Genetic Background Research Articles

Genomic diversity of phages infecting the globally widespread genus Sulfurimonas

The widespread bacterial genus Sulfurimonas is metabolically versatile and occupies a key ecological niche in different habitats, but its interaction with bacteriophages remains unexplored. Here we systematically investigated the genetic diversity, taxonomy and interaction patterns of Sulfurimonas-associated phages based on sequenced microbial genomes and metagenomes. High-confidence phage contigs related to Sulfurimonas were retrieved from various ecosystems, clustered into 61 viral operational taxonomic units across three viral realms, including Duplodnaviria, Monodnaviria and Varidnaviria. Head-tail phages of Caudoviricetes were assigned to 19 genus-level viral clusters, the majority of which were distantly related to known viruses. Notably, diverse double jelly-roll viruses and inoviruses were also linked to Sulfurimonas, representing two commonly overlooked phage groups. Historical and current phage infections were revealed, implying viral impact on the evolution of host adaptive immunity. Additionally, phages carrying auxiliary metabolic genes might benefit hosts by compensating or augmenting sulfur metabolism. This study highlights the diversity and novelty of Sulfurimonas-associated phages with divergent tailless lineages, providing basis for further investigation of phage-host interactions within this genus.

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BackgroundGenome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders. MethodsThrough integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database. ResultsPWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10−7) and response to external stimulus (adjusted P = 4.13 × 10−7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10−2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB. ConclusionsOur findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

An NLR family member X1 mutation (p.Arg707Cys) suppresses hepatitis B virus infection in hepatocytes and favors the interaction of retinoic acid-inducible gene 1 with mitochondrial antiviral signaling protein.

NLR family member X1 (NLRX1) is an important member of the NOD-like receptor (NLR) family and plays unique roles in immune system regulation. Patients with hepatitis B virus (HBV) infection are more likely to have the NLRX1 mutation p.Arg707Cys than healthy individuals. It has been reported that NLRX1 increases the infection rate of HBV in HepG2 cells expressing sodium taurocholate cotransporting polypeptide (NTCP). However, the role of NLRX1 mutation (p.Arg707Cys) in hepatitis remains unclear. We constructed Huh7 cells that stably overexpressed NTCP, using LV003 lentivirus. First, wild-type (WT) and mutant (MT) NLRX1 overexpression plasmids were constructed. The MT plasmid contained a point mutation at position 707 of the WT overexpression plasmid. Then, Huh7-NTCP cells were transfected with the WT or MT NLRX1 overexpression plasmid, and subsequent NLRX1 expression was analyzed using real-time quantitative polymerase chain reaction (RT-qPCR) and western blot. HBV RNA levels were determined using RT-qPCR. HBsAg and HBcAg levels were confirmed immunohistochemically. Interferon alpha (IFN-α), interleukin 6 (IL-6), and type I interferon beta (IFN-β) levels were determined using enzyme-linked immunosorbent assay kits. p-p65, p-interferon regulatory factor (IRF) 3, and p-IRF7 expression levels were examined using western blot. The interaction of NLRX1 and retinoic acid-inducible gene (RIG)-1/mitochondrial antiviral signaling (MAVS) protein was confirmed by coimmunoprecipitation. The interaction of NLRX1 with IFN-α, IL-6, or IFN-β was analyzed by dual luciferase reporter gene assay. The levels of HBV RNA, HBsAg, and HBcAg in infected cells transfected with the WT NLRX1 or MT NLRX1 expression plasmid were higher than those in the untransfected control group; and these levels were lower in the cells transfected with MT NLRX1 than in those transfected with WT NLRX1. The levels of IFN-α, IFN-β, IL-6, p-p65, p-IRF3, and p-IRF7 were lower in cells transfected with WT NLRX1 or MT NLRX1 than in control cells. The levels of IFN-β, p-p65, p-IRF3, and p-IRF7 were higher in cells transfected with MT NLRX1 than in those transfected with WT NLRX1. Moreover, NLRX1 competitively inhibited RIG1 binding to MAVS, but the mutation in MT NLRX1 reduced this inhibitory effect. In addition, NLRX1 decreased the promoter activity of IFN-α, IFN-β, and IL-6. Our findings revealed that NLRX1 is a regulatory factor that inhibits the anti-HBV ability of hepatocytes and that the mutation p.Arg707Cys in NLRX1 suppresses HBV infection and activates the IFN/nuclear factor κB pathway.

