User

Pregnancy in mammals is a highly complex process that requires a precise dialogue between the developing embryo/conceptus and the maternal environment. Our approach involves the application of molecular data science tools, such as transcriptomics, multi-omics data integration and Machine Learning algorithms, to understand the regulation of pregnancy establishment and healthy foetal development in animals. The cow is a species of major interest, given its critical role in achieving sustainable food production. One of our main objectives is to characterise the bidirectional responses between the molecular profiles of the embryo and the endometrium (the inner layer of the uterus in contact with the embryo), leading to a successful pregnancy and the development of healthy offspring. Another broad objective is to test the hypothesis that maternal influences on foetal growth and, thus, on the physiology of the postnatal offspring can be quantified through the molecular signature in maternal blood at different stages of gestation, which in turn can be harnessed to construct predictive models of offspring characteristics.