The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Data Sanitization to Reduce Private Information Leakage from Functional Genomics.

The generation of functional genomics datasets is surging, because they provide insight into gene regulation and organismal phenotypes (e.g., genes upregulated in cancer). The intent behind functional genomics experiments is not necessarily to study genetic variants, yet they pose privacy concerns due to their use of next-generation sequencing. Moreover, there is a great incentive to broadly share raw reads for better statistical power and general research reproducibility. Thus, we need new modes of sharing beyond traditional controlled-access models. Here, we develop a data-sanitization procedure allowing raw functional genomics reads to be shared while minimizing privacy leakage, enabling principled privacy-utility trade-offs. Our protocol works with traditional Illumina-based assays and newer technologies such as 10x single-cell RNA sequencing. It involves quantifying the privacy leakage in reads by statistically linking study participants to known individuals. We carried out these linkages using data from highly accurate reference genomes and more realistic environmental samples.

Recurrent repeat expansions in human cancer genomes.

Expansion of a single repetitive DNA sequence, termed a tandem repeat (TR), is known to cause more than 50 diseases1,2. However, repeat expansions are often not explored beyond neurological and neurodegenerative disorders. In some cancers, mutations accumulate in short tracts of TRs, a phenomenon termed microsatellite instability; however, larger repeat expansions have not been systematically analysed in cancer3-8. Here we identified TR expansions in 2,622 cancer genomes spanning 29 cancer types. In seven cancer types, we found 160 recurrent repeat expansions (rREs), most of which (155/160) were subtype specific. We found that rREs were non-uniformly distributed in the genome with enrichment near candidate cis-regulatory elements, suggesting a potential role in gene regulation. One rRE, a GAAA-repeat expansion, located near a regulatory element in the first intron of UGT2B7 was detected in 34% of renal cell carcinoma samples and was validated by long-read DNA sequencing. Moreover, in preliminary experiments, treating cells that harbour this rRE with a GAAA-targeting molecule led to a dose-dependent decrease in cell proliferation. Overall, our results suggest that rREs may be an important but unexplored source of genetic variation in human cancer, and we provide a comprehensive catalogue for further study.

Functional genomics data: privacy risk assessment and technological mitigation.

The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.

Assessing and mitigating privacy risks of sparse, noisy genotypes by local alignment to haplotype databases.

Single nucleotide polymorphisms (SNPs) from omics data create a reidentification risk for individuals and their relatives. Although the ability of thousands of SNPs (especially rare ones) to identify individuals has been repeatedly shown, the availability of small sets of noisy genotypes, from environmental DNA samples or functional genomics data, motivated us to quantify their informativeness. We present a computational tool suite, termed Privacy Leakage by Inference across Genotypic HMM Trajectories (PLIGHT), using population-genetics-based hidden Markov models (HMMs) of recombination and mutation to find piecewise alignment of small, noisy SNP sets to reference haplotype databases. We explore cases in which query individuals are either known to be in the database, or not, and consider several genotype queries, including those from environmental sample swabs from known individuals and from simulated "mosaics" (two-individual composites). Using PLIGHT on a database with ∼5000 haplotypes, we find for common, noise-free SNPs that only ten are sufficient to identify individuals, ∼20 can identify both components in two-individual mosaics, and 20-30 can identify first-order relatives. Using noisy environmental-sample-derived SNPs, PLIGHT identifies individuals in a database using ∼30 SNPs. Even when the individuals are not in the database, local genotype matches allow for some phenotypic information leakage based on coarse-grained SNP imputation. Finally, by quantifying privacy leakage from sparse SNP sets, PLIGHT helps determine the value of selectively sanitizing released SNPs without explicit assumptions about population membership or allele frequency. To make this practical, we provide a sanitization tool to remove the most identifying SNPs from genomic data.

LDmat: efficiently queryable compression of linkage disequilibrium matrices.

