Compensatory nature of Chargaff’s second parity rule

The second parity rule of Chargaff (A≈T and G≈C within one strand) holds all over the living world with minor exceptions. It is maintained with higher accuracy for long sequences. The question addressed in the article is how different sequence types, with different biases from the parity, contribute to the general effect. It appears that the sequence segments with biases of opposite sign are intermingled, so that with sufficient sequence lengths the parity is established. The parity rule seems to be a cumulative result of a number of independent processes in the genome evolution, with the parity as their intrinsic property. Symmetrical appearance of simple repeats and of Alu sequences in the human DNA strands, and other contributions to the Chargaff parity II rule are discussed.     

Molecular characterization influencing metal resistance in the Cupriavidus/Ralstonia genomes

Our environment is stressed with a load of heavy and toxic metals. Microbes, abundant in our environment, are found to adapt well to this metal-stressed condition. A comparative study among five Cupriavidus/Ralstonia genomes can offer a better perception of their evolutionary mechanisms to adapt to these conditions. We have studied codon usage among 1051 genes common to all these organisms and identified 15 optimal codons frequently used in highly expressed genes present within 1051 genes. We found the core genes of Cupriavidus metallidurans CH34 have a different optimal codon choice for arginine, glycine and alanine in comparison with the other four bacteria. We also found that the synonymous codon usage bias within these 1051 core genes is highly correlated with their gene expression. This supports that translational selection drives synonymous codon usage in the core genes of these genomes. Synonymous codon usage is highly conserved in the core genes of these five genomes. The only exception among them is C. metallidurans CH34. This genomewide shift in synonymous codon choice in C. metallidurans CH34 may have taken place due to the insertion of new genes in its genomes facilitating them to survive in heavy metal containing environment and the co-evolution of the other genes in its genome to achieve a balance in gene expression. Structural studies indicated the presence of a longer N-terminal region containing a copper-binding domain in the cupC proteins of C. metallidurans CH3 that helps it to attain higher binding efficacy with copper in comparison with its orthologs.     

Band reporting rates of waterfowl: does individual heterogeneity bias estimated survival rates?

In capture–recapture studies, the estimation accuracy of demographic parameters is essential to the efficacy of management of hunted animal populations. Dead recovery models based upon the reporting of rings or bands are often used for estimating survival of waterfowl and other harvested species. However, distance from the ringing site or condition of the bird may introduce substantial individual heterogeneity in the conditional band reporting rates (r), which could cause bias in estimated survival rates (S) or suggest nonexistent individual heterogeneity in S. To explore these hypotheses, we ran two sets of simulations (n = 1000) in MARK using Seber''s dead recovery model, allowing time variation on both S and r. This included a series of heterogeneity models, allowing substantial variation on logit(r), and control models with no heterogeneity. We conducted simulations using two different values of S: S = 0.60, which would be typical of dabbling ducks such as mallards (Anas platyrhynchos), and S = 0.80, which would be more typical of sea ducks or geese. We chose a mean reporting rate on the logit scale of −1.9459 with SD = 1.5 for the heterogeneity models (producing a back-transformed mean of 0.196 with SD = 0.196, median = 0.125) and a constant reporting rate for the control models of 0.196. Within these sets of simulations, estimation models where σ_S = 0 and σ_S > 0 (σ_S is SD of individual survival rates on the logit scale) were incorporated to investigate whether real heterogeneity in r would induce apparent individual heterogeneity in S. Models where σ_S = 0 were selected approximately 91% of the time over models where σ_S > 0. Simulation results showed < 0.05% relative bias in estimating survival rates except for models estimating σ_S > 0 when true S = 0.8, where relative bias was a modest 0.5%. These results indicate that considerable variation in reporting rates does not cause major bias in estimated survival rates of waterfowl, further highlighting the robust nature of dead recovery models that are being used for the management of harvested species.     

