Cell-type-specific transcriptomics in chimeric models using transcriptome-based masks

Association of the Sp1 binding site and -1997 promoter variations in COL1A1 with osteoporosis risk: The application of meta-analysis and bioinformatics approaches offers a new perspective for future research

As a complex disease, osteoporosis is influenced by several genetic markers. Many studies have examined the link between the Sp1 binding site +1245 G > T (rs1800012) and -1997 G > T (rs1107946) variations in the COL1A1 gene with osteoporosis risk. However, the findings of these studies have been contradictory; therefore, we performed a meta-analysis to aggregate additional information and obtain increased statistical power to more efficiently estimate this correlation. A meta-analysis was conducted with studies published between 1991-2020 that were identified by a systematic electronic search of the Scopus and Clarivate Analytics databases. Studies with bone mineral density (BMD) data and complete genotypes of the single-nucleotide variations (SNVs) for the overall and postmenopausal female population were included in this meta-analysis and analyzed using the R metaphor package. A relationship between rs1800012 and significantly decreased BMD values at the lumbar spine and femoral neck was found in individuals carrying the "ss" versus the "SS" genotype in the overall population according to a random effects model (p < 0.0001). Similar results were also found in the postmenopausal female population (p = 0.003 and 0.0002, respectively). Such findings might be an indication of increased osteoporosis risk in both studied groups in individuals with the "ss" genotype. Although no association was identified between the -1997 G > T and low BMD in the overall population, those individuals with the "GT" genotype showed a higher level of BMD than those with "GG" in the subgroup analysis (p = 0.007). To determine which transcription factor (TF) might bind to the -1997 G > T in COL1A1, 45 TFs were identified based on bioinformatics predictions. According to the GSE35958 microarray dataset, 16 of 45 TFs showed differential expression profiles in osteoporotic human mesenchymal stem cells relative to normal samples from elderly donors. By identifying candidate TFs for the -1997 G > T site, our study offers a new perspective for future research.

The angiogenic switch leads to a metabolic shift in human glioblastoma

Background

Invasion and angiogenesis are major hallmarks of glioblastoma (GBM) growth. While invasive tumor cells grow adjacent to blood vessels in normal brain tissue, tumor cells within neovascularized regions exhibit hypoxic stress and promote angiogenesis. The distinct microenvironments likely differentially affect metabolic processes within the tumor cells.

Methods

In the present study, we analyzed gene expression and metabolic changes in a human GBM xenograft model that displayed invasive and angiogenic phenotypes. In addition, we used glioma patient biopsies to confirm the results from the xenograft model.

Results

We demonstrate that the angiogenic switch in our xenograft model is linked to a proneural-to-mesenchymal transition that is associated with upregulation of the transcription factors BHLHE40, CEBPB, and STAT3. Metabolic analyses revealed that angiogenic xenografts employed higher rates of glycolysis compared with invasive xenografts. Likewise, patient biopsies exhibited higher expression of the glycolytic enzyme lactate dehydrogenase A and glucose transporter 1 in hypoxic areas compared with the invasive edge and lower-grade tumors. Analysis of the mitochondrial respiratory chain showed reduction of complex I in angiogenic xenografts and hypoxic regions of GBM samples compared with invasive xenografts, nonhypoxic GBM regions, and lower-grade tumors. In vitro hypoxia experiments additionally revealed metabolic adaptation of invasive tumor cells, which increased lactate production under long-term hypoxia.

Conclusions

The use of glycolysis versus mitochondrial respiration for energy production within human GBM tumors is highly dependent on the specific microenvironment. The metabolic adaptability of GBM cells highlights the difficulty of targeting one specific metabolic pathway for effective therapeutic intervention.

A mouse tissue transcription factor atlas

Transcription factors (TFs) drive various biological processes ranging from embryonic development to carcinogenesis. Here, we employ a recently developed concatenated tandem array of consensus TF response elements (catTFRE) approach to profile the activated TFs in 24 adult and 8 fetal mouse tissues on proteome scale. A total of 941 TFs are quantitatively identified, representing over 60% of the TFs in the mouse genome. Using an integrated omics approach, we present a TF network in the major organs of the mouse, allowing data mining and generating knowledge to elucidate the roles of TFs in various biological processes, including tissue type maintenance and determining the general features of a physiological system. This study provides a landscape of TFs in mouse tissues that can be used to elucidate transcriptional regulatory specificity and programming and as a baseline that may facilitate understanding diseases that are regulated by TFs.

