Thymine DNA glycosylase (TDG) is a nuclear receptor coactivator that plays an essential role in the maintenance of epigenetic stability in cells. Here, we demonstrate that the conditional deletion of TDG in adult mice results in a male-predominant onset of hepatocellular carcinoma (HCC). TDG loss leads to a prediabetic state, as well as bile acid (BA) accumulation in the liver and serum of male mice. Consistent with these data, TDG deletion led to dysregulation of the farnesoid X receptor (FXR) and small heterodimer partner (SHP) regulatory cascade in the liver. FXR and SHP are tumor suppressors of HCC and play an essential role in BA and glucose homeostasis. These results indicate that TDG functions as a tumor suppressor of HCC by regulating a transcriptional program that protects against the development of glucose intolerance and BA accumulation in the liver. TP53 deficiency is the most common alteration in cancer; however, this alone is typically insufficient to drive tumorigenesis. To identify genes promoting tumorigenesis in combination with TP53 deficiency, we perform genome-wide CRISPR-Cas9 knockout screens coupled with proliferation and transformation assays in isogenic cell lines. Loss of several known tumor suppressors enhances cellular proliferation and transformation. Loss of neddylation pathway genes promotes uncontrolled proliferation exclusively in TP53-deficient cells. Combined loss of CUL3 and TP53 activates an oncogenic transcriptional program governed by the nuclear factor κB (NF-κB), AP-1, and transforming growth factor β (TGF-β) pathways. This program maintains persistent cellular proliferation, induces partial epithelial to mesenchymal transition, and increases DNA damage, genomic instability, and chromosomal rearrangements. Our findings reveal CUL3 loss as a key event stimulating persistent proliferation in TP53-deficient cells. These findings may be clinically relevant, since TP53-CUL3-deficient cells are highly sensitive to ataxia telangiectasia mutated (ATM) inhibition, exposing a vulnerability that could be exploited for cancer treatment. N6-Methyladenosine (m6A) modification is the major chemical modification in mRNA that controls fundamental biological processes, including cell proliferation. Herein, we demonstrate that fat mass and obesity-associated (FTO) demethylates m6A modification of cyclin D1, the key regulator for G1 phase progression and controls cell proliferation in vitro and in vivo. FTO depletion upregulates cyclin D1 m6A modification, which in turn accelerates the degradation of cyclin D1 mRNA, leading to the impairment of G1 progression. m6A modification of cyclin D1 oscillates in a cell-cycle-dependent manner; m6A levels are suppressed during the G1 phase and enhanced during other phases. Low m6A levels during G1 are associated with the nuclear translocation of FTO from the cytosol. Furthermore, nucleocytoplasmic shuttling of FTO is regulated by casein kinase II-mediated phosphorylation of FTO. Our results highlight the role of m6A in regulating cyclin D1 mRNA stability and add another layer of complexity to cell-cycle regulation. Olfactory neurons allow animals to discriminate nutritious food sources from potential pathogens. From a forward genetic screen, we uncovered a surprising requirement for the olfactory neuron gene olrn-1 in the regulation of intestinal epithelial immunity in Caenorhabditis elegans. During nematode development, olrn-1 is required to program the expression of odorant receptors in the AWC olfactory neuron pair. Here, we show that olrn-1 also functions in AWC neurons in the cell non-autonomous suppression of the canonical p38 MAPK PMK-1 immune pathway in the intestine. Low activity of OLRN-1, which activates the p38 MAPK signaling cassette in AWC neurons during larval development, also de-represses the p38 MAPK PMK-1 pathway in the intestine to promote immune effector transcription, increased clearance of an intestinal pathogen, and resistance to bacterial infection. These data reveal an unexpected connection between olfactory receptor development and innate immunity and show that anti-pathogen defenses in the intestine are developmentally programmed.  https://www.selleckchem.com/products/c646.html  Although the genetic triggers for gonadal sex differentiation vary across species, the cell biology of gonadal development was long thought to be largely conserved. Here, we present a comprehensive analysis of gonadal sex differentiation, using single-cell sequencing in the embryonic chicken gonad during sexual differentiation. The data show that chicken embryonic-supporting cells do not derive from the coelomic epithelium, in contrast to other vertebrates studied. Instead, they derive from a DMRT1+/PAX2+/WNT4+/OSR1+ mesenchymal cell population. We find a greater complexity of gonadal cell types than previously thought, including the identification of two distinct sub-populations of Sertoli cells in developing testes and derivation of embryonic steroidogenic cells from a differentiated supporting-cell lineage. Altogether, these results indicate that, just as the genetic trigger for sex differs across vertebrate groups, cell lineage specification in the gonad may also vary substantially. High-throughput single-cell RNA sequencing (scRNA-seq) has become a frequently used tool to assess immune cell heterogeneity. Recently, the combined measurement of RNA and protein expression was developed, commonly known as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq). Acquisition of protein expression data along with transcriptome data resolves some of the limitations inherent to only assessing transcripts but also nearly doubles the sequencing read depth required per single cell. Furthermore, there is still a paucity of analysis tools to visualize combined transcript-protein datasets. Here, we describe a targeted transcriptomics approach that combines an analysis of over 400 genes with simultaneous measurement of over 40 proteins on 2 × 104 cells in a single experiment. This targeted approach requires only about one-tenth of the read depth compared to a whole-transcriptome approach while retaining high sensitivity for low abundance transcripts. To analyze these multi-omic datasets, we adapted one-dimensional soli expression by nonlinear stochastic embedding (One-SENSE) for intuitive visualization of protein-transcript relationships on a single-cell level.