Spatial genetic patterns generated by two admixing genetic lineages: a simulation study

Two formerly geographically separated lineages of the zebra mussel Dreissena polymorpha had been given the opportunity to mix extensively across the newly built German Main–Danube canal. We had monitored this admixture of mussel lineages and had described spatial patterns in different genetic measures [Müller et al. 2001 (Heredity, 86: 103); 2002 (Proc. R. Soc. Lond., 269: 1139)]. Here, we present an individual-based model to assess the potential of spatial genetic patterns of detecting and quantifying admixture of mussel lineages. Genetic measures studied are (1) allele frequencies, (2) deviations from Hardy–Weinberg expectations of loci (deficit of heterozygotes, HWD) and (3) linkage disequilibria between unlinked loci (LD). For allele frequencies, we observed a cline over the zone of admixture in all simulations of mixing mussel lineages suggesting that these are appropriate for verification of their mixture. The point of the first contact between lineages was always detectable from their intermediate allele frequencies. LD and HWD were only spatially informative for diagnostic loci or loci with very strong differences in allele frequencies of lineages. For such loci, the probability of disequilibria was highest where lineages had met and decreased towards both sources of lineages Main and Danube. The overall probability of detecting any disequilibrium was higher for LD than for HWD and increased with an increasing rate of genetic interchange. Our simulation results are corroborated by our zebra mussel data and studies from literature. They are applicable to any case of two known linearly mixing genetic lineages.     

Delineation of Two Sibling Red Algal Species,Gracilaria Gracilis and Gracilaria Dura (Gracilariales,Rhodophyta), Using Multiple DNA Markers: Resurrection of the Species G. Dura Previously Described in the Northern Atlantic 200 Years Ago1

Molecular markers belonging to the three different genomes, mitochondrial (cox2‐cox3 spacer), plastid (rbcL), and nuclear (internal transcribed spacer [ITS] 2 region), were used to compare samples of the two morphologically related species Gracilaria gracilis (Stackh.) Steentoft, L. M. Irvine et Farnham and G. dura (C. Agardh) J. Agardh collected along Atlantic coasts. In northern Europe, the distinction between these two species is ambiguous, and they are currently recognized under the single name of G. gracilis. The low but congruent patterns of genetic divergence observed for markers of the three genomic compartments highly suggest that these two taxa correspond effectively to two different genetic entities as previously described 200 years ago, based on morphological traits. However, thanks to the combination of different DNA markers, occurrence of “incongruent” cytotypes (i.e., mitotypes of G. dura associated with chlorotypes of G. gracilis) in individuals collected from Brittany, suggests interspecific hybridization between the two sibling species studied.     

Linkage and Association Between CA Repeat Polymorphism of the TNFR2 Gene and Obesity Phenotypes in Two Independent Caucasian Populations

Previously, our group has reported a suggestive linkage evidence of 1p36 with body mass index (BMI) (LOD = 2.09). The tumor necrosis factor receptor 2 (TNFR2) at 1p36 is an excellent positional and functional candidate gene for obesity. In this study, we have investigated the linkage and association between the TNFR2 gene and obesity phenotypes in two large independent samples, using the quantitative transmission disequilibrium tests (QTDT). The first group was made up of 1 836 individuals from 79 multi-generation pedigrees. The second group was a randomly ascertained set of 636 individuals from 157 US Caucasian nuclear families. Obesity phenotypes tested include BMI, fat mass, and percentage fat mass (PFM). A significant result (P = 0.0056) was observed for linkage with BMI in the sample of the multigenerational pedigrees. Our data support the TNFR2 gene as a quantitative trait locus (QTL) underlying BMI variation in the Caucasian populations.     

Linkage disequilibrium between alleles at highly polymorphic mini- and micro-satellite loci of Theileria parva isolated from cattle in three regions of Kenya

Theileria parva schizont-infected lymphocyte culture isolates from western, central and coastal Kenya were analysed for size polymorphism at 30 T. parva-specific variable number tandem repeat (VNTR) loci using a panel of mini- and micro-satellite markers. The mean number of alleles ranged from 3 to 11 at individual loci and 183 distinct alleles were observed in total, indicating high genetic diversity within the T. parva gene pool in Kenyan cattle. The frequency distribution of the length variation of specific alleles among isolates ranged from normal to markedly discontinuous. Genetic relationships between isolates were analysed using standard indices of genetic distance. Genetic distances and dendrograms derived from these using neighbour-joining algorithms did not indicate significant clustering on a geographical basis. Analysis of molecular variance demonstrated that the genetic variation between individual isolates was 72%, but only 2.3% when isolates from different regions were pooled. Both these observations suggest minimal genetic sub-structuring relative to geographical origin. Linkage disequilibrium was observed between pairs of loci within populations, as in certain Ugandan T. parva populations. A novel observation was that disequilibrium was also detected between alleles at three individual pairs of VNTR loci when isolates from the three regional meta-populations were pooled for analysis.     

