BMC Genomic Data

Variant intolerance methods score the essentiality of genes based on large datasets of genetic variants and have been used in population genomics of humans and model organisms. In this paper, we estimated Residual Variation Intolerance Scores for protein-coding genes and predicted protein domains in cattle. In agreement with results from other species, the most variant-tolerant genes and domains included genes related to olfaction and adaptive immunity, whereas the least-variant tolerant genes and domains included genes involved in fundamental cellular processes. There was a moderate positive correlation with estimates from orthologous human genes. We provide estimates of variant intolerance for cattle may be useful for genomic analyses of deleterious variants and population genomics in cattle.

Chromatin profiling methods, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), are used to characterize the genomic localization of DNA-associated proteins. While ChIP and ChIP-seq have been used for decades, an orthogonal approach, CUT&Tag (Cleavage Under Targets and Tagmentation), is gaining popularity as an efficient and cost-effective alternative. Although previous comparative studies note discrepancies in signal-to-noise ratios and detection bias at certain genomic regions, many differences between ChIP-seq and CUT&Tag results remain largely unreconciled. Here, we systematically investigate the disagreeing signals captured by these two methods across well annotated genomic regions. We assess multiple histone mark profiles generated by different groups in two cell lines (K562 and MCF-7). Overall, our analysis indicates that compared to ChIP-seq, CUT&Tag may have limited sensitivity in low-GC environments and, as previously observed, increased signal in hyper-accessible chromatin. Notably, within GC-poor regions of active gene bodies and Polycomb-repressed domains, CUT&Tag exhibits a loss of H3K36me3 and H3K27me3 signal, respectively, where occupancy of these histone marks is otherwise expected. Further, active promoters with discrepant H3K4me3 and H3K27ac signal between the two assays differ systematically in GC content and chromatin accessibility. Promoters differentially enriched for CUT&Tag signal relative to ChIP-seq generally show higher, broader GC-content profiles and higher DNase-seq and ATAC-seq signal, while promoters enriched for ChIP-seq signal harbor the opposite characteristics. A local bias for high GC content and/or chromatin accessibility in CUT&Tag may also explain its differing signal patterns at nucleosome-depleted regions (NDRs) compared to ChIP-seq and MNase-seq promoter profiles. Altogether, our results highlight that studies focused on profiling the intensity and structure of histone modification occupancy can be sensitive to potential biases of CUT&Tag to GC content and chromatin accessibility. These characteristics should be accounted for when selecting a chromatin profiling approach, analyzing and interpreting data as well as drawing biological conclusions.

Chromosomes in Drosophila melanogaster are organized into distinct topologically associated domains delimited by boundaries bound by insulator proteins. The insulator protein BEAF (Boundary Element-Associated Factor of 32kDa) plays roles in both chromatin organization and transcriptional regulation, yet its precise molecular mechanisms remain elusive. To examine the role of BEAF in insulator function we used yeast 2-hybrid assays, pull-down assays with bacterially expressed proteins, and bimolecular fluorescence complementation assays in S2 cells to characterize interactions between BEAF and three co-insulator proteins: CP190, Pzg, and Chro. Our studies pinpoint minimal regions of CP190, Pzg, and Chro that directly interact with BEAF, as well as parts of BEAF that are crucial for its interactions with these co-insulator proteins. Functional analyses in transfected S2 cells revealed distinct regulatory roles for BEAF in association with CP190, Pzg, and Chro. CP190 showed a weak interaction with BEAF, and CP190 bound 2.3 kb upstream of promoter-proximal BEAF could not loop out the intervening DNA to effectively communicate with BEAF for luciferase reporter gene activation. In contrast, more robust interactions were observed between BEAF and both Pzg and Chro. Both could also effectively interact with BEAF from a distance to activate the reporter gene. It is likely that the role of CP190 in long-range insulator interactions is mediated by insulator proteins other than BEAF, although BEAF could help stabilize interactions. On the other hand, we propose that BEAF can directly collaborate with Pzg and Chro to mediate long-range chromatin interactions.

