Estimation of population growth or decline in genetically monitored populations

This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model

1.There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6.Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Reversible phase variation in the phnE gene, which is required for phosphonate metabolism in Escherichia coli K-12

It is known that Escherichia coli K-12 is cryptic (Phn(-)) for utilization of methyl phosphonate (MePn) and that Phn(+) variants can be selected for growth on MePn as the sole P source. Variants arise from deletion via a possible slip strand mechanism of one of three direct 8-bp repeat sequences in phnE, which restores function to a component of a putative ABC type transporter. Here we show that Phn(+) variants are present at the surprisingly high frequency of >10(-2) in K-12 strains. Amplified-fragment length polymorphism analysis was used to monitor instability in phnE in various strains growing under different conditions. This revealed that, once selection for growth on MePn is removed, Phn(+) revertants reappear and accumulate at high levels through reinsertion of the 8-bp repeat element sequence. It appears that, in K-12, phnE contains a high-frequency reversible gene switch, producing phase variation which either allows ("on" form) or blocks ("off" form) MePn utilization. The switch can also block usage of other metabolizable alkyl phosphonates, including the naturally occurring 2-aminoethylphosphonate. All K-12 strains, obtained from collections, appear in the "off" form even when bearing mutations in mutS, mutD, or dnaQ which are known to enhance slip strand events between repetitive sequences. The ability to inactivate the phnE gene appears to be unique to K-12 strains since the B strain is naturally Phn(+) and lacks the inactivating 8-bp insertion in phnE, as do important pathogenic strains for which genome sequences are known and also strains isolated recently from environmental sources.

A Bayesian approach to disease gene location using allelic association

A Bayesian approach to analysing data from family-based association studies is developed. This permits direct assessment of the range of possible values of model parameters, such as the recombination frequency and allelic associations, in the light of the data. In addition, sophisticated comparisons of different models may be handled easily, even when such models are not nested. The methodology is developed in such a way as to allow separate inferences to be made about linkage and association by including theta, the recombination fraction between the marker and disease susceptibility locus under study, explicitly in the model. The method is illustrated by application to a previously published data set. The data analysis raises some interesting issues, notably with regard to the weight of evidence necessary to convince us of linkage between a candidate locus and disease.

A haplotype at the UCP1 gene locus contributes to genetic risk for type 2 diabetes in Asian Indians (CURES-72)

BACKGROUND: The gene encoding for uncoupling protein-1 (UCP1) is considered to be a candidate gene for type 2 diabetes because of its role in thermogenesis and energy expenditure. The objective of the study was to examine whether genetic variations in the UCP1 gene are associated with type 2 diabetes and its related traits in Asian Indians. METHODS: The study subjects, 810 type 2 diabetic subjects and 990 normal glucose tolerant (NGT) subjects, were chosen from the Chennai Urban Rural Epidemiological Study (CURES), an ongoing population-based study in southern India. The polymorphisms were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms, namely -3826A-->G, an A-->C transition in the 5'-untranslated region (UTR) and Met229Leu, were not associated with type 2 diabetes. However, the frequency of the A-C-Met (-3826A-->G-5'UTR A-->C-Met229Leu) haplotype was significantly higher among the type 2 diabetic subjects (2.67%) compared with the NGT subjects (1.45%, P < 0.01). The odds ratio for type 2 diabetes for the individuals carrying the haplotype A-C-Met was 1.82 (95% confidence interval, 1.29-2.78, P = 0.009). CONCLUSIONS: The haplotype, A-C-Met, in the UCP1 gene is significantly associated with the increased genetic risk for developing type 2 diabetes in Asian Indians.

Association of the PPARGC1A gene polymorphism with diabetic nephropathy in an Asian Indian population (CURES-41)

BACKGROUND: The aim of this study was to evaluate the association of polymorphisms of the peroxisome proliferator-activated receptor gamma (PPARG) gene and peroxisome proliferators-activated receptor gamma co-activator 1 alpha (PPARGC1A) gene with diabetic nephropathy (DN) in Asian Indians. METHODS: Six common polymorphisms, 3 of the PPARG gene [-1279G/A, Pro12Ala, and His478His (C/T)] and 3 of the PPARGC1A gene (Thr394Thr, Gly482Ser, and +A2962G) were studied in 571 normal glucose-tolerant (NGT) subjects, 255 type 2 diabetic (T2D) subjects without nephropathy, and 141 DN subjects. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct sequencing. Logistic regression analysis was performed to assess the covariables associated with DN. RESULTS: Among the 6 polymorphisms examined, only the Gly482Ser of the PPARGC1A gene was significantly associated with DN. The genotype frequency of Ser/Ser genotype of the PPARGC1A gene was 8.8% (50/571) in NGT subjects, 7.8% (20/255) in T2D subjects, and 29.8% (42/141) in DN subjects. The odds ratios (ORs) for DN for the susceptible Gly/Ser and Ser/Ser genotype after adjusting for age, sex, body mass index, and duration of diabetes were 2.14 [95% confidence interval (CI), 1.23-3.72; P = 0.007] and 8.01 (95% CI, 3.89-16.47; P < 0.001), respectively. The unadjusted OR for DN for the XA genotype of the Thr394Thr polymorphism was 1.87 (95% CI, 1.20-2.92; P = 0.006) compared to T2D subjects. However, the significance was lost (P = 0.061) when adjusted for age, sex, BMI, and duration of diabetes. The +A2962G of PPARGC1A and the 3 polymorphisms of PPARG were not associated with DN. CONCLUSION: The Gly482Ser polymorphism of the PPARGC1A gene is associated with DN in Asian Indians.

