Quantenbauelemente als aktive Sensoren zur Ladungsbestimmung in elektronischen Nanostrukturen

Eine Methode, die Ladungsmenge auf einem Quantenpunkt (QD) zu messen, ist über die Kopplung des QDs an einen in der Nähe liegenden Quantenpunktkontakt (QPC). Die Potentialänderung am Ort des QPCs bei einer Ladungsänderung des QDs schlägt sich in einer messbaren Leitwertänderung des QPCs nieder. Meist verwendet man den QPC als passiven Sensor, d.h. gemessen wird direkt die Leitwertänderung. Dies schränkt den dynamischen Bereich des Sensors erheblich ein, da der Leitwert des Sensors früher oder später auf einem Leitwertplateau landet und damit seine Funktionalität verliert. In dieser Arbeit werden insbesondere aktive Ladungssensoren aus QPCs und QDs in GaAs-AlGaAs- Heterostrukturen untersucht. Um den Sensor auch bei großen Potentialänderungen nutzen zu können, wird die den Leitwert definierende Gatespannung nachgeregelt, so dass der Leitwert konstant bleibt. Die hierfür notwendige Spannungsänderung ist ein direktes Maß für die Ladung auf dem benachbarten QD: Eine Änderung der Ladung um eine Elementarladung führt zu einer Stufe in der notwendigen Sensorspannung. Für die akkurate Herstellung der Nanostrukturen mittels Elektronenstrahllithographie ist eine Korrektur des Proximity-Effekts zwingend erforderlich. Dieser stellt den wesentlichen Beitrag zur Auflösungsbegrenzung bei der Elektronenstrahllithographie dar. Ebenso ist es notwendig das zweidimensionale Elektronengas für Messungen niederohmig zu kontaktieren. In diesem Sinne sind weitere Themen dieser Arbeit die Strukturierung der ohmschen Kontakte zur besseren Kontaktierung und eine neue Methode zur Bestimmung der Punktspreizfunktion für die Korrektur des Proximity-Effekts

High population frequencies of MICA copy number variations originate from independent recombination events

MICA is a stress-induced ligand of the NKG2D receptor that stimulates NK and T cell responses and was identified as a key determinant of anti-tumor immunity. The MICA gene is located inside the MHC complex and is in strong linkage disequilibrium with HLA-B. While an HLA-B*48-linked MICA deletion-haplotype was previously described in Asian populations, little is known about other MICA copy number variations. Here, we report the genotyping of more than two million individuals revealing high frequencies of MICA duplications (1%) and MICA deletions (0.4%). Their prevalence differs between ethnic groups and can rise to 2.8% (Croatia) and 9.2% (Mexico), respectively. Targeted sequencing of more than 70 samples indicates that these copy number variations originate from independent nonallelic homologous recombination events between segmental duplications upstream of MICA and MICB. Overall, our data warrant further investigation of disease associations and consideration of MICA copy number data in oncological study protocols

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations

The killer-cell immunoglobulin-like receptor (KIR) genes regulate natural killer cell activity, influencing predisposition to immune mediated disease, and affecting hematopoietic stem cell transplantation (HSCT) outcome. Owing to the complexity of the KIR locus, with extensive gene copy number variation (CNV) and allelic diversity, high-resolution characterization of KIR has so far been applied only to relatively small cohorts. Here, we present a comprehensive high-throughput KIR genotyping approach based on next generation sequencing. Through PCR amplification of specific exons, our approach delivers both copy numbers of the individual genes and allelic information for every KIR gene. Ten-fold replicate analysis of a set of 190 samples revealed a precision of 99.9%. Genotyping of an independent set of 360 samples resulted in an accuracy of more than 99% taking into account consistent copy number prediction. We applied the workflow to genotype 1.8 million stem cell donor registry samples. We report on the observed KIR allele diversity and relative abundance of alleles based on a subset of more than 300,000 samples. Furthermore, we identified more than 2,000 previously unreported KIR variants repeatedly in independent samples, underscoring the large diversity of the KIR region that awaits discovery. This cost-efficient high-resolution KIR genotyping approach is now applied to samples of volunteers registering as potential donors for HSCT. This will facilitate the utilization of KIR as additional selection criterion to improve unrelated donor stem cell transplantation outcome. In addition, the approach may serve studies requiring high-resolution KIR genotyping, like population genetics and disease association studies

Common, Intermediate and Well-Documented HLA Alleles in World Populations: CIWD Version 3.0.0

A catalog of common, intermediate and well-documented (CIWD) HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQB1 and -DPB1 alleles has been compiled from over 8 million individuals using data from 20 unrelated hematopoietic stem cell volunteer donor registries. Individuals are divided into seven geographic/ancestral/ethnic groups and data are summarized for each group and for the total population. P (two-field) and G group assignments are divided into one of four frequency categories: common (≥1 in 10 000), intermediate (≥1 in 100 000), well-documented (≥5 occurrences) or not-CIWD. Overall 26% of alleles in IPD-IMGT/HLA version 3.31.0 at P group resolution fall into the three CIWD categories. The two-field catalog includes 18% (n = 545) common, 17% (n = 513) intermediate, and 65% (n = 1997) well-documented alleles. Full-field allele frequency data are provided but are limited in value by the variations in resolution used by the registries. A recommended CIWD list is based on the most frequent category in the total or any of the seven geographic/ancestral/ethnic groups. Data are also provided so users can compile a catalog specific to the population groups that they serve. Comparisons are made to three previous CWD reports representing more limited population groups. This catalog, CIWD version 3.0.0, is a step closer to the collection of global HLA frequencies and to a clearer view of HLA diversity in the human population as a whole