Finding genes that underlie complex traits

Integration of multiple data sources to prioritize candidate genes using discounted rating system

Background

Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their similarity to known disease genes. Most of existing gene prioritization methods access only one genomic data source, which is noisy and incomplete. Thus, there is a need for the integration of multiple data sources containing different information.

Results

In this paper, we proposed a combination strategy, called discounted rating system (DRS). We performed leave one out cross validation to compare it with N-dimensional order statistics (NDOS) used in Endeavour. Results showed that the AUC (Area Under the Curve) values achieved by DRS were comparable with NDOS on most of the disease families. But DRS worked much faster than NDOS, especially when the number of data sources increases. When there are 100 candidate genes and 20 data sources, DRS works more than 180 times faster than NDOS. In the framework of DRS, we give different weights for different data sources. The weighted DRS achieved significantly higher AUC values than NDOS.

Conclusion

The proposed DRS algorithm is a powerful and effective framework for candidate gene prioritization. If weights of different data sources are proper given, the DRS algorithm will perform better.

Interaction of SLC6A4 and DRD2 polymorphisms is associated with a history of delirium tremens

Several genetic polymorphisms have been reported to be associated with alcohol withdrawal seizures (AWS) and delirium tremens (DT). To replicate and further explore these findings, we investigated the effects of 12 previously reported candidate genetic variations in two groups of alcohol-dependent European Americans with a history of withdrawal, which differed according to the presence (n = 112) or absence (n = 92) of AWS and/or DT. Associations of AWS and/or DT with the genomic and clinical characteristics and gene-gene interaction effects were investigated using logistic regression models. None of the polymorphisms were significantly associated with AWS/DT after correction for multiple testing. However, we found a significant interaction effect of the SLC6A4 promoter polymorphism (5-HTTLPR) and DRD2 exon 8 single nucleotide polymorphism rs6276 on AWS and/or DT history (P = 0.009), which became more significant after adjustment for lifetime maximum number of drinks consumed per 24 hours (P < 0.001). Subsequent analysis revealed an even stronger association of the SLC6A4-DRD2 interaction with DT (P < 0.0001), which remained significant after Bonferroni correction. Results reveal decreased likelihood of DT in alcoholics that carry the DRD2 rs6276 G allele and SLC6A4 LL genotype. This study provides the first evidence to implicate the interaction between serotonin and dopamine neurotransmission in the etiology of DT. Replication is necessary to verify this potentially important finding.

Use of rat genomics for investigating the metabolic syndrome

The spontaneously hypertensive rat (SHR) is the most widely used animal model of essential hypertension and accompanying metabolic disturbances. In this model, the use of whole genome sequencing and gene expression profiling techniques, linkage and correlation analyses in recombinant inbred strains, and in vitro and in vivo functional studies in congenic and transgenic lines has recently enabled molecular identification of quantitative trait loci (QTLs) relevant to the metabolic syndrome: (1) a deletion variant in Cd36 (fatty acid translocase) responsible for QTLs on chromosome 4 associated with dyslipidemia, insulin resistance and hypertension, (2) mutated Srebf1 (sterol regulatory element binding factor 1) as a QTL on chromosome 10 influencing dietary-induced changes in hepatic cholesterol levels, and (3) Ogn (osteoglycin) as a QTL on chromosome 17 associated with left ventricular hypertrophy. In addition, selective replacement of the mitochondrial genome of the SHR with the mitochondrial genome of the Brown Norway rat influenced several major metabolic risk factors for type 2 diabetes and provided evidence that spontaneous variation in the mitochondrial genome per se can promote systemic metabolic disturbances relevant to the pathogenesis of metabolic syndrome. Owing to recent progress in the development of rat genomic resources, the pace of QTL identification and discovery of new disease mechanisms can be expected to accelerate in the near future.

Genetic mapping and positional cloning

Genetic mapping and positional cloning of genetically complex traits in the laboratory rat (Rattus norvegicus) has recently led to the identification of various susceptibility genes in different rat models. Rat genetics has benefited from revolutionary advances in molecular biology, genetics, genomics and informatics and provide an unparalleled resource for molecular genetic investigation of mammalian physiopathology and its underlying complex genetic architecture. In this review, we will consider different strategies that are being used in the successful positional cloning of rat complex trait genes in the context of recent progress in rodent and human genetics.

Genetics of hypertension: from experimental animals to humans

Essential hypertension affects 20 to 30% of the population worldwide and contributes significantly to cardiovascular mortality and morbidity. Heridability of blood pressure is around 15 to 40% but there are also substantial environmental factors affecting blood pressure variability. It is assumed that blood pressure is under the control of a large number of genes each of which has only relatively mild effects. It has therefore been difficult to discover the genes that contribute to blood pressure variation using traditional approaches including candidate gene studies and linkage studies. Animal models of hypertension, particularly in the rat, have led to the discovery of quantitative trait loci harbouring one or several hypertension related genes, but translation of these findings into human essential hypertension remains challenging. Recent development of genotyping technology made large scale genome-wide association studies possible. This approach and the study of monogenic forms of hypertension has led to the discovery of novel and robust candidate genes for human essential hypertension, many of which require functional analysis in experimental models.

Genetic regulation of canine skeletal traits: trade-offs between the hind limbs and forelimbs in the fox and dog

Genetic variation in functionally integrated skeletal traits can be maintained over 10 million years despite bottlenecks and stringent selection. Here, we describe an analysis of the genetic architecture of the canid axial skeleton using populations of the Portuguese Water Dog Canis familiaris) and silver fox (Vulpes vulpes). Twenty-one skeletal metrics taken from radiographs of the forelimbs and hind limbs of the fox and dog were used to construct separate anatomical principal component (PC) matrices of the two species. In both species, 15 of the 21 PCs exhibited significant heritability, ranging from 25% to 70%. The second PC, in both species, represents a trade-off in which limb-bone width is inversely correlated with limb-bone length. PC2 accounts for approximately 15% of the observed skeletal variation, approximately 30% of the variation in shape. Many of the other significant PCs affect very small amounts of variation (e.g., 0.2-2%) along trade-off axes that partition function between the forelimbs and hind limbs. These PCs represent shape axes in which an increase in size of an element of the forelimb is associated with a decrease in size of an element of the hind limb and vice versa. In most cases, these trade-offs are heritable in both species and genetic loci have been identified in the Portuguese Water Dog for many of these. These PCs, present in both the dog and the fox, include ones that affect lengths of the forelimb versus the hind limb, length of the forefoot versus that of the hind foot, muscle moment (i.e., lever) arms of the forelimb versus hind limb, and cortical thickness of the bones of the forelimb versus hind limb. These inverse relationships suggest that genetic regulation of the axial skeleton results, in part, from the action of genes that influence suites of functionally integrated traits. Their presence in both dogs and foxes suggests that the genes controlling the regulation of these PCs of the forelimb versus hind limb may be found in other tetrapod taxa.

