Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans

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Serological identification and expression analysis of gastric cancer-associated genes

Serological identification of tumour antigens by recombinant expression cloning has proved to be an effective strategy for the identification of cancer-associated genes having a relevance to cancer aetiology and progression, and for defining possible targets for immunotherapeutic intervention. In the present study we applied this technique to identify immunogenic proteins for gastric cancer that resulted in isolation of 14 distinct serum-reactive antigens. In order to evaluate their role in tumourigenesis and assess the immunogenicity of the identified antigens, we characterised each cDNA clone by DNA sequence analysis, mRNA tissue distribution, comparison of mRNA levels in cancerous and adjacent non-cancerous tissues and the frequency of antibody responses in allogeneic patient and control sera. Previously unknown splice variants of TACC1 and an uncharacterised gene Ga50 were identified. The expression of a newly identified TACC1 isoform is restricted to brain and gastric cancer tissues. Comparison of mRNA levels by semi-quantitative RT–PCR revealed a relative overexpression of three genes in cancer tissues, including growth factor granulin and Tbdn-1 – an orthologue of the mouse acetyltransferase gene which is associated with blood vessel development. An unusual DNA polymorphism – a three-nucleotide deletion was found in NUCB2 cDNA but its mRNA level was consistently decreased in gastric tumours compared with that in the adjacent non-cancerous tissues. This study has revealed several new gastric cancer candidate genes; additional studies are required to gain a deeper insight into their role in the tumorigenesis and their potential as therapeutic targets

lpxC and yafS are the Most Suitable Internal Controls to Normalize Real Time RT-qPCR Expression in the Phytopathogenic Bacteria Dickeya dadantii

Background: Quantitative RT-PCR is the method of choice for studying, with both sensitivity and accuracy, the expression of genes. A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression. Here, we propose a set of reference genes, of the phytopathogenic bacteria Dickeya dadantii and Pectobacterium atrosepticum, which are stable in a wide range of growth conditions. [br/] Results: We extracted, from a D. dadantii micro-array transcript profile dataset comprising thirty-two different growth conditions, an initial set of 49 expressed genes with very low variation in gene expression. Out of these, we retained 10 genes representing different functional categories, different levels of expression (low, medium, and high) and with no systematic variation in expression correlating with growth conditions. We measured the expression of these reference gene candidates using quantitative RT-PCR in 50 different experimental conditions, mimicking the environment encountered by the bacteria in their host and directly during the infection process in planta. The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data. Finally, we demonstrated that the ortholog of lpxC and yafS in Pectobacterium atrosepticum also showed stable expression in diverse growth conditions. [br/] Conclusions: We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection. Thus, these genes are considered suitable for use as reference genes for the normalization of real-time RT-qPCR data of the two main pectinolytic phytopathogenic bacteria D. dadantii and P. atrosepticum and, probably, of other Enterobacteriaceae. Moreover, we defined general criteria to select good reference genes in bacteria

Addressing fluorogenic real-time qPCR inhibition using the novel custom Excel file system 'FocusField2-6GallupqPCRSet-upTool-001' to attain consistently high fidelity qPCR reactions

The purpose of this manuscript is to discuss fluorogenic real-time quantitative polymerase chain reaction (qPCR) inhibition and to introduce/define a novel Microsoft Excel-based file system which provides a way to detect and avoid inhibition, and enables investigators to consistently design dynamically-sound, truly LOG-linear qPCR reactions very quickly. The qPCR problems this invention solves are universal to all qPCR reactions, and it performs all necessary qPCR set-up calculations in about 52 seconds (using a pentium 4 processor) for up to seven qPCR targets and seventy-two samples at a time – calculations that commonly take capable investigators days to finish. We have named this custom Excel-based file system "FocusField2-6GallupqPCRSet-upTool-001" (FF2-6-001 qPCR set-up tool), and are in the process of transforming it into professional qPCR set-up software to be made available in 2007. The current prototype is already fully functional

Using Ribosomal Protein Genes as Reference: A Tale of Caution

Background: Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms "reference genes'' and "housekeeping genes'' are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data. Methodology/Principal Findings: We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes. Conclusions/Significance: Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes

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 Comprehensive Approach to Identify Reliable Reference Gene Candidates to Investigate the Link between Alcoholism and Endocrinology in Sprague-Dawley Rats