Optimization of two-stage genetic designs where data are combined using an accurate and efficient approximation for Pearson's statistic

There is an increasing interest in the use of two-stage case-control studies to reduce genotyping costs in the search for genes underlying common disorders. Instead of analyzing the data from the second stage separately, a more powerful test can be performed by combining the data from both stages. However, standard tests cannot be used because only the markers that are significant in the first stage are selected for the second stage and the test statistics at both stages are dependent because they partly involve the same data. Theoretical approximations are not available for commonly used test statistics and in this specific context simulations can be problematic because of the computational burden. We therefore derived a cost-effective, that is, accurate but fast in terms of central processing unit (CPU) time, approximation for the distribution of Pearson's statistic on 2 xm contingency tables in two-stage design with combined data. We included this approximation in an iterative method for designing optimal two-stage studies. Simulations supported the accuracy of our approximation. Numerical results confirmed that the use of two-stage designs reduces the genotyping burden substantially. Compared to not combining data, combining the data decreases the required sample sizes on average by 15% and the genotyping burden by 5%.     

Local heterozygosity-fitness correlations with global positive effects on fitness in threespine stickleback

The complex interactions between genetic diversity and evolution have important implications in many biological areas including conservation, speciation, and mate choice. A common way to study these interactions is to look at heterozygosity-fitness correlations (HFCs). Until recently, HFCs based on noncoding markers were believed to result primarily from global inbreeding effects. However, accumulating theoretical and empirical evidence shows that HFCs may often result from genes being linked to the markers used (local effect). Moreover, local effect HFCs could differ from global inbreeding effects in their direction and occurrence. Consequently, the investigation of the structure and consequences of local HFCs is emerging as a new important goal in evolutionary biology. In this study of a wild threespine stickleback (Gasterosteus aculeatus) population, we first tested the presence of significant positive or negative local effects of heterozygosity at 30 microsatellites loci on five fitness components: survival, mating success, territoriality, length, and body condition. Then, we evaluated the direction and shape of total impact of local HFCs, and estimated the magnitude of the impacts on fitness using regression coefficients and selection differentials. We found that multilocus heterozygosity was not a reliable estimator of individual inbreeding coefficient, which supported the relevance of single-locus based analyses. Highly significant and temporally stable local HFCs were observed. These were mainly positive, but negative effects of heterozygosity were also found. Strong and opposite effects of heterozygosity are probably present in many populations, but may be blurred in HFC analyses looking for global effects only. In this population, both negative and positive HFCs are apparently driving mate preference by females, which is likely to contribute to the maintenance of both additive and nonadditive genetic variance.     

Statistical methods in genetics

In recent years, a very large variety of statistical methodologies, at various levels of complexity, have been put forward to analyse genotype data and detect genetic variations that may be responsible for increasing the susceptibility to disease. This review provides a concise account of a number of selected statistical methods for population-based association mapping, from single-marker tests of association to multi-marker data mining techniques for gene-gene interaction detection.     

Genetic association of the gene encoding RPGRIP1L with susceptibility to vascular dementia

A previous genome-wide association study (GWAS) failed to discover any nucleotide sequence variant associated with susceptibility to vascular dementia (VaD) and remained a problem of false negatives produced by a low statistical power. The current study was conducted to identify such potential false negatives and to provide comprehensive evidence for the most plausible predisposing genetic factor using large-scale Korean cohorts. We identified the gene encoding retinitis pigmentosa GTPase regulator-interacting protein 1-like (RPGRIP1L) with multiple nucleotide variants associated with susceptibility to VaD by a modest significant threshold (P<10(-4)). Genetic associations were intensively examined with its sequence variants using 207 VaD patients and 207 age- and gender-matched control subjects. Genetic association analysis with dense variants in the region associated with VaD revealed 3 variants (P<0.0017) in strong linkage. Further analysis with VaD-related phenotypes using Korean Association REsource (KARE) cohort data showed that the region of the gene was associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), and blood pressure (BP) (P<7.6×10(-4)). The current study provided the first evidence of the association between RPGRIP1L gene and susceptibility of VaD. Functional studies are needed to understand underlying biological mechanism of the genetic association.     

Identification of a novel duplication CFTRdup2 and functional impact of large rearrangements identified in the CFTR gene

The aim of this study was to investigate associations of two candidate gene SNPs of the endocannabinoid receptor type 1 gene (CNR1) with overweight, obesity and obesity-related traits in Chinese retired women. The study subjects were a subsample of the Taizhou Retiree Women Cohort, consisting of 2812 retired women aged 50-64 years recruited from Taizhou, Jiangsu, China. Neither rs2023239 nor rs806381 polymorphism was significantly associated with body mass index-defined overweight and obesity or waist-to-hip-ratio-defined obesity. For obesity-related traits, rs2023239 was significantly associated with glutamate pyruvate transaminase (GPT) (median, 18.00 vs 17.00 for TT and TC genotypes, respectively, P=0.043). The rs806381 also showed significant association with triglyceride (TG) (mean±SD, 1.46±0.20 vs 1.53±0.20 for GA and GG+AA genotypes, respectively, P=0.013) under the dominant genetic model. In conclusion, the rs2023239 and rs806381 polymorphisms of CNR1 were not associated with increased overweight and obesity risk. But the rs2023239 polymorphism was significantly associated with GPT, and the rs806381 polymorphism was significantly associated with TG.