Phoenix dactylifera L. is an economically, nutritionally, and culturally important fruit crop in the arid and semi-arid regions of the Middle East and North Africa. Here, we present a gap-free, telomere-to-telomere reference genome of the variety Ajwa, along with 19 additional high-quality assemblies (18 female and 1 male). These assemblies reveal updated, corrected chromosome assemblies validated through cytogenetics, Hi-C and optical mapping. Chromosome numbering was revised based on average lengths across all sequenced genomes. The Sex Determination Region (SDR) was inferred on chromosome 14, spanning approximately 15.2 Mb. Nucleolar organizing regions (NORs) were localized on chromosome 10, where a large 45S rDNA locus displayed unique repeat spacer motifs containing transposon-like sequences. In some accessions, a second NOR was identified on the female sex chromosome. This collection of date palm assemblies, anchored by the Ajwa reference genome, provides a fundamental resource for advancing breeding strategies aimed at enhancing the genetic resilience and productivity of date palm.

Date palm (Phoenix dactylifera L.) is an essential fruit crop in arid and semi-arid regions, where tissue culture is widely used for large-scale clonal propagation. However, this technique often generates somaclonal variants that deviate from original cultivar traits, largely due to epigenetic modifications such as DNA methylation. Here, whole genome bisulfite sequencing (WGBS) was applied to two widely cultivated Qatari cultivars, Khalas and Kheneizi, to compare cytosine methylation profiles between tissue culture-derived plants and offshoot-derived controls. Thousands of differentially methylated regions (DMRs) were identified. Khalas exhibited a predominance of hypomethylated regions, whereas Kheneizi showed slightly more hypermethylated regions. Across both cultivars, CG sites tended to lose methylation, while CHG sites more frequently gained methylation in tissue culture-derived plants. Genes overlapping with DMRs (DMGs) displayed cultivar-specific enrichment patterns. In Khalas, hypermethylated DMGs were mainly linked to nuclear organization, chromatin remodeling, and stress signaling, while hypomethylated genes were associated with defense responses and intercellular communication. In Kheneizi, hypermethylated DMGs were enriched in RNA metabolism, translation, and hormone signaling, whereas hypomethylated DMGs were associated with metabolism, phosphorylation-mediated regulation, and stress responses. KEGG enrichment further revealed shared involvement of RNA degradation, mRNA surveillance, aminoacyl-tRNA biosynthesis, and MAPK signaling pathways. These results demonstrate that tissue culture induces DNA methylation changes in date palm, potentially affecting development and contributing to off-type phenotypes. Understanding these epigenetic alterations provides valuable insights for improving clonal fidelity and optimizing tissue culture propagation in perennial crops.

Given the increased predictions on interactome size and demand for protein function information, methods for detecting protein-protein interactions remain a significant development area. The all-vs.-all sequencing (AVA-Seq) method utilizes a convergent fusion plasmid design to make two-hybrid technology amenable to next-generation sequencing. Here, we further innovate to take advantage of synthetic DNA technologies and Oxford Nanopore Technologies long-read sequencing improvements to allow us to determine full-length protein-protein interactions. We tested 3,115 human protein-protein pairs using this approach and recovered 159 protein-protein interactions from a set of 57 full-length human proteins. Fifteen of the 159 full-length protein-protein interactions matched known human interactions. When referencing a human gold standard set of interactions, eight full-length protein-protein interactions were recovered from an expected 28 interaction pairs (28.6%), a typical recovery rate for two-hybrid technologies. The AVA-Seq method, in combination with the ease of synthetic DNA production and the MinION platform, offers a low-cost, high-throughput alternative for determining protein-protein interactions, which can be utilized in research labs at all stages.

The commercial value of economically significant fruits, including date palm fruit (dates), is influenced by various factors, such as biochemical composition and morphological features like size, shape, and visual appearance, which are key determinants of their quality and market value. Dates are typically consumed at the dry stage (Tamar), during which they exhibit a wide range of physical characteristics, such as color, length, weight, and skin appearance. Understanding the genetic basis of these traits is crucial for improving crop quality and breeding new cultivars. In this study, we integrated a genome dataset from highly diverse date cultivars with phenotypes of dry fruit such as length, width, area, and weight, identifying multiple significant genetic loci (SNPs) associated with these traits. We also identified candidate genes located near the associated SNPs that are involved in biological processes such as cell differentiation, proliferation, growth, and the regulation of signalling pathways for growth regulators like auxin and abscisic acid, as observed in other plants. Gene expression analysis reveals that many of these genes are highly expressed in the early stage of fruit development when the fruit attains its maximum size and weight. These findings will enhance our understanding of genetic determinants of fruit size particularly at the commercially important Tamar stage.