MOTIVATION: Linkage disequilibrium (LD) matrices derived from large populations are widely used in population genetics in fine-mapping, LD score regression, and linear mixed models for Genome-wide Association Studies (GWAS). However, these matrices can reach large sizes when they are derived from millions of individuals; hence, moving, sharing and extracting granular information from this large amount of data can be cumbersome. RESULTS: We sought to address the need for compressing and easily querying large LD matrices by developing LDmat. LDmat is a standalone tool to compress large LD matrices in an HDF5 file format and query these compressed matrices. It can extract submatrices corresponding to a sub-region of the genome, a list of select loci, and loci within a minor allele frequency range. LDmat can also rebuild the original file formats from the compressed files. AVAILABILITY AND IMPLEMENTATION: LDmat is implemented in python, and can be installed on Unix systems with the command 'pip install ldmat'. It can also be accessed through https://github.com/G2Lab/ldmat and https://pypi.org/project/ldmat/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Privacy-preserving model evaluation for logistic and linear regression using homomorphically encrypted genotype data.

OBJECTIVE: Linear and logistic regression are widely used statistical techniques in population genetics for analyzing genetic data and uncovering patterns and associations in large genetic datasets, such as identifying genetic variations linked to specific diseases or traits. However, obtaining statistically significant models from these studies requires large amounts of sensitive genotype and phenotype information from thousands of patients, which raises privacy concerns. Although cryptographic techniques such as homomorphic encryption offers a potential solution to the privacy concerns as it allows computations on encrypted data, previous methods leveraging homomorphic encryption have not addressed the confidentiality of shared models, which can leak information about the training data. METHODS: In this work, we present a secure model evaluation method for linear and logistic regression using homomorphic encryption for six prediction tasks, where input genotypes, output outcomes, and model parameters are all encrypted. RESULTS: Our method ensures no private information leakage during inference and achieves high accuracy (≥93% for all outcomes) with each inference taking less than ten seconds for ∼200 genomes. CONCLUSION: Our study demonstrates that it is possible to perform high-quality linear and logistic regression model evaluation while protecting patient confidentiality with theoretical security guarantees. Our implementation and test data are available at https://github.com/G2Lab/privateML/.

Evaluation of the relationship between anxiety levels and dental appearance.

OBJECTIVE: The aim of this study was to evaluate the relationship between personal traits, dental anxiety level and dental appearance of the individuals. STUDY DESIGN: The study included 431 individuals who completed State Trait Anxiety Inventory-Trait Form (STAI-T) and Corah's Dental Anxiety Scale (CDAS) questionnaires during their first appointment at the orthodontic clinic. The Index of Complexity, Outcome and Need (ICON) index scoring was performed using intraoral frontal photographs by an orthodontist. According to the STAI-T scores, three anxiety groups were formed: mild, moderate, and severe. The Kruskal-Wallis H test was used for intergroup comparisons. Spearman's correlation analysis was performed to evaluate the relationship between STAI-T, CDAS, and ICON scores. RESULTS: It was found that 38.28% of the participants had mild, 34.1% had severe, and 27.62% had moderate anxiety levels. CDAS score was significantly lower in the mild anxiety group (p ≤ 0.0001) compared to the groups showing moderate and severe anxiety. There was no significant difference between the moderate and severe anxiety groups. ICON score was significantly higher in the severe anxiety group (p ≤ 0.0001) than the other groups. It was also significantly higher in the moderate anxiety group (p ≤ 0.0001) than in the mild anxiety group. There was a significant positive correlation between STAI-T and both CDAS and ICON scores. There was no significant correlation between CDAS and ICON scores. CONCLUSION: Dental appearance had a significant effect on the general anxiety of individuals. Improving the dental appearance with orthodontic treatments can have positive effects on reducing anxiety. The low level of dental anxiety in individuals with a high need for treatment will facilitate the work of the orthodontist in the procedures to be applied.

FANCY: fast estimation of privacy risk in functional genomics data.

