The central dogma of molecular biology states that DNA codes for RNA and RNA codes for protein. It was widely understood that because protein is translated from mRNA, the amount of mRNA in a cell would somewhat correspond to the quantity of cellular protein. In a new study out of Notre Dame, scientists have shown that this theory is not always correct. While in many cases mRNA and protein levels do correspond, there are a surprisingly high number of exceptions, demonstrating that the amounts of a particular protein can be controlled by multiple mechanisms.
Bioanalytical chemist Norman Dovichi and molecular biologist Paul Huber identified and measured the levels of about 4,000 proteins, which exhibited patterns of expression that reflect key events during early Xenopus development resulting in the largest data set on developmental proteomics for any organism.
The study was conducted in Xenopus laevis embryos, which is a favored model for this type of research. In Xenopus, development takes place in well-defined stages outside the mother, thereby allowing embryogenesis to be monitored in real time. Additionally, embryos develop rapidly, achieving a nearly fully developed nervous system within four days.
Their results are available open access in Scientific Reports.
What’s the strangest thing you have ever dissected?
An international team led by researchers with the Lawrence Berkeley National Laboratory (Berkeley Lab) has developed a new technique for identifying gene enhancers – sequences of DNA that act to amplify the expression of a specific gene – in the genomes of humans and other mammals. Called SIF-seq, for site-specific integration fluorescence-activated cell sorting followed by sequencing, this new technique complements existing genomic tools, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), and offers some additional benefits.
“While ChIP-seq is very powerful in that it can query an entire genome for characteristics associated with enhancer activity in a single experiment, it can fail to identify some enhancers and identify some sites as being enhancers when they really aren’t,” says Diane Dickel, a geneticist with Berkeley Lab’s Genomics Division and member of the SIF-seq development team. “SIF-seq is currently capable of testing only hundreds to a few thousand sites for enhancer activity in a single experiment, but can determine enhancer activity more accurately than ChIP-seq and is therefore a very good validation assay for assessing ChIP-seq results.”
Dickel is the lead author of a paper in Nature Methods describing this new technique. The paper is titled “Function-based identification of mammalian enhancers using site-specific integration.”