Using identity-by-de scent information in affected sib pairs to increase the efficiency of genetic association studies

T he aim of this study was to determine whether identity-by-descent (IBD) information for affected sib pairs (ASPs) can be used to select a sample of cases for a genetic case-control study which will provide more power for detecting association with loci in a known linkage region. By modeling the expected frequency of the disease allele in ASPs showing IBD sharing of 0, 1, or 2 alleles, and considering additive, recessive, and dominant disease models, we show that cases selected from IBD 2 families are best for this purpose, followed by those selected from IBD 1 families; least useful are cases selected from IBD 0 families.

Homologues of the maize rust resistance gene Rp1-D are genetically associated with a major rust resistance QTL in sorghum

As part of a comparative mapping study between sugarcane and sorghum, a sugarcane cDNA clone with homology to the maize Rp1-D rust resistance gene was mapped in sorghum. The cDNA probe hybridised to multiple loci, including one on sorghum linkage group (LG) E in a region where a major rust resistance QTL had been previously mapped. Partial sorghum Rp1-D homologues were isolated from genomic DNA of rust-resistant and -susceptible progeny selected from a sorghum mapping population. Sequencing of the Rp1-D homologues revealed five discrete sequence classes: three from resistant progeny and two from susceptible progeny. PCR primers specific to each sequence class were used to amplify products from the progeny and confirmed that the five sequence classes mapped to the same locus on LG E. Cluster analysis of these sorghum sequences and available sugarcane, maize and sorghum Rp1-D homologue sequences showed that the maize Rp1-D sequence and the partial sugarcane Rp1-D homologue were clustered with one of the sorghum resistant progeny sequence classes, while previously published sorghum Rp1-D homologue sequences clustered with the susceptible progeny sequence classes. Full-length sequence information was obtained for one member of a resistant progeny sequence class (Rp1-SO) and compared with the maize Rp1-D sequence and a previously identified sorghum Rp1 homologue (Rph1-2). There was considerable similarity between the two sorghum sequences and less similarity between the sorghum and maize sequences. These results suggest a conservation of function and gene sequence homology at the Rp1 loci of maize and sorghum and provide a basis for convenient PCR-based screening tools for putative rust resistance alleles in sorghum.

Genetic study of alcoholism and novel gene expression in the alcoholic brain

Alcohol dependence may result from neuroadaptation involving alteration of gene expression after long-term alcohol exposure. The systematic study of gene expression profiles of the human alcoholic brain was initiated using the method of polymerase chain reaction (PCR)-differential display and was followed by DNA microarray. To date, more than 100 alcohol-responsive genes have been identified from the frontal cortex, motor cortex and nucleus accumbens of the human brain. These genes have a wide range of functions in the brain and indicate diverse actions of alcohol on neuronal function. This review discusses the current information on the genetic basis of alcoholism and the induction and characterization of these alcohol-responsive genes.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Detection sensitivity and quantitation of Plasmodium falciparum var gene transcripts by real-time RT-PCR in comparison with conventional RT-PCR

Antigenic variation in Plasmodium falciparum erythrocyte membrane protein 1, caused by a switch in transcription of the encoding var gene, is an important feature of malaria. In this study, we quantified the relative abundance of var gene transcripts present in P. falciparum parasite clones using real-time reverse transcription-polymerase chain reaction (RT-PCR) and conventional RT-PCR combined with cloning and sequencing, with the aim of directly comparing the results obtained. When there was sufficient abundance of RNA for the real-time RT-PCR assay to be operating within the region of good reproducibility, RT-PCR and real-time RT-PCR tended to identify the same dominant transcript, although some transcript-specific issues were identified. When there were differences in the estimated relative amounts of minor transcripts, the RT-PCR assay tended to produce higher estimates than real-time RT-PCR. These results provide valuable information comparing RT-PCR and real-time RT-PCR analysis of samples with small quantities of RNA as might be expected in the analysis of field or clinical samples.

Development of the Minimum Information Specification for in situ Hybridization and Immunohistochemistry Experiments (MISFISHIE)

We describe the creation process of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Modeled after the existing minimum information specification for microarray data, we created a new specification for gene expression localization experiments, initially to facilitate data sharing within a consortium. After successful use within the consortium, the specification was circulated to members of the wider biomedical research community for comment and refinement. After a period of acquiring many new suggested requirements, it was necessary to enter a final phase of excluding those requirements that were deemed inappropriate as a minimum requirement for all experiments. The full specification will soon be published as a version 1.0 proposal to the community, upon which a more full discussion must take place so that the final specification may be achieved with the involvement of the whole community. This paper is part of the special issue of OMICS on data standards.

The human genome and gene expression profiling

The mapping and sequencing of the human genome has generated a large resource for answering questions about human disease. This achievement is akin in scientific importance to developing the periodic table of elements. Plastic surgery has always been at the frontier medical research. This resource will help us to improve our understanding on the many unknown physiological and pathogical conditions we deal with daily, such as wound heating keloid scar formation, Dupuytren's disease, rheumatoid arthritis, vascular malformation and carcinogenesis. We are primed in obtaining both disease and normal tissues to use this resource and applying it to clinical use. This review is about the human genome, the basis of gene expression profiling and how it will affect our clinical and research practices in the future and for those embarking on the use of this new technology as a research tool, we provide a brief insight on its limitations and pitfalls. (C) 2006 The British Association of Plastic Surgeons. Published by Elsevier Ltd. All rights reserved.