It is widely assumed that SOX2 regulates gene expression and facilitates the opening of chromatin by binding directly at SOX motifs. To test this assumption, we created a SOX2 DNA binding mutant to determine whether other regions of SOX2 contribute to gene target specificity. When exogenously expressed in cells, this SOX2 mutant [SOX2(G76P)], like elevated unmodified SOX2, dramatically alters the transcriptome, but it does so by regulating vastly different gene sets and gene networks than SOX2. Consistent with their differential effects on the transcriptome, ChIP-seq analysis demonstrates that SOX2 and SOX2(G76P) associate primarily with different genomic loci, and motif analysis indicates that SOX2 binds primarily at SOX motifs, whereas SOX2(G76P) associates with chromatin at non-SOX motifs, including AP-1 motifs. Additionally, ATAC-seq analysis indicates that SOX2 substantially increases chromatin accessibility, but SOX2(G76P) does not. The findings presented lead to the conclusion that SOX2(G76P) associates with chromatin indirectly by a "piggyback" mechanism through its association with other chromatin-associated proteins, including AP-1 complexes. Remarkably, we also show that SOX2 and SOX2(G76P) each associate with a subset of the same gene loci that contain several different DNA motifs, including AP-1 motifs, but no high confidence SOX motifs. Overall, our findings provide new perspectives on SOX2 and lead to two important conclusions: 1) selection of gene targets by SOX2 is not solely determined by its DNA binding domain, and 2) SOX2 not only associates with chromatin directly by binding to SOX motifs but can also associate with a subset of gene loci indirectly through its association with other chromatin-associated proteins.

Numerous genome-wide association studies in rice have identified loci associated with diverse agronomic traits. However, interpreting the regulatory and functional significance of these loci remains challenging because each locus often contains multiple variants in linkage disequilibrium, many of which lie in non-coding regions. Here, we present a method for prioritizing non-coding variants within an associated locus by integrating chromatin feature information predicted by a pretrained DNA language model fine-tuned on rice ChIP-seq and ATAC-seq datasets. We demonstrate the utility of our method through three case studies. In a post-GWAS analysis of heat tolerance, prioritized variants overlapped promoters of candidate genes previously identified through integrated GWAS and transcriptomic analyses, providing independent support for their potential regulatory roles. For the high-yield gene DEP1, promoter variant prioritization combined with in silico saturation mutagenesis identified a localized regulatory region enriched for high-impact mutations overlapping predicted transcription factor binding sites. For the drought-associated gene OsHAK1, the highest-ranked variant was predicted to be associated with chromatin features in a manner consistent with the reported co-occurrence of H2Bub with H3K4 methylation marks in plants. Overall, these results demonstrate the utility of our method for functionally informative prioritization of non-coding variants, facilitating the interpretation of GWAS loci and the identification of candidate regulatory variants in rice.

Language genes can be tentatively considered as a subset of cognitive genes, although they are often discussed separately. During the evolution of SNVs (single nucleotide variations) in cognition-related genes, do language genes and cognitive genes exhibit significantly different intensities of change at several key evolutionary moments--namely, the inflection points or derivative peak positions of similarity curves drawn from multi-SNV locus bases across samples? In this study, nine distance/similarity metrics (Bray-Curtis, Cosine, Pearson, Spearman, Hamming, Jaccard, Matching, Kulczynski, and Gower) were employed to analyze 413 samples from 11 taxonomic groups, targeting SNV loci in language/cognition-related genes (13,415 effective loci, approximately 400 loci per gene), with pp6 (Homo_sapiens.GRCh38) as the reference. For each method, sample similarities (defined as 1/(1+distance)) were independently sorted in ascending order to generate raw similarity scatterplots. Due to the large sample size and representativeness, the scatter density on the similarity curves was high, and no smoothing was applied. Derivative values were calculated from adjacent similarity differences to identify peaks of evolutionary rate change (top 10 peaks per method). Combined with functional annotations of 33 language/cognition-related genes, we quantified the difference scores and occurrence frequencies of the two gene categories at the peak positions. The results indicate that cognitive-related genes exhibit slightly higher occurrence frequencies in peak windows and higher average difference scores per gene than language genes. Comparative analysis of SNVs at the peak samples and their left-side windows revealed that at positions 381-382, all nine methods shared three intersecting mutation loci, involving language genes (NFXL1, SRGAP2, SRGAP2C); at positions 355-356, there was one intersecting mutation locus, involving a language gene (SRGAP2). This suggests that certain mutations in language genes may have played a distinctive role at critical junctures in the evolution of cognitive abilities.

