Thyroid hormone-dependent gene expression as a biomarker of short-term 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) exposure in European common frog (Rana temporaria) tadpoles

The effects on thyroid hormone-dependent gene biomarker responses of the persistent organochlorine pesticide metabolite 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) were investigated after exposure of 4-week-old European common frog (Rana temporaria) (stage 36) tadpoles to two (0.001 and 0.01 ppm) DDE concentrations. Total body weight, total length, and tail length and width increased after 3-day exposure to DDE. Expression patterns of genes encoding for growth hormone, thyroid-stimulating hormone (TSHβ) and thyroid hormone receptor (TRα and TRβ) isoforms were evaluated in the head, body and tail regions using a validated real-time polymerase chain reaction (PCR) method. The mRNA expression of growth hormone in the body, and TSHβ in the head showed significant DDE concentration-dependent decreases. While DDE caused variable effects on TRα mRNA steady-state, the expression of TRβ was significantly decreased in the tail by DDE in a concentration-specific manner. The effect of DDE exposure on TRβ mRNA expression showed a negative correlation with tail length and width during the exposure period. The unique pattern of a DDE-induced decrease of tail TRβ expression probably reflects the significant role of this thyroid hormone receptor isoform in tail re-absorption and overall metamorphosis in anuran species. Therefore, the present study shows that the evaluation of thyroid hormone-dependent genes may represent quantitative biomarkers of acute exposure to organochlorine pesticides in anuran species during critical developmental periods such as metamorphosis. Given the widespread environmental levels of DDT and its metabolites, these pollutants will remain a subject of concern and their effects on anuran species should be studied in more detail.     

CYP1A1, GSTM1 and GSTT1 polymorphisms and lung cancer: a pooled analysis of gene–gene interactions

Gene–environment interactions have been extensively studied in lung cancer. It is likely that several genetic polymorphisms cooperate in increasing the individual risk. Therefore, the study of gene–gene interactions might be important to identify high-susceptibility subgroups. GSEC is an initiative aimed at collecting available data sets on metabolic polymorphisms and the risks of cancer at several sites and performing pooled analyses of the original data. Authors of published papers have provided original data sets. The present paper refers to gene–gene interactions in lung cancer and considers three polymorphisms in three metabolic genes: CYP1A1, GSTM1 and GSTT1. The present analyses compare the gene–gene interactions of the CYP1A1*2A, GSTM1 and GSTT1 polymorphisms from studies on lung cancer conducted in Europe and the USA between 1991 and 2000. Only Caucasians have been included. The data set includes 1466 cases and 1488 controls. The only clear-cut association was found with CYP1A1*2A. This association remained unchanged after stratification by polymorphisms in other genes (with an odds ratio [OR] of approximately 2.5), except when interaction with GSTM1 was considered. When the OR for CYP1A1*2A was stratified according to the GSTM1 genotype, the OR was increased only among the subjects who had the null (homozygous deletion) GSTM1 genotype (OR=2.8, 95% CI=0.9–8.4). The odds ratio for the interactive term (CYP1A1*2A by GSTM1) in logistic regression was 2.7 (95% CI=0.5–15.3). An association between lung cancer and the homozygous CYP1A1*2A genotype is confirmed. An apparent and biologically plausible interaction is suggested between this genotype and GSTM1.     

Genotyping of IL-8-251 T > A yields prognostic information in patients with gastric carcinoma

Abstract

This study was designed to investigate the association of the IL-8-251?T?>?A gene polymorphism with clinicopathological features and the prognostic role of the gene polymorphism in patients with gastric adenocarcinoma. The gene polymorphism was detected by the polymerase chain reaction–restriction fragment length polymorphism method, followed by univariate and multivariate analyses to elicit its prognostic role. The frequency of IL-8-251?A/A, A/T and T/T genotypes were 11.0% (23/210), 43.8% (92/210) and 45.2% (95/210), respectively. The IL-8-251 gene polymorphism was closely correlated with depth of invasion (p?=?0.007), grade of differentiation (p?=?0.002) and TNM stage (p?=?0.009). A/A genotype carriers showed more frequency of serosa involvement, low grade of differentiation and advanced stage of gastric carcinoma. IL-8-251?T?>?A gene polymorphism have no significant correlation with other clinicopathological features. The 5-year overall survival of IL-8-251?A/A genotype and T allele carriers were 30.8% and 59.2%, respectively. There is a significant discrepancy among the different genotype carriers. Multivariate analysis with the Cox regression model revealed that the IL-8-251?A/A genotype is an independent prognostic indicator (HR?=?2.285, 95% Confidence Interval?=?1.06–4.93, p?=?0.035). We conclude that the IL-8-251?A/A genotype may indicate a poor prognosis for gastric adenocarcinoma patients.     

