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Abstract Background Like its parent base 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) is a direct epigenetic modification of cytosines in the context of CpG dinucleotides. 5hmC is the most abundant oxidized form of 5mC, generated through the action of TET dioxygenases at gene bodies of actively-transcribed genes and at active or lineage-specific enhancers. Although such enrichments are reported for 5hmC, to date, predictive models of gene expression state or putative regulatory regions for genes using 5hmC have not been developed. Results Here, by using only 5hmC enrichment in genic regions and their vicinity, we develop neural network models that predict gene expression state across 49 cell types. We show that our deep neural network models distinguish high vs low expression state utilizing only 5hmC levels and these predictive models generalize to unseen cell types. Further, in order to leverage 5hmC signal in distal enhancers for expression prediction, we employ an Activity-by-Contact model and also develop a graph convolutional neural network model with both utilizing Hi-C data and 5hmC enrichment to prioritize enhancer-promoter links. These approaches identify known and novel putative enhancers for key genes in multiple immune cell subsets. Conclusions Our work highlights the importance of 5hmC in gene regulation through proximal and distal mechanisms and provides a framework to link it to genome function. With the recent advances in 6-letter DNA sequencing by short and long-read techniques, profiling of 5mC and 5hmC may be done routinely in the near future, hence, providing a broad range of applications for the methods developed here.

Summary: Atypical B cells are a population of activated B cells that are commonly enriched in individuals with chronic immune activation but are also part of a normal immune response to infection or vaccination. To better define the role of atypical B cells in the human adaptive immune response, we performed single-cell sequencing of transcriptomes, cell surface markers, and B cell receptors in individuals with chronic exposure to the malaria parasite Plasmodium falciparum, a condition known to lead to accumulation of circulating atypical B cells. We identified three previously uncharacterized populations of atypical B cells with distinct transcriptional and functional profiles and observed marked differences among these three subsets in their ability to produce immunoglobulin G upon T-cell-dependent activation. Our findings help explain the conflicting observations in prior studies regarding the function of atypical B cells and highlight their different roles in the adaptive immune response in chronic inflammatory conditions.

Abstract Ependymoma is a tumor of the brain or spinal cord. The two most common and aggressive molecular groups of ependymoma are the supratentorial ZFTA-fusion associated and the posterior fossa ependymoma group A. In both groups, tumors occur mainly in young children and frequently recur after treatment. Although molecular mechanisms underlying these diseases have recently been uncovered, they remain difficult to target and innovative therapeutic approaches are urgently needed. Here, we use genome-wide chromosome conformation capture (Hi-C), complemented with CTCF and H3K27ac ChIP-seq, as well as gene expression and DNA methylation analysis in primary and relapsed ependymoma tumors, to identify chromosomal conformations and regulatory mechanisms associated with aberrant gene expression. In particular, we observe the formation of new topologically associating domains (‘neo-TADs’) caused by structural variants, group-specific 3D chromatin loops, and the replacement of CTCF insulators by DNA hyper-methylation. Through inhibition experiments, we validate that genes implicated by these 3D genome conformations are essential for the survival of patient-derived ependymoma models in a group-specific manner. Thus, this study extends our ability to reveal tumor-dependency genes by 3D genome conformations even in tumors that lack targetable genetic alterations.

Abstract Changes in the three-dimensional (3D) structure of the genome are an emerging hallmark of cancer. Cancer-associated copy number variants and single nucleotide polymorphisms promote rewiring of chromatin loops, disruption of topologically associating domains (TADs), active/inactive chromatin state switching, leading to oncogene expression and silencing of tumor suppressors. However, little is known about 3D changes during cancer progression to a chemotherapy-resistant state. We integrated chromatin conformation capture (Hi-C), RNA-seq, and whole-genome sequencing obtained from triple-negative breast cancer patient-derived xenograft primary tumors (UCD52) and carboplatin-resistant samples and found increased short-range (

The organisation of mammalian genomes plays a role in many biological processes. Here the authors report dcHiC, a tool which uses a multivariate distance measure to identify changes in compartmentalisation among multiple genome-wide chromatin contact maps, and apply this to different human and mouse datasets.