This study aims to quantify the genetic similarity of different species (from fish to humans) to the human reference genome (pp6, Homo sapiens.GRCh38) based on the allele presence/absence patterns of 33 language/cognition related gene SNV loci, identify key breakpoints during evolution, and evaluate the enrichment of language and cognition genes at these breakpoints. We designed a similarity calculation method relying on binary features (four columns for A/T/C/G), adopted five difference/distance measures (Sorensen, Rogers, Nei, Reynolds, and Hellinger), and converted them into similarity values (1/(1+distance)). For each method, samples were independently ranked, the first derivative of similarity was computed, and the top 12 peaks were selected as candidate breakpoints. Results show that the similarity curves from the five methods are highly consistent (correlation coefficients >0.9), with major peaks concentrated at positions 355, 363, 381, 382, 390, 400, etc., where the corresponding samples are predominantly ancient hominins and primates. Furthermore, we defined 13 peak groups (starting positions 355-401). For each peak within a group, pairwise SNV differences between the peak apex sample and its immediate left neighbor were compared, and the intersection F_INTERSECTION (shared differential loci) was obtained. For each F_INTERSECTION, we calculated the proportions of language genes and cognition genes. In addition, we computed the differential sets between adjacent groups' F_INTERSECTION to trace the gradual emergence of new loci. In F_INTERSECTION, language genes accounted for an average of 59.5%, and cognition genes for an average of 62.9%. The proportion of language genes reached a peak at position 383 (61.2%), while cognition genes peaked at position 386 (64.9%). High frequency peak samples include c25, c27, and ja2, suggesting that language cognition genes may have undergone independent intensification during Eurasian evolution. Differential analysis between adjacent F_INTERSECTION revealed a stepwise acquisition of new loci from position 355 to 401, with three bursts of newly added loci along the entire evolutionary axis. This study provides a quantitative framework based on similarity curves, offers a novel molecular perspective for understanding the evolution of language and cognitive abilities, and highlights the potential importance of East Asian archaic hominins in the evolution of language cognition genes.

Human metabolism converts inorganic arsenic to the pentavalent methylated species MMA(V) and DMA(V), the forms most people excrete, and the forms long read as the end of a detoxification pathway. Whether a transporter sets how much of these metabolites reaches the genome has not been tested in a mammalian cell. We expressed human AQP3, AQP7, AQP9 or AQP10 in HEK293T and MRC5-SV40 cells and measured gamma-H2AX by flow cytometry across dose series of As(V), MMA(V) and DMA(V), pairing every aquaporin with a GFP-Tubulin control and an untransfected mock acquired in the same replicate. As(V) was inactive in HEK293T cells and only weakly active in MRC5-SV40 cells to 20 micromolar, and both methylated species damaged DNA only in the millimolar range, DMA(V) being the more potent of the two in both cell lines. Against that weak baseline, AQP9 and AQP10 raised DMA(V)-induced gamma-H2AX in HEK293T cells by roughly 17 percentage points over the matched control, more than doubling the damage the same exposure produced in control cells, whereas AQP3 and AQP7 changed it not at all. AQP9 alone remained active with MMA(V). The ranking held in MRC5-SV40 fibroblasts at one-sixth the size, and within single wells the damage rose with the amount of AQP9 a cell carried while the control was flat. Aquaglyceroporins therefore discriminate among arsenic species, and AQP9 and AQP10 turn a weakly genotoxic metabolite into a substantially more genotoxic one.

A population-specific missense variant, rs373863828 (G > A, p.Arg457Gln), has been identified in Pacific Islanders and is associated with increased body mass index and lower odds of type 2 diabetes. However, the mechanism underlying these associations is unknown. The variant is located in exon 5 of CREBRF, a gene which is rapidly upregulated in response to nutrient deprivation. This study aimed to assess the effect of rs373863828 on gene expression in adipose tissue from Samoan adults from the Soifua Manuia (''Good Health'') study. Needle subcutaneous adipose (upper buttock) biopsies were obtained in Apia, Samoa, from fasting Samoans without diabetes. RNA isolated from adipose tissue (n=91, 65.9% female) was subjected to bulk paired-end mRNA-sequencing (2x150 base pair). Differential gene expression among the three rs373863828 genotypes (GG, AG, AA) was assessed using a likelihood-ratio test implemented in DESeq2, and overrepresentation analysis for significant differentially expressed genes (DEGs) (padj < 0.1) was performed with clusterProfiler and oRG.DB. Bulk expression was deconvoluted to determine the cell type composition of the adipose tissue. Twenty-two DEGs were associated with rs373863828 genotype including CBX7 (padj=0.026 ) and SELENOM (padj= 0.004), both of which have roles in adipogenesis and metabolism. A single expression profile comprising 13 of the 22 DEGs corresponding to CREBRF genotype was identified, and overrepresentation analysis supported this finding, with terms such as ''keratinocyte differentiation'' and ''skin development'' enriched among significant DEGs. However, PERMANOVA of adipose cell type proportions showed no difference (p > 0.05) among the three genotypes. rs373863828 genotype was associated with expression of 22 genes in whole subcutaneous adipose tissue of this sample of fasting Samoan adults without diabetes. Future work should assess cell- and tissue-specific rs373863828 genotype effects using a combination of single-cell approaches and human cell models with perturbations associated with nutritional stress.

