Real-time quantitative PCR (qPCR) is a powerful tool for quantifying specific DNA target sequences. Although determination of relative quantity is widely accepted as a reliable means of measuring differences between samples, there are advantages to being able to determine the absolute copy numbers of a given target. One approach to absolute quantification relies on construction of an accurate standard curve using appropriate external standards of known concentration. We have validated the use of tissue genomic DNA as a universal external standard to facilitate quantification of any target sequence contained in the genome of a given species, addressing several key technical issues regarding its use. This approach was applied to validate mRNA expression of gene candidates identified from microarray data and to determine gene copies in transgenic mice. A simple method that can assist achieving absolute quantification of gene expression would broadly enhance the uses of real-time qPCR and in particular, augment the evaluation of global gene expression studies.
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http://dx.doi.org/10.1093/nar/gkl400 | DOI Listing |
Sci Rep
December 2024
Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, 2-2-E2, Yamada-Oka, Suita, Osaka, 565-0871, Japan.
Esophageal cancer is a highly aggressive disease, and acquired resistance to chemotherapy remains a significant hurdle in its treatment. mtDNA, crucial for cellular energy production, is prone to mutations at a higher rate than nuclear DNA. These mutations can accumulate and disrupt cellular function; however, mtDNA mutations induced by chemotherapy in esophageal cancer remain unexplored.
View Article and Find Full Text PDFNPJ Biofilms Microbiomes
December 2024
Costerton Biofilm Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, 2200, Denmark.
The evolution of antimicrobial resistance (AMR) in biofilms, driven by mechanisms like oxidative stress, is a major challenge. This study investigates whether antioxidants (AOs) such as N-acetyl-cysteine (NAC) and Edaravone (ED) can reduce AMR in Pseudomonas aeruginosa biofilms exposed to sub-inhibitory concentrations of ciprofloxacin (CIP). In vitro experimental evolution studies were conducted using flow cells and glass beads biofilm models.
View Article and Find Full Text PDFNat Commun
December 2024
Architecture and Dynamics of Biological Macromolecules, Institut Pasteur, Université Paris Cité, CNRS UMR 3528, Paris, France.
Replication Protein A (RPA) plays a pivotal role in DNA replication by coating and protecting exposed single-stranded DNA, and acting as a molecular hub that recruits additional replication factors. We demonstrate that archaeal RPA hosts a winged-helix domain (WH) that interacts with two key actors of the replisome: the DNA primase (PriSL) and the replicative DNA polymerase (PolD). Using an integrative structural biology approach, combining nuclear magnetic resonance, X-ray crystallography and cryo-electron microscopy, we unveil how RPA interacts with PriSL and PolD through two distinct surfaces of the WH domain: an evolutionarily conserved interface and a novel binding site.
View Article and Find Full Text PDFNat Commun
December 2024
Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, Oslo, Norway.
Short tandem repeats (STRs) have emerged as important and hypermutable sites where genetic variation correlates with gene expression in plant and animal systems. Recently, it has been shown that a broad range of transcription factors (TFs) are affected by STRs near or in the DNA target binding site. Despite this, the distribution of STR motif repetitiveness in eukaryote genomes is still largely unknown.
View Article and Find Full Text PDFNat Commun
December 2024
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, 100871, Beijing, China.
Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines.
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