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" (http://comics.metabolomix.com), providing interactive data exploration and hypotheses generation possibilities.

The physical appearance of date palm (Phoenix dactylifera) fruit (dates) is important for its market value. Many date-producing countries experience significant financial losses due to the poor appearance of the fruit, skin separation or puffiness being a major reason. Previous research showed evidence linking the skin separation phenotype to environmental conditions. To investigate this further, a genome-wide association study was conducted using genome data from 199 samples collected from 14 countries. Here, we identified nine genetic loci associated with this phenotype and investigated genes in these regions that may contribute to the phenotype overall. Multiple genes in the associated regions have functional responses to growth regulators and are involved in cell wall development and modification. Analysis of gene expression data shows many are expressed during fruit development. We show that there are both environmental and genetic contributions to the fruit skin separation phenotype. Our results indicate that different date cultivars exhibit varying degrees of skin separation despite genetic similarities or differences. However, genetically different cultivars show extreme differences compared to the phenotype variation between genetically similar cultivars. We demonstrate that beyond environmental factors, genetics is a strong contributor to the most extreme skin separation in some cultivars. Identifying the genetic factors may help better understand the biology and pathways that lead to the environmental effects on skin separation and improve commercial date production. In conclusion, our key finding is that both environmental and genetic factors contribute to skin separation variation, and improvements in environmental factors alone cannot overcome the extreme level of variation observed in some cultivars.

The E3 ubiquitin-ligase UHRF1 is an epigenetic regulator coordinating DNA methylation and histone modifications. However, little is known about how it regulates adipogenesis or metabolism. In this study, we discovered that UHRF1 is a key regulatory factor for adipogenesis, and we identified the altered molecular pathways that UHRF1 targets. Using CRISPR/Cas9-based knockout strategies, we discovered the whole transcriptomic changes upon UHRF1 deletion. Bioinformatics analyses revealed that key adipogenesis regulators such PPAR-γ and C/EBP-α were suppressed, whereas TGF-β signaling and fibrosis markers were upregulated in UHRF1-depleted differentiating adipocytes. Furthermore, UHRF1-depleted cells showed upregulated expression and secretion of TGF-β1, as well as the glycoprotein GPNMB. Treating differentiating preadipocytes with recombinant GPNMB led to an increase in TGF-β protein and secretion levels, which was accompanied by an increase in secretion of fibrosis markers such as MMP13 and a reduction in adipogenic conversion potential. Conversely, UHRF1 overexpression studies in human cells demonstrated downregulated levels of GPNMB and TGF-β, and enhanced adipogenic potential. In conclusion, our data show that UHRF1 positively regulates 3T3-L1 adipogenesis and limits fibrosis by suppressing GPNMB and TGF-β signaling cascade, highlighting the potential relevance of UHRF1 and its targets to the clinical management of obesity and linked metabolic disorders.

Date palm (Phoenix dactylifera) fruit are an economically and culturally significant crop in the Middle East and North Africa. There are hundreds of different commercial cultivars producing dates with distinctive shapes, colors, and sizes. Genetic studies of some Date palm traits have been performed, including for date palm sex-determination, sugar content and fresh fruit colour. In this study, we used genome sequences and image data of 199 dry date fruit (Tamar) samples collected from 14 countries to identify genetic loci associated with the color of this fruit stage. Here, we find loci across multiple linkage groups (LG) associated with dry fruit color phenotype. We recover the previously identified VIR genotype associated with fresh fruit yellow or red color and new associations with the lightness and darkness of dry fruit. This study will add resolution to our understanding of the date palm fruit color phenotype especially at the most commercially important tamar stage.

PDF file - 655K, Supplementary Figure 1. TNRC9 promoted cell proliferation in MDA-MB-231 breast cancer cells. Supplementary Figure 2. shRNA-mediated knockdown of TNRC9. Supplementary Figure 3. H&E staining of tumors (10Magnification) from xenograft nude mice subcutaneously injected with control ZR-75-1cells (upper row I V) were compared with those injected with TNRC9-depeltion ZR-75-1 cells (lower row VI VIII, no palpable tumor in two mice). - represents 400μm. Supplementary Figure 4. Knocking-down TNRC9 sensitizes cancer cells to apoptosis signal. Supplementary Figure 5. BRCA1 and TNRC9 expression in TNRC9 abrogated and control cells. Supplementary Figure 6. The expression profile of TNRC9 knockdown MCF-7 cells. Supplementary Figure 7. In silico analysis of TNRC9 and BRCA1 gene expression among ovarian cancer patients. Supplementary Figure 8. The effects of TNRC9 on luciferase activity driven by BRCA1 promoter. Supplementary Table 1 The list of transcripts significantly altered in TNRC9 knockdown MCF-7 cells comparing to control MCF-7 cells