Transgenerational genetic effects on phenotypic variation and disease risk

Traditionally, we understand that individual phenotypes result primarily from inherited genetic variants together with environmental exposures. However, many studies showed that a remarkable variety of factors including environmental agents, parental behaviors, maternal physiology, xenobiotics, nutritional supplements and others lead to epigenetic changes that can be transmitted to subsequent generations without continued exposure. Recent discoveries show transgenerational epistasis and transgenerational genetic effects where genetic factors in one generation affect phenotypes in subsequent generation without inheritance of the genetic variant in the parents. Together these discoveries implicate a key signaling pathway, chromatin remodeling, methylation, RNA editing and microRNA biology. This exceptional mode of inheritance complicates the search for disease genes and represents perhaps an adaptation to transmit useful gene expression profiles from one generation to the next. In this review, I present evidence for these transgenerational genetic effects, identify their common features, propose a heuristic model to guide the search for mechanisms, discuss the implications, and pose questions whose answers will begin to reveal the underlying mechanisms.

Power of multifactor dimensionality reduction and penalized logistic regression for detecting gene-gene interaction in a case-control study

BACKGROUND

There is a growing awareness that interaction between multiple genes play an important role in the risk of common, complex multi-factorial diseases. Many common diseases are affected by certain genotype combinations (associated with some genes and their interactions). The identification and characterization of these susceptibility genes and gene-gene interaction have been limited by small sample size and large number of potential interactions between genes. Several methods have been proposed to detect gene-gene interaction in a case control study. The penalized logistic regression (PLR), a variant of logistic regression with L2 regularization, is a parametric approach to detect gene-gene interaction. On the other hand, the Multifactor Dimensionality Reduction (MDR) is a nonparametric and genetic model-free approach to detect genotype combinations associated with disease risk.

METHODS

We compared the power of MDR and PLR for detecting two-way and three-way interactions in a case-control study through extensive simulations. We generated several interaction models with different magnitudes of interaction effect. For each model, we simulated 100 datasets, each with 200 cases and 200 controls and 20 SNPs. We considered a wide variety of models such as models with just main effects, models with only interaction effects or models with both main and interaction effects. We also compared the performance of MDR and PLR to detect gene-gene interaction associated with acute rejection(AR) in kidney transplant patients.

RESULTS

In this paper, we have studied the power of MDR and PLR for detecting gene-gene interaction in a case-control study through extensive simulation. We have compared their performances for different two-way and three-way interaction models. We have studied the effect of different allele frequencies on these methods. We have also implemented their performance on a real dataset. As expected, none of these methods were consistently better for all data scenarios, but, generally MDR outperformed PLR for more complex models. The ROC analysis on the real dataset suggests that MDR outperforms PLR in detecting gene-gene interaction on the real dataset.

CONCLUSION

As one might expect, the relative success of each method is context dependent. This study demonstrates the strengths and weaknesses of the methods to detect gene-gene interaction.

Towards a molecular risk map--recent advances on the etiology of inflammatory bowel disease

Recent advances have enabled a comprehensive understanding of the genetic architecture of inflammatory bowel disease (IBD) with over 30 identified and replicated disease loci. The pathophysiological consequences of disease gene variants in Crohn disease and ulcerative colitis, the two main subentities of IBD, so far are only understood on the single disease gene level, yet complex network analyses linking the individual risk factors into a molecular risk map are still missing. In this review, we will focus on recent pathways and cellular functions that emerged from the genetic studies (e.g. innate immunity, autophagy) and delineate the existence of shared (e.g. IL23R, IL12B) and unique (e.g. NOD2 for CD) risk factors for the disease subtypes. Ultimately, the defined molecular profiles may identify individuals at risk early in life and may serve as a guidance to administer personalized interventions for causative therapies and/or early targeted prevention strategies. Due to this comparatively advanced level of molecular understanding in the field, IBD may represent precedent also for future developments of individualized genetic medicine in other polygenic disorders in general.

High-throughput genetic mapping of mutants via quantitative single nucleotide polymorphism typing

Advances in next-generation sequencing technology have facilitated the discovery of single nucleotide polymorphisms (SNPs). Sequenom-based SNP-typing assays were developed for 1359 maize SNPs identified via comparative next-generation transcriptomic sequencing. Approximately 75% of these SNPs were successfully converted into genetic markers that can be scored reliably and used to generate a SNP-based genetic map by genotyping recombinant inbred lines from the intermated B73 x Mo17 population. The quantitative nature of Sequenom-based SNP assays led to the development of a time- and cost-efficient strategy to genetically map mutants via quantitative bulked segregant analysis. This strategy was used to rapidly map the loci associated with several dozen recessive mutants. Because a mutant can be mapped using as few as eight multiplexed sets of SNP assays on a bulk of as few as 20 mutant F(2) individuals, this strategy is expected to be widely adopted for mapping in many species.

Association mapping of cadmium, copper and hydrogen peroxide tolerance of roots and translocation capacities of cadmium and copper in Arabidopsis thaliana

Association mapping analysis of Cd, Cu and H (2)O (2) tolerance, judged by relative root length (RRL: % of root length in stress condition relative to that in control condition), and Cd and Cu translocation ratios (amount of metal in the shoot to the total) were performed using 90 accessions of Arabidopsis thaliana. Using 140 SNPs that were distributed across the genome, association mapping analysis was performed with a haploid setting by the Q + K method, which minimizes detection of false associations by combining the Q-matrix of the structured association (Q) with kinship (K) to control for the population structure. Six, five and five significant (-log (10)P-value is 1.3 > or =) linkages were detected between the SNPs and Cd, Cu and H(2)O(2) resistant RRLs, respectively. In addition, six significant linkages were identified with translocation capacities of Cd and Cu. Among those detected loci, two each of Cu and Cd tolerance RRLs were collocated with those of H(2)O(2) tolerance RRL, while one locus each was detected by Cu and Cd tolerance RRLs that collocated with their translocation ratios. These results suggested that these factors might partly explain the phenotypic variation of tolerance RRLs to Cd and Cu of Arabidopsis thaliana. Finally, using a different approach to analyze interactions between individual phenotypes, namely clustering analysis, we found an expected segregation of resistant SNPs (single-nucleotide polymorphisms) of the multiple RRLs in the typical accession groups carrying multiple traits. Almost none of the loci detected by association mapping analysis were linked to the loci of previously identified critical genes regulating the traits, suggesting that this could be useful to identify complex architecture of genetic factors determining variation among multiple accessions.

Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

The neuronal PAS domain 3 (NPAS3) gene encodes a neuronal transcription factor that is implicated in psychiatric disorders by the identification of a human chromosomal translocation associated with schizophrenia and a mouse knockout model with behavioural and hippocampal neurogenesis defects. To determine its contribution to the risk of psychiatric illness in the general population, we genotyped 70 single-nucleotide polymorphisms across the NPAS3 gene in 368 individuals with bipolar disorder, 386 individuals with schizophrenia and 455 controls. Modestly significant single-marker and global and individual haplotypes were identified in four discrete regions of the gene. The presence of both risk and protective haplotypes at each of these four regions indicated locus and allelic heterogeneity within NPAS3 and suggested a model whereby interactions between variants across the gene might contribute to susceptibility to illness. This was supported by predicting the most likely haplotype for each individual at each associated region and then calculating an NPAS3-mediated 'net genetic load' value. This value differed significantly from controls for both bipolar disorder (P=0.0000010) and schizophrenia (P=0.0000012). Logistic regression analysis also confirmed the combinatorial action of the four associated regions on disease risk. In addition, sensitivity/specificity plots showed that the extremes of the genetic loading distribution possess the greatest predictive power-a feature suggesting multiplicative allele interaction. These data add to recent evidence that the combinatorial analysis of a number of relatively small effect size haplotypes may have significant power to predict an individual's risk of a complex genetic disorder such as psychiatric illness.

