qPCR & RT-qPCR Applications

microRNA (= miRNA) applications in qRT-PCR

In genetics, a miRNA (micro-RNA) is a form of single-stranded RNA which is typically 20-25 nucleotides long, and is thought to regulate the expression of other genes. miRNAs are RNA genes which are transcribed from DNA, but are not translated into protein. The DNA sequence that codes for an miRNA gene is longer than the miRNA. This DNA sequence includes the miRNA sequence and an approximate reverse complement. When this DNA sequence is transcribed into a single-stranded RNA molecule, the miRNA sequence and its reverse- complement base pair to form a double stranded RNA hairpin loop; this forms a primary miRNA structure (pri-miRNA). Most microRNAs in animals are thought to function through the inhibition of effective mRNA translation of target genes through imperfect base-pairing with the 3'-untranslated region (3'-UTR) of target mRNAs. However, the underlying mechanism is poorly understood. MicroRNA targets are largely unknown, but estimates range from one to hundreds of target genes for a given microRNA, based on target predictions using a variety of bioinformatics. The function of miRNAs appears to be in gene regulation. For that purpose, a miRNA is complementary to a part of one or more messenger RNAs (mRNAs). Animal miRNAs are usually complementary to a site in the 3' UTR whereas plant miRNAs are usually complementary to coding regions of mRNAs. The annealing of the miRNA to the mRNA then inhibits protein translation, but sometimes facilitates cleavage of the mRNA. This is thought to be the primary mode of action of plant miRNAs. In such cases, the formation of the double-stranded RNA through the binding of the miRNA triggers the degradation of the mRNA transcript through a process similar to RNA interference (RNAi), though in other cases it is believed that the miRNA complex blocks the protein translation machinery or otherwise prevents protein translation without causing the mRNA to be degraded.


High Resolution Melting (HRM)

HRM is a novel, homogeneous, close-tube, post-PCR method, enabling genomic researchers to analyze genetic variations (SNPs, mutations, methylations) in PCR amplicons. It goes beyond the power of classical melting curve analysis by allowing to study the thermal denaturation of a double-stranded DNA in much more detail and with much higher information yield than ever before. HRM characterizes nucleic acid samples based on their disassociation (melting) behavior. Samples can be discriminated according to their sequence, length, GC content or strand complementarity. Even single base changes such as SNPs (single nucleotide polymorphisms) can be readily identified.  The most important High Resolution Melting application is gene scanning - the search for the presence of unknown variations in PCR amplicons prior to or as an alternative to sequencing. Mutations in PCR products are detectable by High Resolution Melting because they change the shape of DNA melting curves. A combination of new-generation DNA dyes, high-end instrumentation and sophisticated analysis software allows to detect these changes and to derive information about the underlying sequence constellation.

HRM Applications:  The introduction of HRM has renewed interest in the utility of DNA melting for a wide range of uses, including:
  • Mutation discovery (gene scanning)
  • SNP genotyping
  • Characterization of haplotype blocks
  • DNA methylation analysis
  • Species identification
  • DNA mapping
  • Screening for loss of heterozygosity
  • DNA fingerprinting
  • Somatic acquired mutation ratios
  • HLA compatibility typing
  • Identification of candidate predisposition genes
  • Allelic prevalence in a population

Quantitative real-time PCR in single-cells

Single-cell molecular-biology is a relatively new scientific branch in biology. The first single-cell analysis were involved in the characterization of mitochondrial DNA in 1988. Single-cell DNA analysis, in particular genomic DNA, is important and may be informative in the analysis of genetics of cell clonality, genetic anticipation and single-cell DNA polymorphisms. Nowadays for most scientists the quantitative transcriptomics in a single-cell is much more important, and the analytical method of choice is the quantitative real-time RT-PCR. The relative abundance of single mRNAs and their up- or down-regulation in a single cell, compared to their neighbour cells, is the goal. The need for quantitative single-cell mRNA analysis is evident given the vast cellular heterogeneity of all tissue cells and the inability of conventional RNA methods, like northern blotting, RNAse protection assay or classical block RT-PCR, to distinguish individual cellular contributions to mRNA abundance differences.
All pages presents interesting papers, sampling technologies and links about single-cell qRT-PCR, using micro-manipulated or laser-capture microdissected tissue followed by real-time RT-PCR.


digital PCR        (abbreviations:   digital PCR  -  DigitalPCR  -  dPCR  -  dePCR)

Digital PCR (dPCR) is a refinement of conventional PCR methods that can be used to directly quantify and clonally amplify nucleic acids (including DNA, cDNA, methylated DNA, or RNA). The key difference between dPCR and traditional PCR lies in the method of measuring nucleic acids amounts, with the former being a more precise method than PCR. PCR carries out one reaction per single sample. dPCR also carries out a single reaction within a sample, however the sample is separated into a large number of partitions and the reaction is carried out in each partition individually. This separation allows a more reliable collection and sensitive measurement of nucleic acid amounts. The method has been demonstrated as useful for studying variations in gene sequences - such as copy number variants, point mutations, and it is routinely used for clonal amplification of samples for "next-generation sequencing."

small inhibiting RNA  (siRNA)

Small interfering RNA (siRNA), sometimes known as short interfering RNA or silencing RNA, are a class of 20-25 nucleotide-long double-stranded RNA molecules that play a variety of roles in biology. Most notably, it is involved in the RNA interference (RNAi) pathway where the siRNA interferes with the expression of a specific gene. In addition to their role in the RNAi pathway, siRNAs also act in RNAi-related pathways, e.g. as an antiviral mechanism or in shaping the chromatin structure of a genome; the complexity of these pathways is only now being elucidated. SiRNAs were first discovered by David Baulcombe's group in Norwich, England, as part of post-transcriptional gene silencing (PTGS) in plants, and published there findings in Science in a paper titled "A species of small antisense RNA in posttranscriptional gene silencing in plants." Shortly thereafter, in 2001, synthetic siRNAs were then shown to be able to induce RNAi in mammalian cells by Thomas Tuschl and colleagues in a paper, "Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells." published in Nature and Genes & Development. This discovery led to a surge in interest in harnessing RNAi for biomedical research and drug development.

CNV = Copy Number Variants = Copy Number Variation

The human genome is comprised of 6 billion chemical bases (or nucleotides) of DNA packaged into two sets of 23 chromosomes, one set inherited from each parent. The DNA encodes roughly 27,000 genes. It was generally thought that genes were almost always present in two copies in a genome. However, recent discoveries have revealed that large segments of DNA, ranging in size from thousands to millions of DNA bases, can vary in copy-number. Such copy number variations (or CNVs) can encompass genes leading to dosage imbalances. For example, genes that were thought to always occur in two copies per genome have now been found to sometimes be present in one, three, or more than three copies. In a few rare instances the genes are missing altogether. Differences in the DNA sequence of our genomes contribute to our uniqueness. These changes influence most traits including susceptibility to disease. It was thought that single nucleotide changes (called SNPs) in DNA were the most prevalent and important form of genetic variation. The current studies reveal that CNVs comprise at least three times the total nucleotide content of SNPs. Since CNVs often encompass genes, they may have important roles both in human disease and drug response. Understanding the mechanisms of CNV formation may also help us better understand human genome evolution.


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