Molecular evolution of mitochondrial 12S RNA and cytochrome b sequences in the pantherine lineage of Felidae

DNA sequence comparisons of two mitochondrial DNA genes were used to infer phylogenetic relationships among 17 Felidae species, notably 15 in the previously described pantherine lineage. The polymerase chain reaction (PCR) was used to generate sequences of 358 base pairs of the mitochondrial 12S RNA gene and 289 base pairs of the cytochrome b protein coding gene. DNA sequences were compared within and between 17 felid and five nonfelid carnivore species. Evolutionary trees were constructed using phenetic, cladistic, and maximum likelihood algorithms. The combined results suggested several phylogenetic relationships including (1) the recognition of a recently evolved monophyletic genus Panthera consisting of Panthera leo, P. pardus, P. onca, P. uncia, P. tigris, and Neofelis nebulosa; (2) the recent common ancestry of Acinonyx jubatus, the African cheetah, and Puma concolor, the American puma; and (3) two golden cat species, Profelis temmincki and Profelis aurata, are not sister species, and the latter is strongly associated with Caracal caracal. These data add to the growing database of vertebrate mtDNA sequences and, given the relatively recent divergence among the felids represented here (1-10 Myr), allow 12S and cytochrome b sequence evolution to be addressed over a time scale different from those addressed in most work on vertebrate mtDNA.      

Acceptor specificity of the human leukocyte alpha3 fucosyltransferase: role of FucT-VII in the generation of selectin ligands

The alpha3 fucosyltransferase, FucT-VII, is one of the key glycosyltransferases involved in the biosynthesis of the sialyl Lewis X (sLex) antigen on human leukocytes. The sialyl Lewis X antigen (NeuAcalpha(2-3)Galbeta(1-4)[Fucalpha(1-3)]GlcNAc-R) is an essential component of the recruitment of leukocytes to sites of inflammation, mediating the primary interaction between circulating leukocytes and activated endothelium. In order to characterize the enzymatic properties of the leukocyte alpha3 fucosyltransferase FucT-VII, the enzyme has been expressed in Trichoplusia ni insect cells. The enzyme is capable of synthesizing both sLexand sialyl-dimeric-Lexstructures in vitro , from 3'-sialyl-lacNAc and VIM-2 structures, respectively, with only low levels of fucose transfer observed to neutral or 3'-sulfated acceptors. Studies using fucosylated NeuAcalpha(2-3)-(Galbeta(1- 4)GlcNAc)3-Me acceptors demonstrate that FucT-VII is able to synthesize both di-fucosylated and tri-fucosylated structures from mono- fucosylated precursors, but preferentially fucosylates the distal GlcNAc within a polylactosamine chain. Furthermore, the rate of fucosylation of the internal GlcNAc residues is reduced once fucose has been added to the distal GlcNAc. These results indicate that FucT-VII is capable of generating complex selectin ligands, in vitro , however the order of fucose addition to the lactosamine chain affects the rate of selectin ligand synthesis.      

Contribution of subsurface peat to CO2 and CH4 fluxes in a neotropical peatland

Tropical peatlands play an important role in the global carbon cycling but little is known about factors regulating carbon dioxide (CO₂) and methane (CH₄) fluxes from these ecosystems. Here, we test the hypotheses that (i) CO₂ and CH₄ are produced mainly from surface peat and (ii) that the contribution of subsurface peat to net C emissions is governed by substrate availability. To achieve this, in situ and ex situ CO₂ and CH₄ fluxes were determined throughout the peat profiles under three vegetation types along a nutrient gradient in a tropical ombrotrophic peatland in Panama. The peat was also characterized with respect to its organic composition using ¹³C solid state cross‐polarization magic‐angle spinning nuclear magnetic resonance spectroscopy. Deep peat contributed substantially to CO₂ effluxes both with respect to actual in situ and potential ex situ fluxes. CH₄ was produced throughout the peat profile with distinct subsurface peaks, but net emission was limited by oxidation in the surface layers. CO₂ and CH₄ production were strongly substrate‐limited and a large proportion of the variance in their production (30% and 63%, respectively) was related to the quantity of carbohydrates in the peat. Furthermore, CO₂ and CH₄ production differed between vegetation types, suggesting that the quality of plant‐derived carbon inputs is an important driver of trace gas production throughout the peat profile. We conclude that the production of both CO₂ and CH₄ from subsurface peat is a substantial component of the net efflux of these gases, but that gas production through the peat profile is regulated in part by the degree of decomposition of the peat.     

Identification of an S-locus glycoprotein allele introgressed from B. napus ssp. rapifera to B. napus ssp. oleifera.

We have previously described a developmentally regulated mRNA in maize that accumulates in mature embryos and is involved in a variety of stress responses in the plant. The sequence of the encoded 16 kDa protein (MA16) predicts that it is an RNA-binding protein, since it possesses a ribonucleoprotein consensus sequence-type RNA-binding domain (CS-RBD). To assess the predicted RNA binding property of the protein and as a starting point to characterize its function we have used ribohomopolymer-binding assays. Here we show that the MA16-encoded protein binds preferentially to uridine- and guanosine-rich RNAs. In light of these results a likely role for this protein in RNA metabolism during late embryogenesis and in the stress response is discussed.     

