Identification of novel proteins for coronary artery disease by integrating GWAS data and human plasma proteomes.

Background: Most coronary artery disease (CAD) risk loci identified by genome-wide association studies (GWAS) are located in non-coding regions, hampering the interpretation of how they confer CAD risk. It is essential to integrate GWAS with molecular traits data to further explore the genetic basis of CAD. Methods: We used the probabilistic Mendelian randomization (PMR) method to identify potential proteins involved in CAD by integrating CAD GWAS data (∼76,014 cases and ∼264,785 controls) and human plasma proteomes (N = 35,559). Then, Bayesian co-localization analysis, confirmatory PMR analysis using independent plasma proteome data (N = 7752), and gene expression data (N1 = 213, N2 = 670) were performed to validate candidate proteins. We further investigated the associations between candidate proteins and CAD-related traits and explored the rationality and biological functions of candidate proteins through disease enrichment, cell type-specific, GO, and KEGG enrichment analysis. Results: This study inferred that the abundance of 30 proteins in the plasma was causally associated with CAD (P < 0.05/4408, Bonferroni correction), such as PLG, IL15RA, and CSNK2A1. PLG, PSCK9, COLEC11, ZNF180, ERP29, TCP1, FN1, CDH5, IL15RA, MGAT4B, TNFRSF6B, DNM2, and TGF1R were replicated in the confirmatory PMR (P < 0.05). PCSK9 (PP.H4 = 0.99), APOB (PP.H4 = 0.89), FN1 (PP.H4 = 0.87), and APOC1 (PP.H4 = 0.78) coding proteins shared one common variant with CAD. MTAP, TCP1, APOC2, ERP29, MORF4L1, C19orf80, PCSK9, APOC1, EPOR, DNM2, TNFRSF6B, CDKN2B, and LDLR were supported by PMR at the transcriptome level in whole blood and/or coronary arteries (P < 0.05). Enrichment analysis identified multiple pathways involved in cholesterol metabolism, regulation of lipoprotein levels and telomerase, such as cholesterol metabolism (hsa04979, P = 2.25E-7), plasma lipoprotein particle clearance (GO:0034381, P = 5.47E-5), and regulation of telomerase activity (GO:0051972, P = 2.34E-3). Conclusions: Our integration analysis has identified 30 candidate proteins for CAD, which may provide important leads to design future functional studies and potential drug targets for CAD.

In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma.

BACKGROUND: Genetic perturbation screens with single-cell readouts have enabled rich phenotyping of gene function and regulatory networks. These approaches have been challenging in vivo, especially in adult disease models such as cancer, which include mixtures of malignant and microenvironment cells. Glioblastoma (GBM) is a fatal cancer, and methods of systematically interrogating gene function and therapeutic targets in vivo, especially in combination with standard of care treatment such as radiotherapy, are lacking. RESULTS: Here, we iteratively develop a multiplex in vivo perturb-seq CRISPRi platform for single-cell genetic screens in cancer and tumor microenvironment cells that leverages intracranial convection enhanced delivery of sgRNA libraries into mouse models of GBM. Our platform enables potent silencing of drivers of in vivo growth and tumor maintenance as well as genes that sensitize GBM to radiotherapy. We find radiotherapy rewires transcriptional responses to genetic perturbations in an in vivo-dependent manner, revealing heterogenous patterns of treatment sensitization or resistance in GBM. Furthermore, we demonstrate targeting of genes that function in the tumor microenvironment, enabling alterations of ligand-receptor interactions between immune and stromal cells following in vivo CRISPRi perturbations that can affect tumor cell phagocytosis. CONCLUSION: In sum, we demonstrate the utility of multiplexed perturb-seq for in vivo single-cell dissection of adult cancer and normal tissue biology across multiple cell types in the context of therapeutic intervention, a platform with potential for broad application.

High-throughput protein characterization by complementation using DNA barcoded fragment libraries.