Confidence interval of intrinsic optimum temperature estimated using thermodynamic SSI model

The intrinsic optimum temperature for the development of ectotherms is one of the most important factors not only for their physiological processes but also for ecological and evolutional processes. The Sharpe–Schoolfield–Ikemoto (SSI) model succeeded in defining the temperature that can thermodynamically meet the condition that at a particular temperature the probability of an active enzyme reaching its maximum activity is realized. Previously, an algorithm was developed by Ikemoto (Tropical malaria does not mean hot environments. Journal of Medical Entomology, 45, 963–969) to estimate model parameters, but that program was computationally very time consuming. Now, investigators can use the SSI model more easily because a full automatic computer program was designed by Shi et al. (A modified program for estimating the parameters of the SSI model. Environmental Entomology, 40, 462–469). However, the statistical significance of the point estimate of the intrinsic optimum temperature for each ectotherm has not yet been determined. Here, we provided a new method for calculating the confidence interval of the estimated intrinsic optimum temperature by modifying the approximate bootstrap confidence intervals method. For this purpose, it was necessary to develop a new program for a faster estimation of the parameters in the SSI model, which we have also done.     

Single‐nucleotide polymorphism discovery and diversity in the model legume Medicago truncatula

Extensive genomic resources are available in the model legume Medicago truncatula. Here, we present the discovery and design of the first array of single‐nucleotide polymorphism (SNP) markers in M. truncatula through large‐scale Sanger resequencing of genomic fragments spanning the genome, in a diverse panel of 16 M. truncatula accessions. Both anonymous fragments and fragments targeting candidate genes for flowering phenology and symbiosis were surveyed for nucleotide variation in almost 230 kb of unique genomic regions. A set of 384 SNP markers was designed for an Illumina's GoldenGate assay, genotyped on a collection of 192 inbred lines (CC192) representing the geographical range of the species and used to survey the diversity of two natural populations. Finally, 86% of the tested SNPs were of high quality and exhibited polymorphism in the CC192 collection. Even at the population level, we detected polymorphism for more than 50% of the selected SNPs. Analysis of the allele frequency spectrum in the CC192 showed a reduced ascertainment bias, mostly limited to very rare alleles (frequency <0.01). The substantial polymorphism detected at the species and population levels, the high marker quality and the potential to survey large samples of individuals make this set of SNP markers a valuable tool to improve our understanding of the effect of demographic and selective factors that shape the natural genetic diversity within the selfing species Medicago truncatula.     

Lifestyle factors and prostate-specific antigen (PSA) testing in UK Biobank: Implications for epidemiological research

BackgroundThe central role of prostate-specific antigen (PSA) testing in the diagnosis of prostate cancer leads to the possibility that observational studies that report associations between risk factors and prostate cancer could be affected by detection bias. This study aims to investigate whether reported risk factors for prostate cancer are associated with PSA testing in a large middle-aged population-based cohort in the UK.MethodsThe cross-sectional association between a wide range of sociodemographic, lifestyle, dietary and health characteristics with PSA testing was examined in 212,039 men aged 40–69 years in UK Biobank.ResultsA total of 62,022 (29%) men reported they had ever had a PSA test. A wide range of factors was associated with a higher likelihood of PSA testing including age, height, education level, family history of prostate cancer, black ethnic origin, not being in paid/self-employment, living with a wife or partner, having had a vasectomy, being diagnosed with cancer or hypertension and having a high dietary intake of cereal, cooked and salad/raw vegetables, fresh fruit and tea. Conversely, socioeconomic deprivation, Asian ethnic origin, current smoking, low alcohol intake, high body-mass index, high coffee consumption and being diagnosed with diabetes, heart disease or stroke were associated with a lower likelihood of PSA testing.ConclusionsA variety of sociodemographic, lifestyle and health-related characteristics are associated with PSA testing, suggesting that observed associations of some of these traits with risk for prostate cancer in epidemiological studies may be, at least partially, due to detection bias.     

Multidimensional biases,gaps and uncertainties in global plant occurrence information

Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Biases, gaps and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations remain largely unassessed globally. In this synthesis, we propose a conceptual framework for analysing gaps in information coverage, information uncertainties and biases in these metrics along taxonomic, geographical and temporal dimensions, and apply it to all c. 370 000 species of land plants. To this end, we integrated 120 million point‐occurrence records with independent databases on plant taxonomy, distributions and conservation status. We find that different data limitations are prevalent in each dimension. Different metrics of information coverage and uncertainty are largely uncorrelated, and reducing taxonomic, spatial or temporal uncertainty by filtering out records would usually come at great costs to coverage. In light of these multidimensional data limitations, we discuss prospects for global plant ecological and biogeographical research, monitoring and conservation and outline critical next steps towards more effective information usage and mobilisation. Our study provides an empirical baseline for evaluating and improving global floristic knowledge, along with a conceptual framework that can be applied to study other hyperdiverse clades.