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.

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloe festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource, They permit the interrogation of 3806 Neotyphodium genes (Nchip (TM) rnicroarray), and 4195 Neotyphodium and 920 Epichloe genes (EndoChip (TM) microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass-symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloe was performed. (c) 2006 Elsevier

Microarray-based comparative genomic hybridisation of breast cancer patients receiving neoadjuvant chemotherapy

We analysed the molecular genetic profiles of breast cancer samples before and after neoadjuvant chemotherapy with combination doxorubicin and cyclophosphamide (AC). DNA was obtained from microdissected frozen breast core biopsies from 44 patients before chemotherapy. Additional samples were obtained before the second course of chemotherapy (D21) and after the completion of the treatment (surgical specimens) in 17 and 21 patients, respectively. Microarray-based comparative genome hybridisation was performed using a platform containing approx5800 bacterial artificial chromosome clones (genome-wide resolution: 0.9 Mb). Analysis of the 44 pretreatment biopsies revealed that losses of 4p, 4q, 5q, 12q13.11–12q13.12, 17p11.2 and 17q11.2; and gains of 1p, 2p, 7q, 9p, 11q, 19p and 19q were significantly associated with oestrogen receptor negativity. 16q21–q22.1 losses were associated with lobular and 8q24 gains with ductal types. Losses of 5q33.3–q4 and 18p11.31 and gains of 6p25.1–p25.2 and Xp11.4 were associated with HER2 amplification. No correlations between DNA copy number changes and clinical response to AC were found. Microarray-based comparative genome hybridisation analysis of matched pretreatment and D21 biopsies failed to identify statistically significant differences, whereas a comparison between matched pretreatment and surgical samples revealed a statistically significant acquired copy number gain on 11p15.2–11p15.5. The modest chemotherapy-driven genomic changes, despite profound loss of cell numbers, suggest that there is little therapeutic selection of resistant non-modal cell lineages.

On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

Microarray and proteomic analysis of the human alcoholic brain

The superior frontal cortex (SFC) is selectively damaged in chronic alcohol abuse, with localized neuronal loss and tissue atrophy. Regions such as motor cortex show little neuronal loss except in severe co-morbidity (liver cirrhosis or WKS). Altered gene expression was found in microarray comparisons of alcoholic and control SFC samples [1]. We used Western blots and proteomic analysis to identify the proteins that also show differential expression. Tissue was obtained at autopsy under informed, written consent from uncomplicated alcoholics and age- and sex-matched controls. Alcoholics had consumed 80 g ethanol/day chronically (often, 200 g/day for 20 y). Controls either abstained or were social drinkers ( 20 g/day). All subjects had pathological confirmation of liver and brain diagnosis; none had been polydrug abusers. Samples were homogenized in water and clarified by brief centrifugation (1000g, 3 min) before storage at –80°C. For proteomics the thawed suspensions were centrifuged (15000g, 50 min) to prepare soluble fractions. Aliquots were pooled from SFC samples from the 5 chronic alcoholics and 5 matched controls used in the previous microarray study [1]. 2-Dimensional electrophoresis was performed in triplicate using 18 cm format pH 4–7 and pH 6–11 immobilized pH gradients for firstdimension isoelectric focusing. Following second-dimension SDS-PAGE the proteins were fluorescently stained and the images collected by densitometry. 182 proteins differed by 2-fold between cases and controls. 141 showed lower expression in alcoholics, 33 higher, and 8 were new or had disappeared. To date 63 proteins have been identified using MALDI-MS and MS-MS. Western blots were performed on uncentrifuged individual samples from 76 subjects (controls, uncomplicated alcoholics and cirrhotic alcoholics). A common standard was run on every gel. After transfer, immunolabeling, and densitometry, the intensities of the unknown bands were compared to those of the standards. We focused on proteins from transcripts that showed clear differences in a series of microarray studies, classified into common sets including Regulators of G-protein Signaling and Myelin-associated proteins. The preponderantly lower level of differentially expressed proteins in alcoholics parallels the microarray mRNA analysis in the same samples. We found that mRNA and protein expression do not frequently correspond; this may help identify pathogenic processes acting at the level of transcription, translation, or post-translationally.

The Pineapple EST sequencing and microarray project

We have initiated an EST sequencing project to survey a range of expressed sequences from green fruit, yellow fruit, roots, and root-knot nematode infected root/gall tissues. In total, 5681 edited EST sequences were retrieved. Clone redundancy was high in the fruit libraries, with the combined fruit 1548 clone sequences clustering into just 634 contigs comprising 191 consensus sequences and 443 singletons. Half of all fruit EST clone sequences clustered within approximately 14 and 9% of contigs from green unripe and yellow ripe libraries respectively, indicating that a small subset of genes dominates the majority of the transcriptome. The root and root/gall libraries had lower levels of redundancy than the fruit libraries. Half of the root/gall ESTs clustered within approximately 40% of all contigs, indicating the roots possess a more complex transcriptome. Contig assembly and cluster analysis revealed major differences in the abundant gene sequences expressed between the unripe green and the ripe yellow fruit tissues, or gene sequences expressed between the weeks 1-4 and weeks 5-10 nematode infected gall vascular cylinder libraries.