Epigenomic regulation of human T-cell leukemia virus by chromatin-insulator CTCF

Human T-cell leukemia virus type 1 (HTLV-1) is a retrovirus that causes an aggressive T-cell malignancy and a variety of inflammatory conditions. The integrated provirus includes a single binding site for the epigenomic insulator, CCCTC-binding protein (CTCF), but its function remains unclear. In the current study, a mutant virus was examined that eliminates the CTCF-binding site. The mutation did not disrupt the kinetics and levels of virus gene expression, or establishment of or reactivation from latency. However, the mutation disrupted the epigenetic barrier function, resulting in enhanced DNA CpG methylation downstream of the CTCF binding site on both strands of the integrated provirus and H3K4Me3, H3K36Me3, and H3K27Me3 chromatin modifications both up- and downstream of the site. A majority of clonal cell lines infected with wild type HTLV-1 exhibited increased plus strand gene expression with CTCF knockdown, while expression in mutant HTLV-1 clonal lines was unaffected. These findings indicate that CTCF binding regulates HTLV-1 gene expression, DNA and histone methylation in an integration site dependent fashion.     

Traditional cultural landscape in Viñales,Cuba

Biodiversity and Conservation - The Viñales Valley has a wide range of biological and cultural values thanks to both its landscape diversity and the use of low-impact agricultural practices....     

A standardized method for quantifying eggshell spot patterns

Spottiness is an important component of the morphology of bird eggs and a number of methods have been developed for characterizing variation in spottiness. We developed a quantitative method for measuring and comparing eggs to determine if female European Cranes (Grus grus) lay eggs with individually distinct color and spotting patterns. We used photographs taken under standard conditions and developed a computer program (ESPANA) to quantify egg‐spot patterns. The goal of the analysis was to create a “fingerprint” of each eggshell by measuring reflection along virtually drawn lines (transects) on an egg's image. Values measured in the same positions along transects can be compared among eggs by considering them as separate variables defining the pattern. Data were analyzed using cluster analyses and by performing analyses of similarity (ANOSIM). We found that the eggs of female European Cranes (N = 11) had individually distinct color patterns, with eggs laid by a given female more similar to each other than to the eggs of other females. Beyond its potential use for identifying the eggs of specific females, we believe our method could also be useful for investigators quantifying differences in egg‐spot patterns for other reasons, for example, examining possible relationships between egg‐spot patterns and female quality. The program ESPANA is implemented using the Java programming language and is available as supporting information on the Journal of Field Ornithology website.     

Partitioning average competition and extreme-genotype effects in genetically diverse infections

Competition between parasite genotypes in genetically diverse infections is widespread. However, experimental evidence on how genetic diversity influences total parasite load is variable. Here we use an additive partition equation to quantify the negative effect of inter-genotypic competition on total parasite load in diverse infections. Our approach controls for extreme-genotype effects, a process that can potentially neutralise, or even reverse, the negative effect of competition on total parasite load. A single extreme-genotype can have a disproportionate effect on total parasite load if it causes the highest parasite load in its single-infection, while increasing its performance in diverse relative to single infections. We show that in theory such disproportionate effects of extreme-genotypes can lead to a higher total parasite load in diverse infections than expected, even if competition reduces individual parasite performance on average. Controlling for the extreme-genotype effect is only possible if the competition effect on total parasite load is measured appropriately as the average difference between the realised number of each parasite genotype in mixed infections and the expected number based on single infection parasite loads. We apply this approach to sticklebacks that were experimentally infected with different trematode genotypes. On average, genetically diverse infections had lower parasite loads than expected from single-infection results. For the first time we demonstrate that competition between co-infecting genotypes per se caused the parasite load reduction, while extreme-genotype effects were not significant. We thus suggest that to correctly quantify the effect of competition alone on total parasite load in genetically diverse infections, the extreme-genotype effect has to be controlled for.