Toxicants in the environment can significantly impact physiology. Environmental chemical exposures during early developmental stages disturb normal embryonic development and programming, and dramatically impact long-term health as individuals age. Female and male animals show distinct phenotypes when responding to a given chemical exposure. Here, through the TaRGET II (Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription) consortium, we systematically explored sex-specific transcriptomic and epigenomic alterations in response to various toxicants, including arsenic (As), lead (Pb), tributyltin (TBT), bisphenol A (BPA), di(2-ethylhexyl) phthalate (DEHP), dioxin (TCDD), and fine particulate matter (PM2.5), across three time points in mice exposed two weeks prior to conception through gestation and lactation. After being exposed to toxicants during the embryonic and early postnatal developmental stages, 1,025 omics datasets were generated from the liver and analyzed across three mouse life stages. We discovered a significant sex-biased molecular response to distinct exposures in the liver at both the transcriptomic and epigenetic levels, showing dynamic changes across mouse development and aging. The perturbed pathways and transcription factors in response to different chemical exposures in both sexes were further evaluated to measure the sex-specific impact of each toxic exposure in the liver. Overall, this study presents the most detailed investigation of sex-specific molecular signatures under the influence of developmental exposures to toxic substances.

Wildfire smoke is an escalating global public health threat exposing millions of people, including children, to hazardous air pollution each year. Although wildfire smoke toxicants have been linked to a range of adverse health outcomes, including immune dysregulation, the long-term consequences of real-world pediatric wildfire smoke exposure on health and development remain largely unknown. To investigate the persistent effects of early-life exposure on immune health, here we leveraged a cohort of rhesus macaques that experienced nine consecutive days of hazardous wildfire smoke exposure in infancy during the 2020 Oregon Labor Day wildfires. By integrating ex vivo immune stimulations, multiplex cytokine profiling, single-cell transcriptomics, and genome-wide DNA methylation profiling, we identified persistent immunological consequences across molecular and functional levels. We found that a single severe postnatal exposure, in the first three months of life, was associated with persistent change in the innate immune response, including reduced pro-inflammatory cytokine response to a bacterial endotoxin, with subtle but consistent transcriptional changes in myeloid cells, particularly among males. Wildfire smoke exposure was also associated with changes in proportion of B and T/NK cells, and within the T/NK cell compartment, exposed animals exhibited an expansion of cytotoxic cells. Consistent with this, CD8+ T cells displayed extensive transcriptional remodeling and shifted toward more differentiated effector states, with the greatest differentiation observed in animals exposed at the youngest ages. Genome-wide DNA methylation profiling identified smoke-associated methylation changes consistent with acceleration of epigenetic aging, as well as persistent epigenetic alterations impacting genes involved in oxidative stress responses, innate immunity, T cell differentiation, and hematopoiesis. These findings demonstrate that a single severe wildfire smoke exposure during a critical developmental window is associated with extensive immune and epigenetic remodeling that persist years after exposure, providing new insight into the long-term biological consequences of early-life wildfire smoke exposure.

