The complete genome of an individual by massively parallel DNA sequencing

Advances in forensic genetics: Exploring the potential of long read sequencing

DNA-based technologies have been used in forensic practice since the mid-1980s. While PCR-based STR genotyping using Capillary Electrophoresis remains the gold standard for generating DNA profiles in routine casework worldwide, the research community is continually seeking alternative methods capable of providing additional information to enhance discrimination power or contribute with new investigative leads. Oxford Nanopore Technologies (ONT) and PacBio third-generation sequencing have revolutionized the field, offering real-time capabilities, single-molecule resolution, and long-read sequencing (LRS). ONT, the pioneer of nanopore sequencing, uses biological nanopores to analyze nucleic acids in real-time. Its devices have revolutionized sequencing and may represent an interesting alternative for forensic research and routine casework, given that it offers unparalleled flexibility in a portable size: it enables sequencing approaches that range widely from PCR-amplified short target regions (e.g., CODIS STRs) to PCR-free whole transcriptome or even ultra-long whole genome sequencing. Despite its higher error rate compared to Illumina sequencing, it can significantly improve accuracy in read alignment against a reference genome or de novo genome assembly. This is achieved by generating long contiguous sequences that correctly assemble repetitive sections and regions with structural variation. Moreover, it allows real-time determination of DNA methylation status from native DNA without the need for bisulfite conversion. LRS enables the analysis of thousands of markers at once, providing phasing information and eliminating the need for multiple assays. This maximizes the information retrieved from a single invaluable sample. In this review, we explore the potential use of LRS in different forensic genetics approaches.

Uncertainty about paternity: a study on deliberate ignorance

Deliberate ignorance is the willful choice not to know the answer to a question of personal relevance. The question of whether a man is the biological father of his child is a sensitive issue in many cultures and can lead to litigation, divorce, and disinheritance. Thanks to DNA tests, men are easily able to resolve the uncertainty. Psychological theories that picture humans as informavores who are averse to ambiguity suggest men would do a DNA test, as does evolutionary theory, which considers investing in raising a rival's offspring a mistake. We conducted two representative studies using computer-based face-to-face interviews in Germany (n = 969) and Spain (n = 1,002) to investigate whether men actually want to know and how women would react to this desire. As a base line, Germans (Spanish) estimated that 10% (20%) of fathers mistakenly believe that they are the biological father of their child. Nevertheless, in both countries, only 4% of fathers reported that they had performed a DNA paternity test, while 96% said they had not. In contrast, among men without children, 38% (33%) of Germans (Spanish) stated they would do a DNA test if they had children, mostly without telling their partners. Spanish women with children would more often disapprove of a paternity test or threaten their husbands with divorce (25%) than would German women (13%). We find that a simple test of risk aversion, measured also by the purchase of non-mandatory insurances, is correlated with not wanting to know.

The development of inherited cardiac conditions services: current position and future perspectives

BACKGROUND

Over the last two decades, inherited cardiac conditions (ICC) centres have emerged with the aim of improving outcomes for patients and their families, through early diagnosis, genetic testing, risk assessment and specialist treatment.

SOURCES OF DATA

A literature search was performed using PubMed (https://pubmed.ncbi.nlm.nih.gov/). Commissioned ICC service reviews from NHS England, NHS Improvement and PHG Foundation were evaluated.

AREAS OF AGREEMENT

ICC patient management requires a multi-disciplinary approach. ICC services are predominantly based within tertiary centres. Despite expansion, provision of care remains inadequate to meet rising demands. Access to services is inconsistent, partly due to geographic variation and lack of standardized pathways.

AREAS OF CONTROVERSY

The optimal ICC care model remains undecided, although there is growing interest in 'hub-and-spoke' networks, which could aid secondary and tertiary service integration and repatriation of care.

GROWING POINTS

Genetic mainstreaming is a priority for the Genomic Medicine Service Alliance. The benefits of telehealth and virtual clinics have been validated by their use during the COVID-19 pandemic. Other innovations to improve resource efficiency, such as clinical scientist-led and nurse-led clinics, show promise.

AREAS TIMELY FOR DEVELOPING RESEARCH

An update for the NHS ICC service specifications is planned that appears well timed given the rapid evolution of the ICC landscape in the decade since last review. This has the potential to address needs including national audit, standardized pathways and ICC networks to improve governance and equity of care. Delegation of commissioning for specialist services to integrated care systems may also provide opportunity for increased regional direction.

Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review

BACKGROUND

Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation.

OBJECTIVE

This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets.

METHODS

We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success.

RESULTS

From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants.

CONCLUSIONS

On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Detection of Constitutional Structural Variants by Optical Genome Mapping: A Multisite Study of Postnatal Samples

Optical genome mapping is a high-resolution technology that can detect all types of structural variations in the genome. This second phase of a multisite study compares the performance of optical genome mapping and current standard-of-care methods for diagnostic testing of individuals with constitutional disorders, including neurodevelopmental impairments and congenital anomalies. Among the 627 analyses in phase 2, 405 were of retrospective samples supplied by five diagnostic centers in the United States and 94 were prospective samples collected over 18 months by two diagnostic centers (June 2021 to October 2022). Additional samples represented a family cohort to determine inheritance (n = 119) and controls (n = 9). Full concordance of results between optical genome mapping and one or more standard-of-care diagnostic tests was 98.6% (618/627), with partial concordance in an additional 1.1% (7/627).

The reckoning of chromosomal instability: past, present, future

Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.

On the core segmentation algorithms of copy number variation detection tools

Shotgun sequencing is a high-throughput method used to detect copy number variants (CNVs). Although there are numerous CNV detection tools based on shotgun sequencing, their quality varies significantly, leading to performance discrepancies. Therefore, we conducted a comprehensive analysis of next-generation sequencing-based CNV detection tools over the past decade. Our findings revealed that the majority of mainstream tools employ similar detection rationale: calculates the so-called read depth signal from aligned sequencing reads and then segments the signal by utilizing either circular binary segmentation (CBS) or hidden Markov model (HMM). Hence, we compared the performance of those two core segmentation algorithms in CNV detection, considering varying sequencing depths, segment lengths and complex types of CNVs. To ensure a fair comparison, we designed a parametrical model using mainstream statistical distributions, which allows for pre-excluding bias correction such as guanine-cytosine (GC) content during the preprocessing step. The results indicate the following key points: (1) Under ideal conditions, CBS demonstrates high precision, while HMM exhibits a high recall rate. (2) For practical conditions, HMM is advantageous at lower sequencing depths, while CBS is more competitive in detecting small variant segments compared to HMM. (3) In case involving complex CNVs resembling real sequencing, HMM demonstrates more robustness compared with CBS. (4) When facing large-scale sequencing data, HMM costs less time compared with the CBS, while their memory usage is approximately equal. This can provide an important guidance and reference for researchers to develop new tools for CNV detection.

Dissecting the Immune System through Gene Regulation

The immune system plays a dual role in human health, functioning both as a protector against pathogens and, at times, as a contributor to disease. This feature emphasizes the importance to uncover the underlying causes of its malfunctions, necessitating an in-depth analysis in both pathological and physiological conditions to better understand the immune system and immune disorders. Recent advances in scientific technology have enabled extensive investigations into gene regulation, a crucial mechanism governing cellular functionality. Studying gene regulatory mechanisms within the immune system is a promising avenue for enhancing our understanding of immune cells and the immune system as a whole. The gene regulatory mechanisms, revealed through various methodologies, and their implications in the field of immunology are discussed in this chapter.

