Dissection of a quantitative trait locus for genetic hypertension on rat chromosome 10.

We have previously identified a locus on rat chromosome 10 as carrying a major hypertension gene, BP/SP-1. The 100:1 odds support interval for this gene extended over a 35-centimorgan (cM) region of the chromosome that included the angiotensin I-converting enzyme (ACE) locus as demonstrated in a cross between the stroke-prone spontaneously hypertensive rat (SHRSPHD) and the normotensive Wistar-Kyoto (WKY-0HD) rat. Here we report on the further characterization of BP/SP-1, using a congenic strain, WKY-1HD. WKY-1HD animals carry a 6-cM chromosomal fragment genotypically identical with SHRSPHD on chromosome 10, 26 cM away from the ACE locus. Higher blood pressures in the WKY-1HD strain compared with the WKY-0HD strain, as well as absence of linkage of the chromosome 10 region to blood pressure in an F2 (WKY-1HD x SHRSPHD) population suggested the existence of a quantitative trait locus, termed BP/SP-1a, that lies within the SHRSP-congenic region in WKY-1HD. Linkage analysis in the F2 (WKY-0HD x SHRSPHD) cross revealed that BP/SP-1a is linked to basal blood pressure, whereas a second locus on chromosome 10, termed BP/SP-1b, that maps closer to the ACE locus cosegregates predominantly with blood pressure after exposure to excess dietary NaCl. Thus, we hypothesize that the previously reported effect of BP/SP-1 represents a composite phenotype that can be dissected into at least two specific components on the basis of linkage data and congenic experimentation. One of the loci identified, BP/SP-1a, represents the most precisely mapped locus affecting blood pressure that has so far been characterized by random-marker genome screening.

Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Sustainable deployment of QTLs conferring quantitative resistance to crops: first lessons from a stochastic model

International audience

Prediction of IBD based on population history for fine gene mapping

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10-8) and three variants reported as suggestive (P<5×10-7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10-9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10-9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10-8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma. © 2012 Ramasamy et al.

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 x 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 x 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 x 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.

Genome-wide meta-analysis identifies new susceptibility loci for migraine

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P<5x10(-8)). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

ACIAR Improving Postrainy Sorghum Varieties Grain and Fodder in India

Sorghum grown in India in the post-rainy season (Rabi) relies on residual soil moisture, and the crop is commonly exposed to terminal drought stress. But there is a ready market for its high-quality grain and stover (used as fodder on dairy farms). Steps to improve productivity while maintaining quality offer an attractive opportunity for sorghum farmers to improve their incomes. Genetically improving the efficiency of using stored soil moisture is a prime target to maximise grain/stover production and quality of Rabi sorghum. This project aims to achieve this through the application of DNA sequences known as quantitative trait loci (QTLs). The project scientists will introduce marker-assisted introgression of stay-green QTLs into sorghum lines, enhancing both the quality and the quantity of grain/stover of postrainy sorghum. They will also use modelling to identify the key physiological traits involved in a higher, more stable yield across water-limited environments of India and Australia, and the key stay-green QTLs contributing to these traits. The publicly available QTL isolines lines developed in this project will be the basis of new varieties to be bred in a subsequent phase.

Genome-wide association studies of quantitative traits with related individuals: Little (power) lost but much to be gained

For complex disease genetics research in human populations, remarkable progress has been made in recent times with the publication of a number of genome-wide association scans (GWAS) and subsequent statistical replications. These studies have identified new genes and pathways implicated in disease, many of which were not known before. Given these early successes, more GWAS are being conducted and planned, both for disease and quantitative phenotypes. Many researchers and clinicians have DNA samples available on collections of families, including both cases and controls. Twin registries around the world have facilitated the collection of large numbers of families, with DNA and multiple quantitative phenotypes collected on twin pairs and their relatives. In the design of a new GWAS with a fixed budget for the number of chips, the question arises whether to include or exclude related individuals. It is commonly believed to be preferable to use unrelated individuals in the first stage of a GWAS because relatives are 'over-matched' for genotypes. In this study, we quantify that for GWAS of a quantitative phenotype, relative to a sample of unrelated individuals surprisingly little power is lost when using relatives. The advantages of using relatives are manifold, including the ability to perform more quality control, the choice to perform within-family tests of association that are robust to population stratification, and the ability to perform joint linkage and association analysis. Therefore, the advantages of using relatives in GWAS for quantitative traits may well outweigh the small disadvantage in terms of statistical power.

