New Sorex araneus karyotypes from Germany and the postglacial recolonization of central Europe

New G-banded karyotypes from populations of the common shrew Sorex araneus Linnaeus, 1758 provide a clearer picture of the distribution of chromosome races in central Europe. As expected according to their occurrence in neighbouring countries, the Jutland (kq, no), Laska (k/o) and Drnholec (ko, nr) races are also found in Germany. A new chromosome race "Rugen" (kq) is described from this Baltic Island. Together with the previously recorded races Ulm and Mooswald (kr), six chromosome races are now known from Germany. The resulting distribution pattern is characterized by high frequencies of different race-specific metacentrics at the periphery of the country and clines with decreasing frequencies towards the centre which is occupied by the Ulm race. This race is acrocentric for all chromosome arms involved in the observed race-specific fusions and represents a buffer between the surrounding, more metacentric races. According to the present distribution of these metacentrics, a scenario for the postglacial recolonization of central Europe by S. araneus populations on three different routes is proposed: from the east along the northern slopes of the Carpathian Arc, from the south-east along the Danube Valley and from the south-west through the Upper Rhine Valley.

Vaccination-induced functional competence of circulating human tumor-specific CD8 T-cells.

T-cells specific for foreign (e.g., viral) antigens can give rise to strong protective immune responses, whereas self/tumor antigen-specific T-cells are thought to be less powerful. However, synthetic T-cell vaccines composed of Melan-A/MART-1 peptide, CpG and IFA can induce high frequencies of tumor-specific CD8 T-cells in PBMC of melanoma patients. Here we analyzed the functionality of these T-cells directly ex vivo, by multiparameter flow cytometry. The production of multiple cytokines (IFNγ, TNFα, IL-2) and upregulation of LAMP-1 (CD107a) by tumor (Melan-A/MART-1) specific T-cells was comparable to virus (EBV-BMLF1) specific CD8 T-cells. Furthermore, phosphorylation of STAT1, STAT5 and ERK1/2, and expression of CD3 zeta chain were similar in tumor- and virus-specific T-cells, demonstrating functional signaling pathways. Interestingly, high frequencies of functionally competent T-cells were induced irrespective of patient's age or gender. Finally, CD8 T-cell function correlated with disease-free survival. However, this result is preliminary since the study was a Phase I clinical trial. We conclude that human tumor-specific CD8 T-cells can reach functional competence in vivo, encouraging further development and Phase III trials assessing the clinical efficacy of robust vaccination strategies.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.