Generating iAstrocytes From Human Induced Pluripotent Stem Cells by Combining Low-Density Passaging of Neural Progenitor Cells and Transcription Factor NFIA Transdifferentiation.

Astrocytes are key regulators of central nervous system (CNS) homeostasis, and their dysfunction is implicated in neurological and neurodegenerative disorders. Here, we describe a two-step protocol to generate astrocytes from human induced pluripotent stem cells (hiPSCs) using a bankable neural progenitor cell (NPC) intermediate, followed by low-density passaging and overexpression of the gliogenic transcription factor NFIA. A bankable NPC intermediate allows for facile differentiation into both purified neuronal and astrocyte cell types in parallel from the same genetic background, depending on the experimental needs. This article presents a protocol to generate NPCs from hiPSCs, which are then differentiated into hiPSC-derived astrocytes, termed iAstrocytes. The resulting iAstrocytes express key markers of astrocyte identity at transcript and protein levels by bulk RNA-Seq and immunocytochemistry, respectively. Additionally, they respond to the inflammatory stimuli poly(I:C) and generate waves of calcium activity in response to either physical activity or the addition of ATP. Our approach offers a simple and robust method to generate and characterize human astrocytes, which can be used to model human disease affecting this cell type. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Differentiation of hiPSCs to NPCs Basic Protocol 2: Differentiation of NPCs into iAstrocytes Support Protocol 1: Molecular validation of iAstrocytes Support Protocol 2: Calcium imaging-based validation of iAstrocyte function Support Protocol 3: Differentiation of NPCs into neurons.

Reevaluating hybrid neurofibroma/schwannoma: Predominance of schwannoma features despite CD34 positivity and initial neurofibroma diagnosis.

Schwannomas consist of both high-cellularity regions (Antoni A area) and hypocellular regions (Antoni B area) in histopathological findings. Neurofibromas characteristically consist of CD34 positive spindle cells with thin, wavy, nuclei and wavy collagen bands. Previous reports have described segments of schwannomas with neurofibroma features as hybrid tumors, although hybrid tumors were diagnosed based on partial CD34 positivity in many previous reports. On the other hand, the Antoni B area of some schwannomas was reported to be positive for CD34. Therefore, the definition of a hybrid tumor has not been clear. The objective of this study was to determine whether only CD34 positive findings in schwannomas could be used to define a hybrid tumor. In the analysis of our patient with schwannomatosis caused by a novel LZTR1 germline mutation, part of the tumor had CD34 positive hypocellular regions. These regions contained no thin, wavy, nuclei, indicating an Antoni B area. Laser microdissection was used to investigate the genetic background and differences in molecular mechanisms between CD34 positive and CD34 negative regions. All mutations identified in CD34 positive regions were also found in CD34 negative regions. Our data could not clear the genetic background of Antoni B which was CD34 positive area. We then reviewed the pathologies of 66 sporadic schwannomas. Histopathological examinations of all schwannomas revealed the absence of thin, wavy, nuclei and wavy collagen bands, and no hybrid tumors were found in any of the cases. Ten of 66 patients were randomly selected for CD34 immunostaining and positivity was found in all cases. Our data suggest that it is difficult to distinguish schwannomas by staining for CD34 alone, as Antoni B areas can also be positive for CD34. Therefore, CD34 staining alone should not be used to diagnose hybrid tumors in patients with schwannomas.

Impaired insulin signaling and diet-induced type 3 diabetes pathophysiology increase amyloid β expression in the Drosophila model of Alzheimer's disease

Compelling evidence has strongly linked unregulated sugar levels to developing Alzheimer's disease, suggesting Alzheimer's to be ‘diabetes of the brain or ‘type 3 diabetes. Insulin resistance contributes to the pathogenesis of Alzheimer's disease due to uncontrolled and unchecked blood glucose, though the interrelatedness between Alzheimer's disease and type 2 diabetes is debatable. Here we describe the consequences of inducing type 3 diabetes by feeding Drosophila on a high sucrose diet, which effectively mimics the pathophysiology of diabetes. High sucrose diet increases glycogen and lipid accumulation. Inducing type 3 diabetes worsened neurodegeneration and accelerated disease progression in Drosophila expressing the Alzheimer's Familial Arctic mutation. High sucrose milieu also negatively affected locomotor ability and reduced the lifespan in the Alzheimer's disease model of Drosophila. The results showed that creating diabetic conditions by using insulin receptor (InR) knockdown in the eyes of Drosophila led to a degenerative phenotype, indicating a genetic interaction between the insulin signaling pathway and Alzheimer's disease. The expression of PERK reflects disruption in the endoplasmic reticulum homeostasis due to amyloid-β (Aβ) under a high sucrose diet. These observations demonstrated association between type 3 diabetes and Alzheimer's disease, and that a high sucrose environment has a degenerating effect on Alzheimer's disease condition.

Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model-based in silico evidence combined with gene expression assays.

Salmonella enteritidis (SE), a previously widespread infectious disease, is still cited as a major factor in economic losses in commercial chicken production. The host's genetic immune system determines the pathogenicity of a particular bacterium. To shed light on this topic, it was necessary to understand the key candidate genes essential for regulating susceptibility and resistance to the target disease. The field of poultry farming in particular has benefited greatly from the connection between quantitative and molecular genetics. This study aims to identify the most important immune-related genes and their signalling pathways (gene ontology, co-expression and interactions) and to analyse their accumulation in host-resistant SE diseases by combining gene expression assays with model-based in silico evidence. A two-step experimental design is followed. To start, we used free computational tools and online bioinformatics resources, including predicting gene function using a multiple association network integration algorithm (geneMania), the Kyoto Encyclopedia of Genes and Genomes, the Annotation, Visualization and Integrated Discovery (DAVID) database and the stimulator of interferon genes. Natural resistance-associated macrophage protein 1 (NRAMP1), Toll-like receptor 4 (TLR4), interferon-γ (IFNγ), immunoglobulin Y (IgY) and interleukin 8 (IL8) were among the five genes whose expression levels in liver, spleen, and cecum were evaluated at 1107 SE after 48h of inoculation. This molecular study was developed in the second phase of research to validate the in silico observations. Next, we use five promising biomarkers for relative real-time polymerase chain reaction (PCR) quantification: TLR4, IL8, NRAMP1, IFNγ and IgY genes in two case and control assays. The 2-∆∆Ct Livak and Schmittgen method was used to compare the expression of genes in treated and untreated samples. This method normalizes the expression of the target gene to that of actin, an internal control and estimates the change in expression relative to the untreated control. Internal control was provided by the Beta actin gene. Next, statistically, the postdoc test was used for the evaluation of treatments using SAS version 9.4, and p values of 0.05 and 0.01 were chosen for significant level. Interestingly, the results of our study suggest the involvement of various factors in the host immune response to Salmonella. These include inducible nitric oxide synthase, NRAMP1, immunoglobulin light chain (IgL), transforming growth factor B family (TGFb2, TGFb3 and TGFb4), interleukin 2 (IL2), apoptosis inhibitor protein 1 (IAP1), TLR4, myeloid differentiation protein 2 (MD2), IFNγ, caspase 1 (CASP1), lipopolysaccharide-induced tumour necrosis factor (LITAF), cluster of differentiation 28 (CD28) and prosaposin (PSAP). The summary of gene ontology and related genes found for SE resistance was surprisingly comprehensive and covered the following topics: positive regulation of endopeptidase activity, interleukin-8 production, chemokine production, interferon-gamma production, interleukin-6 production, positive regulation of mononuclear cell proliferation and response to interferon-gamma. The role of these promising biomarkers in our networks against SE susceptibility is essentially confirmed by these results. After 48h, the spleen showed significant expression of the tissue-specific gene expression patterns for NRAMP1 and IL8 in the cecum, spleen and liver. Based on this information, this report searches for resistance and susceptibility lineages in most genomic regions for SE. In conclusion, the development of an appropriate selection program to improve resistance to salmonellosis can be facilitated by a comprehensive understanding of the immune responses of the chicken immune system after SE exposure.

