Genome Sequencing Technologies Research Articles

Recently Delisted Songbird Harbors Extensive Genomic Evidence of Inbreeding, Potentially Complicating Future Recovery.

The Kirtland's warbler (Setophaga kirtlandii) is a rare migratory passerine species and habitat specialist of the North American Jack Pine Forests. Their near extinction in the 1970s classified them as endangered and protected under the Endangered Species Act of 1973. After decades of intense conservation management, their population size recovered, and they were delisted from federal protection in 2019. We explore the genomic consequences of this harsh bottleneck and recovery by comparing the genomic architecture of two closely related species whose population sizes have remained large and stable, Hooded Warblers (Setophaga citrina) and American Redstarts (Setophaga ruticilla). We used whole-genome sequencing to characterize the distribution of runs of homozygosity and deleterious genetic variation. We find evidence that Kirtland's warblers exhibit genetic patterns consistent with recent inbreeding. Our results also show that Kirtland's warblers carry an excess proportion of deleterious variation, which could complicate management for this conservation-reliant species. This analysis provides a genetically informed perspective that should be thoroughly considered when delisting other species from federal protections. Through the increasing accessibility of genome sequencing technology, it will be more feasible to monitor the genetic landscape of recovering populations to ensure their long-term survival independent of conservation intervention.

Exploring Microbial Dark Matter for the Discovery of Novel Natural Products: Characteristics, Abundance Challenges and Methods.

The objective of this review is to investigate microbial dark matter (MDM) with a focus on its potential for discovering novel natural products. This first part will examine the characteristics and abundance of these previously unexplored microbial communities, as well as the challenges faced in identifying and harnessing their unique biochemical properties and novel methods in this field. MDMs are thought to hold great potential for the discovery of novel natural products, which could have significant applications in medicine, agriculture, and industry. In recent years, there has been a growing interest in exploring microbial dark matter to unlock its potential. In fact, developments in genome-sequencing technologies and sophisticated phylogenetic procedures and metagenomic techniques have contributed to drastically make important changes in our sights on thediversity of microbial life, including the very outline of the tree of life. This has led to the development of novel technologies and methodologies for studying these elusive microorganisms, such as single-cell genomics, metagenomics, and culturomics. These approaches enable researchers to isolate and analyze individual microbial cells, as well as entire communities, providing insights into their genetic and metabolic potential. By delving into the microbial dark matter, scientists hope to uncover new compounds and biotechnological advancements that could have far-reaching impacts on various fields.

The genome landscape of the Xinglong buffalo

BackgroundXinglong buffalo, as an indigenous breed in Hainan province of China, possesses characteristics such as high humidity tolerance, disease resistance and high reproductive capacity. Combined with whole genome sequencing technology, comprehensive investigation can be undertaken to elucidate the genomic characteristics, functions and genetic variation of Xinglong buffalo population.ResultsXinglong buffalo has the highest genetic diversity, lowest runs of homozygosity average length, and fasted decay of linkage disequilibrium in our study population. Phylogenetic tree results revealed that Xinglong buffalo was gathered together with Fuzhong buffalo firstly. The population genetic structure analysis indicates that at K = 3, the Xinglong buffalo for the first time showed a distinct ancestral origin from other water buffalo. Furthermore, compared to different populations, candidate genes displaying significantly distinct patterns of single nucleotide polymorphisms (SNPs) (e.g., RYR2, COX15, PCDH9, DTWD2, FCRL5) distribution have been identified in the Xinglong buffalo.ConclusionsBased on the whole genome sequencing data, this study identified a substantial number of SNPs and assessed the genetic diversity and selection signatures within the Xinglong buffalo population. These results contribute to understanding the genomic characteristics of Xinglong buffalo and their genetic evolutionary status. However, the practical significance of these signatures for genetic enhancement still requires confirmation through additional samples and further experimental validation.

Molluscan systematics: historical perspectives and the way ahead.