Chronic exposure to inorganic arsenic affects more than 200 million people, and disease outcome varies widely among individuals with comparable intake. Explanations have centered on arsenic metabolism, which acts on arsenite that is already inside the cell. Uptake sits upstream of metabolism and sets how much arsenite reaches the genome, yet whether it acts as a gene-by-environment modifier of genotoxicity has been asserted far more often than it has been measured. We expressed human aquaporin-3 (AQP3), its point mutants and the paralogues AQP7, AQP9 and AQP10 in three human cell lines, and measured DNA damage as {gamma}H2AX by flow cytometry against a damage threshold re-derived from mock-transfected cells in every experiment. In lung fibroblasts, AQP3 raised the {gamma}H2AX-high fraction 2.36-fold at 5 M arsenite. Because a gene-by-environment interaction widens the genotype gap with dose while an independent genotoxin would not, the combination exceeds what the two factors would produce if they simply added by 6.36 percentage points, which is an interaction. The response required the AQP3 sequence, was suppressed by N-acetylcysteine in proportion to arsenite dose, was absent in RKO cells, and was shared with AQP9 and AQP10, which created an arsenite dose-response in a cell line that had none of its own. Low-input RNA sequencing of 135 ten-cell pools located the effect inside the cell: at an identical 1 M applied dose and within a single batch, AQP3 raised HMOX1 (induced when trivalent arsenic modifies KEAP1 thiols, and so a report of intracellular rather than applied exposure) 3.3-fold, a shift equivalent to 40% of the 1-to-10 M interval on the measured dose-response, while AQP3 without arsenite was indistinguishable from untreated. Duplex sequencing detected no consistent change in somatic mutation frequency from arsenite alone at any dose to 10 M, in an assay that resolved a 26-fold response to N-ethyl-N-nitrosourea; the arsenite-induced mutation frequency at the EGFR locus nonetheless differed 1.61-fold by AQP3 genotype. The interaction is therefore not unique to AQP3, and aquaglyceroporin complement belongs alongside metabolism among the host factors that set arsenic susceptibility.

Background Genome-wide association studies have identified >200 loci associated with IBD, yet the causal gene for most remains unknown. As multiple epithelial functions have been linked with susceptibility to IBD, there is a need to prioritize candidate causal genes for functional studies in this cellular context. Methods Using a standardized definition of regions implicated by index SNPs from three GWAS studies, we categorized regions as containing: (1) a known casual gene, (2) a single gene or (3) multiple genes. We then developed an IBD Priority Score to rank genes based on genetic, genomic and functional data. We next developed and applied an Epithelial Priority Score, based on expression patterns and quantitative traits, to prioritize genes for functional validation in epithelial models. Two candidate genes identified through this approach were tested for their impact on viral response pathways in HT-29 cells. Results The IBD Priority Score prioritized a single gene in 71 of the 104 regions containing multiple genes. The Epithelial Priority Score identified 31 epithelial candidates. Functional studies demonstrated that IRF6 enhanced, whereas IRF8 suppressed, antiviral responses in intestinal epithelial cells stimulated with Poly(I:C). Conclusions Combining multiple genetic, genomic, and functional data is a useful approach for prioritizing the most likely causal gene within IBD GWAS loci, and for prioritizing functional validation studies in epithelial cells and tissues. Moreover, we provide functional evidence for two IBD genes playing a role in the regulation of anti-viral responses in intestinal epithelial cells.

Inorganic arsenic (iAs) exposure is linked to impaired glucose homeostasis and type 2 diabetes, yet the magnitude and direction of reported effects vary substantially across studies and populations. The gut microbiome is both a target and a mediator of arsenic toxicity, suggesting that pre-exposure community composition may modulate the development of metabolic dysfunction. To test this, we conducted parallel 50 ppm iAs drinking-water exposures in male C57BL/6J mice at two animal facilities. Results were compared across facilities for metabolic phenotypes, hepatic arsenic levels, targeted and untargeted metabolomics, and shotgun metagenomics. Hepatic arsenic confirmed comparable exposure at both sites; however, the housing facility explained more variance than the iAs treatment group across every data layer. Baseline microbial communities and metabolic phenotypes at each institution differed, and this difference propagated into the iAs treatment effect. Critically, iAs exposure impaired glucose clearance at one site while trending toward improvement at the other. Facility explained 19 to 26% of variance in microbiome, bile acid, polar, and untargeted metabolite ordinations, while iAs treatment did not reach significance. A random forest classifier identified the facility with 96% cross-validated accuracy from 22 microbial species, whereas treatment classification did not exceed 67% accuracy. Functional metagenomic analyses revealed nearly 11,733 (63%) of genes were differentially abundant between facilities compared 139 with iAs treatment. Our results indicate that identical genetics and exposure may produce differential metabolic outcomes on different microbial backgrounds. Characterizing the baseline microbiome and metabolome is therefore critical both for identifying which individuals are most susceptible to the metabolic effects of arsenic exposure and for potentially reducing the risk of exposure through modulation of the gut microbiome.

