An international collaboration led by scientists at The University of South Australia, SA Pathology in Adelaide, and the de Duve Institute, University of Louvain, Belgium, has discovered biallelic MDFIC pathogenic variants underlying the severe lymphatic disorder, central conducting lymphatic anomaly (CCLA), in seven people from six separate families.

Fabric Genomics Inc.’s Gem artificial intelligence algorithm plus whole genome and whole exome data detected more than 90% of disease-causing variants in infants with rare diseases, a study in Genome Medicine demonstrated. The full process from blood sample to shortlist of causative variants and likely diseases takes just a matter of hours and the time to interpret whole genomes is condensed to about 15 minutes.

The most comprehensive international collaborative analysis to date of the impact of variants on gene expression has revealed thousands of previously unknown regulatory genomic regions controlling disease-linked genes, representing a major advance in genomics-driven precision medicine.

Data on the prevalence of diabetes in the U.S. show that non-Hispanic white people are least likely to suffer from the disease. Yet to date most genetic studies of the glycemic traits that are used to diagnose and monitor type 2 diabetes and cardiometabolic health have focused on individuals of European ancestry.

Data on the prevalence of diabetes in the U.S. show that non-Hispanic white people are least likely to suffer from the disease. Yet to date most genetic studies of the glycemic traits that are used to diagnose and monitor type 2 diabetes and cardiometabolic health have focused on individuals of European ancestry.

Researchers at Yale University have described what they have called a “data sanitization tool,” enabling them to strip personal identifiers out of functional genomics data while preserving their usefulness for research.

The Genotype-Tissue Expression (GTEx) project, a multiyear, multi-institutional attempt to catalog how expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) affect protein levels, reported data from its final phase in 15 papers in the Sept, 10, 2020, online issues of the Science and Cell family of journals, as well as in Genome Biology.

Researchers from the Encyclopedia of DNA Elements (ENCODE) consortium reported data from the third phase of the project. Phase III data, which were published in more than a dozen papers in Nature and its sister journals on July 29, 2020, consisted of 6,000 experiments performed on around 1,300 samples.

LONDON – A vast new body of genomics research has identified thousands of rare genetic variants that are predicted to cause loss of function in protein coding genes, providing novel in vivo models of human gene inactivation.

LONDON – A vast new body of genomics research has identified thousands of rare genetic variants that are predicted to cause loss of function in protein coding genes, providing novel in vivo models of human gene inactivation.