A major difference between the divergence patterns within the lines-1 families in mice and voles

L1 retroposons are represented in mice by subfamilies of interspersed sequences of varied abundance. Previous analyses have indicated that subfamilies are generated by duplicative transposition of a small number of members of the L1 family, the progeny of which then become a major component of the murine L1 population, and are not due to any active processes generating homology within preexisting groups of elements in a particular species. In mice, more than a third of the L1 elements belong to a clade that became active approximately 5 Mya and whose elements are > or = 95% identical. We have collected sequence information from 13 L1 elements isolated from two species of voles (Rodentia: Microtinae: Microtus and Arvicola) and have found that divergence within the vole L1 population is quite different from that in mice, in that there is no abundant subfamily of homologous elements. Individual L1 elements from voles are very divergent from one another and belong to a clade that began a period of elevated duplicative transposition approximately 13 Mya. Sequence analyses of portions of these divergent L1 elements (approximately 250 bp each) gave no evidence for concerted evolution having acted on the vole L1 elements since the split of the two vole lineages approximately 3.5 Mya; that is, the observed interspecific divergence (6.7%-24.7%) is not larger than the intraspecific divergence (7.9%-27.2%), and phylogenetic analyses showed no clustering into Arvicola and Microtus clades.      

A data management system for structural genomics

Background  

Structural genomics (SG) projects aim to determine thousands of protein structures by the development of high-throughput techniques for all steps of the experimental structure determination pipeline. Crucial to the success of such endeavours is the careful tracking and archiving of experimental and external data on protein targets.     

心脏特异表达LMNA^E82K转基因小鼠的建立

目的建立心脏特异表达LMNAE82K转基因小鼠,为研究LMNAE82K与心肌病发病机制的关系提供工具动物。方法把LMNAE82K基因插入α-MHC启动子下游,构建转基因表达载体,显微注射法建立C57BL/6JLMNAE82K转基因小鼠,PCR鉴定转基因小鼠的基因型,采用Western Blot鉴定LMNAE82K在心脏组织中的表达,H＆E染色和超声检测转基因小鼠心脏的病理改变。结果建立了2个心脏组织特异表达LMNAE82K的转基因小鼠品系。超声检查显示转基因小鼠心室壁变薄,收缩期容积和舒张期容积增加,射血分数及短轴缩短率降低。结论LMNAE82K转基因小鼠具有LMNAE82K引起的家族性扩心病有类似的病理变化,为研究LMNAE82K与心肌病发病机制的关系的研究提供了有价值的疾病动物模型。     

Molecular phylogeny and divergence times of drosophilid species

The phylogenetic relationships and divergence times of 39 drosophilid species were studied by using the coding region of the Adh gene. Four genera--Scaptodrosophila, Zaprionus, Drosophila, and Scaptomyza (from Hawaii)--and three Drosophila subgenera--Drosophila, Engiscaptomyza, and Sophophora--were included. After conducting statistical analyses of the nucleotide sequences of the Adh, Adhr (Adh-related gene), and nuclear rRNA genes and a 905-bp segment of mitochondrial DNA, we used Scaptodrosophila as the outgroup. The phylogenetic tree obtained showed that the first major division of drosophilid species occurs between subgenus Sophophora (genus Drosophila) and the group including subgenera Drosophila and Engiscaptomyza plus the genera Zaprionus and Scaptomyza. Subgenus Sophophora is then divided into D. willistoni and the clade of D. obscura and D. melanogaster species groups. In the other major drosophilid group, Zaprionus first separates from the other species, and then D. immigrans leaves the remaining group of species. This remaining group then splits into the D. repleta group and the Hawaiian drosophilid cluster (Hawaiian Drosophila, Engiscaptomyza, and Scaptomyza). Engiscaptomyza and Scaptomyza are tightly clustered. Each of the D. repleta, D. obscura, and D. melanogaster groups is monophyletic. The splitting of subgenera Drosophila and Sophophora apparently occurred about 40 Mya, whereas the D. repleta group and the Hawaiian drosophilid cluster separated about 32 Mya. By contrast, the splitting of Engiscaptomyza and Scaptomyza occurred only about 11 Mya, suggesting that Scaptomyza experienced a rapid morphological evolution. The D. obscura and D. melanogaster groups apparently diverged about 25 Mya. Many of the D. repleta group species studied here have two functional Adh genes (Adh-1 and Adh-2), and these duplicated genes can be explained by two duplication events.      

Validated predictive modelling of the environmental resistome

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.