Plot protein: visualization of mutations

Genetic variant profiling of neonatal diabetes mellitus in Iranian patients: Unveiling 58 distinct variants in 14 genes

INTRODUCTION

Neonatal diabetes mellitus (NDM) is a rare non-immunological monogenic disorder characterized by hyperglycemic conditions primarily occurring within the first 6 months of life. The majority of cases are attributed to pathogenic variants in genes affecting beta-cell survival, insulin regulation, and secretion. This study aims to investigate the genetic landscape of NDM in Iran.

METHODS

We recruited a total of 135 patients who were initially diagnosed with diabetes at <12 months of age in Iran and referred to pediatric endocrinology clinics across the country. These patients underwent genetic diagnostic tests conducted by the Exeter Molecular Genetics Laboratory in the UK. The pathogenic variants identified were sorted and described based on type, pathogenicity (according to ACMG/AMP criteria), novelty, and the affected protein domain.

RESULTS

Genetic defects were identified in 93 probands, presenting various pathogenic abnormalities associated with NDM and its associated syndromes. 76% of the patients were born as a result of consanguineous marriage, and a familial history of diabetes was found in 43% of the cases. A total of 58 distinct variants in 14 different genes were discovered, including 20 variants reported for the first time. Causative variants were most frequently identified in EIF2AK3, KCNJ11, and ABCC8, respectively. Notably, EIF2AK3 and ABCC8 exhibited the highest number of novel variants.

DISCUSSION

These findings provide valuable insights into the genetic landscape of NDM in the Iranian population and contribute to the knowledge of novel pathogenic variants within known causative genes.

Structure of SALL4 zinc finger domain reveals link between AT-rich DNA binding and Okihiro syndrome

Spalt-like 4 (SALL4) maintains vertebrate embryonic stem cell identity and is required for the development of multiple organs, including limbs. Mutations in SALL4 are associated with Okihiro syndrome, and SALL4 is also a known target of thalidomide. SALL4 protein has a distinct preference for AT-rich sequences, recognised by a pair of zinc fingers at the C-terminus. However, unlike many characterised zinc finger proteins, SALL4 shows flexible recognition with many different combinations of AT-rich sequences being targeted. SALL4 interacts with the NuRD corepressor complex which potentially mediates repression of AT-rich genes. We present a crystal structure of SALL4 C-terminal zinc fingers with an AT-rich DNA sequence, which shows that SALL4 uses small hydrophobic and polar side chains to provide flexible recognition in the major groove. Missense mutations reported in patients that lie within the C-terminal zinc fingers reduced overall binding to DNA but not the preference for AT-rich sequences. Furthermore, these mutations altered association of SALL4 with AT-rich genomic sites, providing evidence that these mutations are likely pathogenic.

Causative variants linked with limb girdle muscular dystrophy in an Iranian population: 6 novel variants

BACKGROUND

Limb-girdle muscular dystrophy (LGMD) is a non-syndromic muscular dystrophy caused by variations in the genes involved in muscle structure, function and repair. The heterogeneity in the severity, progression, age of onset, and causative genes makes next-generation sequencing (NGS) a necessary approach for the proper diagnosis of LGMD.

METHODS

In this article, 26 Iranian patients with LGMD criteria were diagnosed with disease variants in the genes encoding calpain3, dysferlin, sarcoglycans and Laminin α-2. Patients were referred to the hospital with variable distribution of muscle wasting and progressive weakness in the body. The symptoms along with biochemical and EMG tests were suggestive of LGMD; thus the genomic DNA of patients were investigated by whole-exome sequencing including flanking intronic regions. The target genes were explored for the disease-causing variants. Moreover, the consequence of the amino acid alterations on proteins' secondary structure and function was investigated for a better understanding of the pathogenicity of variants. Variants were sorted based on the genomic region, type and clinical significance.

RESULTS

In a comprehensive investigation of previous clinical records, 6 variations were determined as novel, including c.1354-2 A > T and c.3169_3172dupCGGC in DYSF, c.568 G > T in SGCD, c.7243 C > T, c.8662_8663 insT and c. 4397G > C in LAMA2. Some of the detected variants were located in functional domains and/or near to the post-translational modification sites, altering or removing highly conserved regions of amino acid sequence.

Neurofibromatosis-1 Gene Mutational Profiles Differ Between Syndromic Disease and Sporadic Cancers

Objectives

Variants in the neurofibromatosis type 1 (NF1) gene are not only responsible for the NF1 cancer predisposition syndrome, but also frequently identified in cancers arising in the general population. While germline variants are pathogenic, it is not known whether those that arise in cancer (somatic variants) are passenger or driver variants. To address this question, we sought to define the landscape of NF1 variants in sporadic cancers.

Methods

NF1 variants in sporadic cancers were compiled using data curated on the c-Bio database and compared with published germline variants and Genome Aggregation Database data. Pathogenicity was determined using Polyphen and Sorting Intolerant From Tolerant prediction tools.

Results

The spectrum of NF1 variants in sporadic tumors differ from those most commonly seen in individuals with NF1. In addition, the type and location of the variants in sporadic cancer differ from germline variants, where a high proportion of missense variants were found. Finally, many of the sporadic cancer NF1 variants were not predicted to be pathogenic.

Discussion

Taken together, these findings suggest that a significant proportion of NF1 variants in sporadic cancer may be passenger variants or hypomorphic alleles. Further mechanistic studies are warranted to define their unique roles in nonsyndromic cancer pathobiology.

Oral Phenotype of Singleton-Merten Syndrome: A Systematic Review Illustrated With a Case Report

Background: Singleton-Merten syndrome type 1 (SGMRT1) is a rare autosomal dominant disorder caused by IFIH1 variations with blood vessel calcifications, teeth anomalies, and bone defects. Aim: We aimed to summarize the oral findings in SGMRT1 through a systematic review of the literature and to describe the phenotype of a 10-year-old patient with SGMRT1 diagnosis. Results: A total of 20 patients were described in the literature, in nine articles. Eight IFIH1 mutations were described in 11 families. Delayed eruption, short roots, and premature loss of permanent teeth were the most described features (100%). Impacted teeth (89%) and carious lesions (67%) were also described. Our patient, a 10-year-old male with Singleton-Merten syndrome, presented numerous carious lesions, severe teeth malposition, especially in the anterior arch, and an oral hygiene deficiency with a 100% plaque index. The panoramic X-ray did not show any dental agenesis but revealed very short roots and a decrease in the jaw alveolar bone height. The whole-genome sequencing analysis revealed a heterozygous de novo variant in IFIH1 (NM_022168.4) c.2465G > A (p.Arg822Gln). Conclusion: Confused descriptions of oral features occurred in the literature between congenital findings and "acquired" pathology, especially carious lesions. The dental phenotype of these patients encompasses eruption anomalies (delayed eruption and impacted teeth) and lack of root edification, leading to premature loss of permanent teeth, and it may contribute to the diagnosis. An early diagnosis is essential to prevent teeth loss and to improve the quality of life of these patients. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42022300025].

Missense Variants Reveal Functional Insights Into the Human ARID Family of Gene Regulators

Missense variants are alterations to protein coding sequences that result in amino acid substitutions. They can be deleterious if the amino acid is required for maintaining structure or/and function, but are likely to be tolerated at other sites. Consequently, missense variation within a healthy population can mirror the effects of negative selection on protein structure and function, such that functional sites on proteins are often depleted of missense variants. Advances in high-throughput sequencing have dramatically increased the sample size of available human variation data, allowing for population-wide analysis of selective pressures. In this study, we developed a convenient set of tools, called 1D-to-3D, for visualizing the positions of missense variants on protein sequences and structures. We used these tools to characterize human homologues of the ARID family of gene regulators. ARID family members are implicated in multiple cancer types, developmental disorders, and immunological diseases but current understanding of their mechanistic roles is incomplete. Combined with phylogenetic and structural analyses, our approach allowed us to characterise sites important for protein-protein interactions, histone modification recognition, and DNA binding by the ARID proteins. We find that comparing missense depletion patterns among paralogs can reveal sub-functionalization at the level of domains. We propose that visualizing missense variants and their depletion on structures can serve as a valuable tool for complementing evolutionary and experimental findings.

Immunogenicity and Efficacy of a Recombinant Human Adenovirus Type 5 Vaccine against Zika Virus

Zika virus (ZIKV) is a significant public health concern due to the pathogen's ability to be transmitted by either mosquito bite or sexual transmission, allowing spread to occur throughout the world. The potential consequences of ZIKV infection to human health, specifically neonates, necessitates the development of a safe and effective Zika virus vaccine. Here, we developed an intranasal Zika vaccine based upon the replication-deficient human adenovirus serotype 5 (hAd5) expressing ZIKV pre-membrane and envelope protein (hAd5-ZKV). The hAd5-ZKV vaccine is able to induce both cell-mediated and humoral immune responses to ZIKV epitopes. Importantly, this vaccine generated CD8⁺ T cells specific for a dominant ZIKV T cell epitope and is shown to be protective against a ZIKV challenge by using a pre-clinical model of ZIKV disease. We also demonstrate that the vaccine expresses pre-membrane and envelope protein in a confirmation recognized by ZIKV experienced individuals. Our studies demonstrate that this adenovirus-based vaccine expressing ZIKV proteins is immunogenic and protective in mice, and it encodes ZIKV proteins in a conformation recognized by the human antibody repertoire.

G3viz: an R package to interactively visualize genetic mutation data using a lollipop-diagram

SUMMARY

The lollipop-diagram is one of the widely used graphical representations to visualize and explore translational effects of genetic mutations in cancer genomics. However, an easy-to-use lollipop-diagram tool with full functionality is still lacking. Here, we introduce g3viz, an R package that enables researchers to explore genetic mutation data using a lollipop-diagram in a web browser. With a few lines of R code, users can interactively visualize data details, annotate findings and export resultant diagrams in high-quality figures. Because of usefulness and usability, g3viz can be generally exploited by researchers with different levels of bioinformatics skills and programming experience.

AVAILABILITY AND IMPLEMENTATION

The R package is freely available under the MIT license from CRAN (http://cran.r-project.org/web/packages/g3viz). The g3lollipop JavaScript package is freely available under MIT license at GitHub (https://github.com/g3viz/g3lollipop.js).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mutplot: An easy-to-use online tool for plotting complex mutation data with flexibility

With the development of technology, an enormous amount of sequencing data is being generated rapidly. However, transforming this data into patient care is a critical challenge. There are two difficulties: how to integrate functional information into mutation interpretation and how to make the integration easy to apply. One solution is to visualize amino acid changes with protein structure and function in web app platform. There are multiple existing tools for plotting mutations, but the majority of them requires programming skills that are not common background for clinicians or researchers. Furthermore, the recurrent mutations are the focus and the recurrence cutoff varies. Yet, none of the current software offers customer-defined cutoff. Thus, we developed this user-friendly web-based tool, Mutplot (https://bioinformaticstools.shinyapps.io/lollipop/). Mutplot retrieves up-to-date domain information from the protein resource UniProt (https://www.uniprot.org/), integrates the submitted mutation information and produces lollipop diagrams with annotations and highlighted candidates. It offers flexible output options. For data that follows security standards, the app can also be hosted in web servers inside a firewall or computers without internet with Uniprot database stored on them. Altogether, Mutplot is an excellent tool for visualizing protein mutations, especially for clinicians or researchers without any bioinformatics background.

Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection

Neisseria lactamica is a harmless coloniser of the infant respiratory tract, and has a mutually-excluding relationship with the pathogen Neisseria meningitidis. Here we report controlled human infection with genomically-defined N. lactamica and subsequent bacterial microevolution during 26 weeks of colonisation. We find that most mutations that occur during nasopharyngeal carriage are transient indels within repetitive tracts of putative phase-variable loci associated with host-microbe interactions (pgl and lgt) and iron acquisition (fetA promotor and hpuA). Recurrent polymorphisms occurred in genes associated with energy metabolism (nuoN, rssA) and the CRISPR-associated cas1. A gene encoding a large hypothetical protein was often mutated in 27% of the subjects. In volunteers who were naturally co-colonised with meningococci, recombination altered allelic identity in N. lactamica to resemble meningococcal alleles, including loci associated with metabolism, outer membrane proteins and immune response activators. Our results suggest that phase variable genes are often mutated during carriage-associated microevolution.

Lollipops in the Clinic: Information Dense Mutation Plots for Precision Medicine

INTRODUCTION

Concise visualization is critical to present large amounts of information in a minimal space that can be interpreted quickly. Clinical applications in precision medicine present an important use case due to the time dependent nature of the interpretations, although visualization is increasingly necessary across the life sciences. In this paper we describe the Lollipops software for the presentation of panel or exome sequencing results. Source code and binaries are freely available at https://github.com/pbnjay/lollipops. Although other software and web resources exist to produce lollipop diagrams, these packages are less suited to clinical applications. The demands of precision medicine require the ability to easily fit into a workflow and incorporate external information without manual intervention.

RESULTS

The Lollipops software provides a simple command line interface that only requires an official gene symbol and mutation list making it easily scriptable. External information is integrated using the publicly available Uniprot and Pfam resources. Heuristics are used to select the most informative components and condense them for a concise plot. The output is a flexible Scalable Vector Graphic (SVG) diagram that can be displayed in a web page or graphic illustration tool.

CONCLUSION

The Lollipops software creates information-dense, publication-quality mutation plots for automated pipelines and high-throughput workflows in precision medicine. The automatic data integration enables clinical data security, and visualization heuristics concisely present knowledge with minimal user configuration.

Proteins linked to autosomal dominant and autosomal recessive disorders harbor characteristic rare missense mutation distribution patterns

The role of rare missense variants in disease causation remains difficult to interpret. We explore whether the clustering pattern of rare missense variants (MAF < 0.01) in a protein is associated with mode of inheritance. Mutations in genes associated with autosomal dominant (AD) conditions are known to result in either loss or gain of function, whereas mutations in genes associated with autosomal recessive (AR) conditions invariably result in loss-of-function. Loss-of-function mutations tend to be distributed uniformly along protein sequence, whereas gain-of-function mutations tend to localize to key regions. It has not previously been ascertained whether these patterns hold in general for rare missense mutations. We consider the extent to which rare missense variants are located within annotated protein domains and whether they form clusters, using a new unbiased method called CLUstering by Mutation Position. These approaches quantified a significant difference in clustering between AD and AR diseases. Proteins linked to AD diseases exhibited more clustering of rare missense mutations than those linked to AR diseases (Wilcoxon P = 5.7 × 10(-4), permutation P = 8.4 × 10(-4)). Rare missense mutation in proteins linked to either AD or AR diseases was more clustered than controls (1000G) (Wilcoxon P = 2.8 × 10(-15) for AD and P = 4.5 × 10(-4) for AR, permutation P = 3.1 × 10(-12) for AD and P = 0.03 for AR). The differences in clustering patterns persisted even after removal of the most prominent genes. Testing for such non-random patterns may reveal novel aspects of disease etiology in large sample studies.

Leveraging the new with the old: providing a framework for the integration of historic microarray studies with next generation sequencing

Next Generation Sequencing (NGS) methods are rapidly providing remarkable advances in our ability to study the molecular profiles of human cancers. However, the scientific discovery offered by NGS also includes challenges concerning the interpretation of large and non-trivial experimental results. This task is potentially further complicated when a multitude of molecular profiling modalities are available, with the goal of a more integrative and comprehensive analysis of the cancer biology.

Microarray transcriptome analyses have resulted in important advances in both the scientific and clinical domains of biomedicine. Importantly, as technology advances, it is critical to leverage what has been gained from historic approaches (e.g., microarrays) with new approaches (NGS). In this regard, necessity dictated a need to utilize and leverage the many years of historical microarray data with new NGS approaches. This is especially important since NGS approaches are now entering clinical medicine. For instance, NGS-based comprehensive analysis of certain cancers has already helped to uncover specific mutations that contribute to the malignant process, identify new therapeutic targets, and improve opportunities for choosing the best treatment for an individual patient.

A suite of custom software tools have been developed to rapidly integrate, explore, discover and validate molecular profiling data from the NGS modalities of Whole Exome Sequencing (WES) and RNA-seq with each other, as well as with historical microarray and salient clinical datasets. Importantly, our approach is independent of any particular type of NGS suite(s) or cancer types. This novel bioinformatic framework is now assisting with the scientific and clinical management of patients with multiple myeloma.