Qbase Qpcr

[Tarja Rabito]

The combination of qbasePLUS software with Bio-Rad's CFX96 and CFX384 real-time PCR systems provides our customers with improved accuracy in their qPCR experiments and speeds up data analysis," said Richard Kurtz, Marketing Manager, Amplification, Bio-Rad Laboratories.

qbasePLUS helps researchers accurately analyze gene expression in their real-time PCR data, providing proven solutions for data quality control. The software allows for the elimination of erroneous data, normalization to remove sample-specific nonbiologic variation, and inter-run calibration, which can remove the technical variation between samples analyzed in different runs. Enhancing the reliability of the qPCR data, qbasePLUS conforms to the emerging qPCR best practices standard: Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE), which defines the minimum information required for the evaluation of qPCR results.

Using the CFX96 and CFX384 systems with qbasePLUS software saves time and accelerates research through automated, fast calculations and direct import of data from the system to the software. The combined solution provides researchers with the flexibility to handle both small and large experiments as well as combine data from different experiments using qbasePLUS software as a repository database. For more information please visit www.bio-rad.com/amplification/.

About Bio-Rad

Bio-Rad Laboratories, Inc. (NYSE: BIO and BIOb), has remained at the center of scientific discovery for more than 50 years, manufacturing and distributing a broad range of products for the life science research and clinical diagnostic markets. Bio-Rad is renowned worldwide among hospitals, universities, major research institutions, as well as biotechnology and pharmaceutical companies for its commitment to quality and customer service. Founded in 1952, Bio-Rad is headquartered in Hercules, California, and serves more than 85,000 research and industry customers worldwide through its global network of operations. The company employs over 6,500 people globally and had revenues exceeding $1.7 billion in 2008. For more information, visit www.bio-rad.com.

About Biogazelle

Biogazelle was founded in 2007 as a privately held Ghent University spin-off company specializing in real-time PCR experiment design and data analysis. Its founders' know-how and expertise in nucleic acid quantification and biostatistics is internationally recognized. Biogazelle hopes to be of service to you. For more information, please visit www.biogazelle.com.

This release contains certain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and Section 21E of the Securities Exchange Act of 1934. Forward-looking statements generally can be identified by the use of forward-looking terminology such as, "believe," "expect," "may," "will," "intend," "estimate," "continue," or similar expressions or the negative of those terms or expressions. Such statements involve risks and uncertainties, which could cause actual results to vary materially from those expressed in or indicated by the forward-looking statements. For further information regarding the Company's risks and uncertainties, please refer to the "Risk Factors" in the Company's public reports filed with the Securities and Exchange Commission, including the Company's most recent Annual Report on Form 10-K, Quarterly Reports on Form 10-Q, and Current Reports on Form 8-K. The Company cautions you not to place undue reliance on forward-looking statements, which reflect an analysis only and speak only as of the date hereof. Bio-Rad Laboratories, Inc., disclaims any obligation to update these forward-looking statements.

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Potential utility of 14 candidate housekeeping genes as normalization reference for RT-qPCR analysis with developmental samples (fertilized eggs to late veliger larvae) in Pacific abalone Haliotis discus hannai was evaluated using four different statistical algorithms (geNorm, NormFinder, BestKeeper and comparative ΔCT method). Different algorithms identified different genes as the best candidates, and geometric mean-based final ranking from the most to the least stable expression was as follow: RPL5, RPL4, RPS18, RPL8, RPL7, UBE2, RPL7A, GAPDH, RPL36, PPIB, EF1A, ACTB and B-TU. The findings were further validated via relative quantification of metallothionein (MT) transcripts using the stable and unstable reference genes, and expression levels of MT were greatly influenced according to the choice of reference genes. In overall, our data suggest that RPL5 and RPS18, either singly or in combination, are appropriate for normalizing gene expression in developmental samples of this abalone species, whereas ACTB, B-TU and EF1A are less stable and not recommended. In addition, our findings propose that standard deviations in geometric ranking as well as geometric mean itself should also be taken into account for the final selection of reference gene(s). This study could be a useful basis to facilitate the generation of accurate and reliable RT-qPCR data with developmental samples in this abalone species.

Pacific abalone, Haliotis discus hannai, is one of the most commercially important mollusk species in Korean aquaculture (Park and Kim, 2013). Due to economic interest, various genetic breeding programs are in progress, including selective breeding, chromosome-set manipulation and interspecific hybridization. Comprehensive understanding genes and its expression involved in the development and ontogeny would be a fundamental requirement for all these breeding investigations with regard to evaluate developmental characteristics and early performances of newly developed breeds. Evaluation of reference genes for RT-qPCR normalization in Haliotis species has been reported with respect to type of tissues and experimental challenges using toxicants and bacteria (Wan et al., 2011; Qiu et al., 2013; Lpez-Landavery, 2014; Lee and Nam, 2016a). However, despite its importance, reference genes for developmental samples of abalone species have not been extensively studied.

The objective of this study was to assess suitable reference genes for RT-qPCR normalization with developmental and larval samples in Pacific abalone, H. discus hannai. In this study, we examined the expression patterns of the 14 housekeeping gene candidates with 8 developmental stages (fertilization to late veliger stages) based on 4 different statistical algorithms (geNorm, NormFinder, BestKeeper and comparative ΔCT method). Further, the influence of reference gene choice on the quantification of a target gene was validated using the stable and unstable reference genes recommended by statistical algorithms.

Mature female (n = 5-8) and male (n = 5) abalones were induced to release eggs and sperm based on the conventional method of air exposure followed by ultraviolet (UV)-irradiated seawater treatments. Eggs were washed three times with 1 μm-filtered seawater at 18-19C and inseminated with sperm using wet methods. Fertilized eggs were placed on static incubator containing 1 μm-filtered seawater at 20C until hatch. Fertilization rate was estimated with at least 330 randomly chosen embryos as percentage of embryos showing successful progress initial cleavages (at 2 hours post insemination: HPI) out of initial number of eggs inseminated. Hatching success was also calculated as percentage of hatched larvae out of initial number of eggs with 200-300 eggs. Both fertilization rates and hatching success were estimated in triplicates per egg batch. After hatch, about 300,000-500,000 hatchlings were incubated in rectangular tank containing 15 tons of 1 μm-filtered at 19 1C with a daily water exchange rate of 120%. Rearing of swimming larvae were continued until late veliger stage. Approximately 10,000 embryos were sampled at just fertilized (0 HPI), 2-4 cell stage (2 HPI), 8-16 cell stage (4 HPI), morula stage (5 HPI), gastrula stage (7.5 HPI) and hatching (hatched trocophore; 15 HPI). In addition, about 10,000 swimming larvae at early veliger stage (20 HPH) and late veliger stage (45 HPH) were netted for sampling (Lee and Nam, 2016b). Three independent spawning trials were prepared using different abalone broods in order to prepare three biological replications for each developmental stage. Within each biological replication, triplicate samplings were prepared at each developmental stage as triplicate technical replications.

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