Capture Sequencing Research Articles

Abstract B001: Does deep intronic splicing in breast cancer susceptibility genes contribute to breast cancer?

Abstract Breast cancer (BC) is the most common cancer and leading cause of cancer mortality in women. Average lifetime BC risk for a woman in the United States is 13%. However, pathogenic variants in BC susceptibility genes such as BRCA1/2, ATM, and RAD51C, or high polygenic risk scores substantially increase BC risk. Women with a family history of BC and/or ovarian cancer, BC < age 40, or BC and second primary tumor are considered high-risk with an increased likelihood of having a pathogenic variant in a BC susceptibility gene. Yet, more than 60% of women with high-risk BC test negative for coding variants. In these women, possible causal variation could be non-coding in deep intronic or regulatory regions, or cryptic structural variants (SV). To determine whether deep intronic splicing contributes to BC in high-risk women testing negative for pathogenic coding variants in BC genes, we analyzed the intronic sequences of 649 BRCA1/BRCA2 negative individuals with high-risk BC. The samples had undergone targeted capture sequencing of exons and introns of more than 100 target genes including ATM and RAD51C. From the 649 samples, we identified three intronic splicing variants in ATM and RAD51C in 10 samples (1.5%) that had SpliceAI delta scores >0.5 suggesting changes to splicing. One splicing donor gain variant, RAD51C c.145+246A>T, was found exclusively in women of self-reported African ancestry at a frequency of 0.047. In gnomAD, the variant was found exclusively in individuals of African ancestry at a frequency of 0.012. A 1.3-fold enrichment in variant frequency was observed in AFR women under 65 with breast cancer compared to age-matched cancer free controls in the All of Us dataset. Using lymphoblastoid-cell derived RNA from carriers of RAD51C c.145+246A>T, we performed RT-PCR and cDNA amplification targeting the exons surrounding the variant and observed a lengthened exon. Targeted amplicon sequencing also confirmed the presence of intronic sequence in the variant cDNA. The introduced intronic sequence contains a UGA stop codon 12 bp from the end of the exon which could led to loss of RAD51C function. We have created minigene vectors in the RHCglo background and are performing minigene splicing assays to validate the splicing changes in ATM due to intronic variants. Gene functional assays and association studies will be conducted to determine the functional effects and risk conferred by these variants. Understanding the level of contribution of deep intronic splicing in known BC susceptibility genes is critically important, as results impact sequencing offered to patients, and if positive, their medical management. Citation Format: Mwangala P. Akamandisa, Bradley Wubbenhorst, Kurt D'Andrea, Heather Symecko, Rhonda Gillette, Payal D. Shah, Angela R. Bradbury, Kara N. Maxwell, Susan M. Domchek, Katherine L. Nathanson. Does deep intronic splicing in breast cancer susceptibility genes contribute to breast cancer? [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B001.

GenoBaits®WheatplusEE: a targeted capture sequencing panel for quick and accurate identification of wheat-Thinopyrum derivatives.

A total of 90,000 capture probes derived from wheat and Thinopyrum elongatum were integrated into one chip, which served as an economical genotype for explorating Thinopyrumspecies and their derivatives. Thinopyrum species play a crucial role as a source of new genetic variations for enhancing wheat traits, including resistance to both abiotic and biotic factors. Accurate identification of exogenous chromosome(s) or chromosome segments or genes is essential following the introduction of alien genetic material into wheat, but this task remains challenging. This study aimed to develop a high-resolution wheat-Thinopyrum elongatum array, named GenoBaits®WheatplusEE, to trace alien genetic information by genotyping using a target sequencing system. This GenoBaits®WheatplusEE array included 90,000 capture probes derived from two species and integrated into one chip, with 10,000 and 80,000 originating from wheat and Th. elongatum, respectively. The capture probes were strategically positioned in genes and evenly distributed across the genome, facilitating the development of a roadmap for identifying each alien gene. The array was applied to the high-throughput identification of the alien chromosomes or segments in Thinopyrum and distantly related species and their derivatives. Our results demonstrated that the GenoBaits®WheatplusEE array could be used for direct identification of the breakpoint of alien segments, determine copy number of alien chromosomes, and reveal variations in wheat chromosomes by a single round of target sequencing of the sample. Additionally, we could efficiently and cost-effectively genotype, supporting the exploration of subgenome composition, phylogenetic relationships, and polymorphisms in essential genes (e.g., Fhb7 gene) among Thinopyrum species and their derivatives. We hope that GenoBaits®WheatplusEE will become a widely adopted tool for exporting wild germplasm for wheat improvement in the future.

