Missing Regulation Between Genetic Association and Transcriptional Abundance for Hypercholesterolemia Genes.

Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels.

NERINE reveals rare variant associations in gene networks across multiple phenotypes and implicates an subnetwork in Parkinson's disease.

Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation.

Inherent instability of simple DNA repeats shapes an evolutionarily stable distribution of repeat lengths.

Using the Telomere-to-Telomere reference, we assembled the distribution of simple repeat lengths present in the human genome. Analyzing over two hundred mammalian genomes, we found remarkable consistency in the shape of the distribution across evolutionary epochs. All observed genomes harbor an excess of long repeats, which are prone to developing into repeat expansion disorders.

Quantifying constraint in the human mitochondrial genome.

Mitochondrial DNA (mtDNA) has an important yet often overlooked role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection and represent powerful tools for identifying genetic variation that underlies human phenotypes. However, nuclear constraint models are not applicable to mtDNA, owing to its distinct features.