Immune cells are important in the pathogenesis of COVID-19. Here the authors assessed the effects of COVID-19-risk variants on gene expression in a range of immune cell types, highlighting their potential to impact the function of diverse immune cell types and influence severe disease.

Abstract Background A specific 3-dimensional intrachromosomal architecture of core stem cell factor genes is required to reprogram a somatic cell into pluripotency. As little is known about the epigenetic readers that orchestrate this architectural remodeling, we used a novel chromatin RNA in situ reverse transcription sequencing (CRIST-seq) approach to profile long noncoding RNAs (lncRNAs) in the Oct4 promoter. Results We identify Platr10 as an Oct4 - Sox2 binding lncRNA that is activated in somatic cell reprogramming. Platr10 is essential for the maintenance of pluripotency, and lack of this lncRNA causes stem cells to exit from pluripotency. In fibroblasts, ectopically expressed Platr10 functions in trans to activate core stem cell factor genes and enhance pluripotent reprogramming. Using RNA reverse transcription-associated trap sequencing (RAT-seq), we show that Platr10 interacts with multiple pluripotency-associated genes, including Oct4, Sox2, Klf4, and c-Myc, which have been extensively used to reprogram somatic cells. Mechanistically, we demonstrate that Platr10 helps orchestrate intrachromosomal promoter-enhancer looping and recruits TET1, the enzyme that actively induces DNA demethylation for the initiation of pluripotency. We further show that Platr10 contains an Oct4 binding element that interacts with the Oct4 promoter and a TET1-binding element that recruits TET1. Mutation of either of these two elements abolishes Platr10 activity. Conclusion These data suggest that Platr10 functions as a novel chromatin RNA molecule to control pluripotency in trans by modulating chromatin architecture and regulating DNA methylation in the core stem cell factor network.

Plasmodium knowlesi poses a health threat throughout Southeast Asian communities and currently causes most cases of malaria in Malaysia. This zoonotic parasite species has been studied in Macaca mulatta (rhesus monkeys) as a model for severe malarial infections, chronicity, and antigenic variation. The phenomenon of Plasmodium antigenic variation was first recognized during rhesus monkey infections. Plasmodium-encoded variant proteins were first discovered in this species and found to be expressed at the surface of infected erythrocytes, and then named the Schizont-Infected Cell Agglutination (SICA) antigens. SICA expression was shown to be spleen dependent, as SICA expression is lost after P. knowlesi is passaged in splenectomized rhesus. Here we present data from longitudinal P. knowlesi infections in rhesus with the most comprehensive analysis to date of clinical parameters and infected red blood cell sequestration in the vasculature of tissues from 22 organs. Based on the histopathological analysis of 22 tissue types from 11 rhesus monkeys, we show a comparative distribution of parasitized erythrocytes and the degree of margination of the infected erythrocytes with the endothelium. Interestingly, there was a significantly higher burden of parasites in the gastrointestinal tissues, and extensive margination of the parasites along the endothelium, which may help explain gastrointestinal symptoms frequently reported by patients with P. knowlesi malarial infections. Moreover, this margination was not observed in splenectomized rhesus that were infected with parasites not expressing the SICA proteins. This work provides data that directly supports the view that a subpopulation of P. knowlesi parasites cytoadheres and sequesters, likely via SICA variant antigens acting as ligands. This process is akin to the cytoadhesive function of the related variant antigen proteins, namely Erythrocyte Membrane Protein-1, expressed by Plasmodium falciparum.

