Revisiting Estimates of CTL Killing Rates In Vivo

Recent experimental advances have allowed the estimation of the in vivo rates of killing of infected target cells by cytotoxic T lymphocytes (CTL). We present several refinements to a method applied previously to quantify killing of targets in the spleen using a dynamical model. We reanalyse data previously used to estimate killing rates of CTL specific for two epitopes of lymphocytic choriomeningitis virus (LCMV) in mice and show that, contrary to previous estimates the “killing rate” of effector CTL is approximately twice that of memory CTL. Further, our method allows the fits to be visualized, and reveals one potentially interesting discrepancy between fits and data. We discuss extensions to the basic CTL killing model to explain this discrepancy and propose experimental tests to distinguish between them

Associations of ATR and CHEK1 Single Nucleotide Polymorphisms with Breast Cancer

DNA damage and replication checkpoints mediated by the ATR-CHEK1 pathway are key to the maintenance of genome stability, and both ATR and CHEK1 have been proposed as potential breast cancer susceptibility genes. Many novel variants recently identified by the large resequencing projects have not yet been thoroughly tested in genome-wide association studies for breast cancer susceptibility. We therefore used a tagging SNP (tagSNP) approach based on recent SNP data available from the 1000 genomes projects, to investigate the roles of ATR and CHEK1 in breast cancer risk and survival. ATR and CHEK1 tagSNPs were genotyped in the Sheffield Breast Cancer Study (SBCS; 1011 cases and 1024 controls) using Illumina GoldenGate assays. Untyped SNPs were imputed using IMPUTE2, and associations between genotype and breast cancer risk and survival were evaluated using logistic and Cox proportional hazard regression models respectively on a per allele basis. Significant associations were further examined in a meta-analysis of published data or confirmed in the Utah Breast Cancer Study (UBCS). The most significant associations for breast cancer risk in SBCS came from rs6805118 in ATR (p=7.6x10-5) and rs2155388 in CHEK1 (p=3.1x10-6), but neither remained significant after meta-analysis with other studies. However, meta-analysis of published data revealed a weak association between the ATR SNP rs1802904 (minor allele frequency is 12%) and breast cancer risk, with a summary odds ratio (confidence interval) of 0.90 (0.83-0.98) [p=0.0185] for the minor allele. Further replication of this SNP in larger studies is warranted since it is located in the target region of 2 microRNAs. No evidence of any survival effects of ATR or CHEK1 SNPs were identified. We conclude that common alleles of ATR and CHEK1 are not implicated in breast cancer risk or survival, but we cannot exclude effects of rare alleles and of common alleles with very small effect sizes

Selection for Heterozygosity Gives Hope to a Wild Population of Inbred Wolves

Recent analyses have questioned the usefulness of heterozygosity estimates as measures of the inbreeding coefficient (f), a finding that may have dramatic consequences for the management of endangered populations. We confirm that f and heterozygosity is poorly correlated in a wild and highly inbred wolf population. Yet, our data show that for each level of f, it was the most heterozygous wolves that established themselves as breeders, a selection process that seems to have decelerated the loss of heterozygosity in the population despite a steady increase of f. The markers contributing to the positive relationship between heterozygosity and breeding success were found to be located on different chromosomes, but there was a substantial amount of linkage disequilibrium in the population, indicating that the markers are reflecting heterozygosity over relatively wide genomic regions. Following our results we recommend that management programs of endangered populations include estimates of both f and heterozygosity, as they may contribute with complementary information about population viability

Does Genetic Diversity Predict Health in Humans?

Genetic diversity, especially at genes important for immune functioning within the Major Histocompatibility Complex (MHC), has been associated with fitness-related traits, including disease resistance, in many species. Recently, genetic diversity has been associated with mate preferences in humans. Here we asked whether these preferences are adaptive in terms of obtaining healthier mates. We investigated whether genetic diversity (heterozygosity and standardized mean d2) at MHC and nonMHC microsatellite loci, predicted health in 153 individuals. Individuals with greater allelic diversity (d2) at nonMHC loci and at one MHC locus, linked to HLA-DRB1, reported fewer symptoms over a four-month period than individuals with lower d2. In contrast, there were no associations between MHC or nonMHC heterozygosity and health. NonMHC-d2 has previously been found to predict male preferences for female faces. Thus, the current findings suggest that nonMHC diversity may play a role in both natural and sexual selection acting on human populations

Measurement of the Absolute Magnitude and Time Courses of Mitochondrial Membrane Potential in Primary and Clonal Pancreatic Beta-Cells

The aim of this study was to simplify, improve and validate quantitative measurement of the mitochondrial membrane potential (ΔψM) in pancreatic β-cells. This built on our previously introduced calculation of the absolute magnitude of ΔψM in intact cells, using time-lapse imaging of the non-quench mode fluorescence of tetramethylrhodamine methyl ester and a bis-oxonol plasma membrane potential (ΔψP) indicator. ΔψM is a central mediator of glucose-stimulated insulin secretion in pancreatic β-cells. ΔψM is at the crossroads of cellular energy production and demand, therefore precise assay of its magnitude is a valuable tool to study how these processes interplay in insulin secretion. Dispersed islet cell cultures allowed cell type-specific, single-cell observations of cell-to-cell heterogeneity of ΔψM and ΔψP. Glucose addition caused hyperpolarization of ΔψM and depolarization of ΔψP. The hyperpolarization was a monophasic step increase, even in cells where the ΔψP depolarization was biphasic. The biphasic response of ΔψP was associated with a larger hyperpolarization of ΔψM than the monophasic response. Analysis of the relationships between ΔψP and ΔψM revealed that primary dispersed β-cells responded to glucose heterogeneously, driven by variable activation of energy metabolism. Sensitivity analysis of the calibration was consistent with β-cells having substantial cell-to-cell variations in amounts of mitochondria, and this was predicted not to impair the accuracy of determinations of relative changes in ΔψM and ΔψP. Finally, we demonstrate a significant problem with using an alternative ΔψM probe, rhodamine 123. In glucose-stimulated and oligomycin-inhibited β-cells the principles of the rhodamine 123 assay were breached, resulting in misleading conclusion

Data from: Lineage-specific mapping of quantitative trait loci

We present an approach for quantitative trait locus (QTL) mapping, termed "lineage-specific QTL mapping", for inferring allelic changes of QTL evolution along branches in a phylogeny. We describe and analyze the simplest case: by adding a third taxon into the normal procedure of QTL mapping between pairs of taxa, such inferences can be made along lineages to a presumed common ancestor. While comparisons of QTL maps among species can identify homology of QTLs by apparent co-location, lineage specific mapping of QTL can classify homology into (1) orthology (shared origin of QTL) versus (2) paralogy (independent origin of QTL within resolution of map distance). In this light, we present a graphical method that identifies six modes of QTL evolution in a three taxon comparison. We then apply our model to map lineage-specific QTLs for inbreeding among three taxa of yellow monkeyflower: Mimulus guttatus and two inbreeders M. platycalyx and M. micranthus, but critically assuming outcrossing was the ancestral state. The two most common modes of homology across traits were orthologous (shared ancestry of mutation for QTL alleles). The outbreeder M. guttatus had the fewest lineage- specific QTL, in accordance with the presumed ancestry of outbreeding. Extensions of lineage-specific QTL mapping to other types of data and crosses, and to inference of ancestral QTL state, are discussed