Cancer-associated DNA Hypermethylation of Polycomb Targets Requires DNMT3A Dual Recognition of Histone H2AK119 Ubiquitination and the Nucleosome Acidic Patch.

During tumor development, promoter CpG islands (CGIs) that are normally silenced by Polycomb repressive complexes (PRCs) become DNA hypermethylated. The molecular mechanism by which de novo DNA methyltransferase(s) catalyze CpG methylation at PRC-regulated regions remains unclear. Here we report a cryo-EM structure of the DNMT3A long isoform (DNMT3A1) N-terminal region in complex with a nucleosome carrying PRC1-mediated histone H2A lysine 119 monoubiquitination (H2AK119Ub). We identify regions within the DNMT3A1 N-terminus that bind H2AK119Ub and the nucleosome acidic patch. This bidentate interaction is required for effective DNMT3A1 engagement with H2AK119Ub-modified chromatin in cells. Furthermore, aberrant redistribution of DNMT3A1 to Polycomb target genes inhibits their transcriptional activation during cell differentiation and recapitulates the cancer-associated DNA hypermethylation signature. This effect is rescued by disruption of the DNMT3A1-acidic patch interaction. Together, our analyses reveal a binding interface critical for countering promoter CGI DNA hypermethylation, a major molecular hallmark of cancer.

SMARCAL1 is a dual regulator of innate immune signaling and PD-L1 expression that promotes tumor immune evasion.

Genomic instability can trigger cancer-intrinsic innate immune responses that promote tumor rejection. However, cancer cells often evade these responses by overexpressing immune checkpoint regulators, such as PD-L1. Here, we identify the SNF2-family DNA translocase SMARCAL1 as a factor that favors tumor immune evasion by a dual mechanism involving both the suppression of innate immune signaling and the induction of PD-L1-mediated immune checkpoint responses. Mechanistically, SMARCAL1 limits endogenous DNA damage, thereby suppressing cGAS-STING-dependent signaling during cancer cell growth. Simultaneously, it cooperates with the AP-1 family member JUN to maintain chromatin accessibility at a PD-L1 transcriptional regulatory element, thereby promoting PD-L1 expression in cancer cells. SMARCAL1 loss hinders the ability of tumor cells to induce PD-L1 in response to genomic instability, enhances anti-tumor immune responses and sensitizes tumors to immune checkpoint blockade in a mouse melanoma model. Collectively, these studies uncover SMARCAL1 as a promising target for cancer immunotherapy.

Structural basis of histone H2A lysine 119 deubiquitination by Polycomb repressive deubiquitinase BAP1/ASXL1.

Histone H2A lysine 119 (H2AK119Ub) is monoubiquitinated by Polycomb repressive complex 1 and deubiquitinated by Polycomb repressive deubiquitinase complex (PR-DUB). PR-DUB cleaves H2AK119Ub to restrict focal H2AK119Ub at Polycomb target sites and to protect active genes from aberrant silencing. The PR-DUB subunits (BAP1 and ASXL1) are among the most frequently mutated epigenetic factors in human cancers. How PR-DUB establishes specificity for H2AK119Ub over other nucleosomal ubiquitination sites and how disease-associated mutations of the enzyme affect activity are unclear. Here, we determine a cryo-EM structure of human BAP1 and the ASXL1 DEUBAD in complex with a H2AK119Ub nucleosome. Our structural, biochemical, and cellular data reveal the molecular interactions of BAP1 and ASXL1 with histones and DNA that are critical for restructuring the nucleosome and thus establishing specificity for H2AK119Ub. These results further provide a molecular explanation for how >50 mutations in BAP1 and ASXL1 found in cancer can dysregulate H2AK119Ub deubiquitination, providing insight into understanding cancer etiology.

Multivalent binding of the tardigrade Dsup protein to chromatin promotes yeast survival and longevity upon exposure to oxidative damage.

