extreme trait design to sequence carefully selected probands with extreme phenotypes and their unaffected parents to identify rare de novo variants or mutations. Based on the hypothesis that common and rare variants may colocate in the same disease susceptibility gene, we used next-generation sequencing to sequence these nine published AF susceptibility genes identified by GWAS (a total of 179 exons) in 20 trios, 200 unrelated patients with AF and 200 non-AF controls.

RESULTS

We identified a novel mutation in the 5' untranslated region of the PITX2 gene, which localised in the transcriptionally active enhancer region. We also identified one missense exon mutation in KCNN3, two in ZFHX3 and one in SYNE2. None of these mutations were present in other unrelated patients with AF, healthy controls, unaffected parents and are thus novel and de novo (p<10(-4)). Functional study showed that the mutation in the 5' untranslated region of the PITX2 gene significantly downregulated PITX2 expression in atrial myocytes, either in basal condition or during rapid pacing. In silico analysis showed that the missense mutation in ZFHX3 results in damage of the ZFHX3 protein structure.

CONCLUSIONS

The genetic architecture of subjects with extreme phenotypes of AF is similar to that of rare or Mendelian diseases, and mutations may be the underlying cause.

InterPregGen: genetic studies of pre-eclampsia in three continents

Pre-eclampsia is a major cause of maternal and fetal mortality in pregnancy. The identification of genetic variants which predispose to pre-eclampsia demands large DNA collections from affected mothers and babies and controls, with reliable supporting phenotypic data. The InterPregGen study has assembled a consortium of researchers from Europe, Central Asia and South America with the aim of elucidating the genetic architecture of pre-eclampsia. The MoBa collection is playing a vital role in this collaborative venture, which has the potential to provide new insights into the causes of pre-eclampsia, and provide a rational basis for novel approaches to prevention and treatment.

Association between FOXO3A gene polymorphisms and human longevity: a meta-analysis

Numerous studies have shown associations between the FOXO3A gene, encoding the forkhead box O3 transcription factor, and human or specifically male longevity. However, the associations of specific FOXO3A polymorphisms with longevity remain inconclusive. We performed a meta-analysis of existing studies to clarify these potential associations. A comprehensive search was conducted to identify studies of FOXO3A gene polymorphisms and longevity. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by comparing the minor and major alleles. A total of seven articles reporting associations of FOXO3A polymorphisms with longevity were identified and included in this meta-analysis. These comprised 11 independent studies with 5241 cases and 5724 controls from different ethnic groups. rs2802292, rs2764264, rs13217795, rs1935949 and rs2802288 polymorphisms were associated with human longevity (OR = 1.36, 95% CI = 1.10–1.69, P = 0.005; OR = 1.20, 95% CI = 1.04–1.37, P = 0.01; OR = 1.27, 95% CI = 1.10–1.46, P = 0.001; OR = 1.14, 95% CI = 1.01–1.27 and OR = 1.24, 95% CI = 1.07–1.43, P = 0.003, respectively). Analysis stratified by gender indicated significant associations between rs2802292, rs2764264 and rs13217795 and male longevity (OR = 1.54, 95% CI = 1.33–1.79, P < 0.001; OR = 1.38, 95% CI = 1.15–1.66, P = 0.001; and OR = 1.39, 95% CI = 1.15–1.67, P = 0.001), but rs2802292, rs2764264 and rs1935949 were not linked to female longevity. Moreover, our study showed no association between rs2153960, rs7762395 or rs13220810 polymorphisms and longevity. In conclusion, this meta-analysis indicates a significant association of five FOXO3A gene polymorphisms with longevity, with the effects of rs2802292 and rs2764264 being male-specific. Further investigations are required to confirm these findings.

Toward a road map for global -omics: a primer on -omic technologies

As highlighted in a recent editorial in the Journal (Am J Epidemiol. 2014;180(2):127-128), the research area of "-omics" includes genomics, proteomics, metabolomics, and nascent fields of scientific inquiry such as epigenomics and exposomics. These fields can be collectively referred to as "global -omics." Increasing efforts have been made over the past 2 decades to identify and modify environmental risk factors among persons who are susceptible to disease because of their genotype and to integrate genetic information and other biological variables with information about individual-level risk factors and group-level or societal factors related to the broader residential, behavioral, or cultural context. In genome-wide association studies, only a small proportion of heritability is explained by genetic variants identified to date, which has prompted researchers in bioinformatics and biostatistics to take into account nonlinear relationships due to gene-environment or gene-gene interactions. The exposome, which is dynamic and variable, consists of all of the internal and external exposures an individual incurs over a lifetime. Both the epigenome and exposome change with age. The prenatal and perinatal periods are thought to be important times for epigenetic marking. Once the human epigenome has been fully mapped, identification of the effects of all deleterious environmental exposures according to duration of exposure and time period will be a complex undertaking, requiring collaborative epidemiologic studies.

