Addition of exogenous polypeptides on the mammalian reovirus outer capsid using reverse genetics

Addition of exogenous peptide sequences on viral capsids is a powerful approach to study the process of viral infection or to retarget viruses toward defined cell types. Until recently, it was not possible to manipulate the genome of mammalian reovirus and this was an obstacle to the addition of exogenous sequence tags onto the capsid of a replicating virus. This obstacle has now been overcome by the advent of the plasmid-based reverse genetics system. In the present study, reverse genetics was used to introduce different exogenous peptides, up to 40 amino acids long, at the carboxyl-terminal end of the σ1 outer capsid protein. The tagged viruses obtained were infectious, produce plaques of similar size, and could be easily propagated at hight titers. However, attempts to introduce a 750 nucleotides-long sequence failed, even when it was added after the stop codon, suggesting a possible size limitation at the nucleic acid level.

Simulating Population Genetics of Pathogen Vectors in Changing Landscapes: Guidelines and Application with Triatoma brasiliensis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Tree growth response along an elevational gradient: climate or genetics?

Environment and genetics combine to influence tree growth and should therefore be jointly considered when evaluating forest responses in a warming climate. Here, we combine dendroclimatology and population genetic approaches with the aim of attributing climatic influences on growth of European larch (Larix decidua) and Norway spruce (Picea abies). Increment cores and genomic DNA samples were collected from populations along a ~900-m elevational transect where the air temperature gradient encompasses a ~4 °C temperature difference. We found that low genetic differentiation among populations indicates gene flow is high, suggesting that migration rate is high enough to counteract the selective pressures of local environmental variation. We observed lower growth rates towards higher elevations and a transition from negative to positive correlations with growing season temperature upward along the elevational transect. With increasing elevation there was also a clear increase in the explained variance of growth due to summer temperatures. Comparisons between climate sensitivity patterns observed along this elevational transect with those from Larix and Picea sites distributed across the Alps reveal good agreement, and suggest that tree-ring width (TRW) variations are more climate-driven than genetics-driven at regional and larger scales. We conclude that elevational transects are an extremely valuable platform for understanding climatic-driven changes over time and can be especially powerful when working within an assessed genetic framework.

Reovirus reverse genetics: Incorporation of the CAT gene into the reovirus genome

We have modified the infectious reovirus RNA system so as to generate a reovirus reverse genetics system. The system consists of (i) the plus strands of nine wild-type reovirus genome segments; (ii) transcripts of the genetically modified cDNA form of the tenth genome segment; and (iii) a cell line transformed so as to express the protein normally encoded by the tenth genome segment. In the work described here, we have generated a serotype 3 reovirus into the S2 double-stranded RNA genome segment of which the CAT gene has been cloned. The virus is stable, replicates in cells that have been transformed (so as to express the S2 gene product, protein σ2), and expresses high levels of CAT activity. This technology can be extended to members of the orbivirus and rotavirus genera. This technology provides a powerful system for basic studies of double-stranded RNA virus replication; a nonpathogenic viral vector that replicates to high titers and could be used for clinical applications; and a system for providing nonselectable viral variants (the result of mutations, insertions, and deletions) that could be valuable for the construction of viral vaccine strains against human and animal pathogens.

Allozyme electrophoresis still represents a powerful technique in the management of coral reefs

Understanding genetic variability and gene flow between populations of scleractinian corals separated by one to several hundred kilometers is crucially important as we head into a century of climate change in which an understanding of the connectivity of populations is a critically important question in management. Genetic methods that directly use molecular variance in the DNA should offer greater precision in detecting differences among individuals and populations than the more traditional allozyme electrophoresis. However, this paper highlights the point that the limited number of DNA markers that have been identified for scleractinian coral genetic studies do not necessarily offer greater precision than that offered by allozymes. In fact, at present allozyme electrophoresis yields greater information than the eight different DNA markers used in this study. Given the relative ease of use of allozymes and the wealth of comparable data sets from numerous previously published studies, allozyme electrophoresis should not be dismissed for population structure and connectivity studies on coral reefs. While continued effort should be placed into searching for new DNA markers, until a more sensitive DNA marker becomes available for scleractinian corals, allozyme electrophoresis remains a powerful and relevant technique for understanding the connectivity of coral population studies.

Genetics and genomics of osteoclast differentiation: Integrating cell signaling pathways and gene networks

The regulation of osteoclast differentiation in the bone microenvironment is critical for normal bone remodeling, as well as for various human bone diseases. Over the last decade, our knowledge of how osteoclast differentiation occurs has progressed rapidly. We highlight some of the major advances in understanding how cell signaling and transcription are integrated to direct the differentiation of this cell type. These studies used genetic, molecular, and biochemical approaches. Additionally, we summarize data obtained from studies of osteoclast differentiation that used the functional genomic approach of global gene profiling applied to osteoclast differentiation. This genomic data confirms results from studies using the classical experimental approaches and also may suggest new modes by which osteoclast differentiation and function can be modulated. Two conclusions that emerge are that osteoclast differentiation depends on a combination of fairly ubiquitously expressed transcription factors rather than unique osteoclast factors, and that the overlay of cell signaling pathways on this set of transcription factors provides a powerful mechanism to fine tune the differentiation program in response to the local bone microenvironment.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.

Teaching principles of genetics through SNP analysis

An understanding of inheritance requires comprehension of genetic processes at all levels, from molecules to populations. Frequently genetics courses are separated into molecular and organismal genetics and students may fail to see the relationships between them. This is particularly true with human genetics, because of the difficulties in designing experimental approaches which are consistent with ethical restrictions, student abilities and background knowledge, and available time and materials. During 2005 we used analysis of single nucleotide polymorphisms (SNPs) in two genetic regions to enhance student learning and provide a practical experience in human genetics. Students scanned databases to discover SNPs in a gene of interest, used software to design PCR primers and a restriction enzyme based assay for the alleles, and carried out an analysis of the SNP on anonymous individual and family DNAs. The project occupied eight to ten hours per week for one semester, with some time spent in the laboratory and some spent in database searching, reading and writing the report. In completing their projects, students acquired a knowledge of Mendel’s first law (through looking at inheritance patterns), Mendel’s second law and the exceptions (the concepts of linkage and linkage disequilibrium), DNA structure (primer design and restriction enzyme analysis) and function (SNPs in coding and non-coding regions), population genetics and the statistical analysis of allele frequencies, genomics, bioinformatics and the ethical issues associated with the use of human samples. They also developed skills in presentation of results by publication and conference participation. Deficiencies in their understanding (for example of inheritance patterns, gene structure, statistical approaches and report writing) were detected and guidance given during the project. SNP analysis was found to be a powerful approach to enhance and integrate student understanding of genetic concepts.

Characterization of 10 new tetranucleotide microsatellite markers for the European eagle owl, Bubo bubo: Useful tools for conservation strategies

Bubo bubo is the largest owl in the world, showing a wide geographical distribution throughout the Palaearctic region. It underwent a demographic decline in many European countries during the last century and was considered “vulnerable” (Annex II of the CITES). Nowadays, it is classified as “Least Concern” according to IUCN. Despite its ecological importance and conservation status, few polymorphic molecular markers are available to study its diversity and population genetics. We report on the isolation and development of 10 new microsatellites for the Eagle owl, B. bubo. All loci (10 tetra-nucleotide) are characterized by high polymorphism levels. Number of alleles ranged from 5 to 13 and expected heterozygosity varied from 0.733 to 0.840. These microsatellites would be very useful to assess the genetic diversity, connectivity patterns and parentage of B. bubo. This information will allow to establish new conservation strategies and improve the management of the species.

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.