Effective Alu repeat based RT-qPCR normalization in cancer cell perturbation experiments

Background: Measuring messenger RNA (mRNA) levels using the reverse transcription quantitative polymerase chain reaction (RT-qPCR) is common practice in many laboratories. A specific set of mRNAs as internal control reference genes is considered as the preferred strategy to normalize RT-qPCR data. Proper selection of reference genes is a critical issue, especially in cancer cells that are subjected to different in vitro manipulations. These manipulations may result in dramatic alterations in gene expression levels, even of assumed reference genes. In this study, we evaluated the expression levels of 11 commonly used reference genes as internal controls for normalization of 19 experiments that include neuroblastoma, T-ALL, melanoma, breast cancer, non small cell lung cancer (NSCL), acute myeloid leukemia (AML), prostate cancer, colorectal cancer, and cervical cancer cell lines subjected to various perturbations. Results: The geNorm algorithm in the software package qbase+ was used to rank the candidate reference genes according to their expression stability. We observed that the stability of most of the candidate reference genes varies greatly in perturbation experiments. Expressed Alu repeats show relatively stable expression regardless of experimental condition. These Alu repeats are ranked among the best reference assays in all perturbation experiments and display acceptable average expression stability values (M<0.5). Conclusions: We propose the use of Alu repeats as a reference assay when performing cancer cell perturbation experiments

Validation of suitable internal control genes for expression studies in aging.

Quantitative data from experiments of gene expression are often normalized through levels of housekeeping genes transcription by assuming that expression of these genes is highly uniform. This practice is being questioned as it becomes increasingly clear that the level of housekeeping genes expression may vary considerably in certain biological samples. To date, the validation of reference genes in aging has received little attention and suitable reference genes have not yet been defined. Our aim was to evaluate the expression stability of frequently used reference genes in human peripheral blood mononuclear cells with respect to aging. Using quantitative RT-PCR, we carried out an extensive evaluation of five housekeeping genes, i.e. 18s rRNA, ACTB, GAPDH, HPRT1 and GUSB, for stability of expression in samples from donors in the age range 35-74 years. The consistency in the expression stability was quantified on the basis of the coefficient of variation and two algorithms termed geNorm and NormFinder. Our results indicated GUSB be the most suitable transcript and 18s the least for accurate normalization in PBMCs. We also demonstrated that aging is a confounding factor with respect to stability of 18s, HPRT1 and ACTB expression, which were particularly prone to variability in aged donors

Reference loci for RT-qPCR analysis of differentiating human embryonic stem cells

Background: Selecting stably expressed reference genes is essential for proper reverse transcription quantitative polymerase chain reaction gene expression analysis. However, this choice is not always straightforward. In the case of differentiating human embryonic stem (hES) cells, differentiation itself introduces changes whereby reference gene stability may be influenced. Results: In this study, we evaluated the stability of various references during retinoic acid-induced (2 microM) differentiation of hES cells. Out of 12 candidate references, beta-2-microglobulin, ribosomal protein L13A and Alu repeats are found to be the most stable for this experimental set-up. Conclusions: Our results show that some of the commonly used reference genes are actually not amongst the most stable loci during hES cell differentiation promoted by retinoic acid. Moreover, a novel normalization strategy based on expressed Alu repeats is validated for use in hES cell experiments

Unifying candidate gene and GWAS Approaches in Asthma.

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values <0.0035 (corrected for multiple testing). Combining genotyping and imputation, polymorphisms in DPP10, EDN1, IL12B, IL13, IL4, IL4R and TNF showed associations at a significance level between p = 0.05 and p = 0.0035. These data indicate that (a) GWAS coverage is insufficient for many asthma candidate genes, (b) imputation based on these data is reliable but incomplete, and (c) SNPs in three previously identified asthma candidate genes replicate in our GWAS population with significance after correction for multiple testing in 14 genes

Application of recombinant DNA technology to studies on plant secondary metabolism

This review which is concerned with the application of recombinant DNA technology to studies on plant secondary metabolism, presents the more common plant transformation strategies and shows how these genetic approaches are being used in attempts to manipulate and increase the yield of secondary metabolites, both in cultures and in transformed plants. The different plant transformation strategies reviewed here are: infection with intact Agrobacteria; particle bombardment, vacuum infiltration and floral dip; viral vectors and finally protoplast fusion. The review continues with examples of the application of several of these transformation strategies in the manipulation of secondary metabolism. These are outlined under four subheadings which include developmentally regulated genes, addition of novel genes, down-regulation of specific genes and insertion of regulatory genes. Finally, under concluding remarks, reference is made to the advances achieved in the manipulation of plant secondary metabolism and how these approaches may impact on this new

Stable reference genes for the measurement of transcript abundance during larval caste development in the honeybee

Many genes are differentially regulated by caste development in the honeybee. Identifying and understanding these differences is key to discovering the mechanisms underlying this process. To identify these gene expression differences requires robust methods to measure transcript abundance. RT-qPCR is currently the gold standard to measure gene expression, but requires stable reference genes to compare gene expression changes. Such reference genes have not been established for honeybee caste development. Here, we identify and test potential reference genes that have stable expression throughout larval development between the two female castes. In this study, 15 candidate reference genes were examined to identify the most stable reference genes. Three algorithms (GeNorm, Bestkeeper and NormFinder) were used to rank the candidate reference genes based on their stability between the castes throughout larval development. Of these genes Ndufa8 (the orthologue of a component of complex one of the mitochondrial electron transport chain) and Pros54 (orthologous to a component of the 26S proteasome) were identified as being the most stable. When these two genes were used to normalise expression of two target genes (previously found to be differentially expressed between queen and worker larvae by microarray analysis) they were able to more accurately detect differential expression than two previously used reference genes (awd and RpL12). The identification of these novel reference genes will be of benefit to future studies of caste development in the honeybee

Oculomotor Nucleus

This report contains a gene expression summary of the oculomotor nucleus, derived from the Allen Brain Atlas (ABA) in situ hybridization mouse data set. The structure&#x27;s location and morphological characteristics in the mouse brain are described using the Nissl data found in the Allen Reference Atlas. Using an established algorithm, the expression values of the oculomotor nucleus were compared to the values of the macro/parent-structure, in this case the midbrain, for the purpose of extracting regionally selective gene expression data. The genes with the highest ranking selectivity ratios were manually curated and verified. 50 genes were then selected and compiled for expression characterization. The experimental data for each gene may be accessed via the links provided; additional data in the sagittal plane may also be accessed using the ABA. Correlations between gene expression in the oculomotor nucleus and the rest of the brain, across all genes in the coronal dataset (~4300 genes), were derived computationally. A gene ontology table (derived from DAVID Bioinformatics Resources 2007) is also included, highlighting possible functions of the 50 genes selected for this report