Detection of genomic loci associated with environmental variables using generalized linear mixed models

We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress.

LincRNA-uc002yug.2 involves in alternative splicing of RUNX1 and serves as a predictor for esophageal cancer and prognosis

Long intergenic noncoding RNAs (lincRNAs) have critical regulatory roles in cancer biology; however, the contributions of lincRNAs to esophageal squamous cell carcinoma (ESCC) have been infrequently explored. The aim of this study was to explore the contribution of lincRNAs, located at ESCC susceptibility loci identified by genome-wide association studies, to the risk and prognosis of ESCC. The associations between lincRNAs and the risk and prognosis of ESCC were analyzed in 358 diagnosed patients from eastern China, and the findings were validated in 326 additional patients from southern China. Functional relevance of lincRNAs was further examined by biochemical assays. We found that lincRNA-uc002yug.2 was commonly overexpressed in ESCC compared with paired peritumoral tissue in eastern and southern Chinese populations. The expression levels of lincRNA-uc002yug.2 in ESCC might be a prognostic factor for survival. Moreover, lincRNA-uc002yug.2 promoted a combination of RUNX1 and alternative splicing (AS) factors in the nucleus to produce more RUNX1a, the short isoform and inhibitor of RUNX1, and reduce CEBPα (CCAAT/enhancer-binding protein-α) gene expression, thereby promoting ESCC progression. These results indicated that lincRNA-uc002yug.2 might involve in AS of RUNX1/AML1 and serve as a predictor for esophageal cancer and prognosis.

Association of the endothelial nitric oxide synthase gene G894T polymorphism with the risk of diabetic nephropathy in Qassim region, Saudi Arabia-A pilot study

BACKGROUND

Diabetic nephropathy (DN) is a chronic microangiopathic complication of type 2 diabetes mellitus (DM).Vascular endothelial dysfunction resulting from impaired nitric oxide synthase (NOS) activity in the vascular endothelial cells has been suggested as playing an important role in the pathogenesis of diabetic nephropathy (DN). Endothelial nitric oxide synthase (E-NOS) gene G894T polymorphism has been reported to be associated with endothelial dysfunction leading to DN. Our objective was to evaluate the association of G894T polymorphism of eNOS gene with the risk of DN among type 2 diabetic Saudi patients.

METHODS

One hundred and twenty subjects were included in this study. They were divided into three groups. Group I, 40 controls. Group II, 40 type 2 diabetic patients without nephropathy. Group III, 40 type2 diabetic patients with nephropathy. Endothelial nitric oxide synthase (eNOS) G894Tpolymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Plasma nitric oxide (NO) levels were estimated.

RESULTS

E-NOS genotype frequency showed non-significant differences among the all studied groups (p > 0.05). Both diabetic groups had significantly higher plasma nitrate levels than in controls with a significant increase in group III than in group II patients (all p < 0.0001). E NOS 894TT genotype was associated with higher plasma nitrate levels in all groups.

CONCLUSION

E-NOS gene SNP is not considered as genetic risk factor for DN among type 2 diabetic Saudi patients. The higher plasma levels of nitrates as a marker of oxidative stress in diabetic patients with nephropathy suggest the possible role of oxidative stress but not e-NOS gene SNP in pathogenesis of the DN.

Meta-analysis of the association between polymorphisms of estrogen receptor α genes rs9340799 and rs2234693 and Alzheimer's disease: evidence from 23 articles

OBJECTIVE

A meta-analysis was performed to better clarify the association between polymorphisms of estrogen receptor α genes rs9340799 and rs2234693 and risk of Alzheimer's disease (AD).

METHODS

Pooled odds ratios (ORs) with 95% confidence intervals (CIs) from fixed and random effect models were calculated. Heterogeneity among studies was evaluated using the I(2). Meta-regression was used to explore the potential sources of between-study heterogeneity.

RESULTS

A total of 23 studies about rs9340799 and 24 studies about rs2234693 were included in this meta-analysis. The combined evidence suggested that the x allele of rs9340799 had a significant protective effect on the risk of AD in codominant model (ORs = 0.893, 95%CIs = 0.822-0.970), especially for AD in Asia and sporadic AD (SAD). The p allele of rs2234693 was associated with decreased risk of AD in codominant model for patients with SAD. No publication bias was detected.

CONCLUSIONS

This meta-analysis suggested that x allele of rs9340799 might have a protective effect on the risk of AD in Asia and in patients with SAD. In addition, the p allele of rs2234693 might decrease the risk of patients with SAD.

TGFβ receptor 1: an immune susceptibility gene in HPV-associated cancer

Only a minority of those exposed to human papillomavirus (HPV) develop HPV-related cervical and oropharyngeal cancer. Because host immunity affects infection and progression to cancer, we tested the hypothesis that genetic variation in immune-related genes is a determinant of susceptibility to oropharyngeal cancer and other HPV-associated cancers by performing a multitier integrative computational analysis with oropharyngeal cancer data from a head and neck cancer genome-wide association study (GWAS). Independent analyses, including single-gene, gene-interconnectivity, protein-protein interaction, gene expression, and pathway analysis, identified immune genes and pathways significantly associated with oropharyngeal cancer. TGFβR1, which intersected all tiers of analysis and thus selected for validation, replicated significantly in the head and neck cancer GWAS limited to HPV-seropositive cases and an independent cervical cancer GWAS. The TGFβR1 containing p38-MAPK pathway was significantly associated with oropharyngeal cancer and cervical cancer, and TGFβR1 was overexpressed in oropharyngeal cancer, cervical cancer, and HPV(+) head and neck cancer tumors. These concordant analyses implicate TGFβR1 signaling as a process dysregulated across HPV-related cancers. This study demonstrates that genetic variation in immune-related genes is associated with susceptibility to oropharyngeal cancer and implicates TGFβR1/TGFβ signaling in the development of both oropharyngeal cancer and cervical cancer. Better understanding of the immunogenetic basis of susceptibility to HPV-associated cancers may provide insight into host/virus interactions and immune processes dysregulated in the minority of HPV-exposed individuals who progress to cancer.

Identifying causal variants at loci with multiple signals of association

Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/.

Hypothesis-independent pathway analysis implicates GABA and acetyl-CoA metabolism in primary open-angle glaucoma and normal-pressure glaucoma

Primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide. Using genome-wide association single-nucleotide polymorphism data from the Glaucoma Genes and Environment study and National Eye Institute Glaucoma Human Genetics Collaboration comprising 3,108 cases and 3,430 controls, we assessed biologic pathways as annotated in the KEGG database for association with risk of POAG. After correction for genic overlap among pathways, we found 4 pathways, butanoate metabolism (hsa00650), hematopoietic cell lineage (hsa04640), lysine degradation (hsa00310) and basal transcription factors (hsa03022) related to POAG with permuted p < 0.001. In addition, the human leukocyte antigen (HLA) gene family was significantly associated with POAG (p < 0.001). In the POAG subset with normal-pressure glaucoma (NPG), the butanoate metabolism pathway was also significantly associated (p < 0.001) as well as the MAPK and Hedgehog signaling pathways (hsa04010 and hsa04340), glycosaminoglycan biosynthesis-heparan sulfate pathway (hsa00534) and the phenylalanine, tyrosine and tryptophan biosynthesis pathway (hsa0400). The butanoate metabolism pathway overall, and specifically the aspects of the pathway that contribute to GABA and acetyl-CoA metabolism, was the only pathway significantly associated with both POAG and NPG. Collectively these results implicate GABA and acetyl-CoA metabolism in glaucoma pathogenesis, and suggest new potential therapeutic targets.

A novel method for detecting association between DNA methylation and diseases using spatial information

DNA methylation may represent an important contributor to the missing heritability described in complex trait genetics. However, technology to measure DNA methylation has outpaced statistical methods for analysis. Taking advantage of the recent finding that methylated sites cluster together, we propose a Spatial Clustering Method (SCM) to detect differentially methylated regions (DMRs) in the genome in case and control studies using spatial location information. This new method compares the distribution of distances in cases and controls between DNA methylation marks in the genomic region of interest. A statistic is computed based on these distances. Proper type I error rate is maintained and statistical significance is evaluated using permutation test. The effectiveness of the SCM we propose is evaluated by a simulation study. By simulating a simple disease model, we demonstrate that SCM has good power to detect DMRs associated with the disease. Finally, we applied the SCM to an exploratory analysis of chromosome 14 from a colorectal cancer data set and identified statistically significant genomic regions. Identification of these regions should lead to a better understanding of methylated sites and their contribution to disease. The SCM can be used as a reliable statistical method for the identification of DMRs associated with disease states in exploratory epigenetic analyses.

