RNF4 prevents genomic instability caused by chronic DNA under-replication.

Eukaryotic genome stability is maintained by a complex and diverse set of molecular processes. One class of enzymes that promotes proper DNA repair, replication and cell cycle progression comprises small ubiquitin-like modifier (SUMO)-targeted E3 ligases, or STUbLs. Previously, we reported a role for the budding yeast STUbL synthetically lethal with sgs1 (Slx) 5/8 in preventing G2/M-phase arrest in a minichromosome maintenance protein 10 (Mcm10)-deficient model of replication stress. Here, we extend these studies to human cells, examining the requirement for the human STUbL RING finger protein 4 (RNF4) in MCM10 mutant cancer cells. We find that MCM10 and RNF4 independently promote origin firing but regulate DNA synthesis epistatically and, unlike in yeast, the negative genetic interaction between RNF4 and MCM10 causes cells to accumulate in G1-phase. When MCM10 is deficient, RNF4 prevents excessive DNA under-replication at hard-to-replicate regions that results in large DNA copy number alterations and severely reduced viability. Overall, our findings highlight that STUbLs participate in species-specific mechanisms to maintain genome stability, and that human RNF4 is required for origin activation in the presence of chronic replication stress.

Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens.

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods-autoencoders, robust, and classical principal component analyses (PCA)-for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel "onion" normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.

CD69 marks a subpopulation of acute myeloid leukemia with enhanced colony forming capacity and a unique signaling activation state.

In acute myeloid leukemia (AML), leukemia stem cells (LSCs) have self-renewal potential and are responsible for relapse. We previously showed that, in Mll-AF9/NRASG12V murine AML, CD69 expression marks an LSC-enriched subpopulation with enhanced in vivo self-renewal capacity. Here, we used CyTOF to define activated signaling pathways in LSC subpopulations in Mll-AF9/NRASG12V AML. Furthermore, we compared the signaling activation states of CD69High and CD36High subsets of primary human AML. The human CD69High subset expresses low levels of Ki67 and high levels of NFκB and pMAPKAPKII. Additionally, the human CD69High AML subset also has enhanced colony-forming capacity. We applied Bayesian network modeling to compare the global signaling network within the human AML subsets. We find that distinct signaling states, distinguished by NFκB and pMAPKAPKII levels, correlate with divergent functional subsets, defined by CD69 and CD36 expression, in human AML. Targeting NFκB with proteasome inhibition diminished colony formation.

Immunophenotypically-defined murine AML stem cells harbor self-renewing and non-self-renewing subsets that display unique signaling characteristics.CD69, an NFκB target gene, marks a subset of human AML with increased colony forming capacity and reduced proliferation.NFκB activation correlates with the global signaling pathway activation state in human AML.

Fanconi anemia-associated chromosomal radial formation is dependent on POLθ-mediated alternative end joining.

Activation of the Fanconi anemia (FA) pathway after treatment with mitomycin C (MMC) is essential for preventing chromosome translocations termed "radials." When replication forks stall at MMC-induced interstrand crosslinks (ICLs), the FA pathway is activated to orchestrate ICL unhooking and repair of the DNA break intermediates. However, in FA-deficient cells, how ICL-associated breaks are resolved in a manner that leads to radials is unclear. Here, we demonstrate that MMC-induced radials are dependent on DNA polymerase theta (POLθ)-mediated alternative end joining (A-EJ). Specifically, we show that radials observed in FANCD2-/- cells are dependent on POLθ and DNA ligase III and occur independently of classical non-homologous end joining. Furthermore, treatment of FANCD2-/- cells with POLθ inhibitors abolishes radials and leads to the accumulation of breaks co-localizing with common fragile sites. Uniformly, these observations implicate A-EJ in radial formation and provide mechanistic insights into the treatment of FA pathway-deficient cancers with POLθ inhibitors.

Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens.

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods - autoencoders, robust, and classical principal component analyses (PCA) - for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel "onion" normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.

Genetic architecture of protein and oil content in soybean seed and meal.

Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to map marker-trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker-assisted selection.

Context-dependent regulation of ferroptosis sensitivity.

Ferroptosis is an important mediator of pathophysiological cell death and an emerging target for cancer therapy. Whether ferroptosis sensitivity is governed by a single regulatory mechanism is unclear. Here, based on the integration of 24 published chemical genetic screens combined with targeted follow-up experimentation, we find that the genetic regulation of ferroptosis sensitivity is highly variable and context-dependent. For example, the lipid metabolic gene acyl-coenzyme A (CoA) synthetase long chain family member 4 (ACSL4) appears far more essential for ferroptosis triggered by direct inhibition of the lipid hydroperoxidase glutathione peroxidase 4 (GPX4) than by cystine deprivation. Despite this, distinct pro-ferroptotic stimuli converge upon a common lethal effector mechanism: accumulation of lipid peroxides at the plasma membrane. These results indicate that distinct genetic mechanisms regulate ferroptosis sensitivity, with implications for the initiation and analysis of this process in vivo.

Systematic analysis of bypass suppression of essential genes.

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

Systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism.

The de novo synthesis of fatty acids has emerged as a therapeutic target for various diseases, including cancer. Because cancer cells are intrinsically buffered to combat metabolic stress, it is important to understand how cells may adapt to the loss of de novo fatty acid biosynthesis. Here, we use pooled genome-wide CRISPR screens to systematically map genetic interactions (GIs) in human HAP1 cells carrying a loss-of-function mutation in fatty acid synthase (FASN), whose product catalyses the formation of long-chain fatty acids. FASN-mutant cells show a strong dependence on lipid uptake that is reflected in negative GIs with genes involved in the LDL receptor pathway, vesicle trafficking and protein glycosylation. Further support for these functional relationships is derived from additional GI screens in query cell lines deficient in other genes involved in lipid metabolism, including LDLR, SREBF1, SREBF2 and ACACA. Our GI profiles also identify a potential role for the previously uncharacterized gene C12orf49 (which we call LUR1) in regulation of exogenous lipid uptake through modulation of SREBF2 signalling in response to lipid starvation. Overall, our data highlight the genetic determinants underlying the cellular adaptation associated with loss of de novo fatty acid synthesis and demonstrate the power of systematic GI mapping for uncovering metabolic buffering mechanisms in human cells.

Dbf4-Dependent Kinase (DDK)-Mediated Proteolysis of CENP-A Prevents Mislocalization of CENP-A in Saccharomyces cerevisiae.

The evolutionarily conserved centromeric histone H3 variant (Cse4 in budding yeast, CENP-A in humans) is essential for faithful chromosome segregation. Mislocalization of CENP-A to non-centromeric chromatin contributes to chromosomal instability (CIN) in yeast, fly, and human cells and CENP-A is highly expressed and mislocalized in cancers. Defining mechanisms that prevent mislocalization of CENP-A is an area of active investigation. Ubiquitin-mediated proteolysis of overexpressed Cse4 (GALCSE4) by E3 ubiquitin ligases such as Psh1 prevents mislocalization of Cse4, and psh1Δ strains display synthetic dosage lethality (SDL) with GALCSE4 We previously performed a genome-wide screen and identified five alleles of CDC7 and DBF4 that encode the Dbf4-dependent kinase (DDK) complex, which regulates DNA replication initiation, among the top twelve hits that displayed SDL with GALCSE4 We determined that cdc7-7 strains exhibit defects in ubiquitin-mediated proteolysis of Cse4 and show mislocalization of Cse4 Mutation of MCM5 (mcm5-bob1) bypasses the requirement of Cdc7 for replication initiation and rescues replication defects in a cdc7-7 strain. We determined that mcm5-bob1 does not rescue the SDL and defects in proteolysis of GALCSE4 in a cdc7-7 strain, suggesting a DNA replication-independent role for Cdc7 in Cse4 proteolysis. The SDL phenotype, defects in ubiquitin-mediated proteolysis, and the mislocalization pattern of Cse4 in a cdc7-7psh1Δ strain were similar to that of cdc7-7 and psh1Δ strains, suggesting that Cdc7 regulates Cse4 in a pathway that overlaps with Psh1 Our results define a DNA replication initiation-independent role of DDK as a regulator of Psh1-mediated proteolysis of Cse4 to prevent mislocalization of Cse4.