Mollusca, the second-most diverse animal phylum, is estimated to have over 100,000 living species with great genetic and phenotypic diversity, a rich fossil record, and a considerable evolutionary significance. Early work on molluscan systematics was grounded in morphological and anatomical studies. With the transition from oligo gene Sanger sequencing to cutting-edge genomic sequencing technologies, molecular data has been increasingly utilised, providing abundant information for reconstructing the molluscan phylogenetic tree. However, relationships among and within most major lineages of Mollusca have long been contentious, often due to limited genetic markers, insufficient taxon sampling and phylogenetic conflict. Fortunately, remarkable progress in molluscan systematics has been made in recent years, which has shed light on how major molluscan groups have evolved. In this review of molluscan systematics, we first synthesise the current understanding of the molluscan Tree of Life at higher taxonomic levels. We then discuss how micromolluscs, which have adult individuals with a body size smaller than 5 mm, offer unique insights into Mollusca's vast diversity and deep phylogeny. Despite recent advancements, our knowledge of molluscan systematics and phylogeny still needs refinement. Further advancements in molluscan systematics will arise from integrating comprehensive data sets, including genome-scale data, exceptional fossils, and digital morphological data (including internal structures). Enhanced access to these data sets, combined with increased collaboration among morphologists, palaeontologists, evolutionary developmental biologists, and molecular phylogeneticists, will significantly advance this field.

Metagenomic Analysis Reveals the Effects of Different Land Use Types on Functional Soil Phosphorus Cycling: A Case Study of the Yellow River Alluvial Plain.

Phosphorus (P) is a crucial limiting nutrient in soil ecosystems, significantly influencing soil fertility and plant productivity. Soil microorganisms adapt to phosphorus deficiency and enhance soil phosphorus effectiveness through various mechanisms, which are notably influenced by land use practices. This study examined the impact of different land use types (long-term continuous maize farmland, abandoned evolving grassland, artificial tamarisk forests, artificial ash forests, and wetlands) on soil phosphorus-cycling functional genes within the Tanyang Forest Farm in a typical region of the Yellow River alluvial plain using macro genome sequencing technology. The gene cluster related to inorganic phosphorus solubilization and organic phosphorus mineralization exhibited the highest relative abundance across different land use types (2.24 × 10-3), followed by the gene cluster associated with phosphorus transport and uptake (1.42 × 10-3), with the lowest relative abundance observed for the P-starvation response regulation gene cluster (5.52 × 10-4). Significant differences were found in the physical and chemical properties of the soils and the relative abundance of phosphorus-cycling functional genes among various land use types. The lowest relative abundance of soil phosphorus-cycling functional genes was observed in forestland, with both forestland types showing significantly lower gene abundance compared to wetland, farmland, and grassland. Correlation analysis and redundancy analysis (RDA) revealed a significant relationship between soil physicochemical properties and soil phosphorus-cycling functional genes, with ammonium nitrogen, organic carbon, total nitrogen, and pH being the main environmental factors influencing the abundance of these genes, explaining 70% of the variation in their relative abundance. Our study reveals land use's impact on soil phosphorus-cycling genes, offering genetic insights into microbial responses to land use changes.

Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol.

Pathogen genomics, where whole genome sequencing technologies are used to produce complete genomic sequences of pathogens, is being increasingly used for infectious disease surveillance and outbreak response. Although proof-of-concept studies have highlighted the viability of using pathogen genomics in public health, few studies have investigated how end-users utilize pathogen genomics in public health. We describe a protocol for a study that aims to identify key factors that influence the use of pathogen genomics to inform public health responses against infectious diseases in Australia and New Zealand. We will use qualitative comparative analysis (QCA), a case-oriented methodology that systematically compares and analyses multiple cases (or 'units of analysis'), to identify multiple pathways leading to the use of pathogen genomics results in public health actions. As part of the process, we will develop a rubric to identify and define the use of pathogen genomics and individual factors affecting this process. Simultaneously, we will identify cases where pathogen genomics has been used in public health across Australia and New Zealand. Data for these cases will be collected from document review of publicly available and confidential documents and semi-structured interviews with technicians and end-users and summarized in a case report. These case reports will form the basis for scoring each case on the extent of the use of pathogen genomics data and the presence or absence of specific factors such as the ease of extracting essential information from pathogen genomics reports and perceptions toward pathogen genomics. Using the scores, cases will be analyzed using QCA techniques to identify pathways leading to the use of pathogen genomics data. These pathways will be interpreted alongside the cases to provide rich explanations of the use of pathogen genomics in public health. This study will improve our understanding of the key factors that facilitate or hinder the use of pathogen genomics to inform public health authorities and end-users. These findings may inform ways to enhance the use of pathogen genomics data in public health.

Assessment of genes involved in lysosomal diseases using the ClinGen Clinical Validity framework.

Lysosomal diseases (LDs) are a heterogeneous group of rare genetic disorders that result in impaired lysosomal function, leading to progressive multiorgan system dysfunction. Accurate diagnosis is paramount to initiating targeted therapies early in the disease process in addition to providing prognostic information and appropriate support for families. In recent years, genomic sequencing technologies have become the first-line approach in the diagnosis of LDs. Understanding the clinical validity of the role of a gene in a disease is critical for the development of genomic technologies, such as which genes to include on next generation sequencing panels, and the interpretation of results from exome and genome sequencing. To this aim, the ClinGen Lysosomal Diseases Gene Curation Expert Panel utilized a semi-quantitative framework incorporating genetic and experimental evidence to assess the clinical validity of the 56 LD-associated genes on the Lysosomal Disease Network's list. Here, we describe the results, and the key themes and challenges encountered.

Visualize correlations using heat maps in R

The role of gut microbiota in maintaining of homeostasis and development of pathophysiological disorders has been actively studied over the past decades. With the advent of genome sequencing technology, new opportunities are opening up in this area. With the advent the technology of genome sequencing, new opportunities are opening up in this area. During statistical processing, there is a need to perform correlation analysis. However, with a large number of indicators, visual presentation of data can be difficult. Heat maps allow you to graphically represent large amount of data. The article contains a methodology of graphically representing correlations using heat maps.

Assessment of genes involved in lysosomal diseases using the ClinGen clinical validity framework

Lysosomal diseases (LDs) are a heterogeneous group of rare genetic disorders that result in impaired lysosomal function, leading to progressive multiorgan system dysfunction. Accurate diagnosis is paramount to initiating targeted therapies early in the disease process in addition to providing prognostic information and appropriate support for families. In recent years, genomic sequencing technologies have become the first-line approach in the diagnosis of LDs. Understanding the clinical validity of the role of a gene in a disease is critical for the development of genomic technologies, such as which genes to include on next generation sequencing panels, and the interpretation of results from exome and genome sequencing. To this aim, the ClinGen Lysosomal Diseases Gene Curation Expert Panel utilized a semi-quantitative framework incorporating genetic and experimental evidence to assess the clinical validity of the 56 LD-associated genes on the Lysosomal Disease Network's list. Here, we describe the results, and the key themes and challenges encountered.

Mitochondrial genetic variations in leukemia: a comprehensive overview.

Leukemias are a group of heterogeneous hematological malignancies driven by diverse genetic variations, and the advent of genomic sequencing technologies facilitates the investigation of genetic abnormalities in leukemia. However, these sequencing-based studies mainly focus on nuclear DNAs. Increasing evidence indicates that mitochondrial dysfunction is an important mechanism of leukemia pathogenesis, which is closely related to the mitochondrial genome variations. Here, we provide an overview of current research progress concerning mitochondrial genetic variations in leukemia, encompassing gene mutations and copy number variations. We also summarize currently accessible mitochondrial DNA (mtDNA) sequencing methods. Notably, somatic mtDNA mutations may serve as natural genetic barcodes for lineage tracing and longitudinal assessment of clonal dynamics. Collectively, these findings enhance our understanding of leukemia pathogenesis and foster the identification of novel therapeutic targets and interventions.

