Priit Adler

Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation.

The twenties are typically considered the prime reproductive years for women. However, in today’s modern world, many women are choosing to delay family planning, resulting in an increase of females in their forties seeking fertility treatment. Although in vitro fertilization (IVF) with donated oocytes and preimplantation genetic testing may help to address the impact of maternal age, the success rate for IVF treatment in this age group is still significantly lower. While endometrial changes, such as abnormal endometrial thickness, inflammatory background, and altered hormone response signaling, are associated with aging, little is known about the molecular features of endometrial aging and their impact on the ability to support embryo implantation. To better understand age-specific changes, we performed endometrial transcriptome profiling of young and advanced age females, undergoing hormonal replacement therapy (HRT) before frozen embryo transfer, followed by immunohistology analysis and single-cell-based deconvolution. Here, we identified 491 differentially expressed genes pointing to the effect of aging on decidualization, cell signaling, inflammation and endometrial receptivity. Our results indicate that p16 ^INK4a may be involved in cellular senescence and the suppression of metabolic and inflammatory processes essential for endometrial preparation for embryo implantation. We have also shown that the proportion of ciliated cells along with ciliary processes is affected by endometrial aging. These findings have important implications for future strategies aimed at improving infertility treatment in women of advanced reproductive age.

G:Profiler is a reliable and up-to-date functional enrichment analysis tool that supports various evidence types, identifier types and organisms. The toolset integrates many databases, including Gene Ontology, KEGG and TRANSFAC, to provide a comprehensive and in-depth analysis of gene lists. It also provides interactive and intuitive user interfaces and supports ordered queries and custom statistical backgrounds, among other settings. g:Profiler provides multiple programmatic interfaces to access its functionality. These can be easily integrated into custom workflows and external tools, making them valuable resources for researchers who want to develop their own solutions. g:Profiler has been available since 2007 and is used to analyse millions of queries. Research reproducibility and transparency are achieved by maintaining working versions of all past database releases since 2015. g:Profiler supports 849 species, including vertebrates, plants, fungi, insects and parasites, and can analyse any organism through user-uploaded custom annotation files. In this update article, we introduce a novel filtering method highlighting Gene Ontology driver terms, accompanied by new graph visualizations providing a broader context for significant Gene Ontology terms. As a leading enrichment analysis and gene list interoperability service, g:Profiler offers a valuable resource for genetics, biology and medical researchers. It is freely accessible at https://biit.cs.ut.ee/gprofiler.

Deciphering heterogeneous cellular networks with embedded modules is a great challenge of current systems biology. Experimental and computational studies construct complex networks of molecules that describe various aspects of the cell such as transcriptional regulation, protein interactions and metabolism. Groups of interacting genes and proteins reflect network modules that potentially share regulatory mechanisms and relate to common function. Here, we present GraphWeb, a public web server for biological network analysis and module discovery. GraphWeb provides methods to: ( 1 ) integrate heterogeneous and multispecies data for constructing directed and undirected, weighted and unweighted networks; (ii) discover network modules using a variety of algorithms and topological filters and (iii) interpret modules using functional knowledge of the Gene Ontology and pathways, as well as regulatory features such as binding motifs and microRNA targets. GraphWeb is designed to analyse individual or multiple merged networks, search for conserved features across multiple species, mine large biological networks for smaller modules, discover novel candidates and connections for known pathways and compare results of high-throughput datasets. The GraphWeb is available at http://biit.cs.ut.ee/graphweb/ .