Long-insert sequence capture detects high copy numbers in a defence-related beta-glucosidase gene βglu-1 with large variations in white spruce but not Norway spruce

Conifers are long-lived and slow-evolving, thus requiring effective defences against their fast-evolving insect natural enemies. The copy number variation (CNV) of two key acetophenone biosynthesis genes Ugt5/Ugt5b and βglu-1 may provide a plausible mechanism underlying the constitutively variable defence in white spruce (Picea glauca) against its primary defoliator, spruce budworm. This study develops a long-insert sequence capture probe set (Picea_hung_p1.0) for quantifying copy number of βglu-1-like, Ugt5-like genes and single-copy genes on 38 Norway spruce (Picea abies) and 40 P. glauca individuals from eight and nine provenances across Europe and North America respectively. We developed local assemblies (Piabi_c1.0 and Pigla_c.1.0), full-length transcriptomes (PIAB_v1 and PIGL_v1), and gene models to characterise the diversity of βglu-1 and Ugt5 genes. We observed very large copy numbers of βglu-1, with up to 381 copies in a single P. glauca individual. We observed among-provenance CNV of βglu-1 in P. glauca but not P. abies. Ugt5b was predominantly single-copy in both species. This study generates critical hypotheses for testing the emergence and mechanism of extreme CNV, the dosage effect on phenotype, and the varying copy number of genes with the same pathway. We demonstrate new approaches to overcome experimental challenges in genomic research in conifer defences.

Chromosome-level genome assembly of Hippophae gyantsensis

Hippophae gyantsensis, which is a native tree species in China, is ideal for windbreak and sand-fixing forests. It is an economically and ecologically valuable tree species distributed exclusively in the Qinghai-Tibet Plateau in China. In our study, we assembled a chromosome-level genome of H. gyantsensis using Illumina sequencing, Nanopore sequencing and chromosome structure capture technique. The genome was 716.32 Mb in size with scaffold N50 length of 64.84 Mb. A total of 716.25 Mb genome data was anchored and orientated onto 12 chromosomes with a mounting rate of up to 99.99%. Additionally, the genome was found to comprise approximately 56.84% repeat sequences, of which long terminal repeats(LTRs) that accounted for 33.19% of the entire genome. Meanwhile, a total of 32,316 protein-coding genes were predicted, and 91.07% of these genes were functionally annotated. We also completed a series of comparative genomic analyses to provide researchers with useful reference material for future studies on seabuckthorn.

Genetic Predisposition of Atherosclerotic Cardiovascular Disease in Ancient Human Remains.

Several computed tomographic studies have shown the presence of atherosclerosis in ancient human remains. However, while it is important to understand the development of atherosclerotic cardiovascular disease (ASCVD), genetic data concerning the prevalence of the disease-associated single nucleotide polymorphisms (SNPs) in our ancestors are scarce. For a better understanding of the role of genetics in the evolution of ASCVD, we applied an enrichment capture sequencing approach to mummified human remains from different geographic regions and time periods. Twenty-two mummified individuals were analyzed for their genetic predisposition of ASCVD. Next-generation sequencing methods were applied to ancient DNA (aDNA) samples, including a novel enrichment approach specifically designed to capture SNPs associated with ASCVD in genome-wide association studies of modern humans. Five out of 22 ancient individuals passed all filter steps for calculating a weighted polygenic risk score (PRS) based on 87 SNPs in 56 genes. PRSs were correlated to scores obtained from contemporary people from around the world and cover their complete range. The genetic results of the ancient individuals reflect their phenotypic results, given that the only two mummies showing calcified atherosclerotic arterial plaques on computed tomography scans are the ones exhibiting the highest calculated PRSs. These data show that alleles associated with ASCVD have been widespread for at least 5,000 years. Despite some limitations due to the nature of aDNA, our approach has the potential to lead to a better understanding of the interaction between environmental and genetic influences on the development of ASCVD.

