Functional Genomics Research Articles

Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data

BackgroundIn recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis.ResultsWe proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise.ConclusionShaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud, and its source code is publicly available at https://github.com/WiedenWei/shaoxia.

Chromosome-level genome assembly of the predatory stink bug Arma custos

The stink bug Arma custos (Hemiptera: Pentatomidae) is a predatory enemy successfully used for biocontrol of lepidopteran and coleopteran pests in notorious invasive species. In this study, a high-quality chromosome-scale genome assembly of A. custos was achieved through a combination of Illumina sequencing, PacBio HiFi sequencing, and Hi-C scaffolding techniques. The final assembled genome was 969.02 Mb in size, with 935.94 Mb anchored to seven chromosomes, and a scaffold N50 length of 135.75 Mb. This genome comprised 52.78% repetitive elements. The detected complete BUSCO score was 99.34%, indicating its completeness. A total of 13,708 protein-coding genes were predicted in the genome, and 13219 of them were annotated. This genome provides an invaluable resource for further research on various aspects of predatory bugs, such as biology, genetics, and functional genomics.

Deep learning model for predicting genetic diseases using DNA sequence data

The emergence of machine learning in the recent decade has excelled in determining new potential features and nonlinear relationships existing between the data derived from the DNA sequences of genetic diseases. Machine learning also enhances the process of handling data with maximum predicted variables compared to observations during the data mining process of prediction. In this context, our study presents a deep learning model for predicting Transcription Factor Binding Sites (TFBS) in DNA sequences, with a focus on features within genetic data associated with diseases. Transcription Factors (TFs) play a crucial role in modulating gene expression by binding to TFBS. The accurate prediction of TFBS is essential for understanding genome function and evolution. Thus, we develop an efficient deep learning model that considers TFBS prediction as a nucleotide-level binary classification task. In our proposed model, first we create an input matrix using the original DNA sequences. Next, we encode these DNA sequences using one-hot encoding, representing them as a sequence of numerical values. We then employ three convolutional layers, allowing our model to capture intricate patterns and motif features over a larger spatial range. To capture important features within the DNA sequence and to focus on them, we incorporate an attention layer. Finally, a dense layer, consisting of two fully connected layers and a dropout layer, calculates the probability of TF binding site occurrence based on the features learned by the proposed model. Our experimental results, using in-vivo datasets obtained from Chip-seq, demonstrate the superior performance of our proposed deep learning model in TFBS prediction compared to other existing state-of-the-art methods. The improvement in accuracy is due to additional layers of CNN and then an attention layer in the model. Thus, this result in a better performance of our approach in predicting the transcription factor binding sites and enhancing our understanding of gene regulation and genome function.

Chromosome-level genome assembly of the diploid oat species Avena longiglumis

Chromosome-level genome assembly of the diploid oat species Avena longiglumis

Epistatic interactions between NMD and TRP53 control progenitor cell maintenance and brain size.

Mutations in human nonsense-mediated mRNA decay (NMD) factors are enriched in neurodevelopmental disorders. We show that deletion of key NMD factor Upf2 in mouse embryonic neural progenitor cells causes perinatal microcephaly but deletion in immature neurons does not, indicating NMD's critical roles in progenitors. Upf2 knockout (KO) prolongs the cell cycle of radial glia progenitor cells, promotes their transition into intermediate progenitors, and leads to reduced upper-layer neurons. CRISPRi screening identified Trp53 knockdown rescuing Upf2KO progenitors without globally reversing NMD inhibition, implying marginal contributionsof most NMD targets to the cell cycle defect. Integrated functional genomics shows that NMD degrades selective TRP53 downstream targets, including Cdkn1a, which, without NMD suppression, slow the cell cycle. Trp53KO restores the progenitor cell pool and rescues the microcephaly of Upf2KO mice. Therefore, one physiological role of NMD in the developing brain is to degrade selective TRP53 targets to control progenitor cell cycle and brain size.