Absence of Association of Metabolic Syndrome with PPARGC1A, PPARG and UCP1 Gene Polymorphisms in Asian Indians

The objective of this study was to evaluate the association of PPARG coactivator1 alpha (PPARGC1A), peroxisome proliferator activated receptor gamma (PPARG), and uncoupling protein1 (UCP1) gene polymorphisms with the metabolic syndrome (MS) in an Asian Indian population. Nine common polymorphisms were genotyped via polymerase chain reaction restriction fragment length polymorphism and direct sequencing in 950 normal glucose-tolerant subjects and 550 type 2 diabetic subjects, chosen randomly from the Chennai Urban Rural Epidemiological Study, an ongoing population based study in Southern India. Among the 9 polymorphisms examined, only the Thr394Thr variant of the PPARGC1A gene was significantly associated with diabetes and obesity. The genotype frequency of GA of Thr394Thr variant was 16% (138/887) in the nonMS group and 22% (136/613) in the MS group, and this genotype frequency was significantly higher with MS both in males (p = 0.01) and females (p = 0.05), compared to the without-MS group. Logistic regression analysis revealed that the odds ratio for MS for the susceptible genotype GA of Thr394Thr was 1.411 [95% CI: 1.03-1.84, p = 0.012]. In the multiple logistic regression analysis, however, there was no association of this polymorphism as an independent factor with MS. Hence, the study shows that the polymorphisms in the PPARGC1A, PPARG and UCP1 genes are not associated with MS in Asian Indians.

Peroxisome proliferator-activated receptor-gamma co-activator-1alpha (PGC-1alpha) gene polymorphisms and their relationship to Type 2 diabetes in Asian Indians

AIMS: The objective of the present investigation was to examine the relationship of three polymorphisms, Thr394Thr, Gly482Ser and +A2962G, of the peroxisome proliferator activated receptor-gamma co-activator-1 alpha (PGC-1alpha) gene with Type 2 diabetes in Asian Indians. METHODS: The study group comprised 515 Type 2 diabetic and 882 normal glucose tolerant subjects chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The three polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Haplotype frequencies were estimated using an expectation-maximization (EM) algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms studied were not in linkage disequilibrium. With respect to the Thr394Thr polymorphism, 20% of the Type 2 diabetic patients (103/515) had the GA genotype compared with 12% of the normal glucose tolerance (NGT) subjects (108/882) (P = 0.0004). The frequency of the A allele was also higher in Type 2 diabetic subjects (0.11) compared with NGT subjects (0.07) (P = 0.002). Regression analysis revealed the odds ratio for Type 2 diabetes for the susceptible genotype (XA) to be 1.683 (95% confidence intervals: 1.264-2.241, P = 0.0004). Age adjusted glycated haemoglobin (P = 0.003), serum cholesterol (P = 0.001) and low-density lipoprotein (LDL) cholesterol (P = 0.001) levels and systolic blood pressure (P = 0.001) were higher in the NGT subjects with the XA genotype compared with GG genotype. There were no differences in genotype or allelic distribution between the Type 2 diabetic and NGT subjects with respect to the Gly482Ser and +A2962G polymorphisms. CONCLUSIONS: The A allele of Thr394Thr (G --> A) polymorphism of the PGC-1 gene is associated with Type 2 diabetes in Asian Indian subjects and the XA genotype confers 1.6 times higher risk for Type 2 diabetes compared with the GG genotype in this population.

Frequency of infant stroking reported by mothers moderates the effect of prenatal depression on infant behavioural and physiological outcomes

Animal studies find that prenatal stress is associated with increased physiological and emotional reactivity later in life, mediated via fetal programming of the HPA axis through decreased glucocorticoid receptor (GR) gene expression. Post-natal behaviours, notably licking and grooming in rats, cause decreased behavioural indices of fear and reduced HPA axis reactivity mediated via increased GR gene expression. Post-natal maternal behaviours may therefore be expected to modify prenatal effects, but this has not previously been examined in humans. We examined whether, according to self-report, maternal stroking over the first weeks of life modified associations between prenatal depression and physiological and behavioral outcomes in infancy, hence mimicking effects of rodent licking and grooming. From a general population sample of 1233 first time mothers recruited at 20 weeks gestation we drew a stratified random sample of 316 for assessment at 32 weeks based on reported inter-partner psychological abuse, a risk to child development. Of these 271 provided data at 5, 9 and 29 weeks post delivery. Mothers reported how often they stroked their babies at 5 and 9 weeks. At 29 weeks vagal withdrawal to a stressor, a measure of physiological adaptability, and maternal reported negative emotionality were assessed. There was a significant interaction between prenatal depression and maternal stroking in the prediction of vagal reactivity to a stressor (p = .01), and maternal reports of infant anger proneness (p = .007) and fear (p = .043). Increasing maternal depression was associated with decreasing physiological adaptability, and with increasing negative emotionality, only in the presence of low maternal stroking. These initial findings in humans indicate that maternal stroking in infancy, as reported by mothers, has effects strongly resembling the effects of observed maternal behaviours in animals, pointing to future studies of the epigenetic, physiological and behavioral effects of maternal stroking.

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.