Ensuring the safe use of genomic medicine in children

Several clinical guidelines recommend that genetic testing in children be limited to tests with immediate clinical benefit. However, use of genome risk profiling will not likely meet this requirement, as the benefits are anticipated to be years away. Children who are at higher risk, though, will benefit the most from early initiation of treatment or interventions. The shift in benefit from immediate to long-term benefit warrants a reevaluation of the current practices of testing in children. In this commentary, the authors advocate the use of genomic risk profiling to identify children at increased risk who would benefit from early intervention, but recognize that its integration in clinical practice for this population will require a more nuanced approach to delivery and follow-up. In particular, the importance of counseling, context, consent, communication, and follow-up in the delivery of genomic risk testing to children and adolescents is highlighted.

Dissection of genetic factors modulating fetal growth in cattle indicates a substantial role of the non-SMC condensin I complex, subunit G (NCAPG) gene

The increasing evidence of fetal developmental effects on postnatal life, the still unknown fetal growth mechanisms impairing offspring generated by somatic nuclear transfer techniques, and the impact on stillbirth and dystocia in conventional reproduction have generated increasing attention toward mammalian fetal growth. We identified a highly significant quantitative trait locus (QTL) affecting fetal growth on bovine chromosome 6 in a specific resource population, which was set up by consistent use of embryo transfer and foster mothers and, thus, enabled dissection of fetal-specific genetic components of fetal growth. Merging our data with results from other cattle populations differing in historical and geographical origin and with comparative data from human whole-genome association mapping suggests that a nonsynonymous polymorphism in the non-SMC condensin I complex, subunit G (NCAPG) gene, NCAPG c.1326T>G, is the potential cause of the identified QTL resulting in divergent bovine fetal growth. NCAPG gene expression data in fetal placentomes with different NCAPG c.1326T>G genotypes, which are in line with recent results about differential NCAPG expression in placentomes from studies on assisted reproduction techniques, indicate that the NCAPG locus may give valuable information on the specific mechanisms regulating fetal growth in mammals.

Neurotransmission-related genetic polymorphisms, negative affectivity traits, and gender predict tobacco abstinence symptoms across 44 days with and without nicotine patch

Genetic and personality trait moderators of tobacco abstinence-symptom trajectories were assessed in a highly controlled study. Based on evidence suggesting their importance in stress reactivity and smoking, moderators studied were serotonin transporter gene (5-HTTLPR) and dopamine D2 receptor gene (DRD2) polymorphisms and personality traits related to negative affect (NA). Smokers were randomly assigned to quit smoking with nicotine or placebo patches. Financial incentives resulted in 80% verified abstinence across the 44-day study. Individuals with 1 or 2 short alleles of 5-HTTLPR (S carriers) experienced larger increases in NA symptoms than did those without a short allele. Nicotine replacement therapy (NRT) alleviated anxiety only in S carriers. NRT reduced NA to a greater extent in DRD2 A1 carriers than in A2A2 individuals during the 1st 2 weeks of treatment (when on the 21-mg patch); however, A1 carriers experienced a renewal of NA symptoms when switched to the 7-mg patch and when off the patch, while A2A2 individuals continued to benefit from NRT. The results suggest that the effects of genotype and treatment may vary across different durations of abstinence, treatment doses, and genotypes.

The etiology of autoimmune thyroid disease: a story of genes and environment

Autoimmune thyroid diseases (AITDs), including Graves' disease (GD) and Hashimoto's thyroiditis (HT) are prevalent autoimmune diseases, affecting up to 5% of the general population. Autoimmune thyroid diseases arise due to complex interactions between environmental and genetic factors. Significant progress has been made in our understanding of the genetic and environmental triggers contributing to AITD. However, the interactions between genes and environment are yet to be defined. Among the major AITD susceptibility genes that have been identified and characterized is the HLA-DR gene locus, as well as non-MHC genes including the CTLA-4, CD40, PTPN22, thyroglobulin, and TSH receptor genes. The major environmental triggers of AITD include iodine, medications, infection, smoking, and possibly stress. Recent data on the genetic predisposition to AITD lead to novel putative mechanisms by which the genetic-environmental interactions may lead to the development of thyroid autoimmunity.

Research Actuality in the Genetics of Stroke

Stroke can be viewed as a paradigm for late-onset, complex polygenic diseases. There are two main clinical phenotypes for stroke: ischemic stroke, responsible for 80-90% of stroke events, and hemorrhagic stroke, responsible for the remaining 10-20%. Stroke may either be the outcome of a number of monogenic disorders or, more commonly, a polygenic multifactorial disease. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy (CADASIL), due to mutations in the Notch 3 gene, is the best example of monogenic pathology leading to stroke. The identification of individual causative mutations for polygenic stroke is problematic due to the complexity of such condition. The two main methods of genetic investigation are linkage analyses and association studies, each with advantages and limitations. Associations with polymorphisms in a variety of candidate genes have been investigated, including hemostatic genes, genes controlling homocystein metabolism, the angiotensin-converting enzyme gene, and the endothelial nitric oxide synthase gene. The combination of linkage and association approaches has led to the identification of the first putative gene associated with common polygenic stroke, PDE4D, mapped to chromosome 5q21. The biological revolution of the past years, spurred by the Human Genome Project, promises the advent of novel technologies supported by bioinformatics, which will transform the study of polygenic disorders such as stroke. Understanding the causes of stroke and its effect will allow definition of high-risk populations and make possible specific programs of primary and secondary prevention as well as new therapeutic approaches where prevention has failed.

Systems analysis of bone

The genetic variants contributing to variability in skeletal traits has been well studied, and several hundred QTLs have been mapped and several genes contributing to trait variation have been identified. However, many questions remain unanswered. In particular, it is unclear whether variation in a single gene leads to alterations in function. Bone is a highly adaptive system and genetic variants affecting one trait are often accompanied by compensatory changes in other traits. The functional interactions among traits, which is known as phenotypic integration, has been observed in many biological systems, including bone. Phenotypic integration is a property of bone that is critically important for establishing a mechanically functional structure that is capable of supporting the forces imparted during daily activities. In this paper, bone is reviewed as a system and primarily in the context of functionality. A better understanding of the system properties of bone will lead to novel targets for future genetic analyses and the identification of genes that are directly responsible for regulating bone strength. This systems analysis has the added benefit of leaving a trail of valuable information about how the skeletal system works. This information will provide novel approaches to assessing skeletal health during growth and aging and for developing novel treatment strategies to reduce the morbidity and mortality associated with fragility fractures.

Gene expression profiling as a tool for positional cloning of genes-shortcut or the longest way round

The identification of quantitative trait loci, QTL, in arthritis animal models is a straight forward process. However, to identify the underlying genes is a great challenge. One strategy frequently used, is to combine QTL analysis with genomic/proteomic screens. This has resulted in a number of publications where carefully performed genomic analyses present likely candidate genes for their respective QTL s. However, seldom the findings are reconnected to the QTL controlled phenotypes. In this review, we use our own data as an illustrative example that "very likely candidate genes" identified by genomic/proteomics is not necessarily the same as true QTL underlying genes.

Reporting 678 putative cSNPs from full-length enriched cDNA sequences of the Korean native pig

Sequences from the clones of full-length enriched cDNA libraries serve as valuable resources for functional genomic studies. We have analysed 1970 high-quality chromatograms (Phred value >or= 30) that were obtained from sequencing the 5' ends of brainstem, liver, neocortex and spleen clones derived from full-length enriched cDNA libraries from Korean native pigs. In addition, 50,000 pig expressed sequence tag (EST) sequence trace files were obtained from Genbank and combined with our sequencing information to facilitate SNP identification in silico. The process generated 8118 contigs, of which 239 included minimum one sequence from Korean native pig and contained 678 putative coding single nucleotide polymorphisms (cSNPs). Of these, 33 putative cSNPs were randomly selected for confirmatory analysis and validated using 20 pigs from four different breeds (Duroc, Landrace, Yorkshire, Korean native pig). Of the 33 putative cSNPs, 20 were confirmed (61%), which was similar to the frequency reported in other studies. We also identified 15 new cSNPs from the validation process, which were not detected by our in silico analysis. Our study shows that analysing genetically diverse pig breeds including the Korean native pig could serve as a useful strategy for generating a large number of cSNPs.

The oxytocin receptor (OXTR) contributes to prosocial fund allocations in the dictator game and the social value orientations task

BACKGROUND

Economic games observe social decision making in the laboratory that involves real money payoffs. Previously we have shown that allocation of funds in the Dictator Game (DG), a paradigm that illustrates costly altruistic behavior, is partially determined by promoter-region repeat region variants in the arginine vasopressin 1a receptor gene (AVPR1a). In the current investigation, the gene encoding the related oxytocin receptor (OXTR) was tested for association with the DG and a related paradigm, the Social Values Orientation (SVO) task.

METHODOLOGY/PRINCIPAL FINDINGS

Association (101 male and 102 female students) using a robust-family based test between 15 single tagging SNPs (htSNPs) across the OXTR was demonstrated with both the DG and SVO. Three htSNPs across the gene region showed significant association with both of the two games. The most significant association was observed with rs1042778 (p = 0.001). Haplotype analysis also showed significant associations for both DG and SVO. Following permutation test adjustment, significance was observed for 2-5 locus haplotypes (p<0.05). A second sample of 98 female subjects was subsequently and independently recruited to play the dictator game and was genotyped for the three significant SNPs found in the first sample. The rs1042778 SNP was shown to be significant for the second sample as well (p = 0.004, Fisher's exact test).

CONCLUSIONS

The demonstration that genetic polymorphisms for the OXTR are associated with human prosocial decision making converges with a large body of animal research showing that oxytocin is an important social hormone across vertebrates including Homo sapiens. Individual differences in prosocial behavior have been shown by twin studies to have a substantial genetic basis and the current investigation demonstrates that common variants in the oxytocin receptor gene, an important element of mammalian social circuitry, underlie such individual differences.

Identification of chromosomal regions associated with growth and carcass traits in an F(3) full sib intercross line originating from a cross of chicken lines divergently selected on body weight

An F(3) resource population originating from a cross between two divergently selected lines for high (D+ line) or low (D- line) body weight at 8-weeks of age (BW55) was generated and used for Quantitative Trait Locus (QTL) mapping. From an initial cross of two founder F(0) animals from D(+) and D(-) lines, progeny were randomly intercrossed over two generations following a full sib intercross line (FSIL) design. One hundred and seventy-five genome-wide polymorphic markers were employed in the DNA pooling and selective genotyping of F(3) to identify markers with significant effects on BW55. Fifty-three markers on GGA2, 5 and 11 were then genotyped in the whole F(3) population of 503 birds, where interval mapping with GridQTL software was employed. Eighteen QTL for body weight, carcass traits and some internal organ weights were identified. On GGA2, a comparison between 2-QTL vs. 1-QTL analysis revealed two separate QTL regions for body, feet, breast muscle and carcass weight. Given co-localization of QTL for some highly correlated traits, we concluded that there were 11 distinct QTL mapped. Four QTL localized to already mapped QTL from other studies, but seven QTL have not been previously reported and are hence novel and unique to our selection line. This study provides a low resolution QTL map for various traits and establishes a genetic resource for future fine-mapping and positional cloning in the advanced FSIL generations.

Positional identification of variants of Adamts16 linked to inherited hypertension

A previously reported blood pressure (BP) quantitative trait locus on rat Chromosome 1 was isolated in a short congenic segment spanning 804.6 kb. The 804.6 kb region contained only two genes, LOC306664 and LOC306665. LOC306664 is predicted to translate into A Disintegrin-like and Metalloproteinase with Thrombospondin Motifs-16 (Adamts16). LOC306665 is a novel gene. All predicted exons of both LOC306664 and LOC306665 were sequenced. Non-synonymous variants were identified in only one of these genes, LOC306664. These variants were naturally existing polymorphisms among inbred, outbred and wild rats. The full-length rat transcript of Adamts16 was detected in multiple tissues. Similar to ADAMTS16 in humans, expression of Adamts16 was prominent in the kidney. Renal transcriptome analysis suggested that a network of genes related to BP was differential between congenic and S rats. These genes were also differentially expressed between kidney cell lines with or without knock-down of Adamts16. Adamts16 is conserved between rats and humans. It is a candidate gene within the homologous region on human Chromosome 5, which is linked to systolic and diastolic BP in the Quebec Family Study. Multiple variants, including an Ala to Pro variant in codon 90 (rs2086310) of human ADAMTS16, were associated with human resting systolic BP (SBP). Replication study in GenNet confirmed the association of two variants of ADAMTS16 with SBP, including rs2086310. Overall, our report represents a high resolution positional cloning and translational study for Adamts16 as a candidate gene controlling BP.

Family-based mapping of quantitative trait loci in plant breeding populations with resistance to Fusarium head blight in wheat as an illustration

Traditional quantitative trait loci (QTL) mapping approaches are typically based on early or advanced generation analysis of bi-parental populations. A limitation associated with this methodology is the fact that mapping populations rarely give rise to new cultivars. Additionally, markers linked to the QTL of interest are often not immediately available for use in breeding and they may not be useful within diverse genetic backgrounds. Use of breeding populations for simultaneous QTL mapping, marker validation, marker assisted selection (MAS), and cultivar release has recently caught the attention of plant breeders to circumvent the weaknesses of conventional QTL mapping. The first objective of this study was to test the feasibility of using family-pedigree based QTL mapping techniques generally used with humans and animals within plant breeding populations (PBPs). The second objective was to evaluate two methods (linkage and association) to detect marker-QTL associations. The techniques described in this study were applied to map the well characterized QTL, Fhb1 for Fusarium head blight resistance in wheat (Triticum aestivum L.). The experimental populations consisted of 82 families and 793 individuals. The QTL was mapped using both linkage (variance component and pedigree-wide regression) and association (using quantitative transmission disequilibrium test, QTDT) approaches developed for extended family-pedigrees. Each approach successfully identified the known QTL location with a high probability value. Markers linked to the QTL explained 40-50% of the phenotypic variation. These results show the usefulness of a human genetics approach to detect QTL in PBPs and subsequent use in MAS.

Identification of quantitative trait loci for rice quality in a population of chromosome segment substitution lines

The demand for high quality rice represents a major issue in rice production. The primary components of rice grain quality include appearance, eating, cooking, physico-chemical, milling and nutritional qualities. Most of these traits are complex and controlled by quantitative trait loci (QTLs), so the genetic characterization of these traits is more difficult than that of traits controlled by a single gene. The detection and genetic identification of QTLs can provide insights into the genetic mechanisms underlying quality traits. Chromosome segment substitution lines (CSSLs) are effective tools used in mapping QTLs. In this study, we constructed 154 CSSLs from backcross progeny (BC(3)F(2)) derived from a cross between 'Koshihikari' (an Oryza sativa L. ssp. japonica variety) as the recurrent parent and 'Nona Bokra' (an O. sativa L. ssp. indica variety) as the donor parent. In this process, we carried out marker-assisted selection by using 102 cleaved amplified polymorphic sequence and simple sequence repeat markers covering most of the rice genome. Finally, this set of CSSLs was used to identify QTLs for rice quality traits. Ten QTLs for rice appearance quality traits were detected and eight QTLs concerned physico-chemical traits. These results supply the foundation for further genetic studies and breeding for the improvement of grain quality.

Novel transcripts discovered by mining genomic DNA from defined regions of bovine chromosome 6

BACKGROUND

Linkage analyses strongly suggest a number of QTL for production, health and conformation traits in the middle part of bovine chromosome 6 (BTA6). The identification of the molecular background underlying the genetic variation at the QTL and subsequent functional studies require a well-annotated gene sequence map of the critical QTL intervals. To complete the sequence map of the defined subchromosomal regions on BTA6 poorly covered with comparative gene information, we focused on targeted isolation of transcribed sequences from bovine bacterial artificial chromosome (BAC) clones mapped to the QTL intervals.

RESULTS

Using the method of exon trapping, 92 unique exon trapping sequences (ETS) were discovered in a chromosomal region of poor gene coverage. Sequence identity to the current NCBI sequence assembly for BTA6 was detected for 91% of unique ETS. Comparative sequence similarity search revealed that 11% of the isolated ETS displayed high similarity to genomic sequences located on the syntenic chromosomes of the human and mouse reference genome assemblies. Nearly a third of the ETS identified similar equivalent sequences in genomic sequence scaffolds from the alternative Celera-based sequence assembly of the human genome. Screening gene, EST, and protein databases detected 17% of ETS with identity to known transcribed sequences. Expression analysis of a subset of the ETS showed that most ETS (84%) displayed a distinctive expression pattern in a multi-tissue panel of a lactating cow verifying their existence in the bovine transcriptome.

CONCLUSION

The results of our study demonstrate that the exon trapping method based on region-specific BAC clones is very useful for targeted screening for novel transcripts located within a defined chromosomal region being deficiently endowed with annotated gene information. The majority of identified ETS represents unknown noncoding sequences in intergenic regions on BTA6 displaying a distinctive tissue-specific expression profile. However, their definite regulatory function has to be analyzed in further studies. The novel transcripts will add new sequence information to annotate a complete bovine genome sequence assembly, contribute to establish a detailed transcription map for targeted BTA6 regions and will also be helpful to dissect of the molecular and regulatory background of the QTL detected on BTA6.

Aggressive periodontitis is likely influenced by a few small effect genes

AIM

To evaluate the inheritance mode of aggressive periodontitis in a collection of families with a similar geographic origin.

MATERIALS AND METHODS

Segregation analysis was performed in pedigree data from 74 families by the use of the SEGREG program of SAGE v.5.4.2. Homogeneous no transmission, homogeneous Mendelian transmission, homogeneous general transmission, semi-general transmission and heterogeneous general transmission models were tested assuming the prevalence of aggressive periodontitis as 1% and no deviations from Hardy-Weinberg equilibrium. The parameters of the model were estimated by the method of maximum likelihood, which provides the overall ln (likelihood), -2ln and the AIC (Akaike's score) for each model. The likelihood ratio test (LRT) was used to compare each model against a fully general model (p>0.05).

RESULTS

The most parsimonious mode of inheritance was the semi-general transmission model that allows the heterozygote transmission probability to vary.

CONCLUSION

This result provides strong support for the hypothesis that genetic factors play a role in aggressive periodontitis and that a few loci, each with relatively small effects, contribute to aggressive periodontitis, with or without interaction with environmental factors.

A new PTGDR promoter polymorphism in a population of children with asthma

Recently, functional genetic variants of the PTGDR gene have been associated with asthma. The objective of this work was to study polymorphisms of the promoter region of PTGDR and their haplotype and diplotype combinations in a Spanish population of children with asthma. In this study, 200 Caucasian individuals were included. Asthma was specialist-physician diagnosed according to the ATS criteria. The polymorphisms were analyzed by direct sequencing. In the study, the new polymorphism (-613C > T) in the promoter region of PTGDR was analyzed. The CT genotype was more common in controls (17%) than in patients with asthma (1%) (p-value = 0.0003; OR, 0.057; 95% CI, 0.007-0.441). The CCCT CCCC diplotype (promoter positions -613, -549, -441, and -197) was more frequent in the group of patients with asthma [Fisher's p-value = 0.012; OR, 10.24; 95% CI (1.25-83.68)]; this diplotype is unambiguous. To our knowledge, this is the first study of -613C > T PTGDR polymorphism in patients. This analysis provides more complete information on influence of diplotype combinations of PTGDR polymorphisms in asthma.

Novel strategy using F1-congenic mice for validation of QTLs: studies at the proximal chromosome 10 atherosclerosis susceptibility locus

OBJECTIVE

We have previously identified a quantitative trait locus (QTL) for atherosclerosis susceptibility on proximal chromosome 10 (Chr10) (Ath11) in independent crosses of FVB and C57BL/6 (B6) mice on the apolipoprotein E (ApoE-/-) and LDL receptor (LDLR-/-) deficient backgrounds. The aims of the current study were to (1) test a novel strategy for validating QTLs using interval-specific congenic strains that were heterozygous (F1) across the genome, (2) validate the Chr10 QTL, and (3) to assess whether the phenotype is transferable by bone marrow transplantation.