On the probability of dizygotic twins being concordant for two alleles at multiple polymorphic loci

Accurate determination of same-sex twin zygosity is important for medical, scientific and personal reasons. Determination may be based upon questionnaire data, blood group, enzyme isoforms and fetal membrane examination, but assignment of zygosity must ultimately be confirmed by genotypic data. Here methods are reviewed for calculating average probabilities of correctly concluding a twin pair is monozygotic, given they share the same genotypes across all loci for commonly utilized multiplex short tandem repeat (STR) kits.

A multisite managed environment facility for targeted trait and germplasm phenotyping

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

GENETIC MAPPING OF THE LAMINARIA JAPONICA (LAMINARALES, PHAEOPHYTA) USING AMPLIFIED FRAGMENT LENGTH POLYMORPHISM MARKERS

To establish a molecular-marker-assisted system of breeding and genetic study for Laminaria japonica Aresch., amplified fragment length polymorphism (AFLP) was used to construct a genetic linkage map of L. japonica featuring 230 progeny of F-2 cross population. Eighteen primer combinations produced 370 polymorphic loci and 215 polymorphic loci segregated in a 3:1 Mendelian segregation ratio (P <= 0.05). Of the 215 segregated loci, 142 were ordered into 27 linkage groups. The length of the linkage groups ranged from 6.7 to 90.3 centimorgans (cM) with an average length of 49.6 cM, and the total length was 1,085.8 cM, which covered 68.4% of the estimated 1,586.9 cM genome. The number of mapped markers on each linkage group ranged from 2 to 12, averaging 5.3 markers per group. The average density of the markers was 1 per 9.4 cM. Based on the marker density and the resolution of the map, the constructed linkage map can satisfy the need for quantitative trait locus (QTL) location and molecular-marker-assisted breeding for Laminaria.

Epistasis among Drosophila persimilis factors conferring hybrid male sterility with D. pseudoobscura bogotana.

The Bateson-Dobzhansky-Muller model posits that hybrid incompatibilities result from genetic changes that accumulate during population divergence. Indeed, much effort in recent years has been devoted to identifying genes associated with hybrid incompatibilities, often with limited success, suggesting that hybrid sterility and inviability are frequently caused by complex interactions between multiple loci and not by single or a small number of gene pairs. Our previous study showed that the nature of epistasis between sterility-conferring QTL in the Drosophila persimilis-D. pseudoobscura bogotana species pair is highly specific. Here, we further dissect one of the three QTL underlying hybrid male sterility between these species and provide evidence for multiple factors within this QTL. This result indicates that the number of loci thought to contribute to hybrid dysfunction may have been underestimated, and we discuss how linkage and complex epistasis may be characteristic of the genetics of hybrid incompatibilities. We further pinpoint the location of one locus that confers hybrid male sterility when homozygous, dubbed "mule-like", to roughly 250 kilobases.

Quantitative genetics of CTCF binding reveal local sequence effects and different modes of X-chromosome association.

Associating genetic variation with quantitative measures of gene regulation offers a way to bridge the gap between genotype and complex phenotypes. In order to identify quantitative trait loci (QTLs) that influence the binding of a transcription factor in humans, we measured binding of the multifunctional transcription and chromatin factor CTCF in 51 HapMap cell lines. We identified thousands of QTLs in which genotype differences were associated with differences in CTCF binding strength, hundreds of them confirmed by directly observable allele-specific binding bias. The majority of QTLs were either within 1 kb of the CTCF binding motif, or in linkage disequilibrium with a variant within 1 kb of the motif. On the X chromosome we observed three classes of binding sites: a minority class bound only to the active copy of the X chromosome, the majority class bound to both the active and inactive X, and a small set of female-specific CTCF sites associated with two non-coding RNA genes. In sum, our data reveal extensive genetic effects on CTCF binding, both direct and indirect, and identify a diversity of patterns of CTCF binding on the X chromosome.