Tardigrades are remarkable in their ability to survive extreme environments. The damage suppressor (Dsup) protein is thought responsible for their extreme resistance to reactive oxygen species (ROS) generated by irradiation. Here we show that expression of Ramazzottius varieornatus Dsup in Saccharomyces cerevisiae reduces oxidative DNA damage and extends the lifespan of budding yeast exposed to chronic oxidative genotoxicity. This protection from ROS requires either the Dsup HMGN-like domain or sequences C-terminal to same. Dsup associates with no apparent bias across the yeast genome, using multiple modes of nucleosome binding; the HMGN-like region interacts with both the H2A/H2B acidic patch and H3/H4 histone tails, while the C-terminal region binds DNA. These findings give precedent for engineering an organism by physically shielding its genome to promote survival and longevity in the face of oxidative damage.

Structural basis of histone H2A lysine 119 deubiquitination by Polycomb Repressive Deubiquitinase BAP1/ASXL1.

The maintenance of gene expression patterns during metazoan development is achieved by the actions of Polycomb group (PcG) complexes. An essential modification marking silenced genes is monoubiquitination of histone H2A lysine 119 (H2AK119Ub) deposited by the E3 ubiquitin ligase activity of the non-canonical Polycomb Repressive Complex 1. The Polycomb Repressive Deubiquitinase (PR-DUB) complex cleaves monoubiquitin from histone H2A lysine 119 (H2AK119Ub) to restrict focal H2AK119Ub at Polycomb target sites and to protect active genes from aberrant silencing. BAP1 and ASXL1, subunits that form active PR-DUB, are among the most frequently mutated epigenetic factors in human cancers, underscoring their biological importance. How PR-DUB achieves specificity for H2AK119Ub to regulate Polycomb silencing is unknown, and the mechanisms of most of the mutations in BAP1 and ASXL1 found in cancer have not been established. Here we determine a cryo-EM structure of human BAP1 bound to the ASXL1 DEUBAD domain in complex with a H2AK119Ub nucleosome. Our structural, biochemical, and cellular data reveal the molecular interactions of BAP1 and ASXL1 with histones and DNA that are critical for remodeling the nucleosome and thus establishing specificity for H2AK119Ub. These results further provide a molecular explanation for how >50 mutations in BAP1 and ASXL1 found in cancer can dysregulate H2AK119Ub deubiquitination, providing new insight into understanding cancer etiology. One Sentence Summary: We reveal the molecular mechanism of nucleosomal H2AK119Ub deubiquitination by human BAP1/ASXL1.

Discovery of eQTL Alleles Associated with Autism Spectrum Disorder: A Case-Control Study.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by challenges in social communication as well as repetitive or restrictive behaviors. Many genetic associations with ASD have been identified, but most associations occur in a fraction of the ASD population. Here, we searched for eQTL-associated DNA variants with significantly different allele distributions between ASD-affected and control. Thirty significant DNA variants associated with 174 tissue-specific eQTLs from ASD individuals in the SPARK project were identified. Several significant variants fell within brain-specific regulatory regions or had been associated with a significant change in gene expression in the brain. These eQTLs are a new class of biomarkers that could control the myriad of brain and non-brain phenotypic traits seen in ASD-affected individuals.

Identification of condition-specific biomarker systems in uterine cancer.

Uterine cancer is the fourth most common cancer among women, projected to affect 66,000 US women in 2021. Uterine cancer often arises in the inner lining of the uterus, known as the endometrium, but can present as several different types of cancer, including endometrioid cancer, serous adenocarcinoma, and uterine carcinosarcoma. Previous studies have analyzed the genetic changes between normal and cancerous uterine tissue to identify specific genes of interest, including TP53 and PTEN. Here we used Gaussian Mixture Models to build condition-specific gene coexpression networks for endometrial cancer, uterine carcinosarcoma, and normal uterine tissue. We then incorporated uterine regulatory edges and investigated potential coregulation relationships. These networks were further validated using differential expression analysis, functional enrichment, and a statistical analysis comparing the expression of transcription factors and their target genes across cancerous and normal uterine samples. These networks allow for a more comprehensive look into the biological networks and pathways affected in uterine cancer compared with previous singular gene analyses. We hope this study can be incorporated into existing knowledge surrounding the genetics of uterine cancer and soon become clinical biomarkers as a tool for better prognosis and treatment.

Exploration into biomarker potential of region-specific brain gene co-expression networks.

