Characterization, chromosomal localization, and genetic variation of the porcine heart fatty acid-binding protein gene

The purpose of this study was to detect genetic variation in the porcine H-FABP gene, a candidate gene for meat quality traits in pigs. Lambda phages containing the porcine H-FABP gene were isolated by plaque hybridization with human H-FABP cDNA. The coding and flanking intronic sequences of the porcine H-FABP gene were determined as well as 1.6 kb of the 5 ′ upstream region. The various potential regulatory sequences in this region are in accordance with the function and expression of the protein in muscle and mammary tissue. Furthermore, comparison with the homolog region of the mouse identified a highly conserved 13-bp element (CTTCCT [A/C] TTTCGG) that may be involved in regulation of expression. The porcine H-FABP gene was localized on Chromosome (Chr) 6 by porcine sequence-specific PCR on DNA from a pig/rodent cell hybrid panel. In addition, part of the H-FABP gene was screened for genetic variation by PCR-RFLP analysis. Three PCR-RFLPs were detected, one in the upstream region (HinfI) and two in the second intron (HaeIII and MspI). In most pig breeds the corresponding alleles have a variable distribution, possibly a consequence of selective breeding. This genetic variation will enable us to investigate the role of the H-FABP locus in porcine production and meat quality trait

A biological question and a balanced (orthogonal) design: the ingredients to efficiently analyze two-color microarrays with Confirmatory Factor Analysis

BACKGROUND: Factor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis). A disadvantage is that the representation of data in a reduced set of dimensions can be difficult to interpret, as biological contrasts do not necessarily coincide with single dimensions. However, FA can also be applied as an instrument to confirm what is expected on the basis of pre-established hypotheses (Confirmatory Factor Analysis, CFA). We show that with a hypothesis incorporated in a balanced (orthogonal) design, including 'SelfSelf' hybridizations, dye swaps and independent replications, FA can be used to identify the latent factors underlying the correlation structure among the observed two-color microarray data. An orthogonal design will reflect the principal components associated with each experimental factor. We applied CFA to a microarray study performed to investigate cisplatin resistance in four ovarian cancer cell lines, which only differ in their degree of cisplatin resistance. RESULTS: Two latent factors, coinciding with principal components, representing the differences in cisplatin resistance between the four ovarian cancer cell lines were easily identified. From these two factors 315 genes associated with cisplatin resistance were selected, 199 genes from the first factor (False Discovery Rate (FDR): 19%) and 152 (FDR: 24%) from the second factor, while both gene sets shared 36. The differential expression of 16 genes was validated with reverse transcription-polymerase chain reaction. CONCLUSION: Our results show that FA is an efficient method to analyze two-color microarray data provided that there is a pre-defined hypothesis reflected in an orthogonal design

Evidence Based Selection of Housekeeping Genes

For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes (reference or internal control genes) is required. It is known that commonly used housekeeping genes (e.g. ACTB, GAPDH, HPRT1, and B2M) vary considerably under different experimental conditions and therefore their use for normalization is limited. We performed a meta-analysis of 13,629 human gene array samples in order to identify the most stable expressed genes. Here we show novel candidate housekeeping genes (e.g. RPS13, RPL27, RPS20 and OAZ1) with enhanced stability among a multitude of different cell types and varying experimental conditions. None of the commonly used housekeeping genes were present in the top 50 of the most stable expressed genes. In addition, using 2,543 diverse mouse gene array samples we were able to confirm the enhanced stability of the candidate novel housekeeping genes in another mammalian species. Therefore, the identified novel candidate housekeeping genes seem to be the most appropriate choice for normalizing gene expression data

A New Perspective on Transcriptional System Regulation (TSR): Towards TSR Profiling

It has been hypothesized that the net expression of a gene is determined by the combined effects of various transcriptional system regulators (TSRs). However, characterizing the complexity of regulation of the transcriptome is a major challenge. Principal component analysis on 17,550 heterogeneous human microarray experiments revealed that 50 orthogonal factors (hereafter called TSRs) are able to capture 64% of the variability in expression in a wide range of experimental conditions and tissues. We identified gene clusters controlled in the same direction and show that gene expression can be conceptualized as a process influenced by a fairly limited set of TSRs. Furthermore, TSRs can be linked to biological functions, as we demonstrate a strong relation between TSR-related gene clusters and biological functionality as well as cellular localization, i.e. gene products of similarly regulated genes by a specific TSR are located in identical parts of a cell. Using 3,934 diverse mouse microarray experiments we found striking similarities in transcriptional system regulation between human and mouse. Our results give biological insights into regulation of the cellular transcriptome and provide a tool to characterize expression profiles with highly reliable TSRs instead of thousands of individual genes, leading to a >500-fold reduction of complexity with just 50 TSRs. This might open new avenues for those performing gene expression profiling studies