METHODS AND RESULTS

We generated Chr10 (0 to 21 cM) interval-specific mice on the F1.ApoE-/- background by crossing congenic FVB.ApoE-/-Chr10(B6/FVB) with B6.ApoE-/-, and B6.ApoE-/-Chr10(B6/FVB) with FVB.ApoE-/- mice. Lesion size was significantly larger in the resultant F1.ApoE-/-Chr10(FVB/FVB) mice compared to F1.ApoE-/-Chr10(B6/FVB) and F1.ApoE-/-Chr10(B6/B6) mice, validating the Chr10 QTL. The effect of the congenic interval was more robust on the F1.ApoE-/- than on the FVB.ApoE-/- and B6.ApoE-/- backgrounds. Bone marrow transplantation in congenic mice showed that the effect of the proximal Chr10 interval was not transferable by bone marrow-derived cells.

CONCLUSIONS

A novel strategy of congenic strains on an F1 background proved useful to validate an atherosclerosis susceptibility QTL on mouse proximal Chr10.

What are genes "for" or where are traits "from"? What is the question?

For at least a century it has been known that multiple factors play a role in the development of complex traits, and yet the notion that there are genes "for" such traits, which traces back to Mendel, is still widespread. In this paper, we illustrate how the Mendelian model has tacitly encouraged the idea that we can explain complexity by reducing it to enumerable genes. By this approach many genes associated with simple as well as complex traits have been identified. But the genetic architecture of biological traits, or how they are made, remains largely unknown. In essence, this reflects the tension between reductionism as the current "modus operandi" of science, and the emerging knowledge of the nature of complex traits. Recent interest in systems biology as a unifying approach indicates a reawakened acceptance of the complexity of complex traits, though the temptation is to replace "gene for" thinking by comparably reductionistic "network for" concepts. Both approaches implicitly mix concepts of variants and invariants in genetics. Even the basic question is unclear: what does one need to know to "understand" the genetic basis of complex traits? New operational ideas about how to deal with biological complexity are needed.

A random forest approach to the detection of epistatic interactions in case-control studies

BACKGROUND

The key roles of epistatic interactions between multiple genetic variants in the pathogenesis of complex diseases notwithstanding, the detection of such interactions remains a great challenge in genome-wide association studies. Although some existing multi-locus approaches have shown their successes in small-scale case-control data, the "combination explosion" course prohibits their applications to genome-wide analysis. It is therefore indispensable to develop new methods that are able to reduce the search space for epistatic interactions from an astronomic number of all possible combinations of genetic variants to a manageable set of candidates.

RESULTS

We studied case-control data from the viewpoint of binary classification. More precisely, we treated single nucleotide polymorphism (SNP) markers as categorical features and adopted the random forest to discriminate cases against controls. On the basis of the gini importance given by the random forest, we designed a sliding window sequential forward feature selection (SWSFS) algorithm to select a small set of candidate SNPs that could minimize the classification error and then statistically tested up to three-way interactions of the candidates. We compared this approach with three existing methods on three simulated disease models and showed that our approach is comparable to, sometimes more powerful than, the other methods. We applied our approach to a genome-wide case-control dataset for Age-related Macular Degeneration (AMD) and successfully identified two SNPs that were reported to be associated with this disease.

CONCLUSION

Besides existing pure statistical approaches, we demonstrated the feasibility of incorporating machine learning methods into genome-wide case-control studies. The gini importance offers yet another measure for the associations between SNPs and complex diseases, thereby complementing existing statistical measures to facilitate the identification of epistatic interactions and the understanding of epistasis in the pathogenesis of complex diseases.

Genetic interactions between transcription factors cause natural variation in yeast

Our understanding of the genetic basis of phenotypic diversity is limited by the paucity of examples in which multiple, interacting loci have been identified. We show that natural variation in the efficiency of sporulation, the program in yeast that initiates the sexual phase of the life cycle, between oak tree and vineyard strains is due to allelic variation between four nucleotide changes in three transcription factors: IME1, RME1, and RSF1. Furthermore, we identified that selection has shaped quantitative variation in yeast sporulation between strains. These results illustrate how genetic interactions between transcription factors are a major source of phenotypic diversity within species.

Quantitative trait loci, genes, and polymorphisms that regulate bone mineral density in mouse

This is an in silico analysis of data available from genome-wide scans. Through analysis of QTL, genes and polymorphisms that regulate BMD, we identified 82 BMD QTL, 191 BMD-associated (BMDA) genes, and 83 genes containing known BMD-associated polymorphisms (BMDAP). The catalogue of all BMDA/BMDAP genes and relevant literatures are provided. In total, there are substantially more BMDA/BMDAP genes in regions of the genome where QTL have been identified than in non-QTL regions. Among 191 BMDA genes and 83 BMDAP genes, 133 and 58 are localized in QTL regions, respectively. The difference was still noticeable for the chromosome distribution of these genes between QTL and non-QTL regions. These results have allowed us to generate an integrative profile of QTL, genes, polymorphisms that determine BMD. These data could facilitate more rapid and comprehensive identification of causal genes underlying the determination of BMD in mouse and provide new insights into how BMD is regulated in humans.

A first-generation microsatellite-based genetic linkage map of the Siberian jay (Perisoreus infaustus): insights into avian genome evolution

BACKGROUND

Genomic resources for the majority of free-living vertebrates of ecological and evolutionary importance are scarce. Therefore, linkage maps with high-density genome coverage are needed for progress in genomics of wild species. The Siberian jay (Perisoreus infaustus; Corvidae) is a passerine bird which has been subject to lots of research in the areas of ecology and evolutionary biology. Knowledge of its genome structure and organization is required to advance our understanding of the genetic basis of ecologically important traits in this species, as well as to provide insights into avian genome evolution.

RESULTS

We describe the first genetic linkage map of Siberian jay constructed using 117 microsatellites and a mapping pedigree of 349 animals representing five families from a natural population breeding in western Finland from the years 1975 to 2006. Markers were resolved into nine autosomal and a Z-chromosome-specific linkage group, 10 markers remaining unlinked. The best-position map with the most likely positions of all significantly linked loci had a total sex-average size of 862.8 cM, with an average interval distance of 9.69 cM. The female map covered 988.4 cM, whereas the male map covered only 774 cM. The Z-chromosome linkage group comprised six markers, three pseudoautosomal and three sex-specific loci, and spanned 10.6 cM in females and 48.9 cM in males. Eighty-one of the mapped loci could be ordered on a framework map with odds of >1000:1 covering a total size of 809.6 cM in females and 694.2 cM in males. Significant sex specific distortions towards reduced male recombination rates were revealed in the entire best-position map as well as within two autosomal linkage groups. Comparative mapping between Siberian jay and chicken anchored 22 homologous loci on 6 different linkage groups corresponding to chicken chromosomes Gga1, 2, 3, 4, 5, and Z. Quite a few cases of intra-chromosomal rearrangements within the autosomes and three cases of inter-chromosomal rearrangement between the Siberian jay autosomal linkage groups (LG1, LG2 and LG3) and the chicken sex chromosome GgaZ were observed, suggesting a conserved synteny, but changes in marker order, within autosomes during about 100 million years of avian evolution.