Our ability to predict, control, or design biological function is fundamentally limited by poorly annotated gene function. This can be particularly challenging in non-model systems. Accordingly, there is motivation for new high-throughput methods for accurate functional annotation. Here, we used complementation of auxotrophs and DNA barcode sequencing (Coaux-Seq) to enable high-throughput characterization of protein function. Fragment libraries from eleven genetically diverse bacteria were tested in twenty different auxotrophic strains of Escherichia coli to identify genes that complement missing biochemical activity. We recovered 41% of expected hits, with effectiveness ranging per source genome, and observed success even with distant E. coli relatives like Bacillus subtilis and Bacteroides thetaiotaomicron. Coaux-Seq provided the first experimental validation for 53 proteins, of which 11 are less than 40% identical to an experimentally characterized protein. Among the unexpected function identified was a sulfate uptake transporter, an O-succinylhomoserine sulfhydrylase for methionine synthesis, and an aminotransferase. We also identified instances of cross-feeding wherein protein overexpression and nearby non-auxotrophic strains enabled growth. Altogether, Coaux-Seq's utility is demonstrated, with future applications in ecology, health, and engineering.

Using bioinformatics to investigate functional diversity: a case study of MHC diversity in koalas.

Conservation genomics can greatly improve conservation outcomes of threatened populations, including those impacted by disease. Understanding diversity within immune gene families, including the major histocompatibility complex (MHC) and toll-like receptors (TLR), is important due to the role they play in disease resilience and susceptibility. With recent advancements in sequencing technologies and bioinformatic tools, the cost of generating high-quality sequence data has significantly decreased and made it possible to investigate diversity across entire gene families in large numbers of individuals compared to investigating only a few genes or a few populations previously. Here, we use the koala as a case study for investigating functional diversity across populations. We utilised previous target enrichment data and 438 whole genomes to firstly, determine the level of sequencing depth required to investigate MHC diversity and, secondly, determine the current level of diversity in MHC genes in koala populations. We determined for low complexity, conserved genes such as TLR genes 10 × sequencing depth is sufficient to reliably genotype more than 90% of variants, whereas for complex genes such as the MHC greater than 20 × and preferably 30 × sequencing depth is required. We used whole genome data to identify 270 biallelic SNPs across 24 MHC genes as well as copy number variation (CNV) within class I and class II genes and conduct supertype analysis. Overall, we have provided a bioinformatic workflow for investigating variation in a complex immune gene family from whole genome sequencing data and determined current levels of diversity within koala MHC genes.

An Efficient Fluorescence-Activated Protoplast Sorting (FAPS) and Regeneration Protocol for Canola (Brassica napus).

Protoplast sorting and purification methods are powerful tools enabling the enrichment of cellular subpopulations for basic and applied studies in plant sciences. Fluorescence-activated protoplast sorting (FAPS) is an efficient method to isolate specific protoplast populations based on innate features (size and autofluorescence) or expression of fluorescent proteins. FAPS-based methods have recently been deployed in single-cell purification for single-cell RNA sequencing-based transcriptional profiling studies. Protoplast sorting methods integrated with the ability to culture and recover whole plants add value to functional genomics and gene editing applications. Enriching cells expressing nucleases linked to fluorescent proteins can maximize knockout or knockin editing efficiencies and minimize toxic and off-target effects. Here, we report the protocol for protoplast preparation, sterile cell sorting, culture, and downstream regeneration of plants from canola protoplasts. This protocol can be successfully applied to all totipotent protoplast methods that can regenerate into whole plants. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Preparation of transfected canola protoplasts for sorting Basic Protocol 2: Fluorescence-activated protoplast sorting Basic Protocol 3: Bead culture of sorted protoplasts and recovery of plantlets.

Discovery of therapeutic targets in cancer using chromatin accessibility and transcriptomic data.

