Identification of stable endogenous reference genes for real-time PCR in the human fetal gonad using an external standard technique

Peer reviewedPostprin

RTPrimerDB: the portal for real-time PCR primers and probes

RTPrimerDB (http://www.rtprimerdb.org) is a freely accessible database and analysis tool for real-time quantitative PCR assays. RTPrimerDB includes records with user submitted assays that are linked to genome information from reference databases and quality controlled using an in silico assay evaluation system. The primer evaluation tools intended to assess the specificity and to detect features that could negatively affect the amplification efficiency are combined into a pipeline to test custom-designed primer and probe sequences. An improved user feedback system guides users and submitters to enter practical remarks and details about experimental evaluation analyses. The database is linked with reference databases to allow the submission of assays for all genes and organisms officially registered in Entrez Gene and RefSeq. Records in RTPrimerDB are assigned unique and stable identifiers. The content is provided via an interactive web-based search system and is available for download in the recently developed RDML format and as bulk export file. RTPrimerDB is a one-stop portal for high-quality and highly annotated real-time PCR assays

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure

Development of a new set of reference genes for normalization of real-time RT-PCR data of porcine backfat and longissimus dorsi muscle, and evaluation with PPARGC1A

BACKGROUND: An essential part of using real-time RT-PCR is that expression results have to be normalized before any conclusions can be drawn. This can be done by using one or multiple, validated reference genes, depending on the desired accuracy of the results. In the pig however, very little information is available on the expression stability of reference genes. The aim of this study was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in porcine backfat and longissimus dorsi muscle, both representing an economically important part of a pig's carcass. Because of its multiple functions in fat metabolism and muscle fibre type composition, peroxisome proliferative activated receptor γ coactivator 1α (PPARGC1A) is a very interesting candidate gene for meat quality, and was an ideal gene to evaluate our developed set of reference genes for normalization of mRNA expression data of both tissue types. RESULTS: The mRNA expression stability of 10 reference genes was determined. The expression of RPL13A and SDHA appeared to be highly unstable. After normalization to the geometric mean of the three most stably expressed reference genes (ACTB, TBP and TOP2B), the results not only showed that the mRNA expression of PPARGC1A was significantly higher in each of the longissimus dorsi muscle samples than in backfat (P < 0.05), but also that the expression was significantly higher in the most cranial of the three muscle samples (P < 0.05). CONCLUSION: This study provides a new set of reference genes (ACTB, TBP and TOP2B) suitable for normalization of real-time RT-PCR data of backfat and longissimus dorsi muscle in the pig. The obtained PPARGC1A expression results, after application of this set of reference genes, are a first step in unravelling the PPARGC1A expression pattern in the pig and provide a basis for possible selection towards improved meat quality while maintaining a lean carcass

Identification and expression analysis of genes associated with bovine blastocyst formation

<p>Abstract</p> <p>Background</p> <p>Normal preimplantation embryo development encompasses a series of events including first cleavage division, activation of the embryonic genome, compaction and blastocyst formation.</p> <p>First lineage differentiation starts at the blastocyst stage with the formation of the trophectoderm and the inner cell mass. The main objective of this study was the detection, identification and expression analysis of genes associated with blastocyst formation in order to help us better understand this process. This information could lead to improvements of <it>in vitro </it>embryo production procedures.</p> <p>Results</p> <p>A subtractive cDNA library was constructed enriched for transcripts preferentially expressed at the blastocyst stage compared to the 2-cell and 8-cell stage. Sequence information was obtained for 65 randomly selected clones. The RNA expression levels of 12 candidate genes were determined throughout 3 stages of preimplantation embryo development (2-cell, 8-cell and blastocyst) and compared with the RNA expression levels of <it>in vivo </it>"golden standard" embryos using real-time PCR. The RNA expression profiles of 9 (75%) transcripts (<it>KRT18</it>, <it>FN1</it>, <it>MYL6</it>, <it>ATP1B3</it>, <it>FTH1</it>, <it>HINT1</it>, <it>SLC25A5</it>, <it>ATP6V0B</it>, <it>RPL10</it>) were in agreement with the subtractive cDNA cloning approach, whereas for the remaining 3 (25%) (<it>ACTN1</it>, <it>COPE</it>, <it>EEF1A1</it>) the RNA expression level was equal or even higher at the earlier developmental stages compared to the blastocyst stage. Moreover, significant differences in RNA expression levels were observed between <it>in vitro </it>and <it>in vivo </it>produced embryos. By immunofluorescent labelling, the protein expression of KRT18, FN1 and MYL6 was determined throughout bovine preimplantation embryo development and showed the same pattern as the RNA expression analyses.</p> <p>Conclusion</p> <p>By subtractive cDNA cloning, candidate genes involved in blastocyst formation were identified. For several candidate genes, important differences in gene expression were observed between <it>in vivo </it>and <it>in vitro </it>produced embryos, reflecting the influence of the <it>in vitro </it>culture system on the embryonic gene expression. Both RNA and protein expression analysis demonstrated that <it>KRT18</it>, <it>FN1 </it>and <it>MYL6 </it>are differentially expressed during preimplantation embryo development and those genes can be considered as markers for bovine blastocyst formation.</p

Robust RT-qPCR Data Normalization: Validation and Selection of Internal Reference Genes during Post-Experimental Data Analysis

Reverse transcription and real-time PCR (RT-qPCR) has been widely used for rapid quantification of relative gene expression. To offset technical confounding variations, stably-expressed internal reference genes are measured simultaneously along with target genes for data normalization. Statistic methods have been developed for reference validation; however normalization of RT-qPCR data still remains arbitrary due to pre-experimental determination of particular reference genes. To establish a method for determination of the most stable normalizing factor (NF) across samples for robust data normalization, we measured the expression of 20 candidate reference genes and 7 target genes in 15 Drosophila head cDNA samples using RT-qPCR. The 20 reference genes exhibit sample-specific variation in their expression stability. Unexpectedly the NF variation across samples does not exhibit a continuous decrease with pairwise inclusion of more reference genes, suggesting that either too few or too many reference genes may detriment the robustness of data normalization. The optimal number of reference genes predicted by the minimal and most stable NF variation differs greatly from 1 to more than 10 based on particular sample sets. We also found that GstD1, InR and Hsp70 expression exhibits an age-dependent increase in fly heads; however their relative expression levels are significantly affected by NF using different numbers of reference genes. Due to highly dependent on actual data, RT-qPCR reference genes thus have to be validated and selected at post-experimental data analysis stage rather than by pre-experimental determination