EXO1 resection at G-quadruplex structures facilitates resolution and replication.

G-quadruplexes represent unique roadblocks to DNA replication, which tends to stall at these secondary structures. Although G-quadruplexes can be found throughout the genome, telomeres, due to their G-richness, are particularly predisposed to forming these structures and thus represent difficult-to-replicate regions. Here, we demonstrate that exonuclease 1 (EXO1) plays a key role in the resolution of, and replication through, telomeric G-quadruplexes. When replication forks encounter G-quadruplexes, EXO1 resects the nascent DNA proximal to these structures to facilitate fork progression and faithful replication. In the absence of EXO1, forks accumulate at stabilized G-quadruplexes and ultimately collapse. These collapsed forks are preferentially repaired via error-prone end joining as depletion of EXO1 diverts repair away from error-free homology-dependent repair. Such aberrant repair leads to increased genomic instability, which is exacerbated at chromosome termini in the form of dysfunction and telomere loss.

Single-Cell Gene Expression Analyses Reveal Distinct Self-Renewing and Proliferating Subsets in the Leukemia Stem Cell Compartment in Acute Myeloid Leukemia.

Standard chemotherapy for acute myeloid leukemia (AML) targets proliferative cells and efficiently induces complete remission; however, many patients relapse and die of their disease. Relapse is caused by leukemia stem cells (LSC), the cells with self-renewal capacity. Self-renewal and proliferation are separate functions in normal hematopoietic stem cells (HSC) in steady-state conditions. If these functions are also separate functions in LSCs, then antiproliferative therapies may fail to target self-renewal, allowing for relapse. We investigated whether proliferation and self-renewal are separate functions in LSCs as they often are in HSCs. Distinct transcriptional profiles within LSCs of Mll-AF9/NRASG12V murine AML were identified using single-cell RNA sequencing. Single-cell qPCR revealed that these genes were also differentially expressed in primary human LSCs and normal human HSPCs. A smaller subset of these genes was upregulated in LSCs relative to HSPCs; this subset of genes constitutes "LSC-specific" genes in human AML. To assess the differences between these profiles, we identified cell surface markers, CD69 and CD36, whose genes were differentially expressed between these profiles. In vivo mouse reconstitution assays resealed that only CD69High LSCs were capable of self-renewal and were poorly proliferative. In contrast, CD36High LSCs were unable to transplant leukemia but were highly proliferative. These data demonstrate that the transcriptional foundations of self-renewal and proliferation are distinct in LSCs as they often are in normal stem cells and suggest that therapeutic strategies that target self-renewal, in addition to proliferation, are critical to prevent relapse and improve survival in AML. SIGNIFICANCE: These findings define and functionally validate a self-renewal gene profile of leukemia stem cells at the single-cell level and demonstrate that self-renewal and proliferation are distinct in AML. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/3/458/F1.large.jpg.

Discovering genetic interactions bridging pathways in genome-wide association studies.

Genetic interactions have been reported to underlie phenotypes in a variety of systems, but the extent to which they contribute to complex disease in humans remains unclear. In principle, genome-wide association studies (GWAS) provide a platform for detecting genetic interactions, but existing methods for identifying them from GWAS data tend to focus on testing individual locus pairs, which undermines statistical power. Importantly, a global genetic network mapped for a model eukaryotic organism revealed that genetic interactions often connect genes between compensatory functional modules in a highly coherent manner. Taking advantage of this expected structure, we developed a computational approach called BridGE that identifies pathways connected by genetic interactions from GWAS data. Applying BridGE broadly, we discover significant interactions in Parkinson's disease, schizophrenia, hypertension, prostate cancer, breast cancer, and type 2 diabetes. Our novel approach provides a general framework for mapping complex genetic networks underlying human disease from genome-wide genotype data.