Most cancer types lack targeted therapeutic options, and when first-line targeted therapies are available, treatment resistance is a huge challenge. Recent technological advances enable the use of assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA sequencing (RNA-seq) on patient tissue in a high-throughput manner. Here, we present a computational approach that leverages these datasets to identify drug targets based on tumor lineage. We constructed gene regulatory networks for 371 patients of 22 cancer types using machine learning approaches trained with three-dimensional genomic data for enhancer-to-promoter contacts. Next, we identified the key transcription factors (TFs) in these networks, which are used to find therapeutic vulnerabilities, by direct targeting of either TFs or the proteins that they interact with. We validated four candidates identified for neuroendocrine, liver, and renal cancers, which have a dismal prognosis with current therapeutic options.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics.

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Genome editing: A novel approach to manage insect vectors of plant viruses.

Insect vectors significantly threaten global agriculture by transmitting numerous plant viruses. Various measures, from conventional insecticides to genetic engineering, are used to mitigate this threat. However, none provide complete resistance. Therefore, researchers are looking for novel control options. In recent years with the advancements in genomic technologies, genomes and transcriptomes of various insect vectors have been generated. However, the lack of knowledge about gene functions hinders the development of novel strategies to restrict virus spread. RNA interference (RNAi) is widely used to elucidate gene functions, but its variable efficacy hampers its use in managing insect vectors and plant viruses. Genome editing has the potential to overcome these challenges and has been extensively used in various insect pest species. This review summarizes the progress and potential of genome editing in plant virus vectors and its application as a functional genomic tool to elucidate virus-vector interactions. We also discuss the major challenges associated with editing genes of interest in insect vectors.

FEAtl: a comprehensive web-based expression atlas for functional genomics in tropical and subtropical fruit crops.

BACKGROUND: Fruit crops, including tropical and subtropical fruits like Avocado (Persea americana), Fig (Ficus carica), Date Palm (Phoenix dactylifera), Mango (Mangifera indica), Guava (Psidium guajava), Papaya (Carica papaya), Pineapple (Ananas comosus), and Banana (Musa acuminata) are economically vital, contributing significantly to global agricultural output, as classified by the FAO's World Programme for the Census of Agriculture. Advancements in next-generation sequencing, have transformed fruit crop breeding by providing in-depth genomic and transcriptomic data. RNA sequencing enables high-throughput analysis of gene expression, and functional genomics, crucial for addressing horticultural challenges and enhancing fruit production. The genomic and expression data for key tropical and sub-tropical fruit crops is currently lacking a comprehensive expression atlas, revealing a significant gap in resources for horticulturists who require a unified platform with diverse datasets across various conditions and cultivars. RESULTS: The Fruit Expression Atlas (FEAtl), available at http://backlin.cabgrid.res.in/FEAtl/ , is a first-ever extensive and unified expression atlas for tropical and subtropical fruit crops developed using 3-tier architecture. The expressivity of coding and non-coding genes, encompassing 2,060 RNA-Seq samples across 91 tissue types and 177 BioProjects, it provides a comprehensive view of gene expression patterns for different tissues under various conditions. FEAtl features multiple tabs that cater to different aspects of the dataset, namely, Home, About, Analyze, Statistics, and Team and contains seven central functional modules: Transcript Information,Sample Information, Expression Profiles in FPKM and TPM, Functional Analysis, Genes Based on Tau Score, and Search for Specific Gene. The expression of a transcript of interest can be easily queried by searching by tissue ID and transcript type. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. CONCLUSIONS: This atlas represents a groundbreaking compilation of a wide array of information pertaining to eight distinct fruit crops and serves as a fundamental resource for comparative analysis among different fruit species and is a catalyst for functional genomic studies. Database availability: http://backlin.cabgrid.res.in/FEAtl/ .

Therapeutic modulation of ROCK overcomes metabolic adaptation of cancer cells to OXPHOS inhibition and drives synergistic anti-tumor activity.