An overview of SNP interactions in genome-wide association studies

With the recent explosion in high-throughput genotyping technology, the amount and quality of single-nucleotide polymorphism (SNP) data has increased exponentially. Therefore, the identification of SNP interactions that are associated with common diseases is playing an increasing and important role in interpreting the genetic basis of disease susceptibility and in devising new diagnostic tests and treatments. However, because these data sets are large, although they typically have small sample sizes and low signal-to-noise ratios, there has been no major breakthrough despite many efforts, making this a major focus in the field of bioinformatics. In this article, we review the two main aspects of SNP interaction studies in recent years-the simulation and identification of SNP interactions-and then discuss the principles, efficiency and differences between these methods.

Common and rare genetic risk factors for glaucoma

The characterization of genes responsible for glaucoma is the critical first step toward the development of gene-based diagnostic and screening tests, which could identify individuals at risk for disease before irreversible optic nerve damage occurs. Early-onset forms of glaucoma affecting children and young adults are typically inherited as Mendelian autosomal dominant or recessive traits whereas glaucoma affecting older adults has complex inheritance. In this report, we present a comprehensive overview of the genes and genomic regions contributing to inherited glaucoma.

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease's etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

Variants in Complement Factor H and Complement Factor H-Related Protein Genes, CFHR3 and CFHR1, Affect Complement Activation in IgA Nephropathy

Complement activation is common in patients with IgA nephropathy (IgAN) and associated with disease severity. Our recent genome-wide association study of IgAN identified susceptibility loci on 1q32 containing the complement regulatory protein-encoding genes CFH and CFHR1-5, with rs6677604 in CFH as the top single-nucleotide polymorphism and CFHR3-1 deletion (CFHR3-1∆) as the top signal for copy number variation. In this study, to explore the clinical effects of variation in CFH, CFHR3, and CFHR1 on IgAN susceptibility and progression, we enrolled two populations. Group 1 included 1178 subjects with IgAN and available genome-wide association study data. Group 2 included 365 subjects with IgAN and available clinical follow-up data. In group 1, rs6677604 was associated with mesangial C3 deposition by genotype-phenotype correlation analysis. In group 2, we detected a linkage between the rs6677604-A allele and CFHR3-1∆ and found that the rs6677604-A allele was associated with higher serum levels of CFH and lower levels of the complement activation split product C3a. Furthermore, CFH levels were positively associated with circulating C3 levels and negatively associated with mesangial C3 deposition. Moreover, serum levels of the pathogenic galactose-deficient glycoform of IgA1 were also associated with the degree of mesangial C3 deposition in patients with IgAN. Our findings suggest that genetic variants in CFH, CFHR3, and CFHR1 affect complement activation and thereby, predispose patients to develop IgAN.

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data

Complex diseases are often associated with sets of multiple interacting genetic factors and possibly with unique sets of the genetic factors in different groups of individuals (genetic heterogeneity). We introduce a novel concept of custom correlation coefficient (CCC) between single nucleotide polymorphisms (SNPs) that address genetic heterogeneity by measuring subset correlations autonomously. It is used to develop a 3-step process to identify candidate multi-SNP patterns: (1) pairwise (SNP-SNP) correlations are computed using CCC; (2) clusters of so-correlated SNPs identified; and (3) frequencies of these clusters in disease cases and controls compared to identify disease-associated multi-SNP patterns. This method identified 42 candidate multi-SNP associations with hypertensive heart disease (HHD), among which one cluster of 22 SNPs (six genes) included 13 in SLC8A1 (aka NCX1, an essential component of cardiac excitation-contraction coupling) and another of 32 SNPs had 29 from a different segment of SLC8A1. While allele frequencies show little difference between cases and controls, the cluster of 22 associated alleles were found in 20% of controls but no cases and the other in 3% of controls but 20% of cases. These suggest that both protective and risk effects on HHD could be exerted by combinations of variants in different regions of SLC8A1, modified by variants from other genes. The results demonstrate that this new correlation metric identifies disease-associated multi-SNP patterns overlooked by commonly used correlation measures. Furthermore, computation time using CCC is a small fraction of that required by other methods, thereby enabling the analyses of large GWAS datasets.

Exquisite sequence selectivity with small conditional RNAs

Dynamic RNA nanotechnology based on programmable hybridization cascades with small conditional RNAs (scRNAs) offers a promising conceptual framework for engineering programmable conditional regulation in vivo. While single-base substitution (SBS) somatic mutations and single-nucleotide polymorphisms (SNPs) are important markers and drivers of disease, it is unclear whether synthetic RNA signal transducers are sufficiently programmable to accept a cognate RNA input while rejecting single-nucleotide sequence variants. Here, we explore the limits of scRNA programmability, demonstrating isothermal, enzyme-free genotyping of RNA SBS cancer markers and SNPs using scRNAs that execute a conditional hybridization cascade in the presence of a cognate RNA target. Kinetic discrimination can be engineered on a time scale of choice from minutes to days. To discriminate even the most challenging single-nucleotide sequence variants, including those that lead to nearly isoenergetic RNA wobble pairs, competitive inhibition with an unstructured scavenger strand or with other scRNAs provides a simple and effective principle for achieving exquisite sequence selectivity.

The American cranberry: first insights into the whole genome of a species adapted to bog habitat

BACKGROUND

The American cranberry (Vaccinium macrocarpon Ait.) is one of only three widely-cultivated fruit crops native to North America- the other two are blueberry (Vaccinium spp.) and native grape (Vitis spp.). In terms of taxonomy, cranberries are in the core Ericales, an order for which genome sequence data are currently lacking. In addition, cranberries produce a host of important polyphenolic secondary compounds, some of which are beneficial to human health. Whereas next-generation sequencing technology is allowing the advancement of whole-genome sequencing, one major obstacle to the successful assembly from short-read sequence data of complex diploid (and higher ploidy) organisms is heterozygosity. Cranberry has the advantage of being diploid (2n = 2x = 24) and self-fertile. To minimize the issue of heterozygosity, we sequenced the genome of a fifth-generation inbred genotype (F ≥ 0.97) derived from five generations of selfing originating from the cultivar Ben Lear.

RESULTS

The genome size of V. macrocarpon has been estimated to be about 470 Mb. Genomic sequences were assembled into 229,745 scaffolds representing 420 Mbp (N50 = 4,237 bp) with 20X average coverage. The number of predicted genes was 36,364 and represents 17.7% of the assembled genome. Of the predicted genes, 30,090 were assigned to candidate genes based on homology. Genes supported by transcriptome data totaled 13,170 (36%).

CONCLUSIONS

Shotgun sequencing of the cranberry genome, with an average sequencing coverage of 20X, allowed efficient assembly and gene calling. The candidate genes identified represent a useful collection to further study important biochemical pathways and cellular processes and to use for marker development for breeding and the study of horticultural characteristics, such as disease resistance.

Integrated pathway-based approach identifies association between genomic regions at CTCF and CACNB2 and schizophrenia

In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional consequences of such single-nucleotide polymorphisms (SNPs) in the affected genes or their regulatory regions. The Global Test was applied to detect schizophrenia-associated pathways using discovery and replication datasets comprising 5,040 and 5,082 individuals of European ancestry, respectively. Information concerning functional gene-sets was retrieved from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and the Molecular Signatures Database. Fourteen of the gene-sets or pathways identified in the discovery dataset were confirmed in the replication dataset. These include functional processes involved in transcriptional regulation and gene expression, synapse organization, cell adhesion, and apoptosis. For two genes, i.e. CTCF and CACNB2, evidence for association with schizophrenia was available (at the gene-level) in both the discovery study and published data from the Psychiatric Genomics Consortium schizophrenia study. Furthermore, these genes mapped to four of the 14 presently identified pathways. Several of the SNPs assigned to CTCF and CACNB2 have potential functional consequences, and a gene in close proximity to CACNB2, i.e. ARL5B, was identified as a potential gene of interest. Application of the present hierarchical approach thus allowed: (1) identification of novel biological gene-sets or pathways with potential involvement in the etiology of schizophrenia, as well as replication of these findings in an independent cohort; (2) detection of genes of interest for future follow-up studies; and (3) the highlighting of novel genes in previously reported candidate regions for schizophrenia.