Combined effects of genetic background and diet on mouse metabolism and gene expression

Combined effects of genetic background and diet on mouse metabolism and gene expression

Identification of complex Plasmodium falciparum genetic backgrounds circulating in Africa: a multicountry genomic epidemiology analysis

The population structure of the malaria parasite Plasmodium falciparum can reveal underlying adaptive evolutionary processes. Selective pressures to maintain complex genetic backgrounds can encourage inbreeding, producing distinct parasite clusters identifiable by population structure analyses. We analysed population structure in 3783 Pfalciparum genomes from 21countries across Africa, provided by the MalariaGEN Pf7 dataset. We used Principal Coordinate Analysis to cluster parasites, identity by descent (IBD) methods to identify genomic regions shared by cluster members, and linkage analyses to establish their co-inheritance patterns. Structural variants were reconstructed by de novo assembly and verified by long-read sequencing. We identified a strongly differentiated cluster of parasites, named AF1, comprising 47 (1·2%) of 3783samples analysed, distributed over 13countries across Africa, at locations over 7000km apart. Members of this cluster share a complex genetic background, consisting of up to 23loci harbouring many highly differentiated variants, rarely observed outside the cluster. IBD analyses revealed common ancestry at these loci, irrespective of sampling location. Outside the shared loci, however, AF1 members appear to outbreed with sympatric parasites. The AF1 differentiated variants comprise structural variations, including a gene conversion involving the dblmsp and dblmsp2 genes, and numerous single nucleotide polymorphisms. Several of the genes harbouring these mutations are functionally related, often involved in interactions with red blood cells including invasion, egress, and erythrocyte antigen export. We propose that AF1 parasites have adapted to some unidentified evolutionary niche, probably involving interactions with host erythrocytes. This adaptation involves a complex compendium of interacting variants that are rarely observed in Africa, which remains mostly intact despite recombination events. The term cryptotype was used to describe a common background interspersed with genomic regions of local origin. Bill & Melinda Gates Foundation.

Genetic parameters and genome-wide association analyses for lifetime productivity in Chinese Holstein cattle

Lifetime productivity is a trait of great importance to dairy cattle populations, as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics datasets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the restricted maximum likelihood method. Genome-wide association studies and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-sequencing data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE), whereas the genetic correlation with 305-d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization, and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle, and important candidate genes were identified by integrating genomic and transcriptomic datasets.

GPS-Net: Discovering prognostic pathway modules based on network regularized kernel learning.

The search for prognostic biomarkers capable of predicting patient outcomes, by analyzing gene expression in tissue samples and other molecular profiles, remains largely focused on single-gene-based or global-gene-search approaches. Gene-centric approaches, while foundational, fail to capture the higher-order dependencies that reflect the activities of co-regulated processes, pathway alterations, and regulatory networks, all of which are crucial in determining the patient outcomes in complex diseases like cancer. Here, we introduce GPS-Net, a computational framework that fills the gap in efficiently identifying prognostic modules by incorporating the holistic pathway structures and the network of gene interactions. By innovatively incorporating advanced multiple kernel learning techniques and network-based regularization, the proposed method not only enhances the accuracy of biomarker and pathway identification but also significantly reduces computational complexity, as demonstrated by extensive simulation studies. Applying GPS-Net, we identified key pathways that are predictive of patient outcomes in a cancer immunotherapy study. Overall, our approach provides a novel framework that renders genome-wide pathway-level prognostic analysis both feasible and scalable, synergizing both mechanism-driven and data-driven methodologies for precision genomics.