Estimation of heterozygosity for single-probe multilocus DNA fingerprints

In spite of the increasing application of DNA fingerprinting to natural populations and to the genetic identification of humans, explicit methods for estimation of basic population genetic parameters from DNA fingerprinting data have not been developed. Contributing to this omission is the inability to determine, for multilocus fingerprinting probes, relatively important genetic information, such as the number of loci, the number of alleles, and the distribution of these alleles into specific loci. One of the most useful genetic parameters that could be derived from such data would be the average heterozygosity, which has traditionally been employed to measure the level of genetic variation within populations and to compare genetic variation among different loci. We derive here explicit formulas for both the estimation of average heterozygosity at multiple hypervariable loci and a maximum value for this estimate. These estimates are based upon the DNA restriction-pattern matrices that are typical for fingerprinting studies of humans and natural populations. For several empirical data sets from our laboratory, estimates of average and maximal heterozygosity are shown to be relatively close to each other. Furthermore, variances of these statistics based on simulation studies are relatively small. These observations, as well as consideration of the effect of missing alleles and alternate numbers of loci, suggest that the average heterozygosity can be accurately estimated using phenotypic DNA fingerprint patterns, because this parameter is relatively insensitive to the lack of certain genetic information.      

PDA: Pooled DNA analyzer

Background  

Association mapping using abundant single nucleotide polymorphisms is a powerful tool for identifying disease susceptibility genes for complex traits and exploring possible genetic diversity. Genotyping large numbers of SNPs individually is performed routinely but is cost prohibitive for large-scale genetic studies. DNA pooling is a reliable and cost-saving alternative genotyping method. However, no software has been developed for complete pooled-DNA analyses, including data standardization, allele frequency estimation, and single/multipoint DNA pooling association tests. This motivated the development of the software, 'PDA' (Pooled DNA Analyzer), to analyze pooled DNA data.     

A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

Background

Winter migration of immature brown trout (Salmo trutta) into freshwater rivers has been hypothesized to result from physiologically stressful combinations of high salinity and low temperature in the sea.

Results

We sampled brown trout from two Danish populations entering different saline conditions and quantified expression of the hsp70 and Na/K-ATPases α 1b genes following acclimation to freshwater and full-strength seawater at 2°C and 10°C. An interaction effect of low temperature and high salinity on expression of both hsp70 and Na/K-ATPase α 1b was found in trout from the river entering high saline conditions, while a temperature independent up-regulation of both genes in full-strength seawater was found for trout entering marine conditions with lower salinities.

Conclusion

Overall our results support the hypothesis that physiologically stressful conditions in the sea drive sea-run brown trout into freshwater rivers in winter. However, our results also demonstrate intra-specific differences in expression of important stress and osmoregulative genes most likely reflecting adaptive differences between trout populations on a regional scale, thus strongly suggesting local adaptations driven by the local marine environment.     

Evaluation of approaches for measuring taxonomic completeness of lake profundal macroinvertebrate assemblages

1. Benthic macroinvertebrates (MI) are commonly used to assess freshwater ecosystems with the reference condition approach. Such assessments necessitate control for natural community variation, either by categorical typologies or by predictive models that have been widely and successfully developed for running water biota but not previously for lake profundal invertebrates. 2. We evaluated four modelling techniques [multivariate regression tree (MRT), limiting environmental differences, nonparametric multiplicative regression (NPMR) and River Invertebrate Prediction And Classification System (RIVPACS) and the operative Finnish lake typology for assessing taxonomic completeness (observed‐to‐expected number of taxa, O/E) of profundal MI assemblages. We used data from 74 and 33 minimally disturbed reference lake basins for calibration and validation of the approaches, respectively, and 72 test basins subject to various anthropogenic pressures to evaluate sensitivity to detect impact. Either all predicted taxa (threshold probability of capture P_t = 0+) or only those predicted to be captured with ≥0.25 probability were used to calculate O/E. 3. With P_t = 0.25, all four modelling approaches were accurate (mean O/E = 0.966–1.053) but imprecise (SD of O/E = 0.279–0.304) in predicting the fauna actually observed in validation sites. All models were subtly more precise than a null model (mean 1.038, SD 0.343) or the typology (1.046, 0.327). The taxon‐specific NPMR model was slightly more precise than the other three models based on site groupings. 4. The O/E values correlated relatively weakly (r = 0.55–0.86) among the approaches, which thus produced contrasting lake‐specific assessments, despite their seemingly comparable performances. Indeed, typology, suggesting that MI assemblages were impaired in 56% of test sites, was more sensitive than the other approaches (26–46%) as an indicator of human‐induced deterioration. However, this greater ostensible sensitivity seemed to be biased, as lake morphometry, a main driver of natural community variation, remained uncontrolled by the typology. 5. Generally, our exercise illustrates the inconclusiveness of the common validation criteria for the assessment methods. The apparent poor predictability of the profundal fauna, irrespective of the method, may partly stem from large observation error, which could be alleviated by more intensive sampling. However, instead of an O/E‐taxa index, some other metric encompassing quantitative aspects might be preferable for assessing these species‐poor communities.     

Systems modeling: a pathway to drug discovery

Systems modeling is emerging as a valuable tool in therapeutics. This is seen by the increasing use of clinically relevant computational models and a rise in systems biology companies working with the pharmaceutical industry. Systems models have helped understand the effects of pharmacological intervention at receptor, intracellular and intercellular communication stages of cell signaling. For instance, angiogenesis models at the ligand-receptor interaction level have suggested explanations for the failure of therapies for cardiovascular disease. Intracellular models of myeloma signaling have been used to explore alternative drug targets and treatment schedules. Finally, modeling has suggested novel approaches to treating disorders of intercellular communication, such as diabetes. Systems modeling can thus fill an important niche in therapeutics by making drug discovery a faster and more systematic process.