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with the potential to disrupt metabolic processes and contribute to carcinogenesis; however, molecular evidence linking alternative and emerging PFAS to ovarian cancer (OC) remains limited. We conducted a biomarker-based case-control study integrating exposureomics with multi-omics profiling. Plasma samples from 128 patients with OC and 128 controls were analyzed for 26 PFAS, untargeted metabolomics, lipidomics, and clinical phenotypes, while urine samples from an additional 100 patients and 100 controls underwent untargeted metabolomic and clinical profiling. Single-compound, burden-based, and mixture models were integrated with PFAS-omics association scans, cross-matrix metabolite prioritization, observational exposure-omics-clinical association-chain analyses, and repeated internal cross-validation. Higher PFAS burdens were consistently associated with OC case status, and DONA, GenX, PFNA, PFPeS, PFUdA, and PFTrDA constituted an OC-prioritized six-PFAS mixture. DONA and GenX exhibited the broadest lipid-related bridging signals, particularly across phospholipids, lysophospholipids, sphingolipids, neutral lipids, and acylcarnitines. Integrated plasma and urine analyses further identified five shared metabolites-elaidic acid, hippuric acid, betaine, corticosterone, and taurocholic acid-that provided incremental and complementary discrimination beyond reference models based on clinical variables and tumor markers in internal cross-validation. Collectively, these findings demonstrate that both alternative and emerging PFAS are associated with a distinct OC-related molecular phenotype involving coordinated lipidomic, metabolomic, and hematologic alterations, while highlighting DONA and GenX as the most prominent exposure-related signals.

Transactive response DNA-binding protein 43 (TDP-43) aggregation and loss of function are hallmark features of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) among other neurodegenerative diseases. Despite epidemiological evidence linking environmental exposures to neurodegeneration, few toxicants have been directly associated with neurodegeneration. Here, we performed a high-content imaging screen, using a library of over a thousand chemical compounds that are considered high risk for human exposure and identified 21 toxicants that drive TDP-43 aggregation. Among the top chemical hits, five belonged to the dithiocarbamate (DTC) class of thiol-reactive compounds including the agricultural pesticides thiram and ziram. Thiram directly promoted TDP-43 cysteine oxidation and intermolecular crosslinking, whereas ziram induced TDP-43 aggregation via zinc imbalance and enhanced oxidative stress, suggesting DTCs disrupt redox homeostasis. In primary neurons and human iPSC-derived neurons, DTCs led to TDP-43 aggregation and prominent splicing defects consistent with loss of TDP-43 function. In exposed zebrafish, DTCs impaired TDP-43 function and triggered widespread transcriptional changes reflected by perturbed stress response and metabolic signatures. By combining TDP-43 loss of function mutations with chemical exposures, we observed accelerated TDP-43 loss of function and chemical-induced aggregation, supporting a multiple hit mechanism driving TDP-43 dysfunction. Together, these findings identify DTCs, particularly those used as agricultural pesticides, as dominant modifiers of TDP-43 proteostasis and identify redox imbalance and zinc homeostasis as a central molecular mechanism linking toxicant exposure to TDP-43 proteinopathy.

Trisomy 21 (T21) is the most common genetic cause of intellectual disability, yet the molecular mechanisms underlying maternal meiosis I errors--responsible for ~70% of free T21 cases--remain poorly understood. In this preliminary study, we used long-read sequencing and genome assembly to investigate the DNA sequence and epigenetic features of chromosome 21 (chr21) centromeres in a family with recurrent free T21 due to maternal meiosis I errors. The mother, who had two affected and three unaffected children, showed no mosaicism or structural rearrangements. One of her two chr21 centromeres lacked a pronounced centromere dip region (CDR), displaying instead a diffuse hypomethylation pattern (dCDR) with much higher methylated CpG levels (55%) compared to its homologue (36%). This dCDR was transmitted to an unaffected child and the affected proband analyzed, suggesting it was present in one of the maternal chr21 since she was at least 32 years of age. Chr21 dCDRs were not observed in seven young mothers with children with T21 or previously described in the literature in 108 population haplotypes. We hypothesize that dCDRs may weaken kinetochore function, increasing nondisjunction risk, and propose two models linking such epigenetic variation to maternal age-related T21 risk. These findings highlight the value of complete centromere characterization in families with children with T21 and suggest centromere methylation status of chr21 as a potential T21 risk factor for future investigation.