A Genome-Wide Screen Reveals a Role for the HIR Histone Chaperone Complex in Preventing Mislocalization of Budding Yeast CENP-A.

Centromeric localization of the evolutionarily conserved centromere-specific histone H3 variant CENP-A (Cse4 in yeast) is essential for faithful chromosome segregation. Overexpression and mislocalization of CENP-A lead to chromosome segregation defects in yeast, flies, and human cells. Overexpression of CENP-A has been observed in human cancers; however, the molecular mechanisms preventing CENP-A mislocalization are not fully understood. Here, we used a genome-wide synthetic genetic array (SGA) to identify gene deletions that exhibit synthetic dosage lethality (SDL) when Cse4 is overexpressed. Deletion for genes encoding the replication-independent histone chaperone HIR complex (HIR1, HIR2, HIR3, HPC2) and a Cse4-specific E3 ubiquitin ligase, PSH1, showed highest SDL. We defined a role for Hir2 in proteolysis of Cse4 that prevents mislocalization of Cse4 to noncentromeric regions for genome stability. Hir2 interacts with Cse4 in vivo, and hir2∆ strains exhibit defects in Cse4 proteolysis and stabilization of chromatin-bound Cse4 Mislocalization of Cse4 to noncentromeric regions with a preferential enrichment at promoter regions was observed in hir2∆ strains. We determined that Hir2 facilitates the interaction of Cse4 with Psh1, and that defects in Psh1-mediated proteolysis contribute to increased Cse4 stability and mislocalization of Cse4 in the hir2∆ strain. In summary, our genome-wide screen provides insights into pathways that regulate proteolysis of Cse4 and defines a novel role for the HIR complex in preventing mislocalization of Cse4 by facilitating proteolysis of Cse4, thereby promoting genome stability.

Translocon Declogger Ste24 Protects against IAPP Oligomer-Induced Proteotoxicity.

Aggregates of human islet amyloid polypeptide (IAPP) in the pancreas of patients with type 2 diabetes (T2D) are thought to contribute to ß cell dysfunction and death. To understand how IAPP harms cells and how this might be overcome, we created a yeast model of IAPP toxicity. Ste24, an evolutionarily conserved protease that was recently reported to degrade peptides stuck within the translocon between the cytoplasm and the endoplasmic reticulum, was the strongest suppressor of IAPP toxicity. By testing variants of the human homolog, ZMPSTE24, with varying activity levels, the rescue of IAPP toxicity proved to be directly proportional to the declogging efficiency. Clinically relevant ZMPSTE24 variants identified in the largest database of exomes sequences derived from T2D patients were characterized using the yeast model, revealing 14 partial loss-of-function variants, which were enriched among diabetes patients over 2-fold. Thus, clogging of the translocon by IAPP oligomers may contribute to ß cell failure.

Features of the Chaperone Cellular Network Revealed through Systematic Interaction Mapping.

A comprehensive view of molecular chaperone function in the cell was obtained through a systematic global integrative network approach based on physical (protein-protein) and genetic (gene-gene or epistatic) interaction mapping. This allowed us to decipher interactions involving all core chaperones (67) and cochaperones (15) of Saccharomyces cerevisiae. Our analysis revealed the presence of a large chaperone functional supercomplex, which we named the naturally joined (NAJ) chaperone complex, encompassing Hsp40, Hsp70, Hsp90, AAA+, CCT, and small Hsps. We further found that many chaperones interact with proteins that form foci or condensates under stress conditions. Using an in vitro reconstitution approach, we demonstrate condensate formation for the highly conserved AAA+ ATPases Rvb1 and Rvb2, which are part of the R2TP complex that interacts with Hsp90. This expanded view of the chaperone network in the cell clearly demonstrates the distinction between chaperones having broad versus narrow substrate specificities in protein homeostasis.

Pathway-based discovery of genetic interactions in breast cancer.

Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions.