Human genome sequencing in health and disease

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

STAT3 gain-of-function syndrome, characterized by early-onset autoimmunity and primary immune regulatory disorder, remains poorly understood in terms of its immunological mechanisms. We employed whole-genome sequencing of familial trios to elucidate the pivotal role of de novo mutations in genetic diseases. We identified 37 high-risk pathogenic loci affecting 23 genes, including a novel STAT3 c.508G>A mutation. We also observed significant down-regulation of pathogenic genes in affected individuals, potentially associated with inflammatory responses regulated by PTPN14 via miR378c. These findings enhance our understanding of the pathogenesis of STAT3 gain-of-function syndrome and suggest potential therapeutic strategies. Notably, combined JAK inhibitors and IL-6R antagonists may offer promising treatment avenues for mitigating the severity of STAT3 gain-of-function syndrome.

Expanding phenotype of MED13-associated syndrome presenting novel de novo missense variant in a patient with multiple congenital anomalies

BACKGROUND

Whole exome sequencing allows rapid identification of causative single nucleotide variants and short insertions/deletions in children with congenital anomalies and/or intellectual disability, which aids in accurate diagnosis, prognosis, appropriate therapeutic interventions, and family counselling. Recently, de novo variants in the MED13 gene were described in patients with an intellectual developmental disorder that included global developmental delay, mild congenital heart anomalies, and hearing and vision problems in some patients.

RESULTS

Here we describe an infant who carried a de novo p.Pro835Ser missense variant in the MED13 gene, according to whole exome trio sequencing. He presented with congenital heart anomalies, dysmorphic features, hydrocephalic changes, hypoplastic corpus callosum, bilateral optic nerve atrophy, optic chiasm atrophy, brain stem atrophy, and overall a more severe condition compared to previously described patients.

CONCLUSIONS

Therefore, we propose to expand the MED13-associated phenotype to include severe complications that could end up with multiple organ failure and neonatal death.

Personalized medicine and nutrition in hepatology for preventing chronic liver disease in Mexico

Chronic liver disease is a global health issue. Patients with chronic liver disease require a fresh approach that focuses on the genetic and environmental factors that contribute to disease initiation and progression. Emerging knowledge in the fields of Genomic Medicine and Genomic Nutrition demonstrates differences between countries in terms of genetics and lifestyle risk factors such as diet, physical activity, and mental health in chronic liver disease, which serves as the foundation for the implementation of Personalized Medicine and Nutrition (PerMed-Nut) strategies. Most of the world's populations have descended from various ethnic groupings. Mexico's population has a tripartite ancestral background, consisting of Amerindian, European, and African lineages, which is common across Latin America's regional countries. The purpose of this review is to discuss the genetic and environmental components that could be incorporated into a PerMed-Nut model for metabolic-associated liver disease, viral hepatitis B and C, and hepatocellular carcinoma in Mexico. Additionally, the implementation of the PerMed-Nut approach will require updated medicine and nutrition education curricula. Training and equipping future health professionals and researchers with new clinical and investigative abilities focused on preventing liver illnesses in the field of genomic hepatology globally is a vision that clinicians and nutritionists should be concerned about.

Long-term monitoring of ultratrace nucleic acids using tetrahedral nanostructure-based NgAgo on wearable microneedles

Real-time and continuous monitoring of nucleic acid biomarkers with wearable devices holds potential for personal health management, especially in the context of pandemic surveillance or intensive care unit disease. However, achieving high sensitivity and long-term stability remains challenging. Here, we report a tetrahedral nanostructure-based Natronobacterium gregoryi Argonaute (NgAgo) for long-term stable monitoring of ultratrace unamplified nucleic acids (cell-free DNAs and RNAs) in vivo for sepsis on wearable device. This integrated wireless wearable consists of a flexible circuit board, a microneedle biosensor, and a stretchable epidermis patch with enrichment capability. We comprehensively investigate the recognition mechanism of nucleic acids by NgAgo/guide DNA and signal transformation within the Debye distance. In vivo experiments demonstrate the suitability for real-time monitoring of cell-free DNA and RNA with a sensitivity of 0.3 fM up to 14 days. These results provide a strategy for highly sensitive molecular recognition in vivo and for on-body detection of nucleic acid.

High-throughput omics technologies in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic, relapsing intestinal disease. Elucidation of the pathogenic mechanisms of IBD requires high-throughput technologies (HTTs) to effectively obtain and analyze large amounts of data. Recently, HTTs have been widely used in IBD, including genomics, transcriptomics, proteomics, microbiomics, metabolomics and single-cell sequencing. When combined with endoscopy, the application of these technologies can provide an in-depth understanding on the alterations of intestinal microbe diversity and abundance, the abnormalities of signaling pathway-mediated immune responses and functionality, and the evaluation of therapeutic effects, improving the accuracy of early diagnosis and treatment of IBD. This review comprehensively summarizes the development and advancement of HTTs, and also highlights the challenges and future directions of these technologies in IBD research. Although HTTs have made striking breakthrough in IBD, more standardized methods and large-scale dataset processing are still needed to achieve the goal of personalized medicine.

Genomic insights and prognostic significance of novel biomarkers in pancreatic ductal adenocarcinoma: A comprehensive analysis

Pancreatic ductal adenocarcinoma (PDAC) is a highly prevalent digestive system malignancy, with a significant impact on public health, especially in the elderly population. The advent of the Human Genome Project has opened new avenues for precision medicine, allowing researchers to explore genetic markers and molecular targets for cancer diagnosis and treatment. Despite significant advances in genomic research, early diagnosis of pancreatic cancer remains elusive due to the lack of highly sensitive and specific markers. Therefore, there is a need for in-depth research to identify more precise and reliable diagnostic markers for pancreatic cancer. In this study, we utilized a combination of public databases from different sources to meticulously screen genes associated with prognosis in pancreatic cancer. We used gene differential analysis, univariate cox regression analysis, least absolute selection and shrinkage operator (LASSO) regression, and multivariate cox regression analysis to identify genes associated with prognosis. Subsequently, we constructed a scoring system, validated its validity using survival analysis and ROC analysis, and further confirmed its reliability by nomogram and decision curve analysis (DCA). We evaluated the diagnostic value of this scoring system for pancreatic cancer prognosis and validated the function of the genes using single cell data analysis. Our analysis identifies six genes, including GABRA3, IL20RB, CDK1, GPR87, TTYH3, and KCNA2, that were strongly associated with PDAC prognosis. Clinical prognostic models based on these genes showed strong predictive power not only in the training set but also in external datasets. Functional enrichment analysis revealed significant differences between high- and low-risk groups mainly in immune-related functions. Additionally, we explored the potential of the risk score as a marker for immunotherapy response and identified key factors within the tumor microenvironment. The single-cell RNA sequencing analysis further enriched our understanding of cell clusters and six hub genes expressions. This comprehensive investigation provides valuable insights into pancreatic PDAC and its intricate immune landscape. The identified genes and their functional significance underscore the importance of continued research into improving diagnosis and treatment strategies for PDAC.

Genomic insights into heart health: Exploring the genetic basis of cardiovascular disease

Cardiovascular diseases (CVDs) are considered as the leading cause of death worldwide. CVD continues to be a major cause of death and morbidity despite significant improvements in its detection and treatment. Therefore, it is strategically important to be able to precisely characterize an individual's sensitivity to certain illnesses. The discovery of genes linked to cardiovascular illnesses has benefited from linkage analysis and genome-wide association research. The last 20 years have seen significant advancements in the field of molecular genetics, particularly with the development of new tools like genome-wide association studies. In this article we explore the profound impact of genetic variations on disease development, prognosis, and therapeutic responses. And the significance of genetics in cardiovascular risk assessment and the ever-evolving realm of genetic testing, offering insights into the potential for personalized medicine in this domain. Embracing the future of cardiovascular care, the article explores the implications of pharmacogenomics for tailored treatments, the promise of emerging technologies in cardiovascular genetics and therapies, including the transformative influence of nanotechnology. Furthermore, it delves into the exciting frontiers of gene editing, such as CRISPR/Cas9, as a novel approach to combat cardiovascular diseases. And also explore the potential of stem cell therapy and regenerative medicine, providing a holistic view of the dynamic landscape of cardiovascular genomics and its transformative potential for the field of cardiovascular medicine.

Expression of human BRCA2 in Saccharomyces cerevisiae complements the loss of RAD52 in double-strand break repair

BRCA2 is a tumor-suppressor gene that is normally expressed in the breast and ovarian tissue of mammals. The BRCA2 protein mediates the repair of double-strand breaks (DSBs) using homologous recombination, which is a conserved pathway in eukaryotes. Women who express missense mutations in the BRCA2 gene are predisposed to an elevated lifetime risk for both breast cancer and ovarian cancer. In the present study, the efficiency of human BRCA2 (hBRCA2) in DSB repair was investigated in the budding yeast Saccharomyces cerevisiae. While budding yeast does not possess a true BRCA2 homolog, they have a potential functional homolog known as Rad52, which is an essential repair protein involved in mediating homologous recombination using the same mechanism as BRCA2 in humans. Therefore, to examine the functional overlap between Rad52 in yeast and hBRCA2, we expressed the wild-type hBRCA2 gene in budding yeast with or without Rad52 and monitored ionizing radiation resistance and DSB repair efficiency. We found that the expression of hBRCA2 in rad52 mutants increases both radiation resistance and DSB repair frequency compared to cells not expressing BRCA2. Specifically, BRCA2 improved the protection against ionizing radiation by at least 1.93-fold and the repair frequency by 6.1-fold. In addition, our results show that homology length influences repair efficiency in rad52 mutant cells, which impacts BRCA2 mediated repair of DSBs. This study provides evidence that S. cerevisiae could be used to monitor BRCA2 function, which can help in understanding the genetic consequences of BRCA2 variants and how they may contribute to cancer progression.

Clinical implications of RAB13 expression in pan-cancer based on multi-databases integrative analysis

Worldwide, cancer is a huge burden, and each year sees an increase in its incidence. RAB (Ras-related in brain) 13 is crucial for a number of tumor types. But more research on RAB13's tumor-related mechanism is still required. This study's goal was to investigate RAB13's function in human pan-cancer, and we have also preliminarily explored the relevant mechanisms. To investigate the differential expression, survival prognosis, immunological checkpoints, and pathological stage of RAB13 in human pan-cancer, respectively, databases of TIMER2.0, GEPIA 2, and UALCAN were employed. CBioPortal database was used to analyze the mutation level, meanwhile, PPI network was constructed based on STRING website. The putative functions of RAB13 in immunological infiltration were investigated using single sample gene set enrichment analysis (ssGSEA). The mechanism of RAB13 in hepatocellular cancer was also briefly investigated by us using gene set enrichment analysis (GSEA). RAB13 was differentially expressed in a number of different cancers, including liver hepatocellular carcinoma (LIHC), stomach adenocarcinoma (STAD), etc. Additionally, RAB13 overexpression in LGG and LIHC is associated with a worse prognosis, including overall survival (OS) and disease-free survival (DFS). Then, we observed that early in BLCA, BRAC, CHOL, ESCA, HNSC, KICH, KIRC, LIHC, LUAD, LUSC, and STAD, the level of RAB13 expression was raised. Next, we found that "amplification" was the most common mutation in RAB13. The expression of SLC39A1, JTB, SSR2, SNAPIN, and RHOC was strongly positively linked with RAB13, according to a correlation study. RAB13 favorably regulated B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cell in LIHC, according to immune infiltration analysis. Immune checkpoint study revealed a positive correlation between RAB13 expression and PD1, PDL1, and CTLA4 in LIHC. According to GSEA, RAB13 is involved in a number of processes in LIHC, including MTORC1 signaling, MYC targets v1, G2M checkpoint, MITOTIC spindle, DNA repair, P53 pathway, glycolysis, PI3K-AKT-MTOR signaling, etc. RAB13 is a possible therapeutic target in LIHC and can be used as a prognostic marker.

An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer

BACKGROUND

The epithelial-mesenchymal transition (EMT) plays an indispensable role in the development and progression of Endometrial cancer (EC). Nevertheless, little evidence is reported to uncover the functionality and application of EMT-related molecules in the prognosis of EC. This study aims to develop novel molecular markers for prognosis prediction in patients with EC.

METHODS

RNA sequencing profiles of EC patients obtained from The Cancer Genome Atlas (TCGA) database were used to screen differential expression genes (DEGs) between tumors and normal tissues. The Cox regression model with the LASSO method was utilized to identify survival-related DEGs and to establish a prognostic signature whose performance was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC) and calibration curve. Eventually, functional enrichment analysis and cellular experiments were performed to reveal the roles of prognosis-related genes in EC progression.

RESULTS

A total of 540 EMT-related DEGs in EC were screened, and subsequently a four-gene risk signature comprising SIRT2, SIX1, CDKN2A and PGR was established to predict overall survival of EC. This risk signature could serve as a meaningfully independent indicator for EC prognosis via multivariate Cox regression (HR = 2.002, 95%CI = 1.433-2.798; P < 0.001). The nomogram integrating the risk signature and clinical characteristics exhibited robust validity and performance at predicting EC overall survival indicated by ROC and calibration curve. Functional enrichment analysis revealed that the EMT-related genes risk signature was associated with extracellular matrix organization, mesenchymal development and cellular component morphogenesis, suggesting its possible relevance to epithelial-mesenchymal transition and cancer progression. Functionally, we demonstrated that the silencing of SIX1, SIRT2 and CDKN2A expression could accelerate the migratory and invasive capacities of tumor cells, whereas the downregulation of PGR dramatically inhibited cancer cells migration and invasion.

CONCLUSIONS

Altogether, a novel four-EMT-related genes signature was a potential biomarker for EC prognosis. These findings might help to ameliorate the individualized prognostication and therapeutic treatment of EC patients.

Laser capture microdissection for biomedical research: towards high-throughput, multi-omics, and single-cell resolution

Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context, significantly enhancing our understanding of the intricate and multifaceted biological system. With an increasing focus on spatial heterogeneity, there is a growing need for unbiased, spatially resolved omics technologies. Laser capture microdissection (LCM) is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest (ROIs) from heterogeneous tissues, with resolutions ranging from single cells to cell populations. Thus, LCM has been widely used for studying the cellular and molecular mechanisms of diseases. This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research. Key attributes of application cases are also highlighted, such as throughput and spatial resolution. In addition, we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research, disease diagnosis, and targeted therapy from the perspective of high-throughput, multi-omics, and single-cell resolution.

Zebrafish as a robust preclinical platform for screening plant-derived drugs with anticonvulsant properties-a review

Traditionally, selected plant sources have been explored for medicines to treat convulsions. This continues today, especially in countries with low-income rates and poor medical systems. However, in the low-income countries, plant extracts and isolated drugs are in high demand due to their good safety profiles. Preclinical studies on animal models of seizures/epilepsy have revealed the anticonvulsant and/or antiepileptogenic properties of, at least some, herb preparations or plant metabolites. Still, there is a significant number of plants known in traditional medicine that exert anticonvulsant activity but have not been evaluated on animal models. Zebrafish is recognized as a suitable in vivo model of epilepsy research and is increasingly used as a screening platform. In this review, the results of selected preclinical studies are summarized to provide credible information for the future development of effective screening methods for plant-derived antiseizure/antiepileptic therapeutics using zebrafish models. We compared zebrafish vs. rodent data to show the translational value of the former in epilepsy research. We also surveyed caveats in methodology. Finally, we proposed a pipeline for screening new anticonvulsant plant-derived drugs in zebrafish ("from tank to bedside and back again").

Sequence variants contributing to dysregulated inflammatory responses across keratoconic cone surface in adolescent patients with keratoconus

Background

Keratoconus (KTCN) is the most common corneal ectasia resulting in a conical shape of the cornea. Here, genomic variation in the corneal epithelium (CE) across the keratoconic cone surface in patients with KTCN and its relevance in the functioning of the immune system were assessed.

Methods

Samples from four unrelated adolescent patients with KTCN and two control individuals were obtained during the CXL and PRK procedures, respectively. Three topographic regions, central, middle, and peripheral, were separated towards the whole-genome sequencing (WGS) study embracing a total of 18 experimental samples. The coding and non-coding sequence variation, including structural variation, was assessed and then evaluated together with the previously reported transcriptomic outcomes for the same CE samples and full-thickness corneas.

Results

First, pathway enrichment analysis of genes with identified coding variants pointed to "Antigen presentation" and "Interferon alpha/beta signaling" as the most overrepresented pathways, indicating the involvement of inflammatory responses in KTCN. Both coding and non-coding sequence variants were found in genes (or in their close proximity) linked to the previously revealed KTCN-specific cellular components, namely, "Actin cytoskeleton", "Extracellular matrix", "Collagen-containing extracellular matrix", "Focal adhesion", "Hippo signaling pathway", and "Wnt signaling" pathways. No genomic heterogeneity across the corneal surface was found comparing the assessed topographic regions. Thirty-five chromosomal regions enriched in both coding and non-coding KTCN-specific sequence variants were revealed, with a most representative 5q locus previously recognized as involved in KTCN.

Conclusion

The identified genomic features indicate the involvement of innate and adaptive immune system responses in KTCN pathogenesis.

Error-corrected next generation sequencing - Promises and challenges for genotoxicity and cancer risk assessment

Error-corrected Next Generation Sequencing (ecNGS) is rapidly emerging as a valuable, highly sensitive and accurate method for detecting and characterizing mutations in any cell type, tissue or organism from which DNA can be isolated. Recent mutagenicity and carcinogenicity studies have used ecNGS to quantify drug-/chemical-induced mutations and mutational spectra associated with cancer risk. ecNGS has potential applications in genotoxicity assessment as a new readout for traditional models, for mutagenesis studies in 3D organotypic cultures, and for detecting off-target effects of gene editing tools. Additionally, early data suggest that ecNGS can measure clonal expansion of mutations as a mechanism-agnostic early marker of carcinogenic potential and can evaluate mutational load directly in human biomonitoring studies. In this review, we discuss promising applications, challenges, limitations, and key data initiatives needed to enable regulatory testing and adoption of ecNGS - including for advancing safety assessment, augmenting weight-of-evidence for mutagenicity and carcinogenicity mechanisms, identifying early biomarkers of cancer risk, and managing human health risk from chemical exposures.

Computational Assessment of the Expression-modulating Potential for Non-coding Variants

Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN's superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.

What Can De Novo Protein Design Bring to the Treatment of Hematological Disorders?

Protein therapeutics have been widely used to treat hematological disorders. With the advent of de novo protein design, protein therapeutics are not limited to ameliorating natural proteins but also produce novel protein sequences, folds, and functions with shapes and functions customized to bind to the therapeutic targets. De novo protein techniques have been widely used biomedically to design novel diagnostic and therapeutic drugs, novel vaccines, and novel biological materials. In addition, de novo protein design has provided new options for treating hematological disorders. Scientists have designed protein switches called Colocalization-dependent Latching Orthogonal Cage-Key pRoteins (Co-LOCKR) that perform computations on the surface of cells. De novo designed molecules exhibit a better capacity than the currently available tyrosine kinase inhibitors in chronic myeloid leukemia therapy. De novo designed protein neoleukin-2/15 enhances chimeric antigen receptor T-cell activity. This new technique has great biomedical potential, especially in exploring new treatment methods for hematological disorders. This review discusses the development of de novo protein design and its biological applications, with emphasis on the treatment of hematological disorders.

Opportunities and challenges for newborn screening and early diagnosis of rare diseases in Latin America

Rare diseases (RDs) cause considerable death and disability in Latin America. Still, there is no consensus on their definition across the region. Patients with RDs face a diagnostic odyssey to find a correct diagnosis, which may last many years and creates a burden for caregivers, healthcare systems, and society. These diagnostic delays have repercussions on the health and economic burden created by RDs and continue to represent an unmet medical need. This review analyzes barriers to the widespread adoption of newborn screening (NBS) programs and early diagnostic methods for RDs in Latin America and provides recommendations to achieve this critical objective. Increasing the adoption of NBS programs and promoting early diagnosis of RDs are the first steps to improving health outcomes for patients living with RDs. A coordinated, multistakeholder effort from leaders of patient organizations, government, industry, medical societies, academia, and healthcare services is required to increase the adoption of NBS programs. Patients' best interests should remain the guiding principle for decisions regarding NBS implementation and early diagnosis for RDs.

Analysis of the Potential Relationship between Aging and Pulmonary Fibrosis Based on Transcriptome

Idiopathic pulmonary fibrosis (IPF) is an age-related interstitial lung disease with a high incidence in the elderly. Although many reports have shown that senescence can initiate pulmonary fibrosis, the relationship between aging and pulmonary fibrosis has not been explained systematically. In our study, young and old rats were intratracheally instilled with bleomycin (1 mg/kg), and the basic pathological indexes were determined using a commercial kit, hematoxylin, and eosin (H&E) and Masson's Trichrome staining, immunohistochemistry, immunohistofluorescence, and q-PCR. Then, the lung tissues of rats were sequenced by next-generation sequencing for transcriptome analysis. Bioinformatics was performed to analyze the possible differences in the mechanism of pulmonary fibrosis between aged and young rats. Finally, the related cytokines were determined by q-PCR and ELISA. The results indicate that pulmonary fibrosis in old rats is more serious than that in young rats under the same conditions. Additionally, transcriptomic and bioinformatics analysis with experimental validation indicate that the differences in pulmonary fibrosis between old and young rats are mainly related to the differential expression of cytokines, extracellular matrix (ECM), and other important signaling pathways. In conclusion, aging mainly affects pulmonary fibrosis through the ECM-receptor interaction, immune response, and chemokines.

MinION Whole-Genome Sequencing in Resource-Limited Settings: Challenges and Opportunities

Purpose of Review

The introduction of MinION whole-genome sequencing technology greatly increased and simplified complete genome sequencing in various fields of science across the globe. Sequences have been generated from complex organisms to microorganisms and are stored in genome databases that are readily accessible by researchers. Various new software for genome analysis, along with upgrades to older software packages, are being generated. New protocols are also being validated that enable WGS technology to be rapidly and increasingly used for sequencing in field settings.

Recent Findings

MinION WGS technology has been implemented in developed countries due to its advantages: portability, real-time analysis, and lower cost compared to other sequencing technologies. While these same advantages are critical in developing countries, MinION WGS technology is still under-utilized in resource-limited settings.

Summary

In this review, we look at the applications, advantages, challenges, and opportunities of using MinION WGS in resource-limited settings.

Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty

Climate change is an anthropogenic phenomenon that is alarming scientists and non-scientists alike. The emission of greenhouse gases is causing the temperature of the earth to rise and this increase is accompanied by a multitude of climate change-induced environmental exposures with potential health impacts. Tracking human exposure has been a major research interest of scientists worldwide. This has led to the development of exposome studies that examine internal and external individual exposures over their lifetime and correlate them to health. The monitoring of health has also benefited from significant technological advances in the field of "omics" technologies that analyze physiological changes on the nucleic acid, protein, and metabolism levels, among others. In this review, we discuss various climate change-induced environmental exposures and their potential health implications. We also highlight the potential integration of the technological advancements in the fields of exposome tracking, climate monitoring, and omics technologies shedding light on important questions that need to be answered.

Impact of returning unsolicited genomic results to nongenetic health care providers in the eMERGE III Network

PURPOSE

As genomic sequencing becomes more common, medically actionable secondary findings will increasingly be returned to health care providers (HCPs), who will be faced with managing the resulting patient care. These findings are generally unsolicited, ie, unrelated to the sequencing indication and/or ordered by another clinician.

METHODS

To understand the impact of receiving unsolicited results, we interviewed HCPs who received genomic results for patients enrolled in the Electronic Medical Records and Genomics (eMERGE) Phase III Network, which returned results on >100 actionable genes to eMERGE participants and HCPs.

RESULTS

In total, 16 HCPs across 3 eMERGE sites were interviewed about their experience of receiving a positive (likely pathogenic or pathogenic), negative, or variant of uncertain significance result for a patient enrolled in eMERGE Phase III and about managing their patient on the basis of the result. Although unsolicited, HCPs felt responsible for managing the patient's resulting medical care. HCPs indicated that clinical utility depended on the actionability of results, and whereas comfort levels varied, confidence was improved by the availability of subspecialist consults. HCPs were concerned about patient anxiety, insurability, and missing an actionable result in the electronic health record.

CONCLUSION

Our findings help inform best practices for return of unsolicited genomic screening findings in the future.

Mutational Screening of Skeletal Genes in 14 Chinese Children with Osteogenesis Imperfecta Using Targeted Sequencing

Background

As a heterogeneous hereditary connective tissue disorder, osteogenesis imperfecta (OI) is clinically characterized by increased fracture susceptibility. Analysis of genetic pathogenic variants in patients with OI provides a basis for genetic counseling and prenatal diagnosis.

Methods

In this study, 14 diagnosed OI patients from sporadic Chinese families were enrolled to be screened for potential mutations from these patients by next-generation sequencing technology.

Results

34 different variants were identified. 18 variants were from 4 OI-related genes including COL1A1, COL1A2, P3H1, and WNT1, and 10 variants are novel. Most OI patients (11 out of 14, 78%) harbor variants in type I collagen genes.

Conclusions

Our results support previously established estimates of the distribution and prevalence of OI mutations and highlight both phenotype and genetic heterogeneity among and within families. We report several novel variants of OI, which expands the clinical spectrum of OI. In summary, our data provides disease-causing genes information for genetic counseling towards OI patients and families and also provides a reference for clinicians in the diagnosis of OI, also in prenatal diagnosis of this disease.

RNA polyadenylation patterns in the human transcriptome

The eukaryotic transcriptome undergoes various post-transcriptional modifications which assists gene expression. Polyadenylation is a molecular process occurring at the 3'-end of the RNA molecule which involves the poly(A) polymerase attaching adenine monophosphate molecules in a chain-like fashion to assemble a poly(A) tail. Multiple RNA isoforms are produced with differing 3'-UTR and exonic compositions through alternative polyadenylation (APA) which enhances the diversification of alternatively spliced mRNA transcripts. To study polyadenylation patterns, novel methods have been developed using short-read and long-read sequencing technologies to analyse the 3'-ends of the transcript. Recent studies have identified unique polyadenylation patterns in different cellular functions, including oncogenic activity, which could prove valuable in the understanding of medical genetics, particularly in the discovery of biomarkers in diseased states. We present a review of current literature reporting on polyadenylation and the biological relevance in the mammalian transcriptome, with a focus on the human transcriptome. Additionally, we have explored the various methods available to detect polyadenylation patterns using second and third generation sequencing technologies.

Comparison of seven SNP calling pipelines for the next-generation sequencing data of chickens

Single nucleotide polymorphisms (SNPs) are widely used in genome-wide association studies and population genetics analyses. Next-generation sequencing (NGS) has become convenient, and many SNP-calling pipelines have been developed for human NGS data. We took advantage of a gap knowledge in selecting the appropriated SNP calling pipeline to handle with high-throughput NGS data. To fill this gap, we studied and compared seven SNP calling pipelines, which include 16GT, genome analysis toolkit (GATK), Bcftools-single (Bcftools single sample mode), Bcftools-multiple (Bcftools multiple sample mode), VarScan2-single (VarScan2 single sample mode), VarScan2-multiple (VarScan2 multiple sample mode) and Freebayes pipelines, using 96 NGS data with the different depth gradients of approximately 5X, 10X, 20X, 30X, 40X, and 50X coverage from 16 Rhode Island Red chickens. The sixteen chickens were also genotyped with a 50K SNP array, and the sensitivity and specificity of each pipeline were assessed by comparison to the results of SNP arrays. For each pipeline, except Freebayes, the number of detected SNPs increased as the input read depth increased. In comparison with other pipelines, 16GT, followed by Bcftools-multiple, obtained the most SNPs when the input coverage exceeded 10X, and Bcftools-multiple obtained the most when the input was 5X and 10X. The sensitivity and specificity of each pipeline increased with increasing input. Bcftools-multiple had the highest sensitivity numerically when the input ranged from 5X to 30X, and 16GT showed the highest sensitivity when the input was 40X and 50X. Bcftools-multiple also had the highest specificity, followed by GATK, at almost all input levels. For most calling pipelines, there were no obvious changes in SNP numbers, sensitivities or specificities beyond 20X. In conclusion, (1) if only SNPs were detected, the sequencing depth did not need to exceed 20X; (2) the Bcftools-multiple may be the best choice for detecting SNPs from chicken NGS data, but for a single sample or sequencing depth greater than 20X, 16GT was recommended. Our findings provide a reference for researchers to select suitable pipelines to obtain SNPs from the NGS data of chickens or nonhuman animals.

Improving one-step scarless genome editing in Drosophila melanogaster by combining ovoD co-CRISPR selection with sgRNA target site masking

The precise and rapid construction of alleles through CRISPR/Cas9-mediated genome engineering renders Drosophila melanogaster a powerful animal system for molecular structure–function analyses and human disease models. Application of the ovo^D co-selection method offers expedited generation and enrichment of scarlessly edited alleles without the need for linked transformation markers, which specifically in the case of exon editing can impact allele usability. However, we found that knockin procedures by homology-directed repair (HDR) under ovo^D co-selection resulted in low transformation efficiency. This is likely due to repeated rounds of Cas9 cleavage of HDR donor and/or engineered genomic locus DNA, as noted for other CRISPR/Cas9 editing strategies before, impeding the recovery of correctly edited alleles. Here we provide a one-step protocol to improve the generation of scarless alleles by ovo^D-co-selection with single-guide RNA (sgRNA) binding site masking. Using this workflow, we constructed human disease alleles for two Drosophila genes, unc-13/CG2999 and armadillo/CG11579. We show and quantify how a known countermeasure, the insertion of silent point mutations into protospacer adjacent motif (PAM) or sgRNA homology regions, can potently suppress unintended sequence modifications during CRISPR/Cas9 genome editing of D. melanogaster under ovo^D co-selection. This strongly increased the recovery frequency of disease alleles.

Towards organism-level systems biology by next-generation genetics and whole-organ cell profiling

The system-level identification and analysis of molecular and cellular networks in mammals can be accelerated by "next-generation" genetics, which is defined as genetics that can achieve desired genetic makeup in a single generation without any animal crossing. We recently established a highly efficient procedure for producing knock-out (KO) mice using the "Triple-CRISPR" method, which targets a single gene by triple gRNAs in the CRISPR/Cas9 system. This procedure achieved an almost perfect KO efficiency (96-100%). We also established a highly efficient procedure, the "ES-mouse" method, for producing knock-in (KI) mice within a single generation. In this method, ES cells were treated with three inhibitors to keep their potency and then injected into 8-cell-stage embryos. These procedures dramatically shortened the time required to produce KO or KI mice from years down to about 3 months. The produced KO and KI mice can also be systematically profiled at a single-cell resolution by the "whole-organ cell profiling," which was realized by tissue-clearing methods, such as CUBIC, and an advanced light-sheet microscopy. The review describes the establishment and application of these technologies above in analyzing the three states (NREM sleep, REM sleep, and awake) of mammalian brains. It also discusses the role of calcium and muscarinic receptors in these states as well as the current challenges and future opportunities in the next-generation mammalian genetics and whole-organ cell profiling for organism-level systems biology.

'Omics' of suicidal behaviour: A path to personalised psychiatry

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis

Endometrial hyperplasia (EH) is a precursor for endometrial cancer (EC). However, biomarkers for the progression from EH to EC and standard prognostic biomarkers for EC have not been identified. In this study, we aimed to identify key genes with prognostic significance for the progression from EH to EC. Weighted-gene correlation network analysis (WGCNA) was used to identify hub genes utilizing microarray data (GSE106191) downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified from the Uterine Corpus Endometrial Carcinoma (UCEC) dataset of The Cancer Genome Atlas database. The Limma-Voom R package was applied to detect differentially expressed genes (DEGs; mRNAs) between cancer and normal samples. Genes with |log2 (fold change [FC])| > 1.0 and p < 0.05 were considered as DEGs. Univariate and multivariate Cox regression and survival analyses were performed to identify potential prognostic genes using hub genes overlapping in the two datasets. All analyses were conducted using R Bioconductor and related packages. Through WGCNA and overlapping genes in hub modules with DEGs in the UCEC dataset, we identified 42 hub genes. The results of the univariate and multivariate Cox regression analyses revealed that four hub genes, BUB1B, NDC80, TPX2, and TTK, were independently associated with the prognosis of EC (Hazard ratio [95% confidence interval]: 0.591 [0.382–0.912], p = 0.017; 0.605 [0.371–0.986], p = 0.044; 1.678 [1.132–2.488], p = 0.01; 2.428 [1.372–4.29], p = 0.02, respectively). A nomogram was established with a risk score calculated using the four genes’ coefficients in the multivariate analysis, and tumor grade and stage had a favorable predictive value for the prognosis of EC. The survival analysis showed that the high-risk group had an unfavorable prognosis compared with the low-risk group (p < 0.0001). The receiver operating characteristic curves also indicated that the risk model had a potential predictive value of prognosis with area under the curve 0.807 at 2 years, 0.783 at 3 years, and 0.786 at 5 years. We established a four-gene signature with prognostic significance in EC using WGCNA and established a nomogram to predict the prognosis of EC.

Deciphering pathogenicity of variants of uncertain significance with CRISPR-edited iPSCs

Genetic variants play an important role in conferring risk for cardiovascular diseases (CVDs). With the rapid development of next-generation sequencing (NGS), thousands of genetic variants associated with CVDs have been identified by genome-wide association studies (GWAS), but the function of more than 40% of genetic variants is still unknown. This gap of knowledge is a barrier to the clinical application of the genetic information. However, determining the pathogenicity of a variant of uncertain significance (VUS) is challenging due to the lack of suitable model systems and accessible technologies. By combining clustered regularly interspaced short palindromic repeats (CRISPR) and human induced pluripotent stem cells (iPSCs), unprecedented advances are now possible in determining the pathogenicity of VUS in CVDs. Here, we summarize recent progress and new strategies in deciphering pathogenic variants for CVDs using CRISPR-edited human iPSCs.

A scalable Drosophila assay for clinical interpretation of human PTEN variants in suppression of PI3K/AKT induced cellular proliferation

Gene variant discovery is becoming routine, but it remains difficult to usefully interpret the functional consequence or disease relevance of most variants. To fill this interpretation gap, experimental assays of variant function are becoming common place. Yet, it remains challenging to make these assays reproducible, scalable to high numbers of variants, and capable of assessing defined gene-disease mechanism for clinical interpretation aligned to the ClinGen Sequence Variant Interpretation (SVI) Working Group guidelines for 'well-established assays'. Drosophila melanogaster offers great potential as an assay platform, but was untested for high numbers of human variants adherent to these guidelines. Here, we wished to test the utility of Drosophila as a platform for scalable well-established assays. We took a genetic interaction approach to test the function of ~100 human PTEN variants in cancer-relevant suppression of PI3K/AKT signaling in cellular growth and proliferation. We validated the assay using biochemically characterized PTEN mutants as well as 23 total known pathogenic and benign PTEN variants, all of which the assay correctly assigned into predicted functional categories. Additionally, function calls for these variants correlated very well with our recent published data from a human cell line. Finally, using these pathogenic and benign variants to calibrate the assay, we could set readout thresholds for clinical interpretation of the pathogenicity of 70 other PTEN variants. Overall, we demonstrate that Drosophila offers a powerful assay platform for clinical variant interpretation, that can be used in conjunction with other well-established assays, to increase confidence in the accurate assessment of variant function and pathogenicity.

Molecular autopsy by proxy in preconception counseling

Monogenic diseases that result in early pregnancy loss or neonatal death are genetically and phenotypically highly variable. This often poses significant challenges in arriving at a molecular diagnosis for reproductive planning. Molecular autopsy by proxy (MABP) refers to the genetic testing of relatives of deceased individuals to deduce the cause of death. Here, we specifically tested couples who lost one or more children/pregnancies with no available DNA. We developed our testing strategy using whole exome sequencing data from 83 consanguineous Saudi couples. We detected the shared carrier state of 50 pathogenic variants/likely pathogenic variants in 43 families and of 28 variants of uncertain significance in 24 families. Negative results were seen in 16 couples after variant reclassification. In 10 families, the risk of more than one genetic disease was documented. Secondary findings were seen in 10 families: either genetic variants with potential clinical consequences for the tested individual or a female carrier for X‐linked conditions. This couple‐based approach has enabled molecularly informed genetic counseling for 52% (43/83 families). Given the predominance of autosomal recessive causes of pregnancy and child death in consanguineous populations, MABP can be a helpful approach to consanguineous couples who seek counseling but lack molecular data on their deceased offspring.

REVA as A Well-curated Database for Human Expression-modulating Variants

More than 90% of disease- and trait-associated human variants are noncoding. By systematically screening multiple large-scale studies, we compiled REVA, a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials. We provided 2424 functional annotations that could be used to pinpoint the plausible regulatory mechanism of these variants. We further benchmarked multiple state-of-the-art computational tools and found their limited sensitivity remains a serious challenge for effective large-scale analysis. REVA provides high-quality experimentally tested expression-modulating variants with extensive functional annotations, which will be useful for users in the noncoding variants community. REVA is available at http://reva.gao-lab.org.

Approach to genetic diagnosis of inborn errors of immunity through next-generation sequencing

Patients with inborn errors of immunity (IEI) present with a heterogeneous clinical and immunological phenotype, therefore a correct molecular diagnosis is crucial for the classification and subsequent therapeutic management. On the other hand, IEI are a group of rare congenital diseases with highly diverse features and, in most cases, an as yet unknown genetic etiology. Next generation sequencing has facilitated genetic examinations of rare inherited disorders during the recent years, thus allowing a suitable molecular diagnosis in the IEI patients. This review aimed to investigate the current findings about these techniques in the field of IEI, suggesting an efficient stepwise approach to molecular diagnosis of inborn errors of immunity.

Shall genomic correlation structure be considered in copy number variants detection?

Copy number variation has been identified as a major source of genomic variation associated with disease susceptibility. With the advent of whole-exome sequencing (WES) technology, massive WES data have been generated, allowing for the identification of copy number variants (CNVs) in the protein-coding regions with direct functional interpretation. We have previously shown evidence of the genomic correlation structure in array data and developed a novel chromosomal breakpoint detection algorithm, LDcnv, which showed significantly improved detection power through integrating the correlation structure in a systematic modeling manner. However, it remains unexplored whether the genomic correlation exists in WES data and how such correlation structure integration can improve the CNV detection accuracy. In this study, we first explored the correlation structure of the WES data using the 1000 Genomes Project data. Both real raw read depth and median-normalized data showed strong evidence of the correlation structure. Motivated by this fact, we proposed a correlation-based method, CORRseq, as a novel release of the LDcnv algorithm in profiling WES data. The performance of CORRseq was evaluated in extensive simulation studies and real data analysis from the 1000 Genomes Project. CORRseq outperformed the existing methods in detecting medium and large CNVs. In conclusion, it would be more advantageous to model genomic correlation structure in detecting relatively long CNVs. This study provides great insights for methodology development of CNV detection with NGS data.

Therapies Targeted at Non-Coding RNAs in Prevention and Limitation of Myocardial Infarction and Subsequent Cardiac Remodeling-Current Experience and Perspectives

Myocardial infarction is one of the major causes of mortality worldwide and is a main cause of heart failure. This disease appears as a final point of atherosclerotic plaque progression, destabilization, and rupture. As a consequence of cardiomyocytes death during the infarction, the heart undergoes unfavorable cardiac remodeling, which results in its failure. Therefore, therapies aimed to limit the processes of atherosclerotic plaque progression, cardiac damage during the infarction, and subsequent remodeling are urgently warranted. A hopeful therapeutic option for the future medicine is targeting and regulating non-coding RNA (ncRNA), like microRNA, circular RNA (circRNA), or long non-coding RNA (lncRNA). In this review, the approaches targeted at ncRNAs participating in the aforementioned pathophysiological processes involved in myocardial infarction and their outcomes in preclinical studies have been concisely presented.

Rare disease patient matchmaking: development and outcomes of an internet case-finding strategy in the Undiagnosed Diseases Network

BACKGROUND

Although clinician, researcher, and patient resources for matchmaking exist, finding similar patients remains an obstacle for rare disease diagnosis. The goals of this study were to develop and test the effectiveness of an Internet case-finding strategy and identify factors associated with increased matching within a rare disease population.

METHODS

Public web pages were created for consented participants. Matches made, time to each inquiry and match, and outcomes were recorded and analyzed using descriptive statistics. A Poisson regression model was run to identify characteristics associated with matches.

RESULTS

385 participants were referred to the project and 158 had pages posted. 579 inquiries were received; 89.0% were from the general public and 24.7% resulted in a match. 81.6% of pages received at least one inquiry and 15.0% had at least one patient match. Primary symptom category of neurology, diagnosis, gene page, and photo were associated with increased matches (p ≤ 0.05).

CONCLUSIONS

This Internet case-finding strategy was of interest to patients, families, and clinicians, and similar patients were identified using this approach. Extending matchmaking efforts to the general public resulted in matches and suggests including this population in matchmaking activities can improve identification of similar patients.

Gene Size Matters: An Analysis of Gene Length in the Human Genome

While it is expected for gene length to be associated with factors such as intron number and evolutionary conservation, we are yet to understand the connections between gene length and function in the human genome. In this study, we show that, as expected, there is a strong positive correlation between gene length, transcript length, and protein size as well as a correlation with the number of genetic variants and introns. Among tissue-specific genes, we find that the longest transcripts tend to be expressed in the blood vessels, nerves, thyroid, cervix uteri, and the brain, while the smallest transcripts tend to be expressed in the pancreas, skin, stomach, vagina, and testis. We report, as shown previously, that natural selection suppresses changes for genes with longer transcripts and promotes changes for genes with smaller transcripts. We also observe that genes with longer transcripts tend to have a higher number of co-expressed genes and protein-protein interactions, as well as more associated publications. In the functional analysis, we show that bigger transcripts are often associated with neuronal development, while smaller transcripts tend to play roles in skin development and in the immune system. Furthermore, pathways related to cancer, neurons, and heart diseases tend to have genes with longer transcripts, with smaller transcripts being present in pathways related to immune responses and neurodegenerative diseases. Based on our results, we hypothesize that longer genes tend to be associated with functions that are important in the early development stages, while smaller genes tend to play a role in functions that are important throughout the whole life, like the immune system, which requires fast responses.

Drug Repurposing for Rare Diseases

Currently, there are about 7000 identified rare diseases, together affecting 10% of the population. However, fewer than 6% of all rare diseases have an approved treatment option, highlighting their tremendous unmet needs in drug development. The process of repurposing drugs for new indications, compared with the development of novel orphan drugs, is a time-saving and cost-efficient method resulting in higher success rates, which can therefore drastically reduce the risk of drug development for rare diseases. Although drug repurposing is not novel, new strategies have been developed in recent years to do it in a systematic and rational way. Here, we review applied methodologies, recent accomplished progress, and the challenges associated in drug repurposing for rare diseases.

