Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci

After ingestion of a standardized dose of ethanol, alcohol concentrations were assessed, over 3.5 hours from blood (six readings) and breath (10 readings) in a sample of 412 MZ and DZ twins who took part in an Alcohol Challenge Twin Study (ACTS). Nearly all participants were subsequently genotyped on two polymorphic SNPs in the ADH1B and ADH1C loci known to affect in vitro ADH activity. In the DZ pairs, 14 microsatellite markers covering a 20.5 cM region on chromosome 4 that includes the ADH gene family were assessed, Variation in the timed series of autocorrelated blood and breath alcohol readings was studied using a bivariate simplex design. The contribution of a quantitative trait locus (QTL) or QTL's linked to the ADH region was estimated via a mixture of likelihoods weighted by identity-by-descent probabilities. The effects of allelic substitution at the ADH1B and ADH1C loci were estimated in the means part of the model simultaneously with the effects sex and age. There was a major contribution to variance in alcohol metabolism due to a QTL which accounted for about 64% of the additive genetic covariation common to both blood and breath alcohol readings at the first time point. No effects of the ADH1B*47His or ADH1C*349Ile alleles on in vivo metabolism were observed, although these have been shown to have major effects in vitro. This implies that there is a major determinant of variation for in vivo alcohol metabolism in the ADH region that is not accounted for by these polymorphisms. Earlier analyses of these data suggested that alcohol metabolism is related to drinking behavior and imply that this QTL may be protective against alcohol dependence.

Butyrylcholinesterase: Association with the metabolic syndrome and identification of 2 gene loci affecting activity

Background: Plasma cholinesterase activity is known to be correlated with plasma triglycerides, HDL- and LDL-cholesterol, and other features of the metabolic syndrome. A role in triglyceride metabolism has been proposed. Genetic variants that decrease activity have been studied extensively, but the factors contributing to overall variation in the population are poorly understood. We studied plasma cholinesterase activity in a sample of 2200 adult twins to assess covariation with cardiovascular risk factors and components of the metabolic syndrome, to determine the degree of genetic effects on enzyme activity, and to search for quantitative trait loci affecting activity. Methods and Results: Cholinesterase activity was lower in women than in men before the age of 50, but increased to activity values similar to those in males after that age. There were highly significant correlations with variables associated with the metabolic syndrome: plasma triglyceride, HDL- and LDL-cholesterol, apolipoprotein B and E, urate, and insulin concentrations; gamma-glutamyltransferase and aspartate and alanine aminotransferase activities; body mass index; and blood pressure. The heritability of plasma cholinesterase activity was 65%. Linkage analysis with data from the dizygotic twin pairs showed suggestive linkage on chromosome 3 at the location of the cholinesterase WHO gene and also on chromosome 5. Conclusions: Our results confirm and extend the connection between cholinesterase, cardiovascular risk factors, and metabolic syndrome. They establish a substantial heritability for plasma cholinesterase activity that might be attributable to variation near the structural gene and at an independent locus. (c) 2006 American Association for Clinical Chemistry.

Genome-wide scan of IQ finds significant linkage to a quantitative trait locus on 2q

A genome-wide linkage scan of 795 microsatellite markers (761 autosomal, 34 X chromosome) was performed on Multidimensional Aptitude Battery subtests and verbal, performance and full scale scores, the WAIS-R Digit Symbol subtest, and two word-recognition tests (Schonell Graded Word Reading Test, Cambridge Contextual Reading Test) highly predictive of IQ. The sample included 361 families comprising 2-5 siblings who ranged in age from 15.7 to 22.2 years; genotype, but not phenotype, data were available for 81% of parents. A variance components analysis which controlled for age and sex effects showed significant linkage for the Cambridge reading test and performance IQ to the same region on chromosome 2, with respective LOD scores of 4.15 and 3.68. Suggestive linkage (LOD score > 2.2) for various measures was further supported on chromosomes 6, 7, 11, 14, 21 and 22. Where location of linkage peaks converged for IQ subtests within the same scale, the overall scale score provided increased evidence for linkage to that region over any individual subtest. Association studies of candidate genes, particularly those involved in neural transmission and development, will be directed to genes located under the linkage peaks identified in this study.

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.

