Dynamic modeling of folliculogenesis signaling pathways in the presence of miRNAs expression

An integrated analysis of multiple datasets reveals novel gene signatures in human granulosa cells

Granulosa cells (GCs) play crucial roles in oocyte maturation. Through gap junctions and extracellular vesicles, they mediate the exchange of molecules such as microRNAs and messenger RNAs. Different ovarian cell types exhibit unique gene expression profiles, reflecting their specialized functions and stages. By combining RNA-seq data from various cell types forming the follicle, we aimed at capturing a wide range of expression patterns, offering insights into the functional diversity and complexity of the transcriptome regulation across GCs. Herein, we performed an integrated bioinformatics analysis of RNA sequencing datasets present in public databases, with a unique and standardized workflow., By combining the data from different studies, we successfully increased the robustness and reliability of our findings and discovered novel genes, miRNAs, and signaling pathways associated with GCs function and oocyte maturation. Moreover, our results provide a valuable resource for further wet-lab research on GCs biology and their impact on oocyte development and competence.

Follicle-Stimulating Hormone Glycosylation Variants Distinctly Modulate Pre-antral Follicle Growth and Survival

Follicle-stimulating hormone (FSH) is a key endocrine regulator of ovarian function. FSH is secreted as 2 macroglycosylation variants: partially glycosylated FSH (FSH21/18) and fully glycosylated FSH (FSH24). FSH21/18 is more potent than FSH24 at binding to and activating the FSH receptor (R). The ratio of FSH21/18:FSH24 has been shown to change with age, with FSH21/18 predominant at reproductive prime, and FSH24 predominant during perimenopause/menopause. How these FSH glycosylation variants modulate ovarian follicle functions remains largely unknown. The aim of this study was to investigate the effect of FSH glycosylation variants of pre-antral follicle function. Pre-antral follicles were isolated from 3- to 5-week-old C57BL/6 mice and treated ±10 ng/mL FSH21/18, FSH24, a ratio of 80:20 FSH21/18:FSH24 (to mimic reproductive prime), 50:50 FSH21/18:FSH24 (perimenopause), or 20:80 FSH21/18:FSH24 (menopause) for up to 96 hours. FSH21/18 and 80:20 FSH21/18:FSH24 increased follicle growth, in comparison with control, contrasting with FSH24 and 20:80 FSH21/18:FSH24. Survival rates were decreased in follicles treated with FSH24 or 20:80 FSH21/18:FSH24, with follicles undergoing basement membrane rupture and oocyte extrusion, increased Caspase3 gene and protein expression, and decreased markers of cell proliferation in FSH24 or 20:80 FSH21/18:FSH24-treated follicles. Moreover, this correlated with differential regulation of key genes modulating follicular functions. Pharmacological inhibitors of key FSH signal pathways suggests FSH21/18 and FSH24 initiate different FSHR signal pathway activation, which may determine their differential effects on follicle growth and survival. These data suggest that the nature of FSH glycosylation modulates the follicular cellular environment to regulate follicle growth and survival and may underpin the increasing ovarian resistance to FSH observed during aging.

Omics Multi-Layers Networks Provide Novel Mechanistic and Functional Insights Into Fat Storage and Lipid Metabolism in Poultry

Fatty acid metabolism in poultry has a major impact on production and disease resistance traits. According to the high rate of interactions between lipid metabolism and its regulating properties, a holistic approach is necessary. To study omics multilayers of adipose tissue and identification of genes and miRNAs involved in fat metabolism, storage and endocrine signaling pathways in two groups of broiler chickens with high and low abdominal fat, as well as high-throughput techniques, were used. The gene–miRNA interacting bipartite and metabolic-signaling networks were reconstructed using their interactions. In the analysis of microarray and RNA-Seq data, 1,835 genes were detected by comparing the identified genes with significant expression differences (p.adjust < 0.01, fold change ≥ 2 and ≤ −2). Then, by comparing between different data sets, 34 genes and 19 miRNAs were detected as common and main nodes. A literature mining approach was used, and seven genes were identified and added to the common gene set. Module finding revealed three important and functional modules, which were involved in the peroxisome proliferator-activated receptor (PPAR) signaling pathway, biosynthesis of unsaturated fatty acids, Alzheimer’s disease metabolic pathway, adipocytokine, insulin, PI3K–Akt, mTOR, and AMPK signaling pathway. This approach revealed a new insight to better understand the biological processes associated with adipose tissue.

Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Simple Summary

Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. Gene set enrichment analysis indicated that the identified candidate genes were related to biological processes and functional terms that were involved in growth and lipid metabolism. In conclusion, these results suggest that the incorporation of GWAS results and network analysis can help us to better understand the genetic bases underlying growth and carcass traits.

Abstract

In recent years, studies on the biological mechanisms underlying complex traits have been facilitated by innovations in high-throughput genotyping technology. We conducted a weighted single-step genome-wide association study (WssGWAS) to evaluate backfat thickness, carcass weight, eye muscle area, marbling score, and yearling weight in a cohort of 1540 Hanwoo beef cattle using BovineSNP50 BeadChip. The WssGWAS uncovered thirty-three genomic regions that explained more than 1% of the additive genetic variance, mostly located on chromosomes 6 and 14. Among the identified window regions, seven quantitative trait loci (QTL) had pleiotropic effects and twenty-six QTL were trait-specific. Significant pathways implicated in the measured traits through Gene Ontology (GO) term enrichment analysis included the following: lipid biosynthetic process, regulation of lipid metabolic process, transport or localization of lipid, regulation of growth, developmental growth, and multicellular organism growth. Integration of GWAS results of the studied traits with pathway and network analyses facilitated the exploration of the respective candidate genes involved in several biological functions, particularly lipid and growth metabolism. This study provides novel insight into the genetic bases underlying complex traits and could be useful in developing breeding schemes aimed at improving growth and carcass traits in Hanwoo beef cattle.