Personalized Medicine: The Dawn of a New Era in Healthcare

The landscape of healthcare is transforming with the advent of personalized medicine, an approach that alters medical treatment to each individual's specific characteristics. This paradigm shift is driven by advancements in genomics, molecular biology, and bioinformatics, which have developed a deeper understanding of the genetic and molecular basis of diseases. This new healthcare model is based on precision and individualization, aiming to provide customized healthcare with medical decisions and treatments by considering variability in genes, environment and lifestyle of an individual patient and offer accurate diagnosis, better treatments and prevention plans. The accomplishment of the Human Genome Project in 2003 was a significant advancement in genomics that provided blueprints of the human genome [1]. Rapid progress in genomic sequencing technologies makes it feasible and cost effective. Advanced sequencing techniques including next-generation sequencing allow a detailed analysis of genetic makeup to locate mutations and genetic predispositions for better treatment decisions. Cancer is caused by genetic heterogeneity and has benefited greatly from genomic insights. Molecular profiling of tumor cells allows the identification of specific genetic mutations involved in cancer pathogenesis. Targeted therapies can then be designed to inhibit these specific molecular pathways, leading to more effective and less toxic treatments compared to traditional chemotherapy. For example, in breast cancer the identification of Human epidermal growth factor receptor 2 (HER2) mutations has led to the development of HER2-targeted therapies to improve treatment [2]. Besides oncology, personalized medicine is making progress in other fields. In cardiology, genetic testing allows identification of patients who are at risk of getting inherited cardiovascular diseases. In pharmacology, pharmacogenomics, the study of correlation between genes and immune response of an individual to drugs helps in designing most effective drugs with the least side effects for each patient. In infectious diseases, genomic sequencing of pathogenic microbes can lead to development of appropriate antimicrobial drugs to prevent outbreaks. Despite its progress, the implementation of personalized medicine is facing several challenges. The utilization of genomic data in clinical workflows demands significant changes to healthcare setting and training with concerns about data privacy, equal access to diverse populations and the ethical implications of genetic information. Currently, the universal unavailability of sophisticated bioinformatics tools to interpret complex genomic data is also a challenge. Researchers and policymakers must work in to set guidelines and standards for safe use of personalized medicine. Therefore, personalized medicine is a promising tool, which has revolutionized diagnosis, treatment, and prevention in traditional medicine. Using genomics and molecular biology, we can develop a more precise, predictive, and personalized approach to medicine. This exciting frontier must be navigated with the ultimate goal of improving patient outcomes.

Genetic Diversity Analysis of Capsicum frutescens Based on Simplified Genome Sequencing Technology

Capsicum frutescens (C. frutescens) has rich germplasm resources, but there have been no reports on its genetic diversity analysis alone using simplified genome sequencing technology (GBS). To provide a basis for the breeding of new pepper varieties and the later development of C. frutescens SNP molecular markers, this study used GBS technology to sequence 65 collected pepper germplasm resources. A total of 1,399,391 SNP sites were obtained by GBS simplified genome sequencing, and there were 1,465,897 SNP variant sites. Through population genetic structure analysis, the population structure and phylogenetic tree of 65 C. frutescens germplasms were constructed. The GBS method is also suitable for the genetic relationship analysis of C. frutescens, and it also shows that there is an obvious separation of materials from different origins, and there is also a certain degree of genetic exchange. Most of C. frutescens varieties from Fujian Province and its surrounding areas are clustered together; C. frutescens varieties from western China are also clustered together. We selected T62 and T60 with a genetic distance of 0.2796 and a spiciness level of nine as the female and male parent combinations, respectively, and bred a new high-yield C. frutescens combination, ‘Mingjiao 308’. C. frutescens varieties from the same geographical origin are usually clustered together. These germplasms may contain the ancestry of multiple varieties. This result can also provide basic data for the later construction of an SNP fingerprint database.

Development of Cost-Effective SNP Markers for Genetic Variation Analysis and Variety Identification in Cultivated Pears (Pyrus spp.).

Pear (Pyrus spp.) is a major fruit crop in the Rosaceae family, and extensive efforts have been undertaken to develop elite varieties. With advances in genome sequencing technologies, single-nucleotide polymorphisms (SNPs) are commonly used as DNA markers in crop species. In this study, a large-scale discovery of SNPs was conducted using genotyping by sequencing in a collection of 48 cultivated pear accessions. A total of 256,538 confident SNPs were found on 17 chromosomes, and 288 SNPs were filtered based on polymorphic information content, heterozygosity rate, and genome distribution. This subset of SNPs was used to genotype an additional 144 accessions, consisting of P. pyrifolia (53), P. ussuriensis (27), P. bretschneideri (19), P. communis (26), interspecific hybrids (14), and others (5). The 232 SNPs with reliable polymorphisms revealed genetic variations between and within species in the 192 pear accessions. The Asian species (P. pyrifolia, P. ussuriensis, and P. bretschneideri) and interspecific hybrids were genetically differentiated from the European species (P. communis). Furthermore, the P. pyrifolia population showed higher genetic diversity relative to the other populations. The 232 SNPs and four subsets (192, 96, 48, and 24 SNPs) were assessed for variety identification. The 192 SNP subset identified 173 (90.1%) of 192 accessions, which was comparable to 175 (91.1%) from the 232 SNPs. The other three subsets showed 81.8% (24 SNPs) to 87.5% (96 SNPs) identification rates. The resulting SNPs will be a useful resource to investigate genetic variations and develop an efficient DNA barcoding system for variety identification in cultivated pears.

Assembly and annotation of a chromosome-level reference genome for the endangered Colorado pikeminnow (Ptychocheilus lucius).

Advancements in genome sequencing technology have brought unprecedented accessibility of high-throughput sequencing to species of conservation interest. The potential knowledge gained from application of these techniques is maximized by availability of high-quality, annotated reference genomes for endangered species. However, these vital resources are often lacking for endangered minnows of North America (Cypriniformes: Leuciscidae). One such endangered species, Colorado pikeminnow (Ptychocheilus lucius), is the largest North American minnow and the top-level native aquatic predator in the Colorado River Basin of the southwestern United States and northwestern Mexico. Over the past century, Colorado pikeminnow has suffered habitat loss and population declines due to anthropogenic habitat modifications and invasive species introductions. The lack of genetic resources for Colorado pikeminnow has hindered conservation genomic study of this unique organism. This study seeks to remedy this issue by presenting a high-quality reference genome for Colorado pikeminnow developed from Pacific Biosciences HiFi sequencing and Hi-C scaffolding. The final assembly was a 1.1 Gb genome comprised of 305 contigs including 25 chromosome-sized scaffolds. Measures of quality, contiguity, and completeness met or exceeded those observed for Danio rerio (Danionidae) and 2 other Colorado River Basin leuciscids (Meda fulgida and Tiaroga cobitis). Comparative genomic analyses identified enrichment of gene families for growth, development, immune activity, and gene transcription; all of which are important for a large-bodied piscivorous fish living in a dynamic environment. This reference genome will provide a basis for important conservation genomic study of Colorado pikeminnow and help efforts to better understand the evolution of desert fishes.

Factors Contributing to Emergence of infectious viral diseases in India: Issues and Challenges after COVID-19 Pandemic

Emerging and re-emerging viral infections are major cause of morbidity and mortality in humans and animals. India had experienced numerous infectious disease outbreaks and epidemics in past years. However, tremendous strides have been achieved in the past in the fight against serious epidemic diseases. It has been found that a wide range of complex factors, such as pathogen evolution, human invasion, commerce in wild animals, microbial adaptation, changes in the environment and dynamic interactions between humans and animals influence the emergence and transmission of infectious viral diseases. As the COVID-19 pandemic demonstrated, India's secondary and tertiary health-care system is quite advanced. The study of infectious diseases, in particular their pathogenesis, genetic profile and diagnosis has fundamentally changed with the advent of genome sequencing and nucleic acid detection technology. Additionally, advance therapy and vaccination led to best possible patient management and care. Further scientific investigations and research are needed to discover neglected diseases that have the potential to cause epidemics as well as to develop updated vaccines, modern treatment strategy and diagnostics at molecular level. This evaluation will aid for policymakers, academics and researchers to redesign the course of action to combat the deadly emerging pathogenic viruses and also preserve the ecosystem.

Forensic Characterization, Genomic Variability and Ancestry Analysis of Six Populations from Odisha Using mtDNA SNPs and Autosomal STRs.

Located on India's eastern coast, Odisha is known for its diverse tribes and castes. In the early days of genome sequencing technology, researchers primarily studied the Austroasiatic communities inhabiting this region to reconstruct the ancient origins and dispersal of this broad linguistic group. However, current research has shifted towards identifying population and individual-specific genome variation for forensic applications. This study aims to analyze the forensic efficiency and ancestry of six populations from Odisha. We assessed the SF mtDNA-SNP60™ PCR Amplification Kit by comparing it with PowerPlex® Fusion 6C System, a widely used autosomal STR (aSTR) kit, in an Indian cohort. Although the mtDNA SNP kit showed low discriminating power for individuals of a diverse population, it could identify deep lineage divergence. Also, we utilized mitochondrial and autosomal variation information to analyze the ancestry of six endogamous ethnic groups in Odisha. We observe two extremities-populations with higher West Asian affinity and those with East Asian affinity. This observation is in congruence with the existing information of their tribal and non-tribal affiliation. When compared with neighbouring populations from Central and Eastern India, multivariate analysis showed that the Brahmins clustered separately or with the Gopala, Kaibarta appeared as an intermediate, Pana and Kandha clustered with the Gonds, and Savara with the Munda tribes. Our findings indicate significant deep lineage stratification in the ethnic populations of Odisha and a gene flow from West and East Asia. The artefacts of unique deep lineage in such a diverse population will help in improving forensic identification. In addition, we conclude that the SF mtDNA-SNP60 PCR Amplification Kit may be used only as a supplementary tool for forensic analysis.