Gender and hormonal differences are often correlated with alcohol dependence and related complications like addiction and breast cancer. Estrogen (E2) is an important sex hormone because it serves as a key protein involved in organism level signaling pathways. Alcoholism has been reported to affect estrogen receptor signaling; however, identifying the players involved in such multi-faceted syndrome is complex and requires an interdisciplinary approach. In many situations, preliminary investigations included a straight forward, yet informative biotechniques such as gene expression analyses using quantitative real time PCR (qRT-PCR). The validity of qRT-PCR-based conclusions is affected by the choice of reliable internal controls. With this in mind, we compiled a list of 15 commonly used housekeeping genes (HKGs) as potential reference gene candidates in rat biological models. A comprehensive comparison among 5 statistical approaches (geNorm, dCt method, NormFinder, BestKeeper, and RefFinder) was performed to identify the minimal number as well the most stable reference genes required for reliable normalization in experimental rat groups that comprised sham operated (SO), ovariectomized rats in the absence (OVX) or presence of E2 (OVXE2). These rat groups were subdivided into subgroups that received alcohol in liquid diet or isocalroic control liquid diet for 12 weeks. Our results showed that U87, 5S rRNA, GAPDH, and U5a were the most reliable gene candidates for reference genes in heart and brain tissue. However, different gene stability ranking was specific for each tissue input combination. The present preliminary findings highlight the variability in reference gene rankings across different experimental conditions and analytic methods and constitute a fundamental step for gene expression assays

PDK1 and HR46 Gene Homologs Tie Social Behavior to Ovary Signals

The genetic basis of division of labor in social insects is a central question in evolutionary and behavioral biology. The honey bee is a model for studying evolutionary behavioral genetics because of its well characterized age-correlated division of labor. After an initial period of within-nest tasks, 2–3 week-old worker bees begin foraging outside the nest. Individuals often specialize by biasing their foraging efforts toward collecting pollen or nectar. Efforts to explain the origins of foraging specialization suggest that division of labor between nectar and pollen foraging specialists is influenced by genes with effects on reproductive physiology. Quantitative trait loci (QTL) mapping of foraging behavior also reveals candidate genes for reproductive traits. Here, we address the linkage of reproductive anatomy to behavior, using backcross QTL analysis, behavioral and anatomical phenotyping, candidate gene expression studies, and backcross confirmation of gene-to-anatomical trait associations. Our data show for the first time that the activity of two positional candidate genes for behavior, PDK1 and HR46, have direct genetic relationships to ovary size, a central reproductive trait that correlates with the nectar and pollen foraging bias of workers. These findings implicate two genes that were not known previously to influence complex social behavior. Also, they outline how selection may have acted on gene networks that affect reproductive resource allocation and behavior to facilitate the evolution of social foraging in honey bees

Suitable reference genes for real-time PCR in human HBV-related hepatocellular carcinoma with different clinical prognoses

<p>Abstract</p> <p>Background</p> <p>Housekeeping genes are routinely used as endogenous references to account for experimental differences in gene expression assays. However, recent reports show that they could be de-regulated in different diseases, model animals, or even under varied experimental conditions, which may lead to unreliable results and consequently misinterpretations. This study focused on the selection of suitable reference genes for quantitative PCR in human hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) with different clinical outcomes.</p> <p>Methods</p> <p>We evaluated 6 commonly used housekeeping genes' expression levels in 108 HBV-related HCCs' matched tumor and non-tomor tissue samples with different clinical outcomes and 26 normal liver specimens by real-time PCR. The expression stability of the 6 genes was compared using the software programs geNorm and NormFinder. To show the impact of reference genes on data analysis, we took PGK1 as a target gene normalized by each reference gene, and performed one-way ANOVA and the equivalence test.</p> <p>Results</p> <p>With the geNorm and NormFinder software programs, analysis of TBP and HPRT1 showed the best stability in all tissue samples, while 18s and ACTB were less stable. When 18s or ACTB was used for normalization, no significant difference of PGK1 expression (p > 0.05) was found among HCC tissues with and without metastasis, and normal liver specimens; however, dramatically differences (p < 0.001) were observed when either TBP or the combination of TBP and HPRT1 were selected as reference genes.</p> <p>Conclusion</p> <p>TBP and HPRT1 are the most reliable reference genes for q-PCR normalization in HBV-related HCC specimens. However, the well-used ACTB and 18S are not suitable, which actually lead to the misinterpretation of the results in gene expression analysis.</p