Decoding the role of oxidative stress resistance and alternative carbon substrate assimilation in the mature biofilm growth mode of Candida glabrata

BackgroundBiofilm formation is viewed as a vital mechanism in C. glabrata pathogenesis. Although, it plays a significant role in virulence but transcriptomic architecture and metabolic pathways governing the biofilm growth mode of C. glabrata remain elusive. The present study intended to investigate the genes implicated in biofilm growth phase of C. glabrata through global transcriptomic approach.ResultsFunctional analysis of Differentially expressed genes (DEGs) using gene ontology and pathways analysis revealed that upregulated genes are involved in the glyoxylate cycle, carbon-carbon lyase activity, pre-autophagosomal structure membrane and vacuolar parts whereas, down- regulated genes appear to be associated with glycolysis, ribonucleoside biosynthetic process, ribosomal and translation process in the biofilm growth condition. The RNA-Seq expression of eight selected DEGs (CgICL1, CgMLS1, CgPEP1, and CgNTH1, CgERG9, CgERG11, CgTEF3, and CgCOF1) was performed with quantitative real-time PCR (RT-qPCR). The gene expression profile of selected DEGs with RT-qPCR displayed a similar pattern of expression as observed in RNA-Seq. Phenotype screening of mutant strains generated for genes CgPCK1 and CgPEP1, showed that Cgpck1∆ failed to grow on alternative carbon substrate (Glycerol, Ethanol, Oleic acid) and similarly, Cgpep1∆ unable to grow on YPD medium supplemented with hydrogen peroxide. Our results suggest that in the absence of glucose, C. glabrata assimilate glycerol, oleic acid and generate acetyl coenzyme-A (acetyl-CoA) which is a central and connecting metabolite between catabolic and anabolic pathways (glyoxylate and gluconeogenesis) to produce glucose and fulfil energy requirements.ConclusionsThe study was executed using various approaches (transcriptomics, functional genomics and gene deletion) and it revealed that metabolic plasticity of C. glabrata (NCCPF-100,037) in biofilm stage modulates its virulence and survival ability to counter the stress and may promote its transition from commensal to opportunistic pathogen. The observations deduced from the present study along with future work on characterization of the proteins involved in this intricate process may prove to be beneficial for designing novel antifungal strategies.

Construction and verification of a histone deacetylases-related prognostic signature model for colon cancer

Histone deacetylases (HDACs) contribute significantly to the initiation, progression, and prognosis of colorectal adenocarcinoma (COAD). Additionally, HDACs regulate the tumor microenvironment, immune escape, and tumor stem cells, and are closely linked to COAD prognosis. We developed a prognostic model for COAD that incorporates HDACs to evaluate their specific roles. The COAD dataset containing clinical and mutation data was collected using the TCGA and GEO databases to obtain genes associated with HDAC. LASSO analysis and univariate and multivariate Cox regression analysis were used to determine the presence of prognostic genes. Multivariate Cox analysis was also used to determine risk scores for HDAC-related features. Furthermore, genomic alterations, immune infiltration, and drug response were compared between high- and low-risk groups. Cellular experiments validated the potential regulatory role of BRD3 on COAD proliferation, migration, and apoptosis. The median risk scores, calculated based on the characteristics, demonstrated a more significant prognostic improvement in patients in the low-risk group. Furthermore, HDAC-related features were identified as important independent prognostic factors for patients with COAD. Additionally, genomic mutation status, immune infiltration, and function, as well as response to immunotherapy and chemotherapy, were found to be associated with risk scores. Subgroup analyses indicate that anti-PD-1 therapy may be beneficial for patients in the low-risk group. Additionally, a decrease in risk score was associated with a decrease in immune infiltration. Finally, HCT116 and HT29 cells exhibited inhibition of BRD3 gene proliferation and migration, as well as promotion of apoptosis. In patients with COAD, HDAC-related characteristics may be useful in predicting survival and selecting treatment.

Revealing the Satellite DNA Content in Ancistrus sp. (Siluriformes: Loricariidae) by Genomic and Bioinformatic Analysis