Cost Effectiveness of Whole Exome Sequencing for Children with Developmental Delay in a Developing Country: A Study from Jordan

This retrospective study aimed to determine the cost effectiveness of whole exome sequencing (WES) in the diagnosis of children with developmental delay in a developing country. In this study of 40 patients, the average cost of traditional investigations and indirect costs related to rehabilitation and medications per child were USD847 and 6,585 per year, respectively. With a current cost for WES of approximately USD1,200, we concluded that performing WES could be cost effective, even in countries with limited resources, as it provides the option for genetic counseling in affected families with an ultimate reduction of overall financial burden to both parents and health care system.

Understanding In Vivo Fate of Nucleic Acid and Gene Medicines for the Rational Design of Drugs

Nucleic acid and genetic medicines are increasingly being developed, owing to their potential to treat a variety of intractable diseases. A comprehensive understanding of the in vivo fate of these agents is vital for the rational design, discovery, and fast and straightforward development of the drugs. In case of intravascular administration of nucleic acids and genetic medicines, interaction with blood components, especially plasma proteins, is unavoidable. However, on the flip side, such interaction can be utilized wisely to manipulate the pharmacokinetics of the agents. In other words, plasma protein binding can help in suppressing the elimination of nucleic acids from the blood stream and deliver naked oligonucleotides and gene carriers into target cells. To control the distribution of these agents in the body, the ligand conjugation method is widely applied. It is also important to understand intracellular localization. In this context, endocytosis pathway, endosomal escape, and nuclear transport should be considered and discussed. Encapsulated nucleic acids and genes must be dissociated from the carriers to exert their activity. In this review, we summarize the in vivo fate of nucleic acid and gene medicines and provide guidelines for the rational design of drugs.

A multi-omics view of the complex mechanism of vascular calcification

Vascular calcification is a high incidence and high risk disease with increasing morbidity and high mortality, which is considered the consequence of smooth muscle cell transdifferentiation initiating the mechanism of accumulation of hydroxyl calcium phosphate. Vascular calcification is also thought to be strongly associated with poor outcomes in diabetes and chronic kidney disease. Numerous studies have been accomplished; however, the specific mechanism of the disease remains unclear. Development of the genome project enhanced the understanding of life science and has entered the post-genomic era resulting in a variety of omics techniques used in studies and a large amount of available data; thus, a new perspective on data analysis has been revealed. Omics has a broader perspective and is thus advantageous over a single pathway analysis in the study of complex vascular calcification mechanisms. This paper reviews in detail various omics studies including genomics, proteomics, transcriptomics, metabolomics and multiple group studies on vascular calcification. Advances and deficiencies in the use of omics to study vascular calcification are presented in a comprehensive view. We also review the methodology of the omics studies and omics data analysis and processing. In addition, the methodology and data processing presented here can be applied to other areas. An omics landscape perspective across the boundaries between genomics, transcriptomics, proteomics and metabolomics is used to examine the mechanisms of vascular calcification. The perspective combined with various technologies also provides a direction for the subsequent exploration of clinical significance.

Chemical Proteomics for Expanding the Druggability of Human Disease

Over the past decade, chemical proteomics has emerged as a powerful technique to understand small molecule and protein function in the physiological system and plays a key role in unravelling the cellular targets of pharmacological modulators. Chemical proteomics that integrates activity-based protein profiling (ABPP) with mass spectrometry has been introduced to evaluate small-molecule and protein interaction and expand the druggable proteome. A much larger fraction of the human proteome can now be targeted by small molecules than estimated by past predictions of protein druggability.

Exome sequencing and characterization of 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world¹. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery

Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98% of the genome and are distributed unevenly across chromosomes. MCRs containing the same MCS tend to be located on the same chromosome. Gene Ontology (GO) analyses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgi-related cellular component terms and various enzymatic activities in the GO biological function category. MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks. Moreover, genetic variants discovered by genome-wide association studies and recorded in dbSNP are significantly underrepresented in MCRs. Using simulated HTS datasets, we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions. These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.

An evolutionary, or "Mitocentric" perspective on cellular function and disease

The incidence of common, metabolic diseases (e.g. obesity, cardiovascular disease, diabetes) with complex genetic etiology has been steadily increasing nationally and globally. While identification of a genetic model that explains susceptibility and risk for these diseases has been pursued over several decades, no clear paradigm has yet been found to disentangle the genetic basis of polygenic/complex disease development. Since the evolution of the eukaryotic cell involved a symbiotic interaction between the antecedents of the mitochondrion and nucleus (which itself is a genetic hybrid), we suggest that this history provides a rational basis for investigating whether genetic interaction and co-evolution of these genomes still exists. We propose that both mitochondrial and Mendelian, or "mito-Mendelian" genetics play a significant role in cell function, and thus disease risk. This paradigm contemplates the natural variation and co-evolution of both mitochondrial and nuclear DNA backgrounds on multiple mitochondrial functions that are discussed herein, including energy production, cell signaling and immune response, which collectively can influence disease development. At the nexus of these processes is the economy of mitochondrial metabolism, programmed by both mitochondrial and nuclear genomes.

Histone modifications in epigenetic regulation of cancer: Perspectives and achieved progress

Epigenetic changes associated with histone modifications play an important role in the emergence and maintenance of the phenotype of various cancer types. In contrast to direct mutations in the main DNA sequence, these changes are reversible, which makes the development of inhibitors of enzymes of post-translational histone modifications one of the most promising strategies for the creation of anticancer drugs. To date, a wide variety of histone modifications have been found that play an important role in the regulation of chromatin state, gene expression, and other nuclear events. This review examines the main features of the most common and studied epigenetic histone modifications with a proven role in the pathogenesis of a wide range of malignant neoplasms: acetylation / deacetylation and methylation / demethylation of histone proteins, as well as the role of enzymes of the HAT / HDAC and HMT / HDMT families in the development of oncological pathologies. The data on the relationship between histone modifications and certain types of cancer are presented and discussed. Special attention is devoted to the consideration of various strategies for the development of epigenetic inhibitors. The main directions of the development of inhibitors of histone modifications are analyzed and effective strategies for their creation are identified and discussed. The most promising strategy is the use of multitarget drugs, which will affect multiple molecular targets of cancer. A critical analysis of the current status of approved epigenetic anticancer drugs has also been performed.