While we have abundant data for transcription factor (TF) binding sites and TF expression at the mRNA level, our knowledge of TFs at the protein level and their DNA-binding activities is sparser. Here, the authors address this by using the catTFRE approach to profile active TFs in 24 adult and 8 fetal mouse tissues, and presenting the TF networks in major mouse organs.

Global transcriptional expression in ovarian follicles from Tsaiya ducks (Anas platyrhynchos) with a high-fertilization rate

Novel candidates for biomarkers of a high-fertilization rate were identified here through global transcriptional profiling of ovarian follicles. Some other differentially expressed candidate genes were first noted to influence animal reproduction in our previous cDNA microarray analysis and are now recognized as markers for marker-assisted selection. In the present study, we compared gene expression in ovarian follicles from animals with high- and low-fertilization rates using an oligonucleotide array. On the basis of a fold change of greater than 1.2 and less than -1.2, a difference of >100 Affymetrix arbitrary units between the two groups, and a P value of less than 0.05, 47 genes were found to be associated with fertilization rate. GOEAST and MetaCore software were further used to identify the functional categories of genes that were differentially expressed. Then, we focused on three interesting genes associated with a high-fertilization rate: one of these genes was discovered to participate in signaling pathways of fertilization, and two genes take roles in lipid metabolism. An oligonucleotide array showed that the levels of orthodenticle homeobox 2 (OTX2) and lecithin:cholesterol acyltransferase (LCAT) gene expression were 1.62-fold and 1.95-fold higher in the high-fertilization rate group than in the low-fertilization rate group, respectively (P < 0.05). The level of apolipoprotein A-I (APOA1) gene expression was also higher in the high-fertilization rate group, with a difference of 2.31-fold (P < 0.05). The data were validated through quantitative polymerase chain reaction analysis. These results confirm the usefulness of the array technique and data mining methods in the discovery of new biomarkers and add knowledge to our understanding of the factors affecting fertilization rates in ovarian follicles.

The molecular signature of the stroma response in prostate cancer-induced osteoblastic bone metastasis highlights expansion of hematopoietic and prostate epithelial stem cell niches

The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

Pdx1 (GFP/w) mice for isolation, characterization, and differentiation of pancreatic progenitor cells

It is well known that human cells are diverse with respect to their epigenome, transcriptome, and proteome. In the context of regenerative medicine, it is important for the transplanted cells or tissues to faithfully recapitulate their intended tissue type in each of these respects. Whether the cells chosen for such an application are embryonic, postnatal, or induced pluripotent stem cells, the transplanted product must behave in a predictable and reliable manner to be a safe and effective treatment option. Irrespective of the choice of cells used in such an application, the characterization and understanding of the developmental cues responsible for establishing and maintaining the desired cell phenotype are essential.Animal models are extremely important in understanding the development of a specific tissue, which can then be subsequently extrapolated to human studies. Generation of transgenic animal models with whole-body gene knockout, conditional knockout, constitutive fluorescent gene reporters, and Cre-Lox-based conditional and lineage reporters has revolutionized the field of developmental biology. An intrinsically complex network of the actions and interactions of the multitude of different signalling cascades is required for development. A thorough understanding of such networks, gained through studies on transgenic animal models, is essential for the development of the techniques necessary to reliably differentiate a given stem or progenitor cell population into a specific cell type, such as an islet-like, insulin-producing cell aggregate.In this chapter, we describe the use of GFP (green fluorescent protein)-based reporter mice for isolation of cells of choice, analyzing gene expression in those cells as well as their use for screening signalling molecules to understand their effect on differentiation.

Gene transcription in the zebrafish embryo: regulators and networks

The precise spatial and temporal control of gene expression is a key process in the development, maintenance and regeneration of the vertebrate body. A substantial proportion of vertebrate genomes encode genes that control the transcription of the genetic information into mRNA. The zebrafish is particularly well suited to investigate gene regulatory networks underlying the control of gene expression during development due to the external development of its transparent embryos and the increasingly sophisticated tools for genetic manipulation available for this model system. We review here recent data on the analysis of cis-regulatory modules, transcriptional regulators and their integration into gene regulatory networks in the zebrafish, using the developing spinal cord as example.

RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers.

Preclinical imaging of the cellular and molecular events in the multistep process of bone metastasis

Bone metastasis is a complex process that ultimately leads to devastating metastatic bone disease. It is therefore of key interest to unravel the mechanisms underlying the multistep process of skeletal metastasis and cancer-induced bone disease, and to develop better treatment and management of patients with this devastating disease. Fortunately, novel technologies are rapidly emerging that allow real-time imaging of molecules, pathogenic processes, drug delivery and drug response in preclinical in vivo models. The outcome of these experimental studies will facilitate clinical cancer research by improving the detection of cancer cell invasion, metastasis and therapy response.

In vivo topoisomerase I inhibition attenuates the expression of hypoxia-inducible factor 1α target genes and decreases tumor angiogenesis

Topoisomerase I is a privileged target for widely used anticancer agents such as irinotecan. Although these drugs are classically considered to be DNA-damaging agents, increasing evidence suggests that they might also influence the tumor environment. This study evaluates in vivo cellular and molecular modifications induced by irinotecan, a topoisomerase I-directed agent, in patient-derived colon tumors subcutaneously implanted in athymic nude mice. Irinotecan was given intraperitoneally at 40 mg/kg five times every 5 d, and expression profiles were evaluated at d 25 in tumors from treated and untreated animals. Unexpectedly, the in vivo antitumor activity of irinotecan was closely linked to a downregulation of hypoxia-inducible factor-1α (HIF1A) target genes along with an inhibition of HIF1A protein accumulation. The consequence was a decrease in tumor angiogenesis leading to tumor size stabilization. These results highlight the molecular basis for the antitumor activity of a widely used anticancer agent, and the method used opens the way for mechanistic studies of the in vivo activity of other anticancer therapies.

Detection of interacting transcription factors in human tissues using predicted DNA binding affinity

Background

Tissue-specific gene expression is generally regulated by combinatorial interactions among transcription factors (TFs) which bind to the DNA. Despite this known fact, previous discoveries of the mechanism that controls gene expression usually consider only a single TF.

Results

We provide a prediction of interacting TFs in 22 human tissues based on their DNA-binding affinity in promoter regions. We analyze all possible pairs of 130 vertebrate TFs from the JASPAR database. First, all human promoter regions are scanned for single TF-DNA binding affinities with TRAP and for each TF a ranked list of all promoters ordered by the binding affinity is created. We then study the similarity of the ranked lists and detect candidates for TF-TF interaction by applying a partial independence test for multiway contingency tables. Our candidates are validated by both known protein-protein interactions (PPIs) and known gene regulation mechanisms in the selected tissue. We find that the known PPIs are significantly enriched in the groups of our predicted TF-TF interactions (2 and 7 times more common than expected by chance). In addition, the predicted interacting TFs for studied tissues (liver, muscle, hematopoietic stem cell) are supported in literature to be active regulators or to be expressed in the corresponding tissue.

Conclusions

The findings from this study indicate that tissue-specific gene expression is regulated by one or two central regulators and a large number of TFs interacting with these central hubs. Our results are in agreement with recent experimental studies.

Preclinical models that illuminate the bone metastasis cascade

In this chapter currently available preclinical models of tumor progression and bone metastasis, including genetically engineered mice that develop primary and metastatic carcinomas and transplantable animal models, will be described. Understanding the multistep process of incurable bone metastasis is pivotal to the development of new therapeutic strategies. Novel technologies for imaging molecules or pathologic processes in cancers and their surrounding stroma have emerged rapidly and have greatly facilitated cancer research, in particular the cellular behavior of osteotropic tumors and their response to new and existing therapeutic agents. Optical imaging, in particular, has become an important tool in preclinical bone metastasis models, clinical trials and medical practice. Advances in experimental and clinical imaging will-in the long run-result in significant improvements in diagnosis, tumor localization, enhanced drug delivery and treatment.