MOTIVATION: Functional genomics data are becoming clinically actionable, raising privacy concerns. However, quantifying privacy leakage via genotyping is difficult due to the heterogeneous nature of sequencing techniques. Thus, we present FANCY, a tool that rapidly estimates the number of leaking variants from raw RNA-Seq, ATAC-Seq and ChIP-Seq reads, without explicit genotyping. FANCY employs supervised regression using overall sequencing statistics as features and provides an estimate of the overall privacy risk before data release. RESULTS: FANCY can predict the cumulative number of leaking SNVs with an average 0.95 R2 for all independent test sets. We realize the importance of accurate prediction when the number of leaked variants is low. Thus, we develop a special version of the model, which can make predictions with higher accuracy when the number of leaking variants is low. AVAILABILITY AND IMPLEMENTATION: A python and MATLAB implementation of FANCY, as well as custom scripts to generate the features can be found at https://github.com/gersteinlab/FANCY. We also provide jupyter notebooks so that users can optimize the parameters in the regression model based on their own data. An easy-to-use webserver that takes inputs and displays results can be found at fancy.gersteinlab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Characteristics of Patients Who Underwent a Diagnostic Test for Hereditary Angioedema Admitted Due to Angioedema.

OBJECTIVE: Hereditary angioedema (HAE) is clinically characterized by recurrent attacks of angioedema. This study evaluated the clinical findings and examination results of patients admitted due to angioedema who then underwent a diagnostic test for HAE. The study aimed to assess the contribution of laboratory findings to the diagnostic process and to determine clinicians' level of awareness regarding the differential diagnosis of angioedema and the appropriate laboratory tests. METHODS: Pediatric patients suspected to have HAE based on the presence of angioedema and screened for C1 esterase inhibitor levels and/or function were included in the study. RESULTS: A total of 136 patients were evaluated for a preliminary diagnosis of HAE in the presence of angioedema. Angioedema was accompanied by urticaria in 65 patients (47.7%) and itching in 24 patients (17.6%). Patients were evaluated using laboratory tests, C4 levels were studied in 124 patients (91.1%) and were found to be within normal reference limits. C1 esterase inhibitor levels were studied in all patients and were found to be within normal limits. C1 esterase inhibitor function was also studied in 101 patients (74.2%) and was found to be within normal limits. DISCUSSION: It was concluded that clinicians keep HAE in mind when encountering angioedema, but that increasing their knowledge of clinical findings that assist in differential diagnosis among angioedema types would be useful. The study authors would like to emphasize that this topic should be included in the specialty training curriculum to raise the awareness of clinicians, especially pediatricians, about clinical HAE findings and the algorithmic approach to the differential diagnosis of angioedema.

A COVID-19 first evaluation clinic at a university hospital in Turkey.

BACKGROUND: We aimed to analyze the usefulness of such a reserved area for the admission of the patients' symptoms suggesting COVID-19 and compare the demographic and clinical characteristics of the patients with COVID-19 and without COVID-19 who were admitted to C1 during the first month of the COVID-19 outbreak in our hospital. METHODS: A new area was set up in Hacettepe University Adult Hospital to limit the contact of COVID-19 suspicious patients with other patients, which was named as COVID-19 First Evaluation Outpatient Clinic (C1). C1 had eight isolation rooms and two sampling rooms for SARS-CoV-2 polymerase-chain-reaction (PCR). All rooms were negative-pressurized. Patients who had symptoms that were compatible with COVID-19 were referred to C1 from pretriage areas. All staff received training for the appropriate use of personal protective equipment and were visited daily by the Infection Prevention and Control team. RESULTS: One hundred and ninety-eight (29.4%) of 673 patients who were admitted to C1were diagnosed with COVID-19 between March 20, 2020, and April 19, 2020. SARS-CoV-2 PCR was positive in 142 out of 673 patients. Chest computerized tomography (CT) was performed in 421 patients and COVID-19 was diagnosed in 56 of them based on CT findings despite negative PCR. Four hundred and ninety-three patients were tested for other viral and bacterial infections with multiplex real-time reverse-transcriptase PCR (RTPCR). Blood tests that included complete blood count, renal and liver functions, d-dimer levels, ferritin, C- reactive protein, and procalcitonin were performed in 593 patients. Only one out of 44 healthcare workers who worked at C1 was infected by SARS-CoV-2. DISCUSSION: Early diagnosis of infected patients and ensuring adequate isolation are very important to control the spread of COVID-19. The purpose of setting up the COVID-19 first evaluation outpatient clinic was to prevent the overcrowding of ER due to mild or moderate infections, ensure appropriate distancing and isolation, and enable emergency services to serve for real emergencies. A wellplanned outpatient care area and teamwork including internal medicine, microbiology, and radiology specialists under the supervision of infectious diseases specialists allowed adequate management of the mild-to-moderate patients with suspicion of COVID-19.