Host Genetics Background Affects Intestinal Cancer Development Associated with High-Fat Diet-Induced Obesity and Type 2 Diabetes.

Obesity and type 2 diabetes (T2D) promote inflammation, increasing the risk of colorectal cancer (CRC). High-fat diet (HFD)-induced obesity is key to these diseases through biological mechanisms. This study examined the impact of genetic background on the multimorbidity of intestinal cancer, T2D, and inflammation due to HFD-induced obesity. A cohort of 357 Collaborative Cross (CC) mice from 15 lines was fed either a control chow diet (CHD) or HFD for 12 weeks. Body weight was tracked biweekly, and blood glucose was assessed at weeks 6 and 12 via intraperitoneal glucose tolerance tests (IPGTT). At the study's endpoint, intestinal polyps were counted, and cytokine profiles were analyzed to evaluate the inflammatory response. HFD significantly increased blood glucose levels and body weight, with males showing higher susceptibility to T2D and obesity. Genetic variation across CC lines influenced glucose metabolism, body weight, and polyp development. Mice on HFD developed more intestinal polyps, with males showing higher counts than females. Cytokine analysis revealed diet-induced variations in pro-inflammatory markers like IL-6, IL-17A, and TNF-α, differing by genetic background and sex. Host genetics plays a crucial role in susceptibility to HFD-induced obesity, T2D, CRC, and inflammation. Genetic differences across CC lines contributed to variability in disease outcomes, providing insight into the genetic underpinnings of multimorbidity. This study supports gene-mapping efforts to develop personalized prevention and treatment strategies for these diseases.

ALDH1A3 Contributes to Radiation-Induced Inhibition of Self-Renewal and Promotes Proliferative Activity of p53-Deficient Glioblastoma Stem Cells at the Onset of Differentiation.

ALDH1A3 is a marker for mesenchymal glioblastomas characterized by a greater degree of aggressiveness compared to other major subtypes. ADH1A3 has been implicated in the regulation of stemness and radioresistance mediated by glioblastoma stem cells. Mechanisms by which ALDH1A3 promotes malignant progression of glioblastoma remain elusive posing a challenge for rationalization of ALDH1A3 targeting in glioblastoma, and it is also unclear how ALDH1A3 regulates glioblastoma cells stemness. Usage of different models with diverse genetic backgrounds and often unknown degree of stemness is one possible reason for discrepant views on the role of ALDH1A3 in glioblastoma stem cells. This study clarifies ALDH1A3 impacts on glioblastoma stem cells by modelling ALDH1A3 expression in an otherwise invariable genetic background with consideration of the impacts of inherent plasticity and proliferative changes associated with transitions between cell states. Our main finding is that ALDH1A3 exerts cell-state dependent impact on proliferation of glioblastoma stem cells. We provide evidence that ALDH1A3 augments radiation-induced inhibition of self-renewal and promotes the proliferation of differentiated GSC progenies. Congruent effects ALDH1A3 and radiation on self-renewal and proliferation provides a framework for promoting glioblastoma growth under radiation treatment.

Influence of Mitochondrial NAD(P) + Transhydrogenase (NNT) on Hypothalamic Inflammation and Metabolic Dysfunction Induced by a High-Fat Diet in Mice.