CONCLUSION

The constructed linkage map represents a valuable resource for intraspecific genomics of Siberian jay, as well as for avian comparative genomic studies. Apart from providing novel insights into sex-specific recombination rates and patterns, the described maps - from a previously genomically uncharacterized superfamily (Corvidae) of passerine birds - provide new insights into avian genome evolution. In combination with high-resolution data on quantitative trait variability from the study population, they also provide a foundation for QTL-mapping studies.

A systematic strategy for the discovery of candidate genes responsible for phenotypic variation

It is increasingly common to combine genome-wide expression data with quantitative trait mapping data to aid in the search for sequence polymorphisms responsible for phenotypic variation. By joining these complex but different data types at the level of the biological pathway, we can take advantage of existing biological knowledge to systematically identify possible mechanisms of genotype-phenotype interaction. With the development of web services and workflows, this process can be made rapid and systematic. Our methodology was applied to a use case of resistance to African trypanosomiasis in mice. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://www.myexperiment.org/users/43/workflows .

Predicting Type 1 Diabetes Candidate Genes using Human Protein-Protein Interaction Networks

Background

Proteins directly interacting with each other tend to have similar functions and be involved in the same cellular processes. Mutations in genes that code for them often lead to the same family of disease phenotypes. Efforts have been made to prioritize positional candidate genes for complex diseases utilize the protein-protein interaction (PPI) information. But such an approach is often considered too general to be practically useful for specific diseases.

Results

In this study we investigate the efficacy of this approach in type 1 diabetes (T1D). 266 known disease genes, and 983 positional candidate genes from the 18 established linkage loci of T1D, are compiled from the T1Dbase (http://t1dbase.org). We found that the PPI network of known T1D genes has distinct topological features from others, with significantly higher number of interactions among themselves even after adjusting for their high network degrees (p<1e-5). We then define those positional candidates that are first degree PPI neighbours of the 266 known disease genes to be new candidate disease genes. This leads to a list of 68 genes for further study. Cross validation using the known disease genes as benchmark reveals that the enrichment is ~17.1 fold over random selection, and ~4 fold better than using the linkage information alone. We find that the citations of the new candidates in T1D-related publications are significantly (p<1e-7) more than random, even after excluding the co-citation with the known disease genes; they are significantly over-represented (p<1e-10) in the top 30 GO terms shared by known disease genes. Furthermore, sequence analysis reveals that they contain significantly (p<0.0004) more protein domains that are known to be relevant to T1D. These findings provide indirect validation of the newly predicted candidates.

Conclusion

Our study demonstrates the potential of the PPI information in prioritizing positional candidate genes for T1D.

Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: methodological considerations

INTRODUCTION

Genes play a well-documented role in determining normal cognitive function. This paper focuses on reviewing strategies for the identification of common genetic variation in genes that modulate normal and abnormal cognition with a genome-wide association scan (GWAS). GWASs make it possible to survey the entire genome to discover important but unanticipated genetic influences.

METHODS

The use of a quantitative phenotype in combination with a GWAS provides many advantages over a case-control design, both in power and in physiological understanding of the underlying cognitive processes. We review the major features of this approach, and show how, using a General Linear Model method, the contribution of each Single Nucleotide Polymorphism (SNP) to the phenotype is determined, and adjustments then made for multiple tests. An example of the strategy is presented, in which fMRI measures of cortical inefficiency while performing a working memory task are used as the quantitative phenotype. We estimate power under different effect sizes (10-30%) and variations in allelic frequency for a Quantitative Trait (QT) (10-20%), and compare them to a case-control design with an Odds Ratio (OR) of 1.5, showing how a QT approach is superior to a traditional case-control. In the presented example, this method identifies putative susceptibility genes for schizophrenia which affect prefrontal efficiency and have functions related to cell migration, forebrain development and stress response.

CONCLUSION

The use of QT as phenotypes provide increased statistical power over categorical association approaches and when combined with a GWAS creates a strategy for identification of unanticipated genes that modulate cognitive processes and cognitive disorders.

Silent (synonymous) SNPs: should we care about them?

One of the surprising findings of the Human Genome Project was that single nucleotide polymorphisms (SNPs), which, by definition, have a minor allele frequency greater than 1%, occur at higher rates than previously suspected. When occurring in the gene coding regions, SNPs can be synonymous (i.e., not causing a change in the amino acid) or nonsynonymous (when the amino acid is altered). It has long been assumed that synonymous SNPs are inconsequential, as the primary sequence of the protein is retained. A number of studies have questioned this assumption over the last decade, showing that synonymous mutations are also under evolutionary pressure and they can be implicated in disease. More importantly, several of the mechanisms by which synonymous mutations alter the structure, function, and expression level of proteins are now being elucidated. Studies have demonstrated that synonymous polymorphisms can affect messenger RNA splicing, stability, and structure as well as protein folding. These changes can have a significant effect on the function of proteins, change cellular response to therapeutic targets, and often explain the different responses of individual patients to a certain medication.

High-throughput methods for SNP genotyping

Single nucleotide polymorphisms (SNPs) are ideal markers for identifying genes associated with complex diseases for two main reasons. Firstly, SNPs are densely located on the human genome at about one SNP per approximately 500-1,000 base pairs. Secondly, a large number of commercial platforms are available for semiautomated or fully automated SNP genotyping. These SNP genotyping platforms serve different purposes since they differ in SNP selection, reaction chemistry, signal detection, throughput, cost, and assay flexibility. This chapter aims to give an overview of some of these platforms by explaining the technologies behind each platform and identifying the best application scenarios for each platform through cross-comparison. The readers may delve into more technical details in the following chapters.

Genetic testing for atherosclerosis risk: inevitability or pipe dream?

Family history is a risk factor for coronary artery disease (CAD). However, defining this risk at the DNA level has been elusive. In 2007, four genome-wide association studies reported a strong association between CAD and a region on chromosome 9p21. The high-risk genotype was identified in up to 30% of individuals, creating the potential for a clinical genetic test to assist in the calculation of a patient's CAD risk. However, the reported effect size of the association is modest (OR of approximately 1.3). The present paper examines the feasibility of including DNA tests in CAD risk prediction algorithms. The greatest contribution from the 9p21 association is likely yet to come, as further studies identify the mechanistic basis for the association, possibly leading to additional insights into the progression, prevention and treatment of CAD.

Ashkenazi Jewish centenarians do not demonstrate enrichment in mitochondrial haplogroup J

Background

Association of mitochondrial haplogroup J with longevity has been reported in several population subgroups. While studies from northern Italy and Finland, have described a higher frequency of haplogroup J among centenarians in comparison to non-centenarian, several other studies could not replicate these results and suggested various explanations for the discrepancy.

Methodology/Principal Findings

We have evaluated haplogroup frequencies among Ashkenazi Jewish centenarians using two different sets of matched controls. No difference was observed in the haplogroup J frequencies between the centenarians or either matched control group, despite adequate statistical power to detect such a difference. Furthermore, the lack of association was robust to population substructure in the Ashkenazi Jewish population. Given this discrepancy with the previous reported associations in the northern Italian and the Finnish populations, we conducted re-analysis of these previously published data, which supported one of several possible explanations: i) inadequate matching of cases and controls; ii) inadequate adjustment for multiple comparison testing; iii) cryptic population stratification.

