Copy Number Variation of KIR Genes Influences HIV-1 Control

The authors that the number of activating and inhibitory KIR genes varies between individuals and plays a role in the regulation of immune mechanisms that determine HIV-1 control

Identification and Classification of Conserved RNA Secondary Structures in the Human Genome

The discoveries of microRNAs and riboswitches, among others, have shown functional RNAs to be biologically more important and genomically more prevalent than previously anticipated. We have developed a general comparative genomics method based on phylogenetic stochastic context-free grammars for identifying functional RNAs encoded in the human genome and used it to survey an eight-way genome-wide alignment of the human, chimpanzee, mouse, rat, dog, chicken, zebra-fish, and puffer-fish genomes for deeply conserved functional RNAs. At a loose threshold for acceptance, this search resulted in a set of 48,479 candidate RNA structures. This screen finds a large number of known functional RNAs, including 195 miRNAs, 62 histone 3′UTR stem loops, and various types of known genetic recoding elements. Among the highest-scoring new predictions are 169 new miRNA candidates, as well as new candidate selenocysteine insertion sites, RNA editing hairpins, RNAs involved in transcript auto regulation, and many folds that form singletons or small functional RNA families of completely unknown function. While the rate of false positives in the overall set is difficult to estimate and is likely to be substantial, the results nevertheless provide evidence for many new human functional RNAs and present specific predictions to facilitate their further characterization

ELECTRONIC COMMUNITIES: A FORUM FOR SUPPORTING WOMEN PROFESSIONALS AND STUDENTS IN TECHNICAL AND SCIENTIFIC FIELDS

These e-lists are a feature of MentorNet’s larger electronic mentoring program and were sponsored t

Building a better bridge: Testing e-training to improve e-mentoring programmes in higher education

ABSTRACT Uniting mentoring with e-mail results in expanded opportunities In this article, we examine one feature of a structured e-mentoring programme, a series of interactive, web-based case studies used as training modules, and test it

Lightning talk: PyPop - a software pipeline for large-scale multilocus population genomics

PyPop (Python for Population Genomics) is an open-source framework for performing large-scale population genetic analyses on multilocus genotype and allele frequency data. It computes tests and measures of Hardy-Weinberg equilibrium (locus-level and individual genotype-level), linkage disequilibrum, and selection, and estimates multi-locus haplotypes. PyPop supplements and extends existing population genetic software incorporating them as modules, modified to accommodate highly polymorphic data, rather than reimplementing them from scratch. It facilitates evolutionary analyses by integrating population genetic statistics within and across populations.

Originally developed to analyze the highly polymorphic genetic data of the human leukocyte antigen region of the human genome, PyPop has applicability to any kind of multilocus genetic data. It was the primary platform for evolutionary analysis of data collected for a major NIH-funded collaborative grant that included over 30 laboratories and 200 populations (Lancaster et al., 2007a,b). PyPop has also been successfully used in studies by our group, with collaborators, and in publications by many independent research teams in over 70 peer reviewed papers.

PyPop deploys a standard Extensible Markup Language (XML) output format and integrates the results of multiple analyses on various populations that were performed at different times into a common output format that can be read into a spreadsheet. The XML output format allows PyPop to be embedded as part of larger analysis pipelines. It also features an Application Programming Interface (API) allowing functionality to be incorporated into other programs. This lightning talk will focus on recent features of PyPop which include the prefiltering of the input genotype data and the ability to translate arbitrary allele names into full amino acid or nucleotide sequences.

All code is made available under the terms of the GNU General Public License (GNU GPL):

Homepage: http://www.pypop.org/

References:

Lancaster, A. K., M. P. Nelson, R. M. Single, D. Meyer, and G. Thomson, 2007a Software framework for the Biostatistics Core of the International Histocompatibility Working Group. In J. A. Hansen, editor, Immunobiology of the Human MHC: Proceedings of the 13th International Histocompatibility Workshop and Conference, volume I. Seattle, WA: IHWG Press, 510-517.

Lancaster, A. K., R. M. Single, O. D. Solberg, M. P. Nelson, and G. Thomson, 2007b PyPop update–a software pipeline for large-scale multilocus population genomics. Tissue Antigens 69 Suppl 1:192-7

Diversity of MICA and Linkage Disequilibrium with HLA-B in Two North American Populations

The MICA gene has a high degree of polymorphism. Allelic variation of MICA may influence binding of these ligands to the NK cell receptor NKG2D and may affect organ transplantation and/or disease pathogenesis. Knowledge of the population distribution of MICA alleles and their linkage disequilibrium (LD) with class I human leukocyte antigen (HLA) will enhance our understanding of the potential functional significance of the MICA polymorphism. In the present study, we characterized the MICA and HLA-B polymorphisms in two North American populations: European and African. The individual racial groups showed rather limited variation at the MICA locus, where the same set of three most common alleles, MICA*00201, *004, and *00801, account for 64 and 71% of the allele frequency in European-Americans and African-Americans, respectively. Other common alleles (allele frequency \u3e5% in a population) include MICA*00901 and *010. MICA alleles showed strong linkage disequilibrium with HLA-B. Typically, a common MICA allele has strong LD with several HLA-B alleles, whereas most HLA-B alleles and their related serological groups are associated with a single MICA allele. The lack of evidence for an active diversification of the MICA gene after racial separation indicates an evolutionary history distinct from that of the classical HLA genes