Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

Genome-wide analysis of mammalian promoter architecture and evolution

Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a welldefined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

Genome-wide linkage scan for loci influencing plasma triglycerides

Background: Plasma triglyceride concentration is known to be a significant risk factor for cardiovascular disease (CVD). Previous studies have found that the level of triglycerides is strongly influenced by genetic factors. Methods: To identify quantitative trait loci influencing triglycerides, we conducted a genome-wide linkage scan on data from 485 Australian adult dizygotic twin pairs. Prior to linkage analysis, triglyceride values were adjusted for the effects of covariates including age, sex, time since last meal, time of blood collection (CT) and time to plasma separation. Results: The heritability estimate for ln(triglyceride) adjusted for all above fixed effects was 0.49. The highest multipoint LOD score observed was 2.94 (genome-wide p=0.049) on chromosome 7 (at 65cM). This 7p region contains several candidate genes. Two other regions with suggestive multipoint LOD scores were also identified on chromosome 4 (LOD score=2.26 at 62cM) and chromosome X (LOD score=2.01 at 81cM). Conclusions: The linkage peaks found represent newly identified regions for more detailed study, in particular the significant linkage observed on chromosome 7p13. \ (c) 2006 Elsevier B.V. All rights reserved.

Genome-wide analysis identifies a general requirement for polarity proteins in endocytic traffic

In a genome-wide RNA-mediated interference screen for genes required in membrane traffic - including endocytic uptake, recycling from endosomes to the plasma membrane, and secretion - we identified 168 candidate endocytosis regulators and 100 candidate secretion regulators. Many of these candidates are highly conserved among metazoans but have not been previously implicated in these processes. Among the positives from the screen, we identified PAR-3, PAR-6, PKC-3 and CDC-42, proteins that are well known for their importance in the generation of embryonic and epithelial-cell polarity. Further analysis showed that endocytic transport in Caenorhabditis elegans coelomocytes and human HeLa cells was also compromised after perturbation of CDC-42/Cdc42 or PAR-6/Par6 function, indicating a general requirement for these proteins in regulating endocytic traffic. Consistent with these results, we found that tagged CDC-42/Cdc42 is enriched on recycling endosomes in C. elegans and mammalian cells, suggesting a direct function in the regulation of transport.

Genome-wide Study of Oral Cavity and Pharyngeal Cancer

Peer reviewed

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk

Development and application of sensitive genome-wide platforms to study the genetic and epigenetic (DNA methylation) makeup of gametes and early bovine embryos

Pour ce projet, nous avons développé une plateforme pour l’analyse pangénomique de la méthylation de l’ADN chez le bovin qui est compatible avec des échantillons de petites tailles. Cet outil est utilisé pour étudier les caractéristiques génétiques et épigénétiques (méthylation de l’ADN) des gamètes soumis aux procédures de procréation médicalement assisitée et des embryons précoces. Dans un premier temps, une plateforme d’analyse de biopuces spécifiques pour l’étude de la méthylation de l’ADN chez l’espèce bovine a été développée. Cette plateforme a ensuite été optimisée pour produire des analyses pangénomiques de méthylation de l’ADN fiables et reproductibles à partir d’échantillons de très petites tailles telle que les embryons précoces (≥ 10 ng d’ADN a été utilisé, ce qui correspond à 10 blastocystes en expansion). En outre, cet outil a permis d’évaluer de façon simultanée la méthylation de l’ADN et le transcriptome dans le même échantillon, fournissant ainsi une image complète des profils génétiques et épigénétiques (méthylation de l’ADN). Comme preuve de concept, les profils comparatifs de méthylation de l’ADN spermatique et de blastocystes bovins ont été analysés au niveau de l’ensemble du génome. Dans un deuxième temps, grâce à cette plateforme, les profils globaux de méthylation de l’ADN de taureaux jumeaux monozygotes (MZ) ont été analysés. Malgré qu’ils sont génétiquement identiques, les taureaux jumeaux MZ ont des descendants avec des performances différentes. Par conséquent, l’hypothèse que le profil de méthylation de l’ADN spermatique de taureaux jumeaux MZ est différent a été émise. Dans notre étude, des différences significatives entre les jumeaux MZ au niveau des caractéristiques de la semence ainsi que de la méthylation de l’ADN ont été trouvées, chacune pouvant contribuer à l’obtention de performances divergentes incongrues des filles engendrées par ces jumeaux MZ. Dans la troisième partie de ce projet, la même plateforme a été utilisée pour découvrir les impacts d’une supplémentation à forte concentration en donneur de méthyle universel sur les embryons précoces bovins. La supplémentation avec de grandes quantités d’acide folique (AF) a été largement utilisée et recommandée chez les femmes enceintes pour sa capacité bien établie à prévenir les malformations du tube neural chez les enfants. Cependant, plus récemment, plusieurs études ont rapporté des effets indésirables de l’AF utilisé à des concentrations élevées, non seulement sur le développement de l’embryon, mais aussi chez les adultes. Au niveau cellulaire, l’AF entre dans le métabolisme monocarboné, la seule voie de production de S-adénosyl méthionine (SAM), un donneur universel de groupements méthyles pour une grande variété de biomolécules, y compris l’ADN. Par conséquent, pour résoudre cette controverse, une forte dose de SAM a été utilisée pour traiter des embryons produits in vitro chez le bovin. Ceci a non seulement permis d’influencer le phénotype des embryons précoces, mais aussi d’avoir un impact sur le transcriptome et le méthylome de l’ADN. En somme, le projet en cours a permis le développement d’une plateforme d’analyse de la méthylation de l’ADN à l’échelle du génome entier chez le bovin à coût raisonnable et facile à utiliser qui est compatible avec les embryons précoces. De plus, puisque c’est l’une des premières études de ce genre en biologie de la reproduction bovine, ce projet avait trois objectifs qui a donné plusieurs nouveaux résultats, incluant les profils comparatifs de méthylation de l’ADN au niveau : i) blastocystes versus spermatozoïdes ; ii) semence de taureaux jumeaux MZ et iii) embryons précoces traités à de fortes doses de SAM versus des embryons précoces non traités.

