TransOrGAN: An Artificial Intelligence Mapping of Rat Transcriptomic Profiles between Organs, Ages, and Sexes

Animal studies are required for the evaluation of candidate
drugs
to ensure patient and volunteer safety. Toxicogenomics is often applied
in these studies to gain understanding of the underlying mechanisms
of toxicity, which is usually focused on critical organs such as the
liver or kidney in young male rats. There is a strong ethical reason
to reduce, refine and replace animal use (the 3Rs), where the mapping
of data between organs, sexes and ages could reduce the cost and time
of drug development. Herein, we proposed a generative adversarial
network (GAN)-based framework entitled TransOrGAN that allowed the
molecular mapping of gene expression profiles in different rodent
organ systems and across sex and age groups. We carried out a proof-of-concept
study based on rat RNA-seq data from 288 samples in 9 different organs
of both sexes and 4 developmental stages. First, we demonstrated that
TransOrGAN could infer transcriptomic profiles between any 2 of the
9 organs studied, yielding an average cosine similarity of 0.984 between
synthetic transcriptomic profiles and their corresponding real profiles.
Second, we found that TransOrGAN could infer transcriptomic profiles
observed in females from males, with an average cosine similarity
of 0.984. Third, we found that TransOrGAN could infer transcriptomic
profiles in juvenile, adult, and aged animals from adolescent animals
with an average cosine similarity of 0.981, 0.983, and 0.989, respectively.
Altogether, TransOrGAN is an innovative approach to infer transcriptomic
profiles between ages, sexes, and organ systems, offering the opportunity
to reduce animal usage and to provide an integrated assessment of
toxicity in the whole organism irrespective of sex or age.