BACKGROUND:Bardet-Biedl syndrome (BBS) is an autosomal recessive, genetically heterogeneous, pleiotropic disorder caused by variants in genes involved in the function of the primary cilium. We have harnessed genomics to identify BBS and ophthalmic technologies to describe novel features of BBS.CASE PRESENTATION:A patient with an unclear diagnosis of syndromic type 2 diabetes mellitus, another affected sibling and unaffected siblings and parents were sequenced using DNA extracted from saliva samples. Corneal confocal microscopy (CCM) and retinal spectral domain optical coherence tomography (SD-OCT) were used to identify novel ophthalmic features in these patients. The two affected individuals had a homozygous variant in C8orf37 (p.Trp185*). SD-OCT and CCM demonstrated a marked and patchy reduction in the retinal nerve fiber layer thickness and loss of corneal nerve fibers, respectively.CONCLUSION:This report highlights the use of ophthalmic imaging to identify novel retinal and corneal abnormalities that extend the phenotype of BBS in a patient with syndromic type 2 diabetes.

Colon cancer is often driven by mutations of the adenomatous polyposis coli (APC) gene, an essential tumor suppressor gene of the Wnt β-catenin signaling pathway. APC and its cytoplasmic interactions have been well studied. However, various groups have also observed its presence in the nucleus. Identifying novel interactions of APC in the Wnt pathway will provide an opportunity to understand APC’s nuclear role better and ultimately identify potential cancer treatment targets. We used the all-vs-all sequencing (AVA-Seq) method to interrogate the interactome of protein fragments spanning most of the 60 Wnt β-catenin pathway proteins. Using protein fragments identified the interacting regions between the proteins with more resolution than a full-length protein approach. Pull-down assays were used to validate a subset of these interactions. 74 known and 703 novel Wnt β-catenin pathway protein-protein interactions were recovered in this study. There were 8 known and 31 novel APC protein-protein interactions. Novel interactions of APC and nuclear transcription factors TCF7, JUN, FOSL1, and SOX17 were particularly interesting and confirmed in validation assays. Based on our findings of novel interactions between APC and transcription factors and previous evidence of APC localizing to the nucleus, we suggest APC may compete and repress CTNNB1. This would occur through APC binding to the transcription factors (JUN, FOSL1, TCF7) to regulate the Wnt signaling pathway including through enhanced marking of CTNNB1 for degradation in the nucleus by APC binding with SOX17. Additional novel Wnt β-catenin pathway protein-protein interactions from this study could lead researchers to novel drug designs for cancer.

Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio test, Wald; Wald test, LogRank; log-rank test, HR; Hazardous ratio, HR lower; Hazardous ratio lower 95% bound, HR upper; Hazardous ratio upper 95% bound.

Protein-protein interactions (PPIs) are essential in understanding numerous aspects of protein function. Here, we significantly scaled and modified analyses of the recently developed all-vs-all sequencing (AVA-Seq) approach using a gold-standard human protein interaction set (hsPRS-v2) containing 98 proteins. Binary interaction analyses recovered 20 of 47 (43%) binary PPIs from this positive reference set (PRS), comparing favorably with other methods. However, the increase of 20x in the interaction search space for AVA-Seq analysis in this manuscript resulted in numerous changes to the method required for future use in genome-wide interaction studies. We show that standard sequencing analysis methods must be modified to consider the possible recovery of thousands of positives among millions of tested interactions in a single sequencing run. The PRS data were used to optimize data scaling, auto-activator removal, rank interaction features (such as orientation and unique fragment pairs), and statistical cutoffs. Using these modifications to the method, AVA-Seq recovered >500 known and novel PPIs, including interactions between wild-type fragments of tumor protein p53 and minichromosome maintenance complex proteins 2 and 5 (MCM2 and MCM5) that could be of interest in human disease.

In-depth multiomics phenotyping can provide a molecular understanding of complex physiological processes and their pathologies. Here, we report on the application of 18 diverse deep molecular phenotyping (omics-) technologies to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes study QMDiab. We integrated quantitative readouts of 6,304 molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts using between-platform mutual best correlations, within-platform partial correlations, and genome-, epigenome-, transcriptome-, and phenome-wide associations. The achieved molecular network covers over 34,000 statistically significant trait-trait links and illustrates “The Molecular Human”. We describe the variances explained by each omics layer in the phenotypes age, sex, BMI, and diabetes state, platform complementarity, and the inherent correlation structures of multiomics. Finally, we discuss biological aspects of the networks relevant to the molecular basis of complex disorders. We developed a web-based interface to “The Molecular Human”, which is freely accessible at http://comics.metabolomix.com and allows dynamic interaction with the data.

Additional file 7: Table S7. Summary of immune cell changes and differentially methylated CpGs between recovered and dead patients over four time points 7A. Immune cell changes between recovered and dead patients over four time points, 7B. Differential methylation of CpGs between recovered and died patients over four time points. The b_0, b_1, b_2, and b_3 coefficients correspond to the reference model parameters, where survival phenotype is used as a reference. The d_0, d_1, d_2, d_3 coefficients represent the differences between the reference model and the model parameters in the compared group (died). AveExprs refers to the average log2-expression for an individual immune cell proportion or CpG. The F column contains moderate F-statistics, P-value -raw p-value, and adj.P.Valu- Benjamini-Hochberg adjusted p-value. Other column variables are described in Supplemental table 2B.

Background COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS. Methods We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A multivariate cox proportional risk regression analysis was conducted to identify predictive signatures according to survival. Results The comparison of COVID-19 to controls at inclusion revealed the presence of a 14.4% difference in promoter-associated CpGs in genes that control immune-related pathways such as interferon-gamma and interferon-alpha responses. On day 60, 24% of patients died. The inter-comparison of baseline DNA methylation to the last recorded time point in both COVID-19 groups or the intra-comparison between inclusion and the end of follow-up in every group showed that most changes occurred as the disease progressed, mainly in the AIM gene, which is associated with an intensified immune response in those who recovered. The multivariate Cox proportional risk regression analysis showed that higher methylation of the “Apoptotic execution Pathway” genes (ROC1, ZNF789, and H1F0) at inclusion increases mortality risk by over twofold. Conclusion We observed an epigenetic signature of immune-related genes in COVID-19 patients with ARDS. Further, Hypermethylation of the apoptotic execution pathway genes predicts the outcome. Trial registration : IMRPOVIE study, NCT04473131.

The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.

Background Mutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort. Methods We carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line. Results We identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells. Conclusion We show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.

Objective Identify protein contact points between TP53 and minichromosome maintenance (MCM) complex proteins 2, 3, and 5 with high resolution allowing for potential novel Cancer drug design. Methods A next-generation sequencing-based protein-protein interaction method developed in our laboratory called AVA-Seq was applied to a gold-standard human protein interaction set. Proteins including TP53, MCM2, MCM3, MCM5, HSP90AA1, PCNA, NOD1, and others were sheared and ligated into the AVA-Seq system. Protein-protein interactions were then identified in both mild and stringent selective conditions. Results Known interactions among MCM2, MCM3, and MCM5 were identified with the AVA-Seq system. The interacting regions detected between these three proteins overlap with the structural data of the MCM complex, and novel domains were identified with high resolution determined by multiple overlapping fragments. Fragments of wild type TP53 were shown to interact with MCM2, MCM3, and MCM5, and details on the location of the interactions were provided. Finally, a mini-network of known and novel cancer protein interactions was provided, which could have implications for fundamental changes in multiple cancers. Conclusion We provide a high-resolution mini-interactome that could direct novel drug targets and implicate possible effects of specific cancer mutations.

Protein–protein interactions (PPIs) are essential in understanding numerous aspects of protein function. Here, we significantly scaled and modified analyses of the recently developed all-vs-all sequencing (AVA-Seq) approach using a gold-standard human protein interaction set (hsPRS-v2) containing 98 proteins. Binary interaction analyses recovered 20 of 47 (43%) binary PPIs from this positive reference set (PRS), comparing favorably with other methods. However, the increase of 20× in the interaction search space for AVA-Seq analysis in this manuscript resulted in numerous changes to the method required for future use in genome-wide interaction studies. We show that standard sequencing analysis methods must be modified to consider the possible recovery of thousands of positives among millions of tested interactions in a single sequencing run. The PRS data were used to optimize data scaling, auto-activator removal, rank interaction features (such as orientation and unique fragment pairs), and statistical cutoffs. Using these modifications to the method, AVA-Seq recovered >500 known and novel PPIs, including interactions between wild-type fragments of tumor protein p53 and minichromosome maintenance complex proteins 2 and 5 (MCM2 and MCM5) that could be of interest in human disease.