The mitochondrial protein NAD(P)+ transhydrogenase (NNT) has been implicated in the metabolic derangements observed in obesity. Mice with the C57BL/6J genetic background bear a spontaneous mutation in the Nnt gene and are known to exhibit increased susceptibility to diet-induced metabolic disorders. Most of the studies on NNT in the context of diet-induced obesity have compared C57BL/6J mice with other mouse strains, where differences in genetic background can serve as confounding factors. Moreover, these studies have predominantly employed a high-fat diet (HFD) consisting of approximately 60% of calories from fat, which may not accurately mimic real-world fat-rich diets. In this study, we sought to examine the role of NNT in diet-induced hypothalamic inflammation and metabolic syndrome by using a congenic mice model lacking NNT, along with a HFD providing approximately 45% of calories from fat. Our findings indicate that mice lacking NNT were more protected from HFD-induced weight gain but presented a worse performance on glucose tolerance test, albeit not in insulin tolerance test. Interestingly, the brown adipose tissue of HFD-fed Nnt +/+ mice presented a greater mass and a higher whole-tissue ex-vivo oxygen consumption rate. Also, HFD increased the expression of the inflammatory markers Il1β, Tlr4 and Iba1 in the hypothalamus of Nnt -/- mice. In conclusion, our study highlights the importance of NNT in the context of diet-induced obesity and metabolic syndrome, indicating its contribution to mitigate hypothalamic inflammation and suggesting its role in the brown adipose tissue increased mass.

Minimisation of metabolic networks defines a new functional class of genes

Construction of minimal metabolic networks (MMNs) contributes both to our understanding of the origins of metabolism and to the efficiency of biotechnological processes by preventing the diversion of flux away from product formation. We have designed MMNs using a novel in silico synthetic biology pipeline that removes genes encoding enzymes and transporters from genome-scale metabolic models. The resulting minimal gene-set still ensures both viability and high growth rates. The composition of these MMNs has defined a new functional class of genes termed Network Efficiency Determinants (NEDs). These genes, whilst not essential, are very rarely eliminated in constructing an MMN, suggesting that it is difficult for metabolism to be re-routed to obviate the need for such genes. Moreover, the removal of NED genes from an MMN significantly reduces its global efficiency. Bioinformatic analyses of the NED genes have revealed that not only do these genes have more genetic interactions than the bulk of metabolic genes but their protein products also show more protein-protein interactions. In yeast, NED genes are predominantly single-copy and are highly conserved across evolutionarily distant organisms. These features confirm the importance of the NED genes to the metabolic network, including why they are so rarely excluded during minimisation.

Genome-Wide CRISPR Screen Identifies Genes Involved in Metastasis of Pancreatic Ductal Adenocarcinoma.

Background/Objectives: Early and aggressive metastasis is a major feature of pancreatic ductal adenocarcinoma. Understanding the processes underlying metastasis is crucial for making a difference to disease outcome. Towards these ends, we looked in a comprehensive manner for genes that are metastasis-specific. Methods: A genome-wide CRISPR-Cas9 gene knockout screen with 259,900 single guide RNA constructs was performed on pancreatic cancer cell lines with very high or very low metastatic capacity, respectively. Functional aspects of some of the identified genes were analysed in vitro. The injection of tumour cells with or without a gene knockout into mice was used to confirm the effect on metastasis. Results: The knockout of 590 genes-and, with higher analysis stringency, 67 genes-affected the viability of metastatic cells substantially, while these genes were not vital to non-metastasizing cells. Further evaluations identified different molecular processes related to this observation. One of the genes was MYBL2, encoding for a well-known transcription factor involved in the regulation of cell survival, proliferation, and differentiation in cancer tissues. In our metastasis-focussed study, no novel functional activity was detected for MYBL2, however. Instead, a metastasis-specific transformation of its genetic interaction with FOXM1 was observed. The interaction was synergistic in cells of low metastatic capacity, while there was a strong switch to a buffering mode in metastatic cells. In vivo analyses confirmed the strong effect of MYBL2 on metastasis. Conclusions: The genes found to be critical for the viability of metastatic cells form a basis for further investigations of the processes responsible for triggering and driving metastasis. As shown for MYBL2, unexpected processes of regulating metastasis might also be involved.

Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas

Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

Pleiomorph Sarcome of the Thigh

This article focuses on pleomorphic sarcomas, which are malignant mesenchymal tumors with a complex genetic background underlying their morphological pleomorphism. These are poorly differentiated tumors that can maintain different lines of differentiation, sometimes correlating with clinicopathological or prognostic characteristics. Accurate diagnosis in this group of tumors relies on adequate sampling due to their heterogeneity and evaluation by both microscopy and large immunohistochemistry panels. Molecular analyzes have a limited role in their diagnosis as opposed to translocation-related sarcomas, but they may provide important the anotic and prognostic information in the future

Comparison of Molecularly Identified Resistant and Susceptible Johnsongrass (Sorghum halepense L.) Populations at ALS Gene, in the Absence and Presence of Field Crops

Background/Objectives: Johnsongrass (Sorghum halepense) is an erect tetraploid, perennial, C4 grass weed species categorized among the world’s most noxious weeds due to its high competitive ability against crops and the increased number of field-evolved herbicide-resistant populations. The aim of the present study was to assess the growth rate and performance of resistant (R) johnsongrass genotypes hosting Trp574Leu target-site cross-resistance at ALS gene, inhibiting various herbicides, compared to susceptible (S) conspecific weeds, in the absence and presence of corn or sunflower antagonism. Methods: The aboveground biomass, tiller, and rhizome production ability of one S and one R johnsongrass population with a Trp574-Leu substitution conferring cross-resistance to ALS-inhibiting herbicides were compared under non-competitive conditions. Furthermore, the competitive ability of these two johnsongrass populations against corn or sunflower was determined in a target-neighborhood design. Results: The S and R johnsongrass populations displayed similar growth rates concerning aboveground biomass and tiller number, whereas the R population displayed a slightly greater growth rate for rhizome production compared to the S population. Both populations grown with corn produced more aboveground biomass than the ones grown with sunflowers. The aboveground biomass of corn was reduced to a greater extent than sunflower by the presence of both johnsongrass populations, while both crops were affected more by the S than by the R population. Conclusions: Although the inheritance and the genetic background of plant materls were not addressed, the findings of this study indicate clearly that the growth rate and competitive ability of the ALS-resistant johnsongrass population are not associated with the resistance mechanism involved.

Refractory testicular germ cell tumors are highly sensitive to the targeting of polycomb pathway demethylases KDM6A and KDM6B

Testicular germ cell tumors (TGCTs) can be treated with cisplatin-based therapy. However, a clinically significant number of cisplatin-resistant patients die from progressive disease as no effective alternatives exist. Curative cisplatin therapy results in acute and life-long toxicities in the young TGCT patient population providing a rationale to decrease cisplatin exposure. In contrast to genetic alterations, recent evidence suggests that epigenetics is a major driving factor for TGCT formation, progression, and response to chemotherapy. Hence, targeting epigenetic pathways with “epidrugs” is one potential relatively unexplored strategy to advance TGCT treatment beyond cisplatin. In this report, we demonstrate for the first time that targeting polycomb demethylases KDM6A and KDM6B with epidrug GSK-J4 can treat both cisplatin-sensitive and -resistant TGCTs. While GSK-J4 had minimal effects alone on TGCT tumor growth in vivo, it dramatically sensitized cisplatin-sensitive and -resistant TGCTs to cisplatin. We validated KDM6A/KDM6B as the target of GSK-J4 since KDM6A/KDM6B genetic depletion had a similar effect to GSK-J4 on cisplatin-mediated anti-tumor activity and transcriptome alterations. Pharmacologic and genetic targeting of KDM6A/KDM6B potentiated or primed the p53-dominant transcriptional response to cisplatin, with also evidence for basal activation of p53. Further, several chromatin modifier genes, including BRD4, lysine demethylases, chromodomain helicase DNA binding proteins, and lysine methyltransferases, were repressed with cisplatin only in KDM6A/KDM6B-targeted cells, implying that KDM6A/KDM6B inhibition sets the stage for extensive chromatin remodeling of TGCT cells upon cisplatin treatment. Our findings demonstrate that targeting polycomb demethylases is a new potent pharmacologic strategy for treating cisplatin resistant TGCTs that warrants clinical development.