Monthly Archives: November 2019

This (developmental biology) story is an awesome example of gene-environment interactions. 😊 To start with, animal embryos shape their tissues during development through a variety of mechanisms — one of which involves coordinated constriction of one side of a sheet … Continue reading →

These GEITP pages recently discussed the evolutionary history and divergence of plant genomes, it seems reasonable to note the evolutionary history and divergence of earthworm genomes. The importance of earthworms has long been recognized for their effects on terrestrial systems … Continue reading →

These (gene-environment interactions) GEITP pages have a continued interest in evolution, because that process involves the genomes of all living organisms to “adapt” to changes in the environment in order better to survive (‘survival of the fittest’). Green plants comprise … Continue reading →

These GEITP pages have frequently described the growing appreciation of our intestinal microbiome (bacteria, fungi and viruses) and our increasing appreciation of the brain-gut-microbiome axis. Which species predominate in the microbiota — and what metabolism takes place in the intestine … Continue reading →

This topic is only tangentially related to gene-environment interactions, but, given the incredible amounts of data now available — during this past decade of DNA-sequencing, RNA-sequencing transcriptomics, and comparisons of hundreds of genomes from different species — the bigger and … Continue reading →

In keeping with our GEITP gene-environment interactions theme, this topic concerns interactions between “dietary salt” as the environment, and each person’s genome or genetic susceptibility as the genes. Vascular risk factors — including excessive salt consumption — have long been … Continue reading →

Despite all the ease with which the popular CRISPR/Cas9 gene-editing tool is able to alter genomes, this method is still somewhat prone to errors and unintended effects (so-called “off-targets”). To achieve the best outcome, researchers would like to exchange or … Continue reading →

For today’s topic, cigarette smoking (environmental signal) has an effect on genetic susceptibility (increased risk of type-2 diabetes, i.e. the genome); hence, gene-environment interactions. It has long been known that cigarette smoking increases the risk of type-2 diabetes, because nicotine … Continue reading →

As these GEITP pages continue to emphasize, genome-wide association studies (GWAS) have been used for ~13 years in order to find associations between specific single-nucleotide variants (SNVs) throughout the genome — and the multifactorial trait chosen for study. Multifactorial phenotypes … Continue reading →