A chromosome-level genome assembly of a deep-sea symbiotic Aplacophora mollusc Chaetoderma sp.

The worm-shaped, shell-less Caudofoveata is one of the least known groups of molluscs. As early-branching molluscs, the lack of high-quality genomes hinders our understanding of their evolution and ecology. Here, we report a high-quality chromosome-scale genome of Chaetoderma sp. combining PacBio, Illumina, and high-resolution chromosome conformation capture sequencing. The final assembly has a size of 2.45 Gb, with a scaffold N50 length of 141.46 Mb, and is anchored to 17 chromosomes. Gene annotations showed a high level of accuracy and completeness, with 23,675 predicted protein-coding genes and 94.44% of the metazoan conserved genes by BUSCO assessment. We further present 16S rRNA gene amplicon sequencing of the gut microbiota in Chaetoderma sp., which was dominated by the chemoautotrophic bacteria (phylum Gammaproteobacteria). This chromosome-level genome assembly presents the first genome for the Caudofoveata, which constitutes an important resource for studies ranging from molluscan evolution, symposium, to deep-sea adaptation.

Novel mutation in alpha-spectrin gene in Saudi patients with hereditary spherocytosis

Hereditary spherocytosis (HS) is the most common hereditary hemolytic disorder induced by red blood cell (RBC) membrane defect. This study was undertaken to determine mutations in genes associated with RBC membrane defect in patients with HS such as α-spectrin gene (SPTA1), β-spectrin gene (SPTB), ankyrin gene (ANK1), band 3 anion transport gene (SLC4A1) and erythrocyte membrane protein band 4.1 gene (EPB41). Blood samples were collected from 23 unrelated patients with HS. Patients were diagnosed according to the guidelines from the British Society for Hematology. All hematological examinations for the determination of RBC abnormalities and osmotic fragility tests were conducted. Genomic DNA were extracted from peripheral blood cells and coding exons of known genes for hereditary spherocytosis were enriched using Roche/KAPA sequence capture technology and sequenced on an Illumina system via next-generation sequencing (NGS). The data showed that most of the HS patients confirmed splenomegaly and showed elevated reticulocytes and abnormal bilirubin values. NGS analysis identified the heterozygous variant c.5501G > A in the exon 39 of SPTA1 gene, resulted in a Trp1834*, which leads to a premature stop codon and subsequent mRNA degradation (nonsense- mediated decay) or truncation in α spectrin. Moreover, our data also revealed conventional mutations in genes SPTB, ANK, SLC4A1 and EBP41 in severe patients of HS. In short, this is the first report that determined a novel mutation c.5501G > A in SPTA1 gene in the Saudi population. To the best of our knowledge, this variant c.5501G > A has not been described in global literature so far. This novel mutation in SPTA1 gene is unique in the Saudi population.

Reconstructing DNA methylation maps of ancient populations.

Studying premortem DNA methylation from ancient DNA (aDNA) provides a proxy for ancient gene activity patterns, and hence valuable information on evolutionary changes in gene regulation. Due to statistical limitations, current methods to reconstruct aDNA methylation maps are constrained to high-coverage shotgun samples, which comprise a small minority of available ancient samples. Most samples are sequenced using in-situ hybridization capture sequencing which targets a predefined set of genomic positions. Here, we develop methods to reconstruct aDNA methylation maps of samples that were not sequenced using high-coverage shotgun sequencing, by way of pooling together individuals to obtain a DNA methylation map that is characteristic of a population. We show that the resulting DNA methylation maps capture meaningful biological information and allow for the detection of differential methylation across populations. We offer guidelines on how to carry out comparative studies involving ancient populations, and how to control the rate of falsely discovered differentially methylated regions. The ability to reconstruct DNA methylation maps of past populations allows for the development of a whole new frontier in paleoepigenetic research, tracing DNA methylation changes throughout human history, using data from thousands of ancient samples.

Signatures of local adaptation to current and future climate in phenology-related genes in natural populations of Quercus robur

BackgroundLocal adaptation is a key evolutionary process that enhances the growth of plants in their native habitat compared to non-native habitats, resulting in patterns of adaptive genetic variation across the entire geographic range of the species. The study of population adaptation to local environments and predicting their response to future climate change is important because of climate change.ResultsHere, we explored the genetic diversity of candidate genes associated with bud burst in pedunculate oak individuals sampled from 6 populations in Poland. Single nucleotide polymorphism (SNP) diversity was assessed in 720 candidate genes using the sequence capture technique, yielding 18,799 SNPs. Using landscape genomic approaches, we identified 8 FST outliers and 781 unique SNPs in 389 genes associated with geography, climate, and phenotypic variables (individual/family spring and autumn phenology, family diameter at breast height (DBH), height, and survival) that are potentially involved in local adaptation. Then, using a nonlinear multivariate model, Gradient Forests, we identified vulnerable areas of the pedunculate oak distribution in Poland that are at risk from climate change.ConclusionsThe model revealed that pedunculate oak populations in the eastern part of the analyzed geographical region are the most sensitive to climate change. Our results might offer an initial evaluation of a potential management strategy for preserving the genetic diversity of pedunculate oak.

New recessive compound heterozygous variants of RP1L1 in RP1L1 maculopathy.

To identify a maculopathy patient caused by new recessive compound heterozygous variants in RP1L1. Comprehensive retinal morphological and functional examinations were evaluated for the patient with RP1L1 maculopathy. Targeted sequence capture array technique was used to screen potential pathologic variants. Polymerase chain reaction and Sanger sequencing were used to confirm the screening results. Fundus examination showed round macular lesions appeared in both eyes. Optical coherence tomography showed that the inner segment/outer segment continuity was disorganized and disruptive in the left eye, but it was uneven and slightly elevated in the right eye. Fundus autofluorescence showed patchy hyper-autofluorescence in the macula. Visual field examination indicates central defects in both eyes. Electroretinogram (ERG) and multifocal ERG showed no obvious abnormalities. Fundus fluorescein angiography in the macula showed obviously irregular hyper-fluorescence in the right eye and slightly hyper-fluorescence in the left eye. We found that the proband carried a missense variant (c.1972C>T) and a deletion variant (c.4717_4718del) of RP1L1, which were originated from the parents and formed compound heterozygous variants. Both variants are likely pathogenic according to the ACMG criteria. Multimodal imaging, ERG and detailed medical history are important diagnostic tools for differentiating between acquired and inherited retinal disorders. A maculopathy case with detailed retinal phenotype and new recessive compound heterozygous variants of RP1L1 is identified in a Chinese family, which expands the understanding of phenotype and genotype in RP1L1 maculopathy.

ScKWARN: Kernel-weighted-average robust normalization for single-cell RNA-seq data.

Single-cell RNA-seq normalization is an essential step to correct unwanted biases caused by sequencing depth, capture efficiency, dropout, and other technical factors. Existing normalization methods primarily reduce biases arising from sequencing depth by modeling count-depth relationship and/or assuming a specific distribution for read counts. However, these methods may lead to over or under-correction due to presence of technical biases beyond sequencing depth and the restrictive assumption on models and distributions. We present scKWARN, a Kernel Weighted Average Robust Normalization designed to correct known or hidden technical confounders without assuming specific data distributions or count-depth relationships. scKWARN generates a pseudo expression profile for each cell by borrowing information from its fuzzy technical neighbors through a kernel smoother. It then compares this profile against the reference derived from cells with the same bimodality patterns to determine the normalization factor. As demonstrated in both simulated and real datasets, scKWARN outperforms existing methods in removing a variety of technical biases while preserving true biological heterogeneity. scKWARN is freely available at https://github.com/cyhsuTN/scKWARN.

EBV DNA methylation profiles and its application in distinguishing nasopharyngeal carcinoma and nasal NK/T-cell lymphoma

BackgroundAs an oncovirus, EBV is associated with multiple cancers, including solid tumors and hematological malignancies. EBV methylation plays an important role in regulating tumor occurrence. However, the EBV methylation profiles in EBV-associated tumor tissues are poorly understood.ResultsIn this study, EBV methylation capture sequencing was conducted in several different tumor tissue samples, including NPC, EBVaGC, lung LELC and parotid LELC. Besides, EBV capture sequencing and following qMSP were performed on nasopharyngeal brushing samples from NPC and nasal NKTCL patients. Our results showed that the EBV genome among different types of tumors displayed specific methylation patterns. Among the four types of tumors from epithelial origin (NPC, EBVaGC, lung LELC and parotid LELC), the most significant differences were found between EBVaGC and the others. For example, in EBVaGC, all CpG sites within 1,44,189–1,45,136 bp of the EBV genome sequence on gene RPMS1 were hyper-methylated compared to the others. Differently, significant differences of EBV CpG sites, particularly those located on gene BILF2, were observed between NPC and nasal NKTCL patients in nasopharyngeal brushing samples. Further, the methylated level of BILF2 was further detected using qMSP, and a diagnostic model distinguishing NPC and nasal NKTCL was established. The AUC of the model was 0.9801 (95% CI 0.9524–1.0000), with the sensitivity and specificity of 98.81% (95% CI 93.63–99.94%) and 76.92% (95% CI 49.74–91.82%), respectively.ConclusionsOur study reveals more clues for further understanding the pathogenesis of EBV, and provides a possibility for distinguishing EBV-related tumor by detecting specific EBV CpG sites.

Batch-effect correction in single-cell RNA sequencing data using JIVE.

In single-cell RNA sequencing analysis, addressing batch effects-technical artifacts stemming from factors such as varying sequencing technologies, equipment, and capture times-is crucial. These factors can cause unwanted variation and obfuscate the underlying biological signal of interest. The joint and individual variation explained (JIVE) method can be used to extract shared biological patterns from multi-source sequencing data while adjusting for individual non-biological variations (i.e. batch effect). However, its current implementation is originally designed for bulk sequencing data, making it computationally infeasible for large-scale single-cell sequencing datasets. In this study, we enhance JIVE for large-scale single-cell data by boosting its computational efficiency. Additionally, we introduce a novel application of JIVE for batch-effect correction on multiple single-cell sequencing datasets. Our enhanced method aims to decompose single-cell sequencing datasets into a joint structure capturing the true biological variability and individual structures, which capture technical variability within each batch. This joint structure is then suitable for use in downstream analyses. We benchmarked the results against four popular tools, Seurat v5, Harmony, LIGER, and Combat-seq, which were developed for this purpose. JIVE performed best in terms of preserving cell-type effects and in scenarios in which the batch sizes are balanced. The JIVE implementation used for this analysis can be found at https://github.com/oconnell-statistics-lab/scJIVE.

Artifactual Orthologs and the Need for Diligent Data Exploration in Complex Phylogenomic Datasets: A Museomic Case Study from the Andean Flora.

The Andes mountains of western South America are a globally important biodiversity hotspot, yet there is a paucity of resolved phylogenies for plant clades from this region. Filling an important gap in our understanding of the World's richest flora, we present the first phylogeny of Freziera (Pentaphylacaceae), an Andean-centered, cloud forest radiation. Our dataset was obtained via hybrid-enriched target sequence capture of Angiosperms353 universal loci for 50 of the ca. 75 spp., obtained almost entirely from herbarium specimens. We identify high phylogenomic complexity in Freziera, including the presence of data artifacts. Via by-eye observation of gene trees, detailed examination of warnings from recently improved assembly pipelines, and gene tree filtering, we identified that artifactual orthologs (i.e., the presence of only one copy of a multicopy gene due to differential assembly) were an important source of gene tree heterogeneity that had a negative impact on phylogenetic inference and support. These artifactual orthologs may be common in plant phylogenomic datasets, where multiple instances of genome duplication are common. After accounting for artifactual orthologs as source of gene tree error, we identified a significant, but nonspecific signal of introgression using Patterson's D and f4 statistics. Despite phylogenomic complexity, we were able to resolve Freziera into 9 well-supported subclades whose evolution has been shaped by multiple evolutionary processes, including incomplete lineage sorting, historical gene flow, and gene duplication. Our results highlight the complexities of plant phylogenomics, which are heightened in Andean radiations, and show the impact of filtering data processing artifacts and standard filtering approaches on phylogenetic inference.

