Sex differences in gene regulatory networks during mid-gestational brain development

Abstract

Neurodevelopmental disorders differ considerably between males and females, and fetal brain development is one of the most critical periods to determine risk for these disorders. Transcriptomic studies comparing male and female fetal brain have demonstrated that the highest difference in gene expression occurs in sex chromosomes, but several autossomal genes also demonstrate a slight difference that has not been yet explored. In order to investigate biological pathways underlying fetal brain sex differences, we applied medicine network principles using integrative methods such as co-expression networks (CEMiTool) and regulatory networks (netZoo). The pattern of gene expression from genes in the same pathway tend to reflect biologically relevant phenomena. In this study, network analysis of fetal brain expression reveals regulatory differences between males and females. Integrating two different bioinformatics tools, our results suggest that biological processes such as cell cycle, cell differentiation, energy metabolism and extracellular matrix organization are consistently sex-biased. MSET analysis demonstrates that these differences are relevant to neurodevelopmental disorders, including autism.

Single-cell analysis of sex and gender differences in the human brain during development and disease

“…Previous findings indicate that there are small but consistent SG di↵erences in several brain regions, including the cortex [21]. In addition, SG biases in transcriptome and gene regulatory networks have been observed in the second trimester of pregnancy, very early in the development process [27,28]. During brain development, maturation, and neurological diseases, di↵erences in the number, distribution, and activity of particular cells, such as neurons and immune cells, have been observed between males and females [7,[12][13][14][15][16][17].…”

The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks

“…This PANDA-LIONESS combination has been applied previously in various other settings, such as the study of sex differences in health and disease [47], by our group [20,39,48] and others [49], but the uniqueness of the CCLE data makes this combination particularly powerful on single gene expression samples from collapsed replicates and even in the absence of replicates. To demonstrate the advantage of using netZoo methods in combination, we modified MONSTER to use LIONESS networks as input for the estimation of drivers of transitions between two biological states using a PANDA-LION-ESS-MONSTER pipeline (see the sections "Methods": "TF targeting analysis").…”