Recent Advances in Genomic Approaches for the Detection of Homologous Recombination Deficiency.

Accurate detection of homologous recombination deficiency (HRD) in cancer patients is paramount in clinical applications, as HRD confers sensitivity to poly(ADP-ribose) polymerase (PARP) inhibitors. With the advances in genome sequencing technology, mutational profiling on a genome-wide scale has become readily accessible, and our knowledge of the genomic consequences of HRD has been greatly expanded and refined. Here, we review the recent advances in HRD detection methods. We examine the copy number and structural alterations that often accompany the genome instability that results from HRD, describe the advantages of mutational signature-based methods that do not rely on specific gene mutations, and review some of the existing algorithms used for HRD detection. We also discuss the choice of sequencing platforms (panel, exome, or whole-genome) and catalog the HRD detection assays used in key PARP inhibitor trials.

Variant calling in polyploids for population and quantitative genetics.

Advancements in genome assembly and sequencing technology have made whole genome sequence (WGS) data and reference genomes accessible to study polyploid species. Compared to popular reduced-representation sequencing approaches, the genome-wide coverage and greater marker density provided by WGS data can greatly improve our understanding of polyploid species and polyploid biology. However, biological features that make polyploid species interesting also pose challenges in read mapping, variant identification, and genotype estimation. Accounting for characteristics in variant calling like allelic dosage uncertainty, homology between subgenomes, and variance in chromosome inheritance mode can reduce errors. Here, I discuss the challenges of variant calling in polyploid WGS data and discuss where potential solutions can be integrated into a standard variant calling pipeline.

Improving rigor and reproducibility in chromatin immunoprecipitation assay data analysis workflows with Rocketchip.

As genome sequencing technologies advance, the accumulation of sequencing data in public databases necessitates more robust and adaptable data analysis workflows. Here, we present Rocketchip, which aims to offer a solution to this problem by allowing researchers to easily compare and swap out different components of ChIP-seq, CUT&RUN, and CUT&Tag data analysis, thereby facilitating the identification of reliable analysis methodologies. Rocketchip enables researchers to efficiently process large datasets while ensuring reproducibility and allowing for the reanalysis of existing data. By supporting comparative analyses across different datasets and methodologies, Rocketchip contributes to the rigor and reproducibility of scientific findings. Furthermore, Rocketchip serves as a platform for benchmarking algorithms, allowing researchers to identify the most accurate and efficient analytical approaches to be applied to their data. In emphasizing reproducibility and adaptability, Rocketchip represents a significant step towards fostering robust scientific research practices.

Harnessing technology for infectious disease response in conflict zones: Challenges, innovations, and policy implications.

Epidemic outbreaks of infectious diseases in conflict zones are complex threats to public health and humanitarian activities that require creativity approaches of reducing their damage. This narrative review focuses on the technology intersection with infectious disease response in conflict zones, and complexity of healthcare infrastructure, population displacement, and security risks. This narrative review explores how conflict-related destruction is harmful towards healthcare systems and the impediments to disease surveillance and response activities. In this regards, the review also considered the contributions of technological innovations, such as the improvement of epidemiological surveillance, mobile health (mHealth) technologies, genomic sequencing, and surveillance technologies, in strengthening infectious disease management in conflict settings. Ethical issues related to data privacy, security and fairness are also covered. By advisement on policy that focuses on investment in surveillance systems, diagnostic capacity, capacity building, collaboration, and even ethical governance, stakeholders can leverage technology to enhance the response to infectious disease in conflict settings and, thus, protect the global health security. This review is full of information for researchers, policymakers, and practitioners who are dealing with the issues of infectious disease outbreaks in conflicts worn areas.