Fetal development is highly sensitive to environmental influences, including maternal smoking during pregnancy (MSDP) and air pollution. The placenta may play a central role in mediating these effects through epigenetic mechanisms, including small non-coding RNAs (sncRNAs). While most studies have focused on microRNAs (miRNAs), other sncRNA classes remain poorly characterized. Here, we characterized the placental sncRNA landscape and investigated its associations with prenatal exposure to MSDP and air pollution. The sncRNA expression profile of 390 chorionic villi samples from the Barcelona Life Study Cohort (BiSC) was measured using small RNA sequencing and the seqBuster/seqCluster pipeline. MSDP was assessed via questionnaire, and prenatal exposure to black carbon (BC), particulate matter [&le;]2.5 m (PM2.5), and nitrogen dioxide (NO2) was estimated using hybrid dispersion-land-use regression (LUR) spatiotemporal models. Associations were evaluated using linear regressions adjusted for relevant covariates. We identified 979 placental sncRNA clusters, assigned primarily to miRNAs (33.2%), piRNAs (26.4%), snoRNAs (12.2%), tRFs (7.8%), and others (20.4%). MSDP was associated with the downregulation of miR-421 and the upregulation of multiple snoRNAs from the imprinted DLK1-DIO3 locus (SNORD113-4, SNORD114-2, SNORD114-3, and SNORD114-17), as well as the piR-26394. No sncRNAs remained significantly associated with air pollution after multiple-testing correction, although several miRNAs showed suggestive associations. Overall, this study provides a comprehensive characterization of placental sncRNAs and identifies previously unreported smoking-associated sncRNAs within the imprinted DLK1-DIO3 locus, expanding our understanding of placental epigenetic responses to prenatal environmental exposures.

Vertical transmission of SARS-CoV-2 is controversial. Owing to the low expression of ACE2 along with TMPRSS2 in placenta, role of secondary receptors becomes significant. In our study we predicted twelve interactors of spike protein expressed in placenta through interactome analysis followed by docking and molecular dynamic simulation. Three interactors of SARS-CoV-2 spike protein were found to be CD147, EGFR and LDLR. Expression at transcriptomic and translational level by real-time PCR and immunohistochemistry respectively was observed in placenta samples obtained from women with COVID exposure risk and compared to control. Elevated protein levels of CD147 (OR=14.667), ACE2 (OR=8.25) and LDLR (OR=1.9) was associated with higher exposure risk. However, the variation in mRNA expression was not statistically significant. Computational study showed that CD147/basigin, EGFR and LDLR stably interact with spike protein outside its primary receptor binding domain. In-vitro binding assay confirmed the physical interaction between spike protein and the placental receptors. In-silico site-directed mutagenesis further identified key potential binding hotspots of spike protein- Tyr28 and Trp64 for CD147, Phe643, Val642, Thr632 for LDLR and Leu8, Phe59, Phe32, Tyr28, Trp64, Trwp152, His245, and Val213 for EGFR. Finally, concluded that CD147, EGFR and LDLR might act as secondary non-canonical cofactors for SARS-CoV-2 spike protein in placenta, thereby increasing its susceptibility and tissue tropism. The study overall gives a better insight into potential placental suscpetibility providing targeted therapeutic opportunities.

BackgroundThe variants G1 and G2 within the APOL1 gene confer a higher risk of APOL1-mediated kidney disease (AMKD) whilst associated with an evolutionary advantage against trypanosome-mediated sleeping sickness. MethodsIn this study, we analysed transcriptome data of kidney biopsies from FSGS patients with the APOL1 high-risk (HR) and low-risk (LR) variants and compared it to cellular models based on patient-specific podocytes, HEK cells with engineered over-expressing HR variants and HR variant single-cell-RNA-seq data from kidney organoids. ResultsWe identified a signature of up- and down-regulated genes between biopsies from FSGS patients with APOL1 HR and LR variants. The up-regulated genes are functionally annotated to be associated with Calcium and mTOR signaling, whilst the down-regulated genes with inflammatory and immune response pathways. These pathways were confirmed by comparing with cellular models. Analysis of small molecules reverting the IFN-{gamma} stimulated gene expression to the non-stimulated gene expression in genome-edited APOL-G1 kidney organoids revealed several putative candidates such as the mTOR inhibitor AZD-2014. ConclusionWe have unveiled a signature of up- and down-regulated genes between APOL1 HR and LR kidney biopsies which could be assigned as associated with Calcium and mTOR signaling and down-regulated immune response.