Abstract We present Mustache, a new method for multi-scale detection of chromatin loops from Hi-C and Micro-C contact maps. Mustache employs scale-space theory, a technical advance in computer vision, to detect blob-shaped objects in contact maps. Mustache is scalable to kilobase-resolution maps and reports loops that are highly consistent between replicates and between Hi-C and Micro-C datasets. Compared to other loop callers, such as HiCCUPS and SIP, Mustache recovers a higher number of published ChIA-PET and HiChIP loops as well as loops linking promoters to regulatory elements. Overall, Mustache enables an efficient and comprehensive analysis of chromatin loops. Available at: https://github.com/ay-lab/mustache .

In multiple myeloma, a 4;14 translocation induces overexpression of histone methyltransferase NSD2, resulting in expansion of H3K36me2 and shrinkage of H3K27me3 domains. Here the authors find that CTCF, H3K27ac and gene expression changes cluster within a subset of insulated domains implicating 3D chromosome organization as a key factor in the NSD2-mediated phenotype.

HiChIP/PLAC-seq assay is popular for profiling 3D genome interactions among regulatory elements at kilobase resolution. Here the authors describe FitHiChIP an empirical null-based, flexible computational method for statistical significance estimation and loop calling from HiChIP data.

Abstract Background Hi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. Results Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector, and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established measures, such as the ratio of intra- to interchromosomal interactions, and novel ones, such as QuASAR-QC, to identify low-quality experiments. Conclusions In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

Genotype imputation estimates the genotypes of unobserved variants using the genotype data of other observed variants based on a collection of haplotypes for thousands of individuals, which is known as a haplotype reference panel. In general, more accurate imputation results were obtained using a larger size of haplotype reference panel. Most of the existing genotype imputation methods explicitly require the haplotype reference panel in precise form, but the accessibility of haplotype data is often limited, due to the requirement of agreements from the donors. Since de-identified information such as summary statistics or model parameters can be used publicly, imputation methods using de-identified haplotype reference information might be useful to enhance the quality of imputation results under the condition where the access of the haplotype data is limited. In this study, we proposed a novel imputation method that handles the reference panel as its model parameters by using bidirectional recurrent neural network (RNN). The model parameters are presented in the form of de-identified information from which the restoration of the genotype data at the individual-level is almost impossible. We demonstrated that the proposed method provides comparable imputation accuracy when compared with the existing imputation methods using haplotype datasets from the 1000 Genomes Project (1KGP) and the Haplotype Reference Consortium. We also considered a scenario where a subset of haplotypes is made available only in de-identified form for the haplotype reference panel. In the evaluation using the 1KGP dataset under the scenario, the imputation accuracy of the proposed method is much higher than that of the existing imputation methods. We therefore conclude that our RNN-based method is quite promising to further promote the data-sharing of sensitive genome data under the recent movement for the protection of individuals’ privacy. Author summary Genotype imputation estimates the genotypes of unobserved variants using the genotype data of other observed variants based on a collection of genome data of a large number of individuals called a reference panel. In general, more accurate imputation results are obtained using a larger size of the reference panel. Although most of the existing imputation methods use the reference panel in an explicit form, the accessibility of genome data is often limited due to the requirement of agreements from the donors. We thus proposed a new imputation method that handles the reference panel as its model parameters by using bidirectional recurrent neural network. Since it is almost impossible to restore genome data at the individual-level from the model parameters, they can be shared publicly as the de-identified information even when the accessibility of the original reference panel is limited. We demonstrate that the proposed method provides comparable imputation accuracy with the existing methods. We also considered a scenario where a part of the genome data is made available only in de-identified form for the reference panel and have shown that the imputation accuracy of the proposed method is much higher than that of the existing methods under the scenario.

The development of malaria parasites is controlled by coordinated changes in gene expression. Here, the authors show that the three-dimensional genome structure of human malaria parasites is strongly connected with transcriptional activity of specific gene families throughout the life cycles of Plasmodium falciparum and Plasmodium vivax parasites.