A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

Identification of causal relationships among traits related to drought resistance in Stylosanthes scabra using QTL analysis

Previous studies have shown that a negative relationship exists between transpiration efficiency (TE) and carbon isotope discrimination (Delta) and between TE and specific leaf area (SLA) in Stylosanthes scabra, A glasshouse experiment was conducted to confirm these relationships in an F-2 population and to study the causal nature of these relationships through quantitative trait loci (QTL) analysis, One hundred and twenty F-2 genotypes from a cross between two genotypes within S. scabra were used. Three replications for each genotype were maintained through vegetative propagation, Water stress was imposed by maintaining plants at 40% of field capacity for about 45 d. To facilitate QTL analysis, a genetic linkage map consisting of 151 RAPD markers was developed, Results from this study show that Delta was significantly and negatively correlated with TE and biomass production. Similarly, SLA showed significant negative correlation with TE and biomass production, Most of the QTL for TE and Delta were present on linkage groups 5 and 11. Similarly, QTL for SLA, transpiration and biomass productivity traits were clustered on linkage groups 13 and 24, One unlinked marker was also associated with these traits, There were several markers coincident between different traits, At all the coincident QTL, the direction of QTL effects was consistent with phenotypic data, At the coincident markers between TE and Delta, high alleles of TE were associated with low alleles of Delta. Similarly, low alleles of SLA were associated with high alleles of biomass productivity traits and transpiration. At the coincident markers between trans-4-hydroxy-N-methyl proline (MHP) and relative water content (RWC), low alleles of MHP were associated with high alleles of RWC, This study suggests the causal nature of the relationship between TE and Delta. Phenotypic data and QTL, data show that SLA was more closely associated with biomass production than with TE, This study also shows that a cause-effect relationship may exist between SLA and biomass production.

Future contributions of crop modelling - from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement

Crop modelling has evolved over the last 30 or so years in concert with advances in crop physiology, crop ecology and computing technology. Having reached a respectable degree of acceptance, it is appropriate to review briefly the course of developments in crop modelling and to project what might be major contributions of crop modelling in the future. Two major opportunities are envisioned for increased modelling activity in the future. One opportunity is in a continuing central, heuristic role to support scientific investigation, to facilitate decision making by crop managers, and to aid in education. Heuristic activities will also extend to the broader system-level issues of environmental and ecological aspects of crop production. The second opportunity is projected as a prime contributor in understanding and advancing the genetic regulation of plant performance and plant improvement. Physiological dissection and modelling of traits provides an avenue by which crop modelling could contribute to enhancing integration of molecular genetic technologies in crop improvement. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Cosegregation analysis of natriuretic peptide genes and blood pressure in the spontaneously hypertensive rat

1. The natriuretic peptide precursor A (Nppa) and B (Nppb) genes are candidate genes for hypertension and cardiac hypertrophy in the spontaneously hypertensive rat (SHR). The purpose of the present study was to determine the role of the Nppa and Nppb genes in the development of hypertension in the SHR. 2. A cohort (n = 162) of F2 segregating intercross animals was established between strains of hypertensive SHR and normotensive Wistar-Kyoto rats. Blood pressure and heart weight were measured in each rat at 12-16 weeks of age. Rats were genotyped using 11 informative microsatellite markers, distributed in the vicinity of the Nppa marker on rat chromosome 5 including an Nppb marker. The phenotype values were compared with genotype using the computer package MAP-MAKER 3.0 (Whitehead Institute, Boston, MA, USA) to determine whether there was a link between the genetic variants of the natriuretic peptide family and blood pressure or cardiac hypertrophy. 3. A strong correlation was observed between the Nppa marker and blood pressure. A quantitative trait locus (QTL) for blood pressure on chromosome 5 was identified between the Nppa locus and the D5Mgh15 marker, less than 2 cM from the Nppa locus. The linkage score for the blood pressure QTL on chromosome 5 was 3.8 and the QTL accounted for 43% of the total variance of systolic blood pressure, 54% of diastolic blood pressure and 59% of mean blood pressure. No association was found between the Nppb gene and blood pressure. This is the first report of linkage between the Nppa marker and blood pressure in the rat. There was no correlation between the Nppa or Nppb genes or other markers in this region and either heart weight or left ventricular weight in F2 rats. 4. These findings suggest the existence of a blood pressure-dependent Nppa marker variant or a gene close to Nppa predisposing to spontaneous hypertension in the rat. It provides a strong foundation for further detailed genetic studies in congenic strains, which may help to narrow down the location of this gene and lead to positional cloning.