Introduction: Eukaryotic genomes are composed of simple, repetitive sequences, including satellite DNAs (satDNA), which are noncoding sequences arranged in tandem arrays. These sequences play a crucial role in genomic functions and innovations, influencing processes such as the maintenance of nuclear material, the formation of heterochromatin and the differentiation of sex chromosomes. In this genomic era, advances in next-generation sequencing and bioinformatics tools have facilitated the exhaustive cataloging of repetitive elements in genomes, particularly in non-model species. This study focuses on the satDNA content of Ancistrus sp., a diverse species of fish from the Loricariidae family. The genus Ancistrus shows significant karyotypic evolution, with extensive variability from the ancestral diploid number. Methods: By means of bioinformatic approaches, 40 satDNA families in Ancistrus sp., constituting 5.19% of the genome were identified. Analysis of the abundance and divergence landscape revealed diverse profiles, indicating recent amplification and homogenization of these satDNA sequences. Results: The most abundant satellite, AnSat1-142, constitutes 2.1% of the genome, while the least abundant, AnSat40-52, represents 0.0034%. The length of the monomer repeat varies from 16 to 142 base pairs, with an average length of 61 bp. These results contribute to understanding the genomic dynamics and evolution of satDNAs in Ancistrus sp. Conclusion: The study underscores the variability of satDNAs between fish species and provides valuable information on chromosome organization and the evolution of repetitive elements in non-model organisms.

PAGER-scFGA: unveiling cell functions and molecular mechanisms in cell trajectories through single-cell functional genomics analysis.

Background: Understanding how cells and tissues respond to stress factors and perturbations during disease processes is crucial for developing effective prevention, diagnosis, and treatment strategies. Single-cell RNA sequencing (scRNA-seq) enables high-resolution identification of cells and exploration of cell heterogeneity, shedding light on cell differentiation/maturation and functional differences. Recent advancements in multimodal sequencing technologies have focused on improving access to cell-specific subgroups for functional genomics analysis. To facilitate the functional annotation of cell groups and characterization of molecular mechanisms underlying cell trajectories, we introduce the Pathways, Annotated Gene Lists, and Gene Signatures Electronic Repository for Single-Cell Functional Genomics Analysis (PAGER-scFGA). Results: We have developed PAGER-scFGA, which integrates cell functional annotations and gene-set enrichment analysis into popular single-cell analysis pipelines such as Scanpy. Using differentially expressed genes (DEGs) from pairwise cell clusters, PAGER-scFGA infers cell functions through the enrichment of potential cell-marker genesets. Moreover, PAGER-scFGA provides pathways, annotated gene lists, and gene signatures (PAGs) enriched in specific cell subsets with tissue compositions and continuous transitions along cell trajectories. Additionally, PAGER-scFGA enables the construction of a gene subcellular map based on DEGs and allows examination of the gene functional compartments (GFCs) underlying cell maturation/differentiation. In a real-world case study of mouse natural killer (mNK) cells, PAGER-scFGA revealed two major stages of natural killer (NK) cells and three trajectories from the precursor stage to NK T-like mature stage within blood, spleen, and bone marrow tissues. As the trajectories progress to later stages, the DEGs exhibit greater divergence and variability. However, the DEGs in different trajectories still interact within a network during NK cell maturation. Notably, PAGER-scFGA unveiled cell cytotoxicity, exocytosis, and the response to interleukin (IL) signaling pathways and associated network models during the progression from precursor NK cells to mature NK cells. Conclusion: PAGER-scFGA enables in-depth exploration of functional insights and presents a comprehensive knowledge map of gene networks and GFCs, which can be utilized for future studies and hypothesis generation. It is expected to become an indispensable tool for inferring cell functions and detecting molecular mechanisms within cell trajectories in single-cell studies. The web app (accessible at https://au-singlecell.streamlit.app/) is publicly available.

Haplotype-resolved genomes of octoploid species in Phyllanthaceae family reveal a critical role for polyploidization and hybridization in speciation.

The Phyllanthaceae family comprises a diverse range of plants with medicinal, edible, and ornamental value, extensively cultivated worldwide. Polyploid species commonly occur in Phyllanthaceae. Due to the rather complex genomes and evolutionary histories, their speciation process has been still lacking in research. In this study, we generated chromosome-scale haplotype-resolved genomes of two octoploid species (Phyllanthus emblica and Sauropus spatulifolius) in Phyllanthaceae family. Combined with our previously reported one tetraploid (Sauropus androgynus) and one diploid species (Phyllanthus cochinchinensis) from the same family, we explored their speciation history. The three polyploid species were all identified as allopolyploids with subgenome A/B. Each of their two distinct subgenome groups from various species was uncovered to independently share a common diploid ancestor (Ancestor-AA and Ancestor-BB). Via different evolutionary routes, comprising various scenarios of bifurcating divergence, allopolyploidization (hybrid polyploidization), and autopolyploidization, they finally evolved to the current tetraploid S. androgynus, and octoploid S. spatulifolius and P. emblica, respectively. We further discuss the variations in copy number of alleles and the potential impacts within the two octoploids. In addition, we also investigated the fluctuation of metabolites with medical values and identified the key factor in its biosynthesis process in octoploids species. Our study reconstructed the evolutionary history of these Phyllanthaceae species, highlighting the critical roles of polyploidization and hybridization in their speciation processes. The high-quality genomes of the two octoploid species provide valuable genomic resources for further research of evolution and functional genomics.