Variations in the 17q21 locus are linked to asthma susceptibility and other autoimmune diseases. Here, the authors perform cell type-specific functional genomic analyses of asthma-risk SNPs, and show a genotype specific mechanism of differential gene regulation relevant to immune function.

Current Hi-C analysis approaches are unable to account for reads that align to multiple locations, and hence underestimate biological signal from repetitive regions of genomes. We developed and validated mHi-C, a multi-read mapping strategy to probabilistically allocate Hi-C multi-reads. mHi-C exhibited superior performance over utilizing only uni-reads and heuristic approaches aimed at rescuing multi-reads on benchmarks. Specifically, mHi-C increased the sequencing depth by an average of 20% resulting in higher reproducibility of contact matrices and detected interactions across biological replicates. The impact of the multi-reads on the detection of significant interactions is influenced marginally by the relative contribution of multi-reads to the sequencing depth compared to uni-reads, cis-to-trans ratio of contacts, and the broad data quality as reflected by the proportion of mappable reads of datasets. Computational experiments highlighted that in Hi-C studies with short read lengths, mHi-C rescued multi-reads can emulate the effect of longer reads. mHi-C also revealed biologically supported bona fide promoter-enhancer interactions and topologically associating domains involving repetitive genomic regions, thereby unlocking a previously masked portion of the genome for conformation capture studies.

Assembly of kinetochore complexes, involving greater than one hundred proteins, is essential for chromosome segregation and genome stability. Neocentromeres, or new centromeres, occur when kinetochores assemble de novo, at DNA loci not previously associated with kinetochore proteins, and they restore chromosome segregation to chromosomes lacking a functional centromere. Neocentromeres have been observed in a number of diseases and may play an evolutionary role in adaptation or speciation. However, the consequences of neocentromere formation on chromosome missegregation rates, gene expression, and three-dimensional (3D) nuclear structure are not well understood. Here, we used Candida albicans, an organism with small, epigenetically-inherited centromeres, as a model system to study the functions of twenty different neocentromere loci along a single chromosome, chromosome 5. Comparison of neocentromere properties relative to native centromere functions revealed that all twenty neocentromeres mediated chromosome segregation, albeit to different degrees. Some neocentromeres also caused reduced levels of transcription from genes found within the neocentromere region. Furthermore, like native centromeres, neocentromeres clustered in 3D with active/functional centromeres, indicating that formation of a new centromere mediates the reorganization of 3D nuclear architecture. This demonstrates that centromere clustering depends on epigenetically defined function and not on the primary DNA sequence, and that neocentromere function is independent of its distance from the native centromere position. Together, the results show that a neocentromere can form at many loci along a chromosome and can support the assembly of a functional kinetochore that exhibits native centromere functions including chromosome segregation accuracy and centromere clustering within the nucleus.

Gene transcription can be regulated by remote enhancer regions through chromosome looping either in cis or in trans. Cancer cells are characterized by wholesale changes in long-range gene interactions, but the role that these long-range interactions play in cancer progression and metastasis is not well understood. In this study, we used IGFBP3, a gene involved in breast cancer pathogenesis, as bait in a 4C-seq experiment comparing normal breast cells (HMEC) with two breast cancer cell lines (MCF7, an ER positive cell line, and MDA-MB-231, a triple negative cell line). The IGFBP3 long-range interaction profile was substantially altered in breast cancer. Many interactions seen in normal breast cells are lost and novel interactions appear in cancer lines. We found that in HMEC, the breast carcinoma amplified sequence gene family (BCAS) 1-4 were among the top 10 most significantly enriched regions of interaction with IGFBP3. 3D-FISH analysis indicated that the translocation-prone BCAS genes, which are located on chromosomes 1, 17, and 20, are in close physical proximity with IGFBP3 and each other in normal breast cells. We also found that epidermal growth factor receptor (EGFR), a gene implicated in tumorigenesis, interacts significantly with IGFBP3 and that this interaction may play a role in their regulation. Breakpoint analysis suggests that when an IGFBP3 interacting region undergoes a translocation an additional interaction detectable by 4C is gained. Overall, our data from multiple lines of evidence suggest an important role for long-range chromosomal interactions in the pathogenesis of cancer.