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.

On systems thinking, systems biology and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

The potential of microarrays to assist shrimp breeding and production: a review

The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

Relationships between hard-seededness and seed weight in mungbean (Vigna radiata) assessed by QTL analysis

Weather damage reduces the value of commercial mungbean, but hard-seededness can reduce the level of damage. However, attempts to breed large- and hard-seeded mungbean varieties have been unsuccessful. To understand the relationship between seed weight and hard-seededness, these traits were investigated using a quantitative trait loci (QTL) mapping approach with a recombinant inbred population derived from a cross between a completely soft-seeded variety and a completely hard-seeded genotype. The two parental genotypes also had a sixfold difference in seed weight. QTL analyses revealed four loci for hard-seededness and I I loci for seed weight. Two of the hardseededness loci co-localized with seed weight QTL. When seed weight was used as a covariate in the analysis of hard-seededness from the field data, two of the four hard-seeded QTL remained significant with the effect at one of these remaining unchanged. These results explain why retaining hard-seededness in large seeded mungbean lines has been unsuccessful. The existence of a persistent locus, however, indicated that breeding large and persistently hard-seeded varieties of mungbean may be possible.

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.

Analysing diversity in sugarcane resistance gene analogues

As resistance genes have been shown to contain conserved motifs and cluster in many plant genomes, the identification of resistance gene analogues can be used as a strategy for both the discovery of DNA markers linked to disease resistance loci and the map-based cloning of disease resistance genes. Sugarcane suffers from many important diseases and an analysis of resistance gene analogues offers a means to identify DNA markers linked to resistance loci. However, sugarcane has the most complex genome of any crop plant and initially it is important to understand the extent of resistance gene analogue diversity in the sugarcane genome before genetic analysis. We review herein how more than 100 expressed sequence tags with homology to different resistance genes have been identified in sugarcane with many mapped as single-dose restriction fragment length polymorphism markers. Importantly, some of these resistance gene analogues have been shown to be linked to disease resistance genes or disease quantitative trait loci. In an attempt to more efficiently analyse additional resistance gene analogues in sugarcane, we report on experiments aimed at investigating the molecular diversity of several resistance gene analogue families using a modified form of a technique termed Ecotilling. Using Ecotilling, we were able to rapidly detect single nucleotide polymorphisms in fragments amplified by PCR from four different resistance gene analogue families, SoRP1D, SoPTO, SoXa21 and SoHs1pro-1. An analysis of a diverse set of sugarcane varieties, including modern sugarcane cultivars and several S. officinarum and S. spontaneum clones, indicated that all amplicons, apart from SoHs1pro-1, contained significant polymorphism within the gene region studied. However, a comparison among these sugarcane clones, including between the parents of two sugarcane mapping populations, indicated that most polymorphisms were multi-dose, not single-dose, preventing their genetic map location or association with disease susceptibility or resistance from being determined.

Congruence in QTL for adventitious rooting in Pinus elliottii X Pinus caribaea hybrids resolves between and within-species effects

Targeting between-species effects for improvement in synthetic hybrid populations derived from outcrossing parental tree species may be one way to increase the efficacy and predictability of hybrid breeding. We present a comparative analysis of the quantitative trait loci (QTL) which resolved between from within-species effects for adventitious rooting in two populations of hybrids between Pinus elliottii and P. caribaea, an outbred F-1 (n=287) and an inbred-like F-2 family (n=357). Most small to moderate effect QTL (each explaining 2-5% of phenotypic variation, PV) were congruent (3 out of 4 QTL in each family) and therefore considered within-species effects as they segregated in both families. A single large effect QTL (40% PV) was detected uniquely in the F-2 family and assumed to be due to a between-species effect, resulting from a genetic locus with contrasting alleles in each parental species. Oligogenic as opposed to polygenic architecture was supported in both families (60% and 20% PV explained by 4 QTL in the F-2 and F-1 respectively). The importance of adventitious rooting for adaptation to survive water-logged environments was thought in part to explain oligogenic architecture of what is believed to be a complex trait controlled by many hundreds of genes.