Conclusions/Significance

There does not exist a universal association of mitochondrial haplogroup J with longevity across all population groups. Reported associations in specialized populations may reflect genetic or other interactions specific to those populations or else cryptic confounding influences, such as inadequate matching attributable to population substructure, which are of general relevance to all studies of the possible association of mitochondrial DNA haplogroups with common complex phenotypes.

A critical analysis of production-associated DNA polymorphisms in the genes of cattle, goat, sheep, and pig

Increasing productivity is one of the main objectives in animal production. Traditional breeding methods have led to increased gains in some traits but gains are not easily attainable in traits with low heritabilities. Exploiting the genetic variations underlying desired phenotypes is the goal of today's animal producers. Such positive genetic variants must, however, be known before possible application. Consequently, candidate genes of traits of interest have been searched for possible relationships with such traits or to explain reported quantitative trait loci (QTL) for such traits. DNA variants or polymorphisms have been identified in many such genes and their relationships with production traits determined. However, only a few genes have been evaluated, given the wealth of information on reported QTL for production traits, and in most cases genes are only partially investigated. This review presents available information on DNA variants for production traits and discusses steps that are required for effective utilization of this information for successful marker-assisted selection programs.

Analysis of the individual and aggregate genetic contributions of previously identified serine peptidase inhibitor Kazal type 5 (SPINK5), kallikrein-related peptidase 7 (KLK7), and filaggrin (FLG) polymorphisms to eczema risk

BACKGROUND

Polymorphisms in the serine protease inhibitor gene serine peptidase inhibitor Kazal type 5 (SPINK5) and the serine protease kallikrein-related peptidase 7 gene (KLK7) appear to confer risk to eczema in some cohorts, but these findings have not been widely replicated. These genes encode proteins thought to be involved in the regulation of posttranslation processing of filaggrin (FLG), the strongest identified genetic risk factor for eczema to date.

OBJECTIVES

We sought to clarify the individual risk of eczema conferred by the SPINK5 polymorphism rs2303067 (Glu420Lys) and a previously described insertion in the 3' untranslated region of KLK7 and to examine potential epistatic effects between these variants and FLG mutations.

METHODS

Initially, we examined the effects of these polymorphisms and FLG in 486 unrelated patients from a German family-based study, an additional 287 German patients, and 418 unrelated Irish/English patients with eczema (n for 3 genes studied = 1191 vs 4544 control subjects). We then additionally studied the SPINK5 polymorphism and FLG mutations in 1583 patients with eczema from the Avon Longitudinal Study of Parents and Children cohort (sample size for 2 genes studied = 2774 vs 10,607 control subjects).

RESULTS

No association was seen with the SPINK5 or KLK7 variants in the case-control analysis; however, a weaker effect was observed for the SPINK5 variant with maternal transmission in the family-based study. No interactions were seen between the polymorphisms in KLK7, SPINK5, and FLG.

CONCLUSION

The SPINK5 420LysSer mutation confers a risk of eczema when maternally inherited but is not a major eczema risk factor. The KLK7 insertion appears to confer no risk of eczema. We found no interaction between the SPINK5 risk allele or the putative KLK7 risk allele and FLG mutations.

Joint genetic susceptibility to type 1 diabetes and autoimmune thyroiditis: from epidemiology to mechanisms

Type 1 diabetes (T1D) and autoimmune thyroid diseases (AITD) frequently occur together within families and in the same individual. The co-occurrence of T1D and AITD in the same patient is one of the variants of the autoimmune polyglandular syndrome type 3 [APS3 variant (APS3v)]. Epidemiological data point to a strong genetic influence on the shared susceptibility to T1D and AITD. Recently, significant progress has been made in our understanding of the genetic association between T1D and AITD. At least three genes have been confirmed as major joint susceptibility genes for T1D and AITD: human leukocyte antigen class II, cytotoxic T-lymphocyte antigen 4 (CTLA-4), and protein tyrosine phosphatase non-receptor type 22. Moreover, the first whole genome linkage study has been recently completed, and additional genes will soon be identified. Not unexpectedly, all the joint genes for T1D and AITD identified so far are involved in immune regulation, specifically in the presentation of antigenic peptides to T cells. One of the lessons learned from the analysis of the joint susceptibility genes for T1D and AITD is that subset analysis is a key to dissecting the etiology of complex diseases. One of the best demonstrations of the power of subset analysis is the CTLA-4 gene in T1D. Although CTLA-4 showed very weak association with T1D, when analyzed in the subset of patients with both T1D and AITD, the genetic effect of CTLA-4 was significantly stronger. Gene-gene and genetic-epigenetic interactions most likely play a role in the shared genetic susceptibility to T1D and AITD. Dissecting these mechanisms will lead to a better understanding of the etiology of T1D and AITD, as well as autoimmunity in general.

Association study of tryptophan hydroxylase 1 and arylalkylamine N-acetyltransferase polymorphisms with adolescent idiopathic scoliosis in Han Chinese

STUDY DESIGN

A genetic association study of tryptophan hydroxylase 1 gene (TPH1) and arylalkylamine N-acetyltransferase gene(AANAT) with adolescent idiopathic scoliosis (AIS) in Han Chinese.

OBJECTIVE

To access whether TPH1 and AANAT polymorphisms are associated with the predisposition, gender, and/or severity of AIS.

SUMMARY OF BACKGROUND DATA

Studies have shown that AIS is a multifactorial inheritance disease, but the etiology is still unknown. In addition, several lines of evidence show that melatonin deficiency is closely associated with AIS, although there are still doubts and debates. Some polymorphisms in TPH1 and AANAT, the genes of 2 critical enzymes involved in melatonin biosynthesis, may contribute to variability of melatonin production in pineal glands.

METHODS

We genotyped 16 reported single nuclear polymorphisms (SNPs) present in TPH1 and AANAT in 103 AIS patients and 108 controls with matched sex and age. The data of 6 SNPs with minor allele frequence (MAF) above 5% were analyzed by the allelic and genotypic association analysis, the genotype-phenotype (gender and Cobb angle) association analysis, and the haplotype analysis.

RESULTS

The single SNP analysis showed that rs10488682, located in the promoter region of TPH1, was related with the occurrence of AIS (P < 0.05). No SNP was found to be correlated with gender or Cobb angle. Two makers (rs8176799 and rs2108977) in TPH1 were found to be in strong LD [ D' = 1.0 (95% CI, 0.9-1.0), gamma = 0.501, LOD = 18.93] in the controls. Both global haplotype analysis and individual haplotype analysis showed that there was no haplotype significantly associated with AIS in this LD block.

CONCLUSION

TPH1 polymorphisms were associated with AIS but not with gender and Cobb angle in AIS patients. AANAT polymorphisms were not associated with AIS. These results suggested that TPH1 was an AIS predisposition gene, and there was a close relationship between the dyssynthesis of melatonin and AIS.