BackgroundComputing the long term behavior of regulatory and signaling networks is critical in understanding how biological functions take place in organisms. Steady states of these networks determine the activity levels of individual entities in the long run. Identifying all the steady states of these networks is difficult due to the state space explosion problem.MethodologyIn this paper, we propose a method for identifying all the steady states of Boolean regulatory and signaling networks accurately and efficiently. We build a mathematical model that allows pruning a large portion of the state space quickly without causing any false dismissals. For the remaining state space, which is typically very small compared to the whole state space, we develop a randomized traversal method that extracts the steady states. We estimate the number of steady states, and the expected behavior of individual genes and gene pairs in steady states in an online fashion. Also, we formulate a stopping criterion that terminates the traversal as soon as user supplied percentage of the results are returned with high confidence.ConclusionsThis method identifies the observed steady states of boolean biological networks computationally. Our algorithm successfully reported the G1 phases of both budding and fission yeast cell cycles. Besides, the experiments suggest that this method is useful in identifying co-expressed genes as well. By analyzing the steady state profile of Hedgehog network, we were able to find the highly co-expressed gene pair GL1-SMO together with other such pairs.AvailabilitySource code of this work is available at http://bioinformatics.cise.ufl.edu/palSteady.html twocolumnfalse].

Today, many factors, especially the increasing world population and developing technology, increase the energy needs of people and societies day by day. The fact that fossil resources are both in danger of depletion and have negative environmental impacts has directed countries to new resources. The study focuses on the effective use of renewable energy sources (RES) and the evaluation of waste to meet the electricity and heat energy needs of Yiğit Harman Village, located in the Solhan district of Bingöl Province. For this purpose, a renewable-energy-based combined heat and power system (CHP) was designed using HOMER Pro software (version 3.14.2, Homer Energy LLC, Boulder, CO, USA). Solar, wind, biomass, and hydrogen energy sources were used, considering the resources of the region. Using the designed model, the entire electricity energy requirement and half of the heat energy were completely met by the region’s available RESs. In addition to the technical analysis, economic and environmental analyses were also conducted, and LCOE, NPC, and CO2 emission values were obtained as 0.271 USD/kWh, USD 739,772, and 37,958 kg/yr, respectively. These results indicate that with an investment of approximately USD 7000 per household, the electrical and thermal energy needs for 25 years can be met.

Abstract Background This study aims to conduct a bibliometric analysis of the current literature related to facial feminization surgery (FFS) and facial masculinization surgery (FMS) to understand the patterns, trends, and evolution of research topics. In addition, it aims to objectively identify the important articles that constitute the primary backbone of the FFS/FMS literature and provide a resource for education and new studies in this emerging field. Results Using the principles of the Leiden Manifesto, 384 publications from the Web of Science from 1987 to 2023 were analyzed. The analysis included cross-country collaboration, keyword trends, affiliations, co-citation networks, and clustering. The results showed an increasing trend in FFS/FMS publications, with the USA leading in both publications (n = 238) and citations (n = 2420). The most cited journal was the Journal of Plastic and Reconstructive Surgery. The results indicate a high growth rate, with an H-index of 34 and an average citation of 11.41 per article. Co-occurrence analysis revealed evolving keywords such as “forehead” (n = 52) and “quality of life” (n = 44). The timeline view illustrated the terms reflecting current areas of interest such as #patient satisfaction and #gender-affirming care. Conclusion The study reveals the influence of countries, institutions, authors, and emerging trends, supporting the anticipation that FFS/FMS will be a critical field of study in the future. The findings contribute to understanding the global landscape of FFS/FMS research, facilitating informed decision-making for researchers, and clinicians in the field of maxillofacial surgery.