Multiple horizontal transfer events of a DNA transposon into turtles, fishes, and a frog

Horizontal transfer of transposable elements (HTT) has been reported across many species and the impact of such events on genome structure and function has been well described. However, few studies have focused on reptilian genomes, especially HTT events in Testudines (turtles). Here, as a consequence of investigating the repetitive content of Malaclemys terrapin terrapin (Diamondback turtle) we found a high similarity DNA transposon, annotated in RepBase as hAT-6_XT, shared between other turtle species, ray-finned fishes, and a frog. hAT-6_XT was notably absent in reptilian taxa closely related to turtles, such as crocodiles and birds. Successful invasion of DNA transposons into new genomes requires the conservation of specific residues in the encoded transposase, and through structural analysis, these residues were identified indicating some retention of functional transposition activity. We document six recent independent HTT events of a DNA transposon in turtles, which are known to have a low genomic evolutionary rate and ancient repeats.

Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum.

The gene expression landscape across different tissues and developmental stages reflects their biological functions and evolutionary patterns. Integrative and comprehensive analyses of all transcriptomic data in an organism are instrumental to obtaining a comprehensive picture of gene expression landscape. Such studies are still very limited in sorghum, which limits the discovery of the genetic basis underlying complex agricultural traits in sorghum. We characterized the genome-wide expression landscape for sorghum using 873 RNA-sequencing (RNA-seq) datasets representing 19 tissues. Our integrative analysis of these RNA-seq data provides the most comprehensive transcriptomic atlas for sorghum, which will be valuable for the sorghum research community for functional characterizations of sorghum genes. Based on the transcriptome atlas, we identified 595 housekeeping genes (HKGs) and 2080 tissue-specific expression genes (TEGs) for the 19 tissues. We identified different gene features between HKGs and TEGs, and we found that HKGs have experienced stronger selective constraints than TEGs. Furthermore, we built a transcriptome-wide co-expression network (TW-CEN) comprising 35 modules with each module enriched in specific Gene Ontology terms. High-connectivity genes in TW-CEN tend to express at high levels while undergoing intensive selective pressure. We also built global and seed-preferential co-expression networks of starch synthesis pathways, which indicated that photosynthesis and microtubule-based movement play important roles in starch synthesis. The global transcriptome atlas of sorghum generated by this study provides an important functional genomics resource for trait discovery and insight into starch synthesis regulation in sorghum.

An integrated toolkit for human microglia functional genomics

SummaryBackgroundMicroglia, the brain’s resident immune cells, play vital roles in brain development, and disorders like Alzheimer’s disease (AD). Human iPSC-derived microglia (iMG) provide a promising model to study these processes. However, existing iMG generation protocols face challenges, such as prolonged differentiation time, lack of detailed characterization, and limited gene function investigation via CRISPR-Cas9.MethodsOur integrated toolkit for in-vitro microglia functional genomics optimizes iPSC differentiation into iMG through a streamlined two-step, 20-day process, producing iMG with a normal karyotype. We confirmed the iMG’s authenticity and quality through single-cell RNA sequencing, chromatin accessibility profiles (ATAC-Seq), proteomics and functional tests. The toolkit also incorporates a drug-dependent CRISPR-ON/OFF system for temporally controlled gene expression. Further, we facilitate the use of multi-omic data by providing online searchable platform that compares new iMG profiles to human primary microglia: https://sherlab.shinyapps.io/IPSC-derived-Microglia/.ResultsOur method generates iMG that closely align with human primary microglia in terms of transcriptomic, proteomic, and chromatin accessibility profiles. Functionally, these iMG exhibit Ca2 + transients, cytokine driven migration, immune responses to inflammatory signals, and active phagocytosis of CNS related substrates including synaptosomes, amyloid beta and myelin. Significantly, the toolkit facilitates repeated iMG harvesting, essential for large-scale experiments like CRISPR-Cas9 screens. The standalone ATAC-Seq profiles of our iMG closely resemble primary microglia, positioning them as ideal tools to study AD-associated single nucleotide variants (SNV) especially in the genome regulatory regions.ConclusionsOur advanced two-step protocol rapidly and efficiently produces authentic iMG. With features like the CRISPR-ON/OFF system and a comprehensive multi-omic data platform, our toolkit equips researchers for robust microglial functional genomic studies. By facilitating detailed SNV investigation and offering a sustainable cell harvest mechanism, the toolkit heralds significant progress in neurodegenerative disease drug research and therapeutic advancement.