Spatial and temporal population genetic variation and structure of Nothotsuga longibracteata (Pinaceae), a relic conifer species endemic to subtropical China

Nothotsuga longibracteata, a relic and endangered conifer species endemic to subtropical China, was studied for examining the spatial-temporal population genetic variation and structure to understand the historical biogeographical processes underlying the present geographical distribution. Ten populations were sampled over the entire natural range of the species for spatial analysis, while three key populations with large population sizes and varied age structure were selected for temporal analyses using both nuclear microsatellites (nSSR) and chloroplast microsatellites (cpSSR). A recent bottleneck was detected in the natural populations of N. longibracteata. The spatial genetic analysis showed significant population genetic differentiation across its total geographical range. Notwithstanding, the temporal genetic analysis revealed that the level of genetic diversity between different age class subpopulations remained constant over time. Eleven refugia of the Last Glacial Maximum were identified, which deserve particular attention for conservation management.     

Individual dispersal,landscape connectivity and ecological networks

Connectivity is classically considered an emergent property of landscapes encapsulating individuals' flows across space. However, its operational use requires a precise understanding of why and how organisms disperse. Such movements, and hence landscape connectivity, will obviously vary according to both organism properties and landscape features. We review whether landscape connectivity estimates could gain in both precision and generality by incorporating three fundamental outcomes of dispersal theory. Firstly, dispersal is a multi‐causal process; its restriction to an ‘escape reaction’ to environmental unsuitability is an oversimplification, as dispersing individuals can leave excellent quality habitat patches or stay in poor‐quality habitats according to the relative costs and benefits of dispersal and philopatry. Secondly, species, populations and individuals do not always react similarly to those cues that trigger dispersal, which sometimes results in contrasting dispersal strategies. Finally, dispersal is a major component of fitness and is thus under strong selective pressures, which could generate rapid adaptations of dispersal strategies. Such evolutionary responses will entail spatiotemporal variation in landscape connectivity. We thus strongly recommend the use of genetic tools to: (i) assess gene flow intensity and direction among populations in a given landscape; and (ii) accurately estimate landscape features impacting gene flow, and hence landscape connectivity. Such approaches will provide the basic data for planning corridors or stepping stones aiming at (re)connecting local populations of a given species in a given landscape. This strategy is clearly species‐ and landscape‐specific. But we suggest that the ecological network in a given landscape could be designed by stacking up such linkages designed for several species living in different ecosystems. This procedure relies on the use of umbrella species that are representative of other species living in the same ecosystem.     

A high density physical map of chromosome 1BL supports evolutionary studies,map-based cloning and sequencing in wheat

Background

As for other major crops, achieving a complete wheat genome sequence is essential for the application of genomics to breeding new and improved varieties. To overcome the complexities of the large, highly repetitive and hexaploid wheat genome, the International Wheat Genome Sequencing Consortium established a chromosome-based strategy that was validated by the construction of the physical map of chromosome 3B. Here, we present improved strategies for the construction of highly integrated and ordered wheat physical maps, using chromosome 1BL as a template, and illustrate their potential for evolutionary studies and map-based cloning.

Results

Using a combination of novel high throughput marker assays and an assembly program, we developed a high quality physical map representing 93% of wheat chromosome 1BL, anchored and ordered with 5,489 markers including 1,161 genes. Analysis of the gene space organization and evolution revealed that gene distribution and conservation along the chromosome results from the superimposition of the ancestral grass and recent wheat evolutionary patterns, leading to a peak of synteny in the central part of the chromosome arm and an increased density of non-collinear genes towards the telomere. With a density of about 11 markers per Mb, the 1BL physical map provides 916 markers, including 193 genes, for fine mapping the 40 QTLs mapped on this chromosome.

Conclusions

Here, we demonstrate that high marker density physical maps can be developed in complex genomes such as wheat to accelerate map-based cloning, gain new insights into genome evolution, and provide a foundation for reference sequencing.