Investigation of flexible graphene hybrid knitted sensor for joint motion recognition based on convolutional neural network fusion long short-term memory network

Wearable electronics have attracted have attracted widespread attentions for their promising applications in motion monitoring and human-computer interaction. This paper proposes a flexible wearable joint movement intelligent sensing and recognition system to achieve stable and reliable motion feature extraction and recognition. Flexible graphene hybrid knitted sensor were prepared by transferring graphenes (GNs) agent onto stretchable knitted products via a simple spray-drying approach. The small dynamic movement of human joints for the prepared GNs hybrid sensing gloves, elbow pads and knee pads were converted into electrical signals for sensitive detection. The convolutional neural network fusion long short-term memory (CNN-LSTM) network with self-attention mechanism (SAM) is established for feature training and intelligent dynamic recognition of the measured joint information. The interconnected conductive networks endowed knitted sensor with good flexibility and remarkable electrical conductivity of 37 S/m. The unique conductive networks in the fabric offered excellent linearity and repeatable resistance response variation for better detection of joint motion. The resistant signal was analyzed by feature extraction, data correlation capture and time sequence relationship modeling. Finally, the test results show that the proposed CNN-LSTM with SAM network achieves 97%, 96% and 100% correct recognition rates for gesture signals, elbow and wrist signals and knee signals respectively, which is obviously higher than other recognition algorithms. It has great application prospects in the fields of smart wear, medical detection, and smart elderly care.

Handwritten text recognition using deep learning techniques: A survey

HTR (Handwritten Text Recognition) is the automated process of converting handwritten text into digital text, holding immense value in digitizing historical records and facilitating data entry. Through a combination of image processing and HTR systems decode handwritten characters and words. Pre-processing techniques increases image quality by reducing noise and correcting orientation, while models, like “convolutional neural networks” and “recurrent neural networks”, extract features and capture sequence patterns. Effective HTR models demand diverse training datasets and involve supervised learning to align predicted text with actual transcriptions. Post processing tools, including language models and spell-checkers, refine recognition outcomes. HTR's significance spans historical archive digitization, automated form processing, and aiding individuals with disabilities. Challenges persist in deciphering complex handwriting and handling degraded documents. The integration of deep learning advances HTR, enhancing its accuracy and efficiency, thereby expanding access to handwritten texts and enabling their digital search ability and edit ability. The outcome of this endeavor is a robust and user-friendly tool capable of converting handwritten notes, letters, manuscripts, and other textual materials into editable digital text. This project contributes significantly to bridging the gap between analog and digital information, offering immense potential for archival preservation, data accessibility improved productivity across domains.

Skeleton-Based Action Segmentation With Multi-Stage Spatial-Temporal Graph Convolutional Neural Networks

The ability to identify and temporally segment fine-grained actions in motion capture sequences is crucial for applications in human movement analysis. Motion capture is typically performed with optical or inertial measurement systems, which encode human movement as a time series of human joint locations and orientations or their higher-order representations. State-of-the-art action segmentation approaches use multiple stages of temporal convolutions. The main idea is to generate an initial prediction with several layers of temporal convolutions and refine these predictions over multiple stages, also with temporal convolutions. Although these approaches capture long-term temporal patterns, the initial predictions do not adequately consider the spatial hierarchy among the human joints. To address this limitation, we recently introduced multi-stage spatial-temporal graph convolutional neural networks (MS-GCN). Our framework replaces the initial stage of temporal convolutions with spatial graph convolutions and dilated temporal convolutions, which better exploit the spatial configuration of the joints and their long-term temporal dynamics. Our framework was compared to four strong baselines on five tasks. Experimental results demonstrate that our framework is a strong baseline for skeleton-based action segmentation.

Germline susceptibility from broad genomic profiling of pediatric brain cancers.

Identifying germline predisposition in CNS malignancies is of increasing clinical importance, as it contributes to diagnosis and prognosis, and determines aspects of treatment. The inclusion of germline testing has historically been limited due to challenges surrounding access to genetic counseling, complexity in acquiring a germline comparator specimen, concerns about the impact of findings, or cost considerations. These limitations were further defined by the breadth and scope of clinical testing to precisely identify complex variants as well as concerns regarding the clinical interpretation of variants including those of uncertain significance. In the course of conducting an IRB-approved protocol that performed genomic, transcriptomic and methylation-based characterization of pediatric CNS malignancies, we cataloged germline predisposition to cancer based on paired exome capture sequencing, coupled with computational analyses to identify variants in known cancer predisposition genes and interpret them relative to established clinical guidelines. In certain cases, these findings refined diagnosis or prognosis or provided important information for treatment planning. We outline our aggregate findings on cancer predisposition within this cohort which identified 16% of individuals (27 of 168) harboring a variant predicting cancer susceptibility and contextualize the impact of these results in terms of treatment-related aspects of precision oncology.

Hypermethylation of Bmp2 and Fgfr2 Promoter Regions in Bone Marrow Mesenchymal Stem Cells Leads to Bone Loss in Prematurely Aged Mice.

Osteoporosis is an age-related, systemic skeletal disease that poses a significant public health challenge in contemporary society. Development at the epigenetic level is emerging as an important pathogenic mechanism of osteoporosis. Despite indications of a robust association between DNA methylation and osteoporosis development, a comprehensive understanding of the specific role of DNA methylation in osteoporosis remains limited. In this study, significant bone loss was detected at the beginning of eight weeks of age in mouse models of premature aging (SHJHhr mice). We identified a notable upregulation of DNA methyltransferase 3b/3l (Dnmt3b/l) and downregulation of ten eleven translocation dioxygenase 1 (Tet1) in bone marrow mesenchymal stem cells (BMSCs) isolated from SHJHhr mice, along with an increase in the overall 5-methylcytosine (5mC) levels. Moreover, methylation capture sequencing revealed genomic hypermethylation in SHJHhr mice BMSCs. Integrated methylome and transcriptome analyses revealed several crucial methylated genes and networks that are potentially associated with osteoporosis development. Notably, elevated methylation levels of genes linked to the Wnt signaling pathway, particularly bone morphogenetic protein 2 (Bmp2) and fibroblast growth factor receptor (Fgfr2), appeared to compromise the osteogenic differentiation potential of BMSCs. Concurrently, DNA methyltransferase inhibitors attenuated the methylation of the promoter regions of Bmp2 and Fgfr2 and rescued the osteogenic differentiation potential of the BMSCs from SHJHhr mice. In summary, our study provides novel insights into the role of DNA methylation in the development of osteoporosis and suggests promising prospects for employing epigenetic interventions to manage osteoporosis.

Three-Dimensional Chromosomal Landscape Revealing miR-146a Dysfunctional Enhancer in Lupus and Establishing a CRISPR-Mediated Approach to Inhibit the Interferon Pathway.

The diminished expression of microRNA-146a (miR-146a) in systemic lupus erythematosus (SLE) contributes to the aberrant activation of the interferon pathway. Despite its significance, the underlying mechanism driving this reduced expression remains elusive. Considering the integral role of enhancers in steering gene expression, our study seeks to pinpoint the SLE-affected enhancers responsible for modulating miR-146a expression. Additionally, we aim to elucidate the mechanisms by which these enhancers influence the contribution of miR-146a to the activation of the interferon pathway. Circular chromosome conformation capture sequencing and epigenomic profiles were applied to identify candidate enhancers of miR-146a. CRISPR activation was performed to screen functional enhancers. Differential analysis of chromatin accessibility was used to identify SLE-dysregulated enhancers, and the mechanism underlying enhancer dysfunction was investigated by analyzing transcription factor binding. The therapeutic value of a lupus-related enhancer was further evaluated by targeting it in the peripheral blood mononuclear cells (PBMCs) of patients with SLE through a CRISPR activation approach. We identified shared and cell-specific enhancers of miR-146a in distinct immune cells. An enhancer 32.5 kb downstream of miR-146a possesses less accessibility in SLE, and its chromatin openness was negatively correlated with SLE disease activity. Moreover, CCAAT/enhancer binding protein α, a down-regulated transcription factor in patients with SLE, binds to the 32.5-kb enhancer and induces the epigenomic change of this locus. Furthermore, CRISPR-based activation of this enhancer in SLE PBMCs could inhibit the activity of interferon pathway. Our work defines a promising target for SLE intervention. We adopted integrative approaches to define cell-specific and functional enhancers of the SLE critical gene and investigated the mechanism underlying its dysregulation mediated by a lupus-related enhancer.