Chromosome-level genome assembly and characterization of the Calophaca sinica genome.

Calophaca sinica is a rare plant endemic to northern China which belongs to the Fabaceae family and possesses rich nutritional value. To support the preservation of the genetic resources of this plant, we have successfully generated a high-quality genome of C. sinica (1.06 Gb). Notably, transposable elements (TEs) constituted ~73% of the genome, with long terminal repeat retrotransposons (LTR-RTs) dominating this group of elements (~54% of the genome). The average intron length of the C. sinica genome was noticeably longer than what has been observed for closely related species. The expansion of LTR-RTs and elongated introns emerged had the largest influence on the enlarged genome size of C. sinica in comparison to other Fabaceae species. The proliferation of TEs could be explained by certain modes of gene duplication, namely, whole genome duplication (WGD) and dispersed duplication (DSD). Gene family expansion, which was found to enhance genes associated with metabolism, genetic maintenance, and environmental stress resistance, was a result of transposed duplicated genes (TRD) and WGD. The presented genomic analysis sheds light on the genetic architecture of C. sinica, as well as provides a starting point for future evolutionary biology, ecology, and functional genomics studies centred around C. sinica and closely related species.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.

The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds' mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene's product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.

Genome sequencing and assembly of Indian golden silkmoth, Antheraea assamensis Helfer (Saturniidae, Lepidoptera)

Muga silkworm (Antheraea assamensis), one of the economically important wild silkmoths, is unique among saturniid silkmoths. It is confined to the North-eastern part of India. Muga silk has the highest value among the other silks. Unlike other silkmoths, A. assamensis has a low chromosome number (n = 15), and ZZ/ZO sex chromosome system. Here, we report the first high-quality draft genome of A. assamensis, assembled by employing the Illumina and PacBio sequencing platforms. The assembled genome of A. assamensis is 501.18 Mb long, with 2697 scaffolds and an N50 of 683.23 Kb. The genome encompasses 18,385 protein-coding genes, 86.29% of which were functionally annotated. Phylogenetic analysis of A. assamensis revealed its divergence from other Antheraea species approximately 28.7 million years ago. Moreover, an investigation into detoxification-related gene families, CYP450, GST, and ABC-transporter, revealed a significant expansion in A. assamensis as compared to the Bombyx mori. This expansion is comparable to Spodoptera litura, suggesting adaptive responses linked to the polyphagous behavior observed in these insects. This study provides valuable insights into the molecular basis of evolutionary divergence and adaptations in muga silkmoth. The genome assembly reported in this study will significantly help in the functional genomics studies on A. assamensis and other Antheraea species along with comparative genomics analyses of Bombycoidea insects.

Abstract NG08: Dissecting and quantifying pancreatic cancer plasticity using single-cell multiomics, lineage tracing and functional genomics reveals novel mediators of therapy resistance

Abstract NG08: Dissecting and quantifying pancreatic cancer plasticity using single-cell multiomics, lineage tracing and functional genomics reveals novel mediators of therapy resistance

Genetic analysis of scab disease resistance in common bean (Phaseolus vulgaris) varieties using GWAS and functional genomics approaches