Rediscovering tandem repeat variation in schizophrenia: challenges and opportunities

Tandem repeats (TRs) are prevalent throughout the genome, constituting at least 3% of the genome, and often highly polymorphic. The high mutation rate of TRs, which can be orders of magnitude higher than single-nucleotide polymorphisms and indels, indicates that they are likely to make significant contributions to phenotypic variation, yet their contribution to schizophrenia has been largely ignored by recent genome-wide association studies (GWAS). Tandem repeat expansions are already known causative factors for over 50 disorders, while common tandem repeat variation is increasingly being identified as significantly associated with complex disease and gene regulation. The current review summarizes key background concepts of tandem repeat variation as pertains to disease risk, elucidating their potential for schizophrenia association. An overview of next-generation sequencing-based methods that may be applied for TR genome-wide identification is provided, and some key methodological challenges in TR analyses are delineated.

Sequential sequencing by synthesis and the next-generation sequencing revolution

The impact of next-generation sequencing (NGS) cannot be overestimated. The technology has transformed the field of life science, contributing to a dramatic expansion in our understanding of human health and disease and our understanding of biology and ecology. The vast majority of the major NGS systems today are based on the concept of 'sequencing by synthesis' (SBS) with sequential detection of nucleotide incorporation using an engineered DNA polymerase. Based on this strategy, various alternative platforms have been developed, including the use of either native nucleotides or reversible terminators and different strategies for the attachment of DNA to a solid support. In this review, some of the key concepts leading to this remarkable development are discussed.

Genotype specific and microbiome effects of hypoxia in the model organism Daphnia magna

The fitness of the host is highly influenced by the interplay between the host and its associated microbiota. The flexible nature of these microbiota enables them to respond swiftly to shifts in the environment, which plays a key role in the host's capacity to withstand environmental stresses. To understand the role of the microbiome in host tolerance to hypoxia, one of the most significant chemical changes occurring in water ecosystems due to climate change, we performed a reciprocal gut transplant experiment with the freshwater crustacean Daphnia magna. In a microbiome transplant experiment, two genotypes of germ-free recipients were inoculated with gut microbiota from Daphnia donors of their own genotype or from the other genotype, that had been either pre-exposed to normoxic or hypoxic conditions. We found that D. magna individuals had a higher survival probability in hypoxia if their microbiome had been pre-exposed to hypoxia. The bacterial communities of the recipients changed over time with a reduction in alpha diversity, which was stronger when donors were pre-exposed to a hypoxic environment. While donor genotype had no influence on the long-term survival probability in hypoxia, donor genotypes was the most influential factor of the microbial community 3 days after the transplantation. Our results indicate that microbiome influencing factors mediate host fitness in a hypoxic environment in a time depending way.

[Genomic newborn screening-research approaches, challenges, and opportunities]

The application of high-throughput sequencing methods for population-based genomic newborn screening offers numerous opportunities for improving population health. The use of genome-based sequencing technology holds potential to enable the diagnosis of virtually any genetic disorder at an early stage and offers great flexibility when it comes to selection and expansion of target diseases. National and international efforts are therefore being made to investigate the ethical, legal, social, psychological, and technical aspects of genomic newborn screening. In addition to the many opportunities, there are numerous challenges and questions that remain to be answered: When and how should legal guardians be informed about such screening? Which diseases should be screened for? How should incidental findings or identification of a genetic predisposition be dealt with? Should data be stored long term and if so, how can this be done securely? Provided there is an appropriate regulatory framework and a transparent consent process, genomic newborn screening has the potential to fundamentally change the way in which we screen for congenital diseases. However, there is still much to be done. To achieve understanding and acceptance of genomic newborn screening amongst all stakeholders and thus to maximize its benefits for the population, a public discourse on the possibilities and limitations of genomic newborn screening is of critical importance. This article aims to provide an overview of the innovative technical developments in the field of human genetics, describe national and international approaches, and discuss challenges and opportunities of genomic newborn screening development.