A new perspective on the relationship between anchorage and palatal morphology: Three-dimensional digital model analysis.

Background: The tooth movements were generally analyzed in two dimensions on cephalometric radiographs. Nowaday, 3D digital model analysis, which does not have any harmful effects on patients, can be used to evaluate the palatal morphology and coronal tooth movements in a very comfortable and easy way. Aims: To investigate the effect of palatal morphology on anchorage reinforcement during intraoral molar distalization with pendulum appliance using 3D model analysis. Materials and Methods: The material consisted of before (T0) and after (T1) dental plaster models of Class II malocclusion patients (17 females, 3 males) treated with pendulum appliance for molar distalization and Nance appliance for anchorage. T0 and T1 digital models were superimposed using the palatal area as a reference via three points and surface-matching software, and the changes in teeth movement were calculated for left and right central incisors, first premolars, and first and second molars. Palatal morphology was evaluated at T0 on digital models as palatal inclination, palatal depth angles, and anterior hard palate area. Wilcoxon test was used to evaluate the treatment results and Spearman's correlation analysis was performed to evaluate the relationship between palatal morphology and dental movement. The upper limit for the level of significance was taken as 0.05. Results: Mesial movement of first premolars and distal movement of first and second molars were found to be statistically significant (P < 0.001). A weak negative correlation was found between the palatal inclination and the movement of first premolars (P < 0.045 and P < 0.003). Palatal depth angles and anterior hard palate area had no correlation with dental movements. Conclusion: Presented results supported that the mesial movement of premolar teeth decreased as the inclination of the palate increased.

Expect the unexpected: fungemia caused by uncommon Candida species in a Turkish University Hospital.

Fungemia caused by uncommon Candida species (UCS) (other than C.albicans, C.glabrata, C.parapsilosis, C.tropicalis, C.krusei) is a rare but emerging threat with their potential to exhibit reduced susceptibility or resistance to antifungal agents. We identified 25 patients with UCS fungemia (9 C.kefyr, 8 C.lusitaniae, 4 C.dubliniensis, 2 C.guilliermondii, 1 C.pelliculosa, 1 C.rugosa) through January 2011 and August 2018. Echinocandins were the most common administered agents, followed by fluconazole. Overall mortality was 44%. Echinocandins and voriconazole showed sufficient activity against all tested isolates. High fluconazole MICs among C.guilliermondii, C.pelliculosa, and C.rugosa were determined. MIC value of C.pelliculosa was above the epidemiological cut-off proposed for fluconazole.

DiNeR: a Differential graphical model for analysis of co-regulation Network Rewiring.

BACKGROUND: During transcription, numerous transcription factors (TFs) bind to targets in a highly coordinated manner to control the gene expression. Alterations in groups of TF-binding profiles (i.e. "co-binding changes") can affect the co-regulating associations between TFs (i.e. "rewiring the co-regulator network"). This, in turn, can potentially drive downstream expression changes, phenotypic variation, and even disease. However, quantification of co-regulatory network rewiring has not been comprehensively studied. RESULTS: To address this, we propose DiNeR, a computational method to directly construct a differential TF co-regulation network from paired disease-to-normal ChIP-seq data. Specifically, DiNeR uses a graphical model to capture the gained and lost edges in the co-regulation network. Then, it adopts a stability-based, sparsity-tuning criterion -- by sub-sampling the complete binding profiles to remove spurious edges -- to report only significant co-regulation alterations. Finally, DiNeR highlights hubs in the resultant differential network as key TFs associated with disease. We assembled genome-wide binding profiles of 104 TFs in the K562 and GM12878 cell lines, which loosely model the transition between normal and cancerous states in chronic myeloid leukemia (CML). In total, we identified 351 significantly altered TF co-regulation pairs. In particular, we found that the co-binding of the tumor suppressor BRCA1 and RNA polymerase II, a well-known transcriptional pair in healthy cells, was disrupted in tumors. Thus, DiNeR successfully extracted hub regulators and discovered well-known risk genes. CONCLUSIONS: Our method DiNeR makes it possible to quantify changes in co-regulatory networks and identify alterations to TF co-binding patterns, highlighting key disease regulators. Our method DiNeR makes it possible to quantify changes in co-regulatory networks and identify alterations to TF co-binding patterns, highlighting key disease regulators.