IntroductionScab is a fungal disease of common beans caused by the pathogen Elsinoë phaseoli. The disease results in major economic losses on common beans, and there are efforts to develop integrated pest management strategies to control the disease. Modern computational biology and bioinformatics tools were utilized to identify scab disease resistance genes in the common bean by identification of genomic regions and genes associated with resistance to scab disease during natural infection in the field.MethodsA diverse set of common bean accessions were analyzed for genetic association with scab disease resistance using a Genome-Wide Association Study design of infected plants and non-infected plants (controls). A fixed and random model circulating probability unification model of these two covariates that considers a minor allele frequency threshold value of 0.03 were deployed during the analysis. Annotation of genes proteins with significant association values was conducted using a machine learning algorithm of support vector machine on prPred using python3 on Linux Ubuntu 18.04 computing platform with an accuracy of 0.935.ResultsCommon bean accessions tested showed varying phenotypes of susceptibility to scab disease. Out of 179 accessions, 16 and 163 accessions were observed to be resistant and susceptible to scab disease, respectively. Genomic analysis revealed a significant association on chromosome one SNP S1_6571566 where the protein-coding sequence had a resistant possibility of 55% and annotated to the Enhancer of Poly-comb like protein.ConclusionThe significant differences in the phenotypic variability for scab disease indicate wide genetic variability among the common bean accessions. The resistant gene associated with scab disease was successfully identified by GWAS analysis. The identified common bean accessions resistant to scab disease can be adopted into breeding programs as sources of resistance.

Abstract LB427: UBA1 blockade induces homologous recombination deficiency and is synthetic lethal with PARP inhibition

Abstract Therapeutic strategies targeting DNA damage have revolutionized cancer treatment, yet their efficacy often comes at the cost of substantial adverse effects. The emergence of poly-ADP-ribose polymerase (PARP) inhibition as a targeted approach to disrupt DNA repair in tumors deficient in homologous recombination (HR) has shown promise. However, the limited response of most cancers to PARP inhibitors has posed a significant challenge. This study employs a genome-wide CRISPR knockout functional genomics screen, revealing that depletion of ubiquitin-activating enzyme E1 (UBA1) enhances sensitivity to PARP inhibition in HR-proficient ovarian cancer cells. Validation across different ovarian and breast cancer cell lineages, utilizing cell line and organoid models, establishes that pharmacological inhibition of UBA1, a pivotal player in ubiquitination, sensitizes cells to PARP inhibition and other DNA damaging therapies. In vivo experiments combining PARP and UBA1 inhibition demonstrate not only tolerability but also significant extension of survival in patient-derived xenografts compared to individual therapies. Mechanistic studies uncover that UBA1 inhibition not only impedes HR repair, sensitizing cells to PARP inhibition, but also induces widespread increases in PARylation, subsequently targeted by PARP inhibition. These findings underscore the multifaceted pathways through which UBA1 inhibition potentiates the efficacy of PARP inhibition. The demonstrated tolerability and substantial therapeutic gains establish the combined approach as a promising strategy to maximize the benefits of PARP inhibition in cancer therapy. Citation Format: Sharad Awasthi, Daniel J. McGrail, S. Stephen Yi, Nidhi Sahni. UBA1 blockade induces homologous recombination deficiency and is synthetic lethal with PARP inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB427.

RNA three-dimensional structure drives the sequence organization of potato spindle tuber viroid quasispecies.

RNA viruses and viroids exist and evolve as quasispecies due to error-prone replication. Quasispecies consist of a few dominant master sequences alongside numerous variants that contribute to genetic diversity. Upon environmental changes, certain variants within quasispecies have the potential to become the dominant sequences, leading to the emergence of novel infectious strains. However, the emergence of new infectious variants remains unpredictable. Using mutant pools prepared by saturation mutagenesis of selected stem and loop regions, our study of potato spindle tuber viroid (PSTVd) demonstrates that mutants forming local three-dimensional (3D) structures similar to the wild type (WT) are more likely to accumulate in PSTVd quasispecies. The selection mechanisms underlying this biased accumulation are likely associated with cell-to-cell movement and long-distance trafficking. Moreover, certain trafficking-defective PSTVd mutants can be spread by functional sister genomes in the quasispecies. Our study reveals that the RNA 3D structure of stems and loops constrains the evolution of viroid quasispecies. Mutants with a structure similar to WT have a higher likelihood of being maintained within the quasispecies and can potentially give rise to novel infectious variants. These findings emphasize the potential of targeting RNA 3D structure as a more robust approach to defend against viroid infections.