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

Expression stability of commonly used reference genes in canine articular connective tissues

<p>Abstract</p> <p>Background</p> <p>The quantification of gene expression in tissue samples requires the use of reference genes to normalise transcript numbers between different samples. Reference gene stability may vary between different tissues, and between the same tissue in different disease states. We evaluated the stability of 9 reference genes commonly used in human gene expression studies. Real-time reverse transcription PCR and a mathematical algorithm were used to establish which reference genes were most stably expressed in normal and diseased canine articular tissues and two canine cell lines stimulated with lipolysaccaride (LPS).</p> <p>Results</p> <p>The optimal reference genes for comparing gene expression data between normal and diseased infrapatella fat pad were <it>RPL13A </it>and <it>YWHAZ </it>(M = 0.56). The ideal reference genes for comparing normal and osteoarthritic (OA) cartilage were <it>RPL13A </it>and <it>SDHA </it>(M = 0.57). The best reference genes for comparing normal and ruptured canine cranial cruciate ligament were <it>B2M </it>and <it>TBP </it>(M = 0.59). The best reference genes for normalising gene expression data from normal and LPS stimulated cell lines were <it>SDHA </it>and <it>YWHAZ </it>(K6) or <it>SDHA </it>and <it>HMBS </it>(DH82), which had expression stability (M) values of 0.05 (K6) and 0.07 (DH82) respectively. The number of reference genes required to reduce pairwise variation (V) to <0.20 was 4 for cell lines, 5 for cartilage, 7 for cranial cruciate ligament and 8 for fat tissue. Reference gene stability was not related to the level of gene expression.</p> <p>Conclusion</p> <p>The reference genes demonstrating the most stable expression within each different canine articular tissue were identified, but no single reference gene was identified as having stable expression in all different tissue types. This study underlines the necessity to select reference genes on the basis of tissue and disease specific expression profile evaluation and highlights the requirement for the identification of new reference genes with greater expression stability for use in canine articular tissue gene expression studies.</p

Transcriptome analyses reveal reduced hepatic lipid synthesis and accumulation in more feed efficient beef cattle

peer-reviewedThe genetic mechanisms controlling residual feed intake (RFI) in beef cattle are still largely unknown. Here we performed whole transcriptome analyses to identify differentially expressed (DE) genes and their functional roles in liver tissues between six extreme high and six extreme low RFI steers from three beef breed populations including Angus, Charolais, and Kinsella Composite (KC). On average, the next generation sequencing yielded 34 million single-end reads per sample, of which 87% were uniquely mapped to the bovine reference genome. At false discovery rate (FDR)  2, 72, 41, and 175 DE genes were identified in Angus, Charolais, and KC, respectively. Most of the DE genes were breed-specific, while five genes including TP53INP1, LURAP1L, SCD, LPIN1, and ENSBTAG00000047029 were common across the three breeds, with TP53INP1, LURAP1L, SCD, and LPIN1 being downregulated in low RFI steers of all three breeds. The DE genes are mainly involved in lipid, amino acid and carbohydrate metabolism, energy production, molecular transport, small molecule biochemistry, cellular development, and cell death and survival. Furthermore, our differential gene expression results suggest reduced hepatic lipid synthesis and accumulation processes in more feed efficient beef cattle of all three studied breeds