Computational construction of 3D chromatin ensembles and prediction of functional interactions of alpha-globin locus from 5C data.

Conformation capture technologies measure frequencies of interactions between chromatin regions. However, understanding gene-regulation require knowledge of detailed spatial structures of heterogeneous chromatin in cells. Here we describe the nC-SAC (n-Constrained-Self Avoiding Chromatin) method that transforms experimental interaction frequencies into 3D ensembles of chromatin chains. nC-SAC first distinguishes specific from non-specific interaction frequencies, then generates 3D chromatin ensembles using identified specific interactions as spatial constraints. Application to α-globin locus shows that these constraints (∼20%) drive the formation of ∼99% all experimentally captured interactions, in which ∼30% additional to the imposed constraints is found to be specific. Many novel specific spatial contacts not captured by experiments are also predicted. A subset, of which independent ChIA-PET data are available, is validated to be RNAPII-, CTCF-, and RAD21-mediated. Their positioning in the architectural context of imposed specific interactions from nC-SAC is highly important. Our results also suggest the presence of a many-body structural unit involving α-globin gene, its enhancers, and POL3RK gene for regulating the expression of α-globin in silent cells.

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

Nanosilver coated orthodontic brackets: in vivo antibacterial properties and ion release.

INTRODUCTION: Silver nanoparticles are currently utilized in the fields of dentistry. The aim of this study was to evaluate the antibacterial properties and ion release of nanosilver coated orthodontic brackets compared to conventional brackets. METHODS: Nanosilver coating process was applied to standard orthodontic brackets placed on the mandibular incisors of Wistar Albino rats in the study group and conventional brackets in the control group. Dental plaque, mucosal vestibular smears, saliva, and blood samples were collected from rats at various days. The amounts of nanosilver ions in blood and saliva were measured and microbiological evaluation was made for Streptococcus mutans. For testing cariogenicity, all rats were sacrificed at the end of 75 days under anaesthesia. Teeth were stained using a caries indicator, then the caries ratio was assessed. RESULTS: Nanosilver coated orthodontic bracket favoured the inhibition of S.mutans on Day 30 and reduction of caries on the smooth surfaces. The nanosilver amounts in the saliva and serum samples were significantly higher in the study group on Day 7. CONCLUSION: It is suggested that nanosilver coated orthodontic brackets, as an antibacterial agent without patient compliance, could be helpful for the prevention of white spot lesions during fixed orthodontic treatment.

Spatial confinement is a major determinant of the folding landscape of human chromosomes.

The global architecture of the cell nucleus and the spatial organization of chromatin play important roles in gene expression and nuclear function. Single-cell imaging and chromosome conformation capture-based techniques provide a wealth of information on the spatial organization of chromosomes. However, a mechanistic model that can account for all observed scaling behaviors governing long-range chromatin interactions is missing. Here we describe a model called constrained self-avoiding chromatin (C-SAC) for studying spatial structures of chromosomes, as the available space is a key determinant of chromosome folding. We studied large ensembles of model chromatin chains with appropriate fiber diameter, persistence length and excluded volume under spatial confinement. We show that the equilibrium ensemble of randomly folded chromosomes in the confined nuclear volume gives rise to the experimentally observed higher-order architecture of human chromosomes, including average scaling properties of mean-square spatial distance, end-to-end distance, contact probability and their chromosome-to-chromosome variabilities. Our results indicate that the overall structure of a human chromosome is dictated by the spatial confinement of the nuclear space, which may undergo significant tissue- and developmental stage-specific size changes.