Genomic studies have identified frequent mutations in subunits of the SWI/SNF chromatin remodeling complex including SMARCA4 and ARID1A in non-small cell lung cancer. Previously, we and others have identified that SMARCA4-mutant lung cancers are highly dependent on oxidative phosphorylation (OXPHOS). Despite initial excitements, therapeutics targeting metabolic pathways such as OXPHOS have largely been disappointing due to rapid adaptation of cancer cells to inhibition of single metabolic enzymes or pathways, suggesting novel combination strategies to overcome adaptive responses are urgently needed. Here, we performed a functional genomics screen using CRISPR-Cas9 library targeting genes with available FDA approved therapeutics and identified ROCK1/2 as a top hit that sensitizes cancer cells to OXPHOS inhibition. We validate these results by orthogonal genetic and pharmacologic approaches by demonstrating that KD025 (Belumosudil), an FDA approved ROCK inhibitor, has highly synergistic anti-cancer activity in vitro and in vivo in combination with OXPHOS inhibition. Mechanistically, we showed that this combination induced a rapid, profound energetic stress and cell cycle arrest that was in part due to ROCK inhibition-mediated suppression of the adaptive increase in glycolysis normally seen by OXPHOS inhibition. Furthermore, we applied global phosphoproteomics and kinase-motif enrichment analysis to uncover a dynamic regulatory kinome upon combination of OXPHOS and ROCK inhibition. Importantly, we found converging phosphorylation-dependent regulatory cross-talk by AMPK and ROCK kinases on key RHO GTPase signaling/ROCK-dependent substrates such as PPP1R12A, NUMA1 and PKMYT1 that are known regulators of cell cycle progression. Taken together, our study identified ROCK kinases as critical mediators of metabolic adaptation of cancer cells to OXPHOS inhibition and provides a strong rationale for pursuing ROCK inhibitors as novel combination partners to OXPHOS inhibitors in cancer treatment.

A disease-associated PPP2R3C-MAP3K1 phospho-regulatory module controls centrosome function.

Centrosomes have critical roles in microtubule organization, ciliogenesis, and cell signaling.1,2,3,4,5,6,7,8 Centrosomal alterations also contribute to diseases, including microcephaly, cancer, and ciliopathies.9,10,11,12,13 To date, over 150 centrosomal proteins have been identified, including several kinases and phosphatases that control centrosome biogenesis, function, and maintenance.2,3,4,5,14,15,16,17,18,19,20,21 However, the regulatory mechanisms that govern centrosome function are not fully defined, and thus how defects in centrosomal regulation contribute to disease is incompletely understood. Using a systems genetics approach, we find here that PPP2R3C, a poorly characterized PP2A phosphatase subunit, is a distal centriole protein and functional partner of centriolar proteins CEP350 and FOP. We further show that a key function of PPP2R3C is to counteract the kinase activity of MAP3K1. In support of this model, MAP3K1 knockout suppresses growth defects caused by PPP2R3C inactivation, and MAP3K1 and PPP2R3C have opposing effects on basal and microtubule stress-induced JNK signaling. Illustrating the importance of balanced MAP3K1 and PPP2R3C activities, acute overexpression of MAP3K1 severely inhibits centrosome function and triggers rapid centriole disintegration. Additionally, inactivating PPP2R3C mutations and activating MAP3K1 mutations both cause congenital syndromes characterized by gonadal dysgenesis.22,23,24,25,26,27,28 As a syndromic PPP2R3C variant is defective in centriolar localization and binding to centriolar protein FOP, we propose that imbalanced activity of this centrosomal kinase-phosphatase pair is the shared cause of these disorders. Thus, our findings reveal a new centrosomal phospho-regulatory module, shed light on disorders of gonadal development, and illustrate the power of systems genetics to identify previously unrecognized gene functions.

Genomic insights of Lactiplantibacillus plantarum CNPC024: a potential probiotic strain producing immune-boosting tryptophan-derived metabolites.