Genome-wide mapping of RNA Pol-II promoter usage in mouse tissues by ChIP-seq

Alternative promoters that are differentially used in various cellular contexts and tissue types add to the transcriptional complexity in mammalian genome. Identification of alternative promoters and the annotation of their activity in different tissues is one of the major challenges in understanding the transcriptional regulation of the mammalian genes and their isoforms. To determine the use of alternative promoters in different tissues, we performed ChIP-seq experiments using antibody against RNA Pol-II, in five adult mouse tissues (brain, liver, lung, spleen and kidney). Our analysis identified 38 639 Pol-II promoters, including 12 270 novel promoters, for both protein coding and non-coding mouse genes. Of these, 6384 promoters are tissue specific which are CpG poor and we find that only 34% of the novel promoters are located in CpG-rich regions, suggesting that novel promoters are mostly tissue specific. By identifying the Pol-II bound promoter(s) of each annotated gene in a given tissue, we found that 37% of the protein coding genes use alternative promoters in the five mouse tissues. The promoter annotations and ChIP-seq data presented here will aid ongoing efforts of characterizing gene regulatory regions in mammalian genomes.

Validation of a mouse xenograft model system for gene expression analysis of human acute lymphoblastic leukaemia

BACKGROUND

Pre-clinical models that effectively recapitulate human disease are critical for expanding our knowledge of cancer biology and drug resistance mechanisms. For haematological malignancies, the non-obese diabetic/severe combined immunodeficient (NOD/SCID) mouse is one of the most successful models to study paediatric acute lymphoblastic leukaemia (ALL). However, for this model to be effective for studying engraftment and therapy responses at the whole genome level, careful molecular characterisation is essential.

RESULTS

Here, we sought to validate species-specific gene expression profiling in the high engraftment continuous ALL NOD/SCID xenograft. Using the human Affymetrix whole transcript platform we analysed transcriptional profiles from engrafted tissues without prior cell separation of mouse cells and found it to return highly reproducible profiles in xenografts from individual mice. The model was further tested with experimental mixtures of human and mouse cells, demonstrating that the presence of mouse cells does not significantly skew expression profiles when xenografts contain 90% or more human cells. In addition, we present a novel in silico and experimental masking approach to identify probes and transcript clusters susceptible to cross-species hybridisation.

CONCLUSIONS

We demonstrate species-specific transcriptional profiles can be obtained from xenografts when high levels of engraftment are achieved or with the application of transcript cluster masks. Importantly, this masking approach can be applied and adapted to other xenograft models where human tissue infiltration is lower. This model provides a powerful platform for identifying genes and pathways associated with ALL disease progression and response to therapy in vivo.

An atlas of combinatorial transcriptional regulation in mouse and man

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

Identification of differentially expressed sense and antisense transcript pairs in breast epithelial tissues

BACKGROUND

More than 20% of human transcripts have naturally occurring antisense products (or natural antisense transcripts--NATs), some of which may play a key role in a range of human diseases. To date, several databases of in silico defined human sense-antisense (SAS) pairs have appeared, however no study has focused on differential expression of SAS pairs in breast tissue. We therefore investigated the expression levels of sense and antisense transcripts in normal and malignant human breast epithelia using the Affymetrix HG-U133 Plus 2.0 and Almac Diagnostics Breast Cancer DSA microarray technologies as well as massively parallel signature sequencing (MPSS) data.

RESULTS

The expression of more than 2500 antisense transcripts were detected in normal breast duct luminal cells and in primary breast tumors substantially enriched for their epithelial cell content by DSA microarray. Expression of 431 NATs were confirmed by either of the other two technologies. A corresponding sense transcript could be identified on DSA for 257 antisense transcripts. Of these SAS pairs, 163 have not been previously reported. A positive correlation of differential expression between normal and malignant breast samples was observed for most SAS pairs. Orientation specific RT-QPCR of selected SAS pairs validated their expression in several breast cancer cell lines and solid breast tumours.

CONCLUSION

Disease-focused and antisense enriched microarray platforms (such as Breast Cancer DSA) confirm the assumption that antisense transcription in the human breast is more prevalent than previously anticipated. Expression of a proportion of these NATs has already been confirmed by other technologies while the true existence of the remaining ones has to be validated. Nevertheless, future studies will reveal whether the relative abundances of antisense and sense transcripts have regulatory influences on the translation of these mRNAs.

