One of the best characteristics for the functional status of a certain cell is its gene expression pattern. Cells belonging to different tissues, cells in different developmental or metabolic stages, cells under the influence of specific compounds, or cells within a carcinogenic process differ by their gene expression patterns and thus by their mRNA pools. Currently, the most important technique for the accurate quantitation of gene expression is the fluorescent quantitative real-time RT-PCR (Muller et al., 2002a).
Reverse transcription (RT) followed by the polymerase chain reaction (PCR) is the technique of choice to analyze mRNA expression derived from various sources. Real-time RT-PCR is highly sensitive and allows quantification of rare transcripts and small changes in gene expression. It is easy to perform, provide the necessary accuracy, and produce reliable as well as rapid quantification results (Pfaffl, 2001). Many of the key proteins (i.e. cytokines and transcription factors) are found in such low abundance that real-time RT-PCR quantification of their mRNAs represents the only technique sensitive enough to measure their expression reliably in vivo, low copy number targets of interest for which alternative assays either do not exist or lack the required sensitivity, (Huggett et al., 2005a)
RNA cannot serve as a template for PCR, the first step in an RT-PCR assay is the reverse transcription of the RNA template into complimentary DNA and followed by its exponential amplification in a PCR reaction. Usually, this involves the use of dedicated RNA and DNA-dependent DNA polymerases, either in separate (‘two-enzyme/two-tube’) or in single (‘two-enzyme/one-tube’) reactions, as the use of dedicated enzymes with different proper...
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...rse transcription polymerase chain reaction assays." Journal of molecular endocrinology 25.2 (2000b): 169-193. (article given)
3. Huggett, J., et al. "Real-time RT-PCR normalisation; strategies and considerations." Genes and immunity 6.4 (2005a): 279-284.
4. Huggett, J., et al. "Real-time RT-PCR normalisation; strategies and considerations." Genes and immunity 6.4 (2005b): 279-284.
5. Muller, Patrick Y., et al. "Short technical report processing of gene expression data generated by quantitative Real-Time RT-PCR." Biotechniques 32.6 (2002a): 1372-1379.
6. Muller, Patrick Y., et al. "Short technical report processing of gene expression data generated by quantitative Real-Time RT-PCR." Biotechniques 32.6 (2002b): 1372-1379.
7. Pfaffl, Michael W. "A new mathematical model for relative quantification in real-time RT–PCR." Nucleic acids research 29.9 (2001): e45-e45.
Ligation of EGFP into pET41a(+) vector transformed into E. coli cells followed by PCR amplification of extracted DNA plasmid for success evaluation along with gel electrophoresis at each step.
Digestion of the haemolytic and non-haemolytic cells allowed for easier identification of fragments during electrophoresis analysis. Lane 12 in figure 3 show the size markers of SPP1 digested with EcoR1 while lanes 6 and 7 show samples of pK184hlyA and pBluescript digested with EcoR1 and Pst1. Lane 4 was loaded with plasmid DNA from haemolytic cells digested with EcoR1 and Pst1 while lane 5 was loaded with EcoR1 and Pst1 digested DNA from non-haemolytic cells. There was a lack of technical success in both lanes due to no bands appearing in lane 4 and only a single band appearing in lane 5. Theoretically, two bands should appear in both lanes after successful to allow for fragment identification. A possible explanation for the single, large fragment in lane 5 is that successful digestion did not take place and the plasmid was only cut at one restriction site leaving a large linear fragment of plasmid DNA. The absence of bands in lane 4 could be because there was not enough plasmid loaded into the lane. Another possibility could be that low plasmid yield as obtained when eluting the experimental samples in order to purify it. Lanes 8 and 9 belonged to another group and show technical success as two bands were present in both the haemolytic (lane 8) and non-haemolytic (lane 9) lanes. If the
completed, the tubes are stored at 4°C until analysis of the tubes. To alylize the PCR results with
Miller, K. R., & Levine, J. S. (2010). Miller & Levine biology. Boston, Mass.: Pearson.
In this lab we amplified a region of DNA that is found in the mitochondria. Mitochondria have their own set of DNA. Mitochondrial DNA has “16,500 DNA building blocks (base pairs), representing a small fraction of the total DNA in cells. — Mitochondrial DNA contains 37 genes,” (Genetics Home Reference, NIH, 2014) The part of the DNA that we amplified was the D-loop region. This part of the mitochondrial genome is the origin of replication for the mitochondria. This part of the mitochondria is also “prone to somatic mutation, which are a type of non-inherited mutation.” (Genetics Home Reference, NIH, 2014) One’s mitochondrial DNA is only inherited from the maternal side. The reason why is because when “an egg cell is fertilized, nuclear chromosomes from a sperm cell enter the egg and combine with the egg’s nuclear DNA producing a mixture of both parents’ genetic code.” (Groleau, PBS, 2014) Since the mtDNA is the exact same as the mother’s one can trace back the lineage of their maternal side and trace from what part of the world they are descended from. The mtDNA contains a history storybook of the travels and nomadic paths their ancestors took before their creation. The purpose of amplifying this region of mtDNA is to trace back our lineage.
2. Cytokines in Cancer Therapy. Francis R. Balkwill. Oxford University Press, NY, 1989. pp 1-8.
Schulman, Joshua M., and David E. Fisher. "Abstract." National Center for Biotechnology Information. U.S. National Library of Medicine, 28 Aug. 0005. Web. 24 Apr. 2014.
This creates two stages of analysis that take place during experimental design using bioinformatics tools. These are gene finding and gene function prediction; together, they can identify potential targets for research and elicit important functional characteristics of the coded protein that confirm the significance of a gene.... ... middle of paper ... ...
This data is used in DESeq66, which is an R Bioconductor package, to calculate differentially expressed genes between HPC and PFC. DESeq provides various statistical tests for determining differentially expressed genes in gene expression data67 The inputs for DESeq are raw counts obtained from HTSeq. DESeq takes into account the total size of each library to perform calculations on fold change as well as significance based on p-value and adjusted p-value. The transcript biotypes were obtained from the Ensembl GTF annotation file (Mus musculus genome build NCBIM37). Using the annotation file, we identified 34,379 transcripts from HPC and 32,909 transcripts from PFC. Analysis of this dataset by blasting against the EMBL database containing 2,057 lncRNAs led to the identification of 1,982 lncRNAs from HPC and 1,936 lncRNAs from PFC (Fig 1, from Kadakkuzha et al., submitted to Genome
Miller, K. R., & Levine, J. S. (2010). Miller & Levine biology. Boston, Mass: Pearson
In case of cell based labeling assays the use of genetically modified cell lines alters cellular behavior.
Michener, William K. and Haeuber, Richard A., Bioscience. American Institute of Biological Science. Sep98. Vol. 48. Issue 9. p677.
Gonzaga-Jauregui, Cludia, James R Lupski and Richard A Gibbs. Human Genome Sequencing in Health and Disease. 2012. 17 March 2014 .
Transcriptomics- the study of gene expression (Sorek & Cossart, 2010; Stewart, Sharma, Bryant, Eppley, & DeLong, 2011; Z. Wang, Gerstein, & Snyder, 2009)
Blood and urine based biomarkers used in molecular pathology are only indicative of the average response of the cell population affected with little or no information of the range of response or variability form areas of tissue (Naddler and Langley 2001)