Probiogenomics can provide important insights bout probiotic candidate bacteria. This study aimed to perform an in-depth genomic characterization of the probiotic candidate Lactiplantibacillus plantarum CNPC024 to investigate its probiosis mechanisms, identify metabolic pathways that might benefit the host, and improve the safety assessment for this strain to be effectively used as a probiotic. After whole-genome sequencing in Illumina MiSeq platform, the de novo genome assembly resulted in a 3.2 Mb draft genome. According to the Average Nucleotide Identity (ANI) analysis with 46 randomly validated probiotic LAB belonging to the Lactobacillaceae family, the strain showed a 99% nucleotide identity with other L. plantarum probiotic species. We identified a set of determinants conferring tolerance to bile salts and low pH conditions, as well as temperature, oxidative and osmotic stressors via the glutathione-glutaredoxin system (Grxs). As a ß­galactosidase­producing strain, it has the potential to be used in fermented dairy products for lactose-intolerant individuals. There were no significant hits for transferable antibiotic-resistance genes. We also identified gene clusters associated with production of bacteriocins (plantaricins E, F and K). Lastly, we detected metabolic pathways associated with the production of tryptophan-derived metabolites that could potentially modulate the host's immune responses.

Genome-wide CRISPR-Cas9 knockout screens identify DNMT1 as a druggable dependency in sonic hedgehog medulloblastoma.

Sonic hedgehog subgroup of medulloblastoma (SHH-MB) is characterized by aberrant activation of the SHH signaling pathway. An inhibition of the positive SHH regulator Smoothened (SMO) has demonstrated promising clinical efficacy. Yet, primary and acquired resistance to SMO inhibitors limit their efficacy. An understanding of underlying molecular mechanisms of resistance to therapy is warranted to bridge this unmet need. Here, we make use of genome-wide CRISPR-Cas9 knockout screens in murine SMB21 and human DAOY cells, in order to unravel genetic dependencies and drug-related genetic interactors that could serve as alternative therapeutic targets for SHH-MB. Our screens reinforce SMB21 cells as a faithful model system for SHH-MB, as opposed to DAOY cells, and identify members of the epigenetic machinery including DNA methyltransferase 1 (DNMT1) as druggable targets in SHH-dependent tumors. We show that Dnmt1 plays a crucial role in normal murine cerebellar development and is required for SHH-MB growth in vivo. Additionally, DNMT1 pharmacological inhibition alone and in combination with SMO inhibition effectively inhibits tumor growth in murine and human SHH-MB cell models and prolongs survival of SHH-MB mouse models by inhibiting SHH signaling output downstream of SMO. In conclusion, our data highlight the potential of inhibiting epigenetic regulators as a novel therapeutic avenue in SMO-inhibitor sensitive as well as resistant SHH-MBs.

Functional genomic analysis of genes important for Candida albicans fitness in diverse environmental conditions.

Fungal pathogens such as Candida albicans pose a significant threat to human health with limited treatment options available. One strategy to expand the therapeutic target space is to identify genes important for pathogen growth in host-relevant environments. Here, we leverage a pooled functional genomic screening strategy to identify genes important for fitness of C. albicans in diverse conditions. We identify an essential gene with no known Saccharomyces cerevisiae homolog, C1_09670C, and demonstrate that it encodes subunit 3 of replication factor A (Rfa3). Furthermore, we apply computational analyses to identify functionally coherent gene clusters and predict gene function. Through this approach, we predict the cell-cycle-associated function of C3_06880W, a previously uncharacterized gene required for fitness specifically at elevated temperatures, and follow-up assays confirm that C3_06880W encodes Iml3, a component of the C. albicans kinetochore with roles in virulence in vivo. Overall, this work reveals insights into the vulnerabilities of C. albicans.

Genotype-First Approach Identifies an Association between rs28374544/FOG2S657G and Liver Disease through Alterations in mTORC1 Signaling.