Nuclear reprogramming in heterokaryons is rapid, extensive, and bidirectional

An understanding of nuclear reprogramming is fundamental to the use of cells in regenerative medicine. Due to technological obstacles, the time course and extent of reprogramming of cells following fusion has not been assessed to date. Here, we show that hundreds of genes are activated or repressed within hours of fusion of human keratinocytes and mouse muscle cells in heterokaryons, and extensive changes are observed within 4 days. This study was made possible by the development of a broadly applicable approach, species-specific transcriptome amplification (SSTA), which enables global resolution of transcripts derived from the nuclei of two species, even when the proportions of species-specific transcripts are highly skewed. Remarkably, either phenotype can be dominant; an excess of primary keratinocytes leads to activation of the keratinocyte program in muscle cells and the converse is true when muscle cells are in excess. We conclude that nuclear reprogramming in heterokaryons is rapid, extensive, bidirectional, and dictated by the balance of regulators contributed by the cell types.

Impact of normalization on miRNA microarray expression profiling

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Contaminating cells alter gene signatures in whole organ versus laser capture microdissected tumors: a comparison of experimental breast cancers and their lymph node metastases

Genome-wide expression profiling has expedited our molecular understanding of the different subtypes of breast cancers, as well as defined the differences among genes expressed in primary tumors and their metastases. Laser-capture microdissection (LCM) coupled to gene expression analysis allows us to understand how specific cell types contribute to the total cancer gene expression signature. Expression profiling was used to define genes that contribute to breast cancer spread into and/or growth within draining lymph nodes (LN). Whole tumor xenografts and their matched whole LN metastases were compared to LCM captured cancer cells from the same tumors and matched LN metastases. One-thousand nine-hundred thirty genes were identified by the whole organ method alone, and 1,281 genes by the LCM method alone. However, less than 1% (30 genes) of genes that changed between tumors and LN metastases were common to both methods. Several of these genes have previously been implicated in cancer aggressiveness. Our data show that whole-organ and LCM based gene expression profiling yield distinctly different lists of metastasis-promoting genes. Contamination of the tumor cells, and cross reactivity of mouse RNA to human-specific chips may explain these differences, and suggests that LCM-derived data may be more accurate.

High-density rhesus macaque oligonucleotide microarray design using early-stage rhesus genome sequence information and human genome annotations

Background

Until recently, few genomic reagents specific for non-human primate research have been available. To address this need, we have constructed a macaque-specific high-density oligonucleotide microarray by using highly fragmented low-pass sequence contigs from the rhesus genome project together with the detailed sequence and exon structure of the human genome. Using this method, we designed oligonucleotide probes to over 17,000 distinct rhesus/human gene orthologs and increased by four-fold the number of available genes relative to our first-generation expressed sequence tag (EST)-derived array.

Results

We constructed a database containing 248,000 exon sequences from 23,000 human RefSeq genes and compared each human exon with its best matching sequence in the January 2005 version of the rhesus genome project list of 486,000 DNA contigs. Best matching rhesus exon sequences for each of the 23,000 human genes were then concatenated in the proper order and orientation to produce a rhesus "virtual transcriptome." Microarray probes were designed, one per gene, to the region closest to the 3' untranslated region (UTR) of each rhesus virtual transcript. Each probe was compared to a composite rhesus/human transcript database to test for cross-hybridization potential yielding a final probe set representing 18,296 rhesus/human gene orthologs, including transcript variants, and over 17,000 distinct genes. We hybridized mRNA from rhesus brain and spleen to both the EST- and genome-derived microarrays. Besides four-fold greater gene coverage, the genome-derived array also showed greater mean signal intensities for genes present on both arrays. Genome-derived probes showed 99.4% identity when compared to 4,767 rhesus GenBank sequence tag site (STS) sequences indicating that early stage low-pass versions of complex genomes are of sufficient quality to yield valuable functional genomic information when combined with finished genome information from a closely related species.

Conclusion

The number of different genes represented on microarrays for unfinished genomes can be greatly increased by matching known gene transcript annotations from a closely related species with sequence data from the unfinished genome. Signal intensity on both EST- and genome-derived arrays was highly correlated with probe distance from the 3' UTR, information often missing from ESTs yet present in early-stage genome projects.

Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis

BACKGROUND

Many model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV) infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye.

RESULTS

The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes.

CONCLUSION

The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data

INTRODUCTION

Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells.

METHODS

Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays.

RESULTS

MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours.

CONCLUSION

Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.