The human brain is a complex organ that consists of several regions each with a unique gene expression pattern. Our intent in this study was to construct a gene co-expression network (GCN) for the normal brain using RNA expression profiles from the Genotype-Tissue Expression (GTEx) project. The brain GCN contains gene correlation relationships that are broadly present in the brain or specific to thirteen brain regions, which we later combined into six overarching brain mini-GCNs based on the brain's structure. Using the expression profiles of brain region-specific GCN edges, we determined how well the brain region samples could be discriminated from each other, visually with t-SNE plots or quantitatively with the Gene Oracle deep learning classifier. Next, we tested these gene sets on their relevance to human tumors of brain and non-brain origin. Interestingly, we found that genes in the six brain mini-GCNs showed markedly higher mutation rates in tumors relative to matched sets of random genes. Further, we found that cortex genes subdivided Head and Neck Squamous Cell Carcinoma (HNSC) tumors and Pheochromocytoma and Paraganglioma (PCPG) tumors into distinct groups. The brain GCN and mini-GCNs are useful resources for the classification of brain regions and identification of biomarker genes for brain related phenotypes.

NetExtractor: Extracting a Cerebellar Tissue Gene Regulatory Network Using Differentially Expressed High Mutual Information Binary RNA Profiles.

Bigenic expression relationships are conventionally defined based on metrics such as Pearson or Spearman correlation that cannot typically detect latent, non-linear dependencies or require the relationship to be monotonic. Further, the combination of intrinsic and extrinsic noise as well as embedded relationships between sample sub-populations reduces the probability of extracting biologically relevant edges during the construction of gene co-expression networks (GCNs). In this report, we address these problems via our NetExtractor algorithm. NetExtractor examines all pairwise gene expression profiles first with Gaussian mixture models (GMMs) to identify sample sub-populations followed by mutual information (MI) analysis that is capable of detecting non-linear differential bigenic expression relationships. We applied NetExtractor to brain tissue RNA profiles from the Genotype-Tissue Expression (GTEx) project to obtain a brain tissue specific gene expression relationship network centered on cerebellar and cerebellar hemisphere enriched edges. We leveraged the PsychENCODE pre-frontal cortex (PFC) gene regulatory network (GRN) to construct a cerebellar cortex (cerebellar) GRN associated with transcriptionally active regions in cerebellar tissue. Thus, we demonstrate the utility of our NetExtractor approach to detect biologically relevant and novel non-linear binary gene relationships.

Autism risk genes are evolutionarily ancient and maintain a unique feature landscape that echoes their function.

Previous research on autism risk (ASD), developmental regulatory (DevReg), and central nervous system (CNS) genes suggests they tend to be large in size, enriched in nested repeats, and mutation intolerant. The relevance of these genomic features is intriguing yet poorly understood. In this study, we investigated the feature landscape of these gene groups to discover structural themes useful in interpreting their function, developmental patterns, and evolutionary history. ASD, DevReg, CNS, housekeeping, and whole genome control (WGC) groups were compiled using various resources. Multiple gene features of interest were extracted from NCBI/UCSC Bioinformatics. Residual variation intolerance scores, Exome Aggregation Consortium pLI scores, and copy number variation data from Decipher were used to estimate variation intolerance. Gene age and protein-protein interactions (PPI) were estimated using Ensembl and EBI Intact databases, respectively. Compared to WGC: ASD, DevReg, and CNS genes are longer, produce larger proteins, maintain greater numbers/density of conserved noncoding elements and transposable elements, produce more transcript variants, and are comparatively variation intolerant. After controlling for gene size, mutation tolerance, and clinical association, ASD genes still retain many of these same features. In addition, we also found that ASD genes that are extremely mutation intolerant have larger PPI networks. These data support many of the recent findings within the field of autism genetics but also expand our understanding of the evolution of these broad gene groups, their potential regulatory complexity, and the extent to which they interact with the cellular network. Autism Res 2019, 12: 860-869. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism risk genes are more ancient compared to other genes in the genome. As such, they exhibit physical features related to their age, including long gene and protein size and regulatory sequences that help to control gene expression. They share many of these same features with other genes that are expressed in the brain and/or are associated with prenatal development.