Survival-Related Profile, Pathways, and Transcription Factors in Ovarian Cancer

Ate van der Zee and colleagues analyze the gene expression profiles of ovarian cancer samples from 157 patients, and identify an 86-gene expression profile that seems to predict overall survival

Genetic control of intramuscular fat accretion in pigs : the role of heart and adipocyte fatty acid-binding proteins

Contains fulltext : 18917_genecoofi.pdf (publisher's version ) (Open Access)162 p

Characterization, chromosomal localization, and genetic variation of the porcine heart fatty acid-binding protein gene

ISSN:0938-8990ISSN:1432-177

Gene expression profiling in livers of mice after acute inhibition of beta-oxidation

AbstractInborn errors of mitochondrial β-oxidation cause ectopic fat accumulation, particularly in the liver. Fatty liver is associated with insulin resistance and predisposes to hepatic fibrosis. The factors underlying the pathophysiological consequences of hepatic fat accumulation have remained poorly defined. Gene expression profiling in a model of acute fatty liver disease induced by blocking long-chain fatty acid β-oxidation was performed to study the early effects of steatosis on the transcriptome. Tetradecylglycidic acid (TDGA) was used to irreversibly inhibit carnitine palmitoyltransferase 1, a key enzyme in the control of mitochondrial β-oxidation. TDGA treatment induced massive microvesicular hepatic steatosis within a 12-h time frame in male C57BL6/J mice. Increased hepatic long-chain acyl-CoA content, particularly of C16:0, C16:1 and C18:1, was associated with profound effects on the transcriptome as revealed by unbiased gene expression profiling and quantitative real-time PCR. The results indicate drastic changes in the expression of genes encoding proteins involved in lipid, carbohydrate, and amino acid metabolism. Pathway analysis identified transcription factors and coregulators such as hepatocyte nuclear factor 4 (HNF4), peroxisome proliferator-activated receptor-α (PPAR-α), and PPAR gamma coactivator 1α (PGC-1α ) as key players in these metabolic adaptations. Apoptotic and profibrotic responses were also affected. Surprisingly, a strong reduction in the expression of genes involved in hepatic bile salt metabolism and transport was observed. Therefore, this transcriptome analysis opens new avenues for research

Gene expression profile in flow-associated pulmonary arterial hypertension with neointimal lesions

Pulmonary arterial hypertension (PAH) is a pulmonary angioproliferative disease with high morbidity and mortality, characterized by a typical pattern of pulmonary vascular remodeling including neointimal lesions. In congenital heart disease, increased pulmonary blood flow has appeared to be a key mediator in the development of these characteristic lesions, but the molecular mechanisms underlying the pulmonary vascular lesions are largely unknown. We employed a rat model of flow-associated PAH, which induced specific pulmonary neointimal lesions. We identified gene expression profiles in rats specifically related to the addition of increased pulmonary blood flow to monocrotaline and the associated occurrence of neointimal lesions. Increased pulmonary blood flow induced the expression of the transcription factors activating transcription factor-3 (ATF3) and early growth response factor-1 (EGR-1), for which presence was confirmed in neointimal lesions. Monocrotaline alone induced increased numbers of activated mast cells and their products. We further identified molecular pathways that may be involved in treatment with the prostacyclin analog iloprost, a vasoactive compound with clinically beneficial effects in patients with PAH, which were similar to pathways described in samples from patient studies. These pathways, associated with the development of angioproliferative lesions as well as with the response to therapy in PAH, may provide new therapeutic targets

Comparison of brain and blood gene expression in an animal model of negative symptoms in schizophrenia

Objectives: To investigate the potential of white blood cells as probes for central processes we have measured gene expression in both the anterior cingulate cortex and white blood cells using a putative animal model of negative symptoms in schizophrenia. Methods: The model is based on the capability of ketamine to induce psychotic symptoms in healthy volunteers and to worsen such symptoms in schizophrenic patients. Classical fear conditioning is used to assess emotional processing and cognitive function in animals exposed to sub-chronic ketamine vs. controls. Gene expression was measured using a commercially sourced whole genome rat gene array. Data analyses were performed using ANOVA (Systat 11). Results: In both anterior cingulate cortex and white blood cells a significant interaction between ketamine and fear conditioning could be observed. The outcome is largely supported by our subsequent metagene analysis. Moreover, the correlation between gene expression in brain and blood is about constant when no ketamine is present (r-0.4). With ketamine, however, the correlation becomes very low (r similar to 02) when there is no fear, but it increases to -0.6 when fear and ketamine are both present. Our results show that under normal conditions ketamine lowers gene expression in the brain, but this effect is completely reversed in combination with fear conditioning, indicating a stimulatory action. Conclusion: This paradoxical outcome indicates that extreme care must be taken when using gene expression data from white blood cells as marker for psychiatric disorders, especially when pharmacological and environmental interactions are at play. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved