Genomics and predictive medicine

Progress in understanding of structural and functional human genome organization and deciphering primary DNA sequence in human cells allowed for hitherto unreachable new capabilities of medical genetics in identifying the causes and mechanisms of inherited and inborn pathology. Implementation of genetics into medicine is progressively advancing along with improvement of molecular analysis of genome. Knowledge of genome and its functions allows to provide more accurate diagnosis, predict, to a considerable extent, the presence of genetic predisposition of a person to pathology, and to assess the chances for developing one or another disease. This approach became the basis for a new area of medical genetics named predictive medicine. The progress of predictive medicine refl ects success in tremendous upgrowth of molecular genetic methods and new capabilities of studying structure and functions of genome. Within less than 15 years after deciphering genome, medical genetics has travelled a long way from a single gene analysis to whole genome studies, from screening of genetic associations to systems genetics of multifactorial diseases, from translational to high-precision genetics, and from genetic passport idea to electronic genetic health records. The development of a genetic passport, prognostic genetic testing, and genomic chart of reproductive health is especially relevant for current practical medicine.

GeneNetwork: a continuously updated tool for systems genetics analyses

GeneNetwork and its earlier iteration, WebQTL, have now been an important database and toolkit for quantitative trait genetics research for two decades. Recent improvements to GeneNetwork have reinvigorated it, including the addition of data from 10 species, multi-omics analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for predictive medicine and systems genetics, which is constantly being maintained and improved. Here, we give a brief overview of the process for carrying out some of the most common functions on GeneNetwork, as a gateway to deeper analyses, demonstrating how a small number of plausible candidate genes can be found for a typical immune phenotype.