Agrigenomics, smart food and nutrigenomics

Agrigenomics, smart food and nutrigenomics

Given the changing environment, our expanding population, and increasing demands for nutrition, the need to optimize agriculture is of fundamental importance. The application of genomics technologies to the breeding and management of crops and livestock allows researchers to generate new opportunities for improving food production and developing sustainable practices to address these challenges. 

Agrigenomics (or Agricultural genomics) is a key driver of sustainable production and is important for finding solutions to the challenge of feeding the global population. Genomic technologies have revolutionized the breeding and management of crops and livestock. Agrigenomics uses genotyping and next-generation sequencing technologies to study agricultural species to gain a better understanding of the genetic variation influencing phenotypes and to identify the genetic markers linked to desirable traits, that can be used to inform cultivation and breeding decisions. For example applying genomics technologies to study crops grown in drylands of Asia and Sub-Saharan Africa could see breakthroughs that support new, more resilient crops to feed the people living in these areas. Agrigenomics is also being applied in areas such as food safety, to accurately and precisely trace beef, pork, poultry and seafood products from the fork to the farm.

The link between diet and health is well established, and according to WHO reports diet factors influence the occurrence of more than 2/3 of diseases. Nutrigenomics (also known as nutritional genomics) analyses the direct influence of nutrients on gene expression. Nutrigenomics applies high throughput functional genomic technologies to discover how nutrition influences the expression of the genome helping us to understand how nutrients influence cells, organs and the whole body. The main challenges for nutrigenomics is the design of meaningful studies capable of deciphering the nutrient-gene interactions against a background of individuals’ genetic differences and the integration, interrogation and interpretation of the vast data sets that such studies produce.