Mother–Fetus Immune Cross-Talk Coordinates “Extrinsic”/“Intrinsic” Embryo Gene Expression Noise and Growth Stability

Abstract

Developmental instability (DI) is thought to be inversely related to a capacity of an organism to buffer its development against random genetic and environmental perturbations. DI is represented by a trait’s inter- and intra-individual variabilities. The inter-individual variability (inversely referred to as canalization) indicates the capability of organisms to reproduce a trait from individual to individual. The intra-individual variability reflects an organism’s capability to stabilize a trait internally under the same conditions, and, for symmetric traits, it is expressed as fluctuating asymmetry (FA). When representing a trait as a random variable conditioned on environmental fluctuations, it is clear that, in statistical terms, the DI partitions into “extrinsic” (canalization) and “intrinsic” (FA) components of a trait’s variance/noise. We established a simple statistical framework to dissect both parts of a symmetric trait variance/noise using a PCA (principal component analysis) projection of the left/right measurements on eigenvectors followed by GAMLSS (generalized additive models for location scale and shape) modeling of eigenvalues. The first eigenvalue represents “extrinsic” and the second—“intrinsic” DI components. We applied this framework to investigate the impact of mother–fetus major histocompatibility complex (MHC)-mediated immune cross-talk on gene expression noise and developmental stability. We showed that “intrinsic” gene noise for the entire transcriptional landscape could be estimated from a small subset of randomly selected genes. Using a diagnostic set of genes, we found that allogeneic MHC combinations tended to decrease “extrinsic” and “intrinsic” gene noise in C57BL/6J embryos developing in the surrogate NOD-SCID and BALB/c mothers. The “intrinsic” gene noise was negatively correlated with growth (embryonic mass) and the levels of placental growth factor (PLGF), but not vascular endothelial growth factor (VEGF). However, it was positively associated with phenotypic growth instability and noise in PLGF. In mammals, the mother–fetus MHC interaction plays a significant role in development, contributing to the fitness of the offspring. Our results demonstrate that a positive impact of distant MHC combinations on embryonic growth could be mediated by the reduction of “intrinsic” gene noise followed by the developmental stabilization of growth.

Developmental Biology: Computational and Experimental Approaches

“…This Special Issue entitled “Developmental Biology: Computational and Experimental Approaches” of the International Journal of Molecular Sciences includes six contributions as original articles [ 4 , 5 , 6 , 7 , 8 , 9 ], providing new information about the experimental and computational approaches that promote technical progress for research into developmental biology.…”

“…One study included in this Special Issue on computer-based and experimental approaches in developmental biology put together [ 5 ] two independent lines of research: at the phenotypic level, there is an in vivo assessment of variation in mammalian progeny due to mother–fetus immune cross-talk, and at the molecular level, there is an in silico assessment of variation in gene expression depending on the environmental effects on the nucleosome packaging of these genes (i.e., transcriptional noise) [ 10 ]. As a result, this enabled Babochkina et al [ 5 ] to concurrently measure the “extrinsic” and “intrinsic” components of within-species variation as an all-time attribute of any biological species. It was thus found that “extrinsic” variation may have a positive effect on embryonic development (i.e., something resembling heterosis and hybrid vigor) through a decrease in “intrinsic” transcriptional noise (e.g., stressless pregnancy) followed by growth stabilization as development proceeds.…”

“…Our Special Issue devoted to developmental biology shows that the matter of identification of the molecular mechanisms underlying signal transduction and gene expression in normal embryogenesis [ 4 , 5 ] and normal prepuberty [ 6 ], in abnormal processes due to polymorphisms (SNPs) [ 7 ], in cancers [ 8 ], and in infection caused by SARS-CoV-2 [ 9 ] is one of the first priorities of modern experimental and computer-based studies.…”