Nonparametric Evaluation of Quantitative Traits in Population-Based Association Studies when the Genetic Model is Unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

Genome-wide copy number variation (CNV) detection in Nelore cattle reveals highly frequent variants in genome regions harboring QTLs affecting production traits.

Background: Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance. Results: Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively. Conclusions: Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.

Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Abstract Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10−22). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10−34). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

The obesity-associated polymorphisms FTO rs9939609 and MC4R rs17782313 and endometrial cancer risk in non-Hispanic white women

Overweight and obesity are strongly associated with endometrial cancer. Several independent genome-wide association studies recently identified two common polymorphisms, FTO rs9939609 and MC4R rs17782313, that are linked to increased body weight and obesity. We examined the association of FTO rs9939609 and MC4R rs17782313 with endometrial cancer risk in a pooled analysis of nine case-control studies within the Epidemiology of Endometrial Cancer Consortium (E2C2). This analysis included 3601 non-Hispanic white women with histologically-confirmed endometrial carcinoma and 5275 frequency-matched controls. Unconditional logistic regression models were used to assess the relation of FTO rs9939609 and MC4R rs17782313 genotypes to the risk of endometrial cancer. Among control women, both the FTO rs9939609 A and MC4R rs17782313 C alleles were associated with a 16% increased risk of being overweight (p = 0.001 and p = 0.004, respectively). In case-control analyses, carriers of the FTO rs9939609 AA genotype were at increased risk of endometrial carcinoma compared to women with the TT genotype [odds ratio (OR) = 1.17; 95% confidence interval (CI): 1.03–1.32, p = 0.01]. However, this association was no longer apparent after adjusting for body mass index (BMI), suggesting mediation of the gene-disease effect through body weight. The MC4R rs17782313 polymorphism was not related to endometrial cancer risk (per allele OR = 0.98; 95% CI: 0.91–1.06; p = 0.68). FTO rs9939609 is a susceptibility marker for white non-Hispanic women at higher risk of endometrial cancer. Although FTO rs9939609 alone might have limited clinical or public health significance for identifying women at high risk for endometrial cancer beyond that of excess body weight, further investigation of obesity-related genetic markers might help to identify the pathways that influence endometrial carcinogenesis.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

Molecular genetics of migraine

Migraine is a common neurological disorder with a significantly heritable component. It is a complex disease and despite numerous molecular genetic studies, the exact pathogenesis causing the neurological disturbance remains poorly understood. Although several known molecular mechanisms have been associated with an increased risk for developing migraine, there remains significant scope for future studies. The majority of studies have investigated the most plausible candidate genes involved in common migraine pathogenesis utilising criteria that takes into account a combination of physiological functionality in conjunction with regions of genomic association. Thus, far genes involved in neurological, vascular or hormonal pathways have been identified and investigated on this basis. Genome-wide association studies (GWAS) studies have helped to identify novel regions that may be associated with migraine and have aided in providing the basis for further molecular investigations. However, further studies utilising sequencing technologies are required to characterise the genetic basis for migraine.