Metabolic dysfunction-associated Fatty Liver Disease (MAFLD) has emerged as one of the leading cardiometabolic diseases. Friend of GATA2 (FOG2) is a transcriptional co-regulator that has been shown to regulate hepatic lipid metabolism and accumulation. Using meta-analysis from several different biobank datasets, we identified a coding variant of FOG2 (rs28374544, A1969G, S657G) predominantly found in individuals of African ancestry (minor allele frequency~20%), which is associated with liver failure/cirrhosis phenotype and liver injury. To gain insight into potential pathways associated with this variant, we interrogated a previously published genomics dataset of 38 human induced pluripotent stem cell (iPSCs) lines differentiated into hepatocytes (iHeps). Using Differential Gene Expression Analysis and Gene Set Enrichment Analysis, we identified the mTORC1 pathway as differentially regulated between iHeps from individuals with and without the variant. Transient lipid-based transfections were performed on the human hepatoma cell line (Huh7) using wild-type FOG2 and FOG2S657G and demonstrated that FOG2S657G increased mTORC1 signaling, de novo lipogenesis, and cellular triglyceride synthesis and mass. In addition, we observed a significant downregulation of oxidative phosphorylation in FOG2S657G cells in fatty acid-loaded cells but not untreated cells, suggesting that FOG2S657G may also reduce fatty acid to promote lipid accumulation. Taken together, our multi-pronged approach suggests a model whereby the FOG2S657G may promote MAFLD through mTORC1 activation, increased de novo lipogenesis, and lipid accumulation. Our results provide insights into the molecular mechanisms by which FOG2S657G may affect the complex molecular landscape underlying MAFLD.

Leveraging Functional Genomics for Understanding Beef Quality Complexities and Breeding Beef Cattle for Improved Meat Quality.

Consumer perception of beef is heavily influenced by overall meat quality, a critical factor in the cattle industry. Genomics has the potential to improve important beef quality traits and identify genetic markers and causal variants associated with these traits through genomic selection (GS) and genome-wide association studies (GWAS) approaches. Transcriptomics, proteomics, and metabolomics provide insights into underlying genetic mechanisms by identifying differentially expressed genes, proteins, and metabolic pathways linked to quality traits, complementing GWAS data. Leveraging these functional genomics techniques can optimize beef cattle breeding for enhanced quality traits to meet high-quality beef demand. This paper provides a comprehensive overview of the current state of applications of omics technologies in uncovering functional variants underlying beef quality complexities. By highlighting the latest findings from GWAS, GS, transcriptomics, proteomics, and metabolomics studies, this work seeks to serve as a valuable resource for fostering a deeper understanding of the complex relationships between genetics, gene expression, protein dynamics, and metabolic pathways in shaping beef quality.

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation.

BACKGROUND: Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases. RESULTS: We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays. CONCLUSIONS: Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

The importance of functional genomics studies in precision rheumatology.

Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.

Exploring the full potential of sperm function with nanotechnology tools.

Sperm quality is essential to guarantee the success of assisted reproduction. However, selecting high-quality sperm and maintaining it during (cryo)preservation for high efficiency remains challenging in livestock reproduction. A comprehensive understanding of sperm biology allows for better assessment of sperm quality, which could replace conventional sperm analyses used today to predict fertility with low accuracy. Omics approaches have revealed numerous biomarkers associated with various sperm phenotypic traits such as quality, survival during storage, freezability, and fertility. At the same time, nanotechnology is emerging as a new biotechnology with high potential for use in preparing sperm intended to improve reproduction in livestock. The unique physicochemical properties of nanoparticles make them exciting tools for targeting (e.g., sperm damage and sexing) and non-targeting bioapplications. Recent advances in sperm biology have led to the discovery of numerous biomarkers, making it possible to target specific subpopulations of spermatozoa within the ejaculate. In this review, we explore potential biomarkers associated with sperm phenotypes and highlight the benefits of combining these biomarkers with nanoparticles to further improve sperm preparation and technology.