Next-Generation sequencing transforming clinical practice and precision medicine

Next-generation sequencing (NGS) has revolutionized the field of genomics and is rapidly transforming clinical diagnosis and precision medicine. This advanced sequencing technology enables the rapid and cost-effective analysis of large-scale genomic data, allowing comprehensive exploration of the genetic landscape of diseases. In clinical diagnosis, NGS has proven to be a powerful tool for identifying disease-causing variants, enabling accurate and early detection of genetic disorders. Additionally, NGS facilitates the identification of novel disease-associated genes and variants, aiding in the development of targeted therapies and personalized treatment strategies. NGS greatly benefits precision medicine by enhancing our understanding of disease mechanisms and enabling the identification of specific molecular markers for disease subtypes, thus enabling tailored medical interventions based on individual characteristics. Furthermore, NGS contributes to the development of non-invasive diagnostic approaches, such as liquid biopsies, which can monitor disease progression and treatment response. The potential of NGS in clinical diagnosis and precision medicine is vast, yet challenges persist in data analysis, interpretation, and protocol standardization. This review highlights NGS applications in disease diagnosis, prognosis, and personalized treatment strategies, while also addressing challenges and future prospects in fully harnessing genomic potential within clinical practice.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer's dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

The NCI-MATCH trial: lessons for precision oncology

The NCI-MATCH (Molecular Analysis for Therapy Choice) trial ( NCT02465060 ) was launched in 2015 as a genomically driven, signal-seeking precision medicine platform trial-largely for patients with treatment-refractory, malignant solid tumors. Having completed in 2023, it remains one of the largest tumor-agnostic, precision oncology trials undertaken to date. Nearly 6,000 patients underwent screening and molecular testing, with a total of 1,593 patients (inclusive of continued accrual from standard next-generation sequencing) being assigned to one of 38 substudies. Each substudy was a phase 2 trial of a therapy matched to a genomic alteration, with a primary endpoint of objective tumor response by RECIST criteria. In this Perspective, we summarize the outcomes of the initial 27 substudies in NCI-MATCH, which met its signal-seeking objective with 7/27 positive substudies (25.9%). We discuss key aspects of the design and operational conduct of the trial, highlighting important lessons for future precision medicine studies.

A review of the pangenome: how it affects our understanding of genomic variation, selection and breeding in domestic animals?

As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.

Genetic Characterization of Listeria from Food of Non-Animal Origin Products and from Producing and Processing Companies in Bavaria, Germany

Reported cases of listeriosis from food of non-animal origin (FNAO) are increasing. In order to assess the risk of exposure to Listeria monocytogenes from FNAO, the genetic characterization of the pathogen in FNAO products and in primary production and processing plants needs to be investigated. For this, 123 samples of fresh and frozen soft fruit and 407 samples of 39 plants in Bavaria, Germany that produce and process FNAO were investigated for Listeria contamination. As a result, 64 Listeria spp. isolates were detected using ISO 11290-1:2017. Environmental swabs and water and food samples were investigated. L. seeligeri (36/64, 56.25%) was the most frequently identified species, followed by L. monocytogenes (8/64, 12.50%), L. innocua (8/64, 12.50%), L. ivanovii (6/64, 9.38%), L. newyorkensis (5/64, 7.81%), and L. grayi (1/64, 1.56%). Those isolates were subsequently sequenced by whole-genome sequencing and subjected to pangenome analysis to retrieve data on the genotype, serotype, antimicrobial resistance (AMR), and virulence markers. Eight out of sixty-four Listeria spp. isolates were identified as L. monocytogenes. The serogroup analysis detected that 62.5% of the L. monocytogenes isolates belonged to serogroup IIa (1/2a and 3a) and 37.5% to serogroup IVb (4b, 4d, and 4e). Furthermore, the MLST (multilocus sequence typing) analysis of the eight detected L. monocytogenes isolates identified seven different sequence types (STs) and clonal complexes (CCs), i.e., ST1/CC1, ST2/CC2, ST6/CC6, ST7/CC7, ST21/CC21, ST504/CC475, and ST1413/CC739. The core genome MLST analysis also showed high allelic differences and suggests plant-specific isolates. Regarding the AMR, we detected phenotypic resistance against benzylpenicillin, fosfomycin, and moxifloxacin in all eight L. monocytogenes isolates. Moreover, virulence factors, such as prfA, hly, plcA, plcB, hpt, actA, inlA, inlB, and mpl, were identified in pathogenic and nonpathogenic Listeria species. The significance of L. monocytogenes in FNAO is growing and should receive increasing levels of attention.

Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases

The outbreak of COVID-19 has positively impacted the NGS market recently. Targeted sequencing (TS) has become an important routine technique in both clinical and research settings, with advantages including high confidence and accuracy, a reasonable turnaround time, relatively low cost, and fewer data burdens with the level of bioinformatics or computational demand. Since there are no clear consensus guidelines on the wide range of next-generation sequencing (NGS) platforms and techniques, there is a vital need for researchers and clinicians to develop efficient approaches, especially for the molecular diagnosis of diseases in the emergency of the disease and the global pandemic outbreak of COVID-19. In this review, we aim to summarize different methods of TS, demonstrate parameters for TS assay designs, illustrate different TS panels, discuss their limitations, and present the challenges of TS concerning their clinical application for the molecular diagnosis of human diseases.

Functional Endophytes Regulating Plant Secondary Metabolism: Current Status, Prospects and Applications

Endophytes, which are widely found in host plants and have no harmful effects, are a vital biological resource. Plant endophytes promote plant growth and enhance plants' resistance to diseases, pests, and environmental stresses. In addition, they enhance the synthesis of important secondary metabolites in plants and improve the potential applicability of plants in agriculture, medicine, food, and horticulture. In this review, we summarize the recent progress in understanding the interaction between endophytes and plants and summarize the construction of synthetic microbial communities (SynComs) and metaomics analysis of the interaction between endophytes and plants. The application and development prospects of endophytes in agriculture, medicine, and other industries are also discussed to provide a reference for further study of the interaction between endophytes and plants and further development and utilization of endophytes.

Unlocking a novel determinant of athletic performance: The role of the gut microbiota, short-chain fatty acids, and "biotics" in exercise

The gut microbiota refers to the collection of trillions of intestinal microorganisms that modulate central aspects of health and disease through influential effects on host physiology. Recently, a connection has been made between the gut microbiota and exercise. Initial investigations demonstrated the beneficial effects of exercise on the gut microbiota, with cross-sectional studies revealing positive correlations between exercise-associated states, and healthy gut microbiota and exercise interventions showed post-intervention increases in the abundance of beneficial bacterial taxa. More recent investigations have focused on exploring the reverse relationship: the influence of the gut microbiota on exercise performance. Murine investigations have revealed that certain bacterial taxa may enhance endurance exercise performance by augmenting various aspects of lactate metabolism. Further, short-chain fatty acids-which modulate metabolism at various organ sites, including within skeletal muscle-have been shown to enhance endurance exercise capacity in mice. This review highlights what is currently known about the connection between the gut microbiota and exercise, with a particular focus on the ergogenic potential of the gut microbiota and how it may be leveraged to enhance endurance exercise performance.

Machine Learning Aided Interpretable Approach for Single Nucleotide-Based DNA Sequencing using a Model Nanopore

Solid-state nanopore-based electrical detection of DNA nucleotides with the quantum tunneling technique has emerged as a powerful strategy to be the next-generation sequencing technology. However, experimental complexity has been a foremost obstacle in achieving a more accurate high-throughput analysis with industrial scalability. Here, with one of the nucleotide training data sets of a model monolayer gold nanopore, we have predicted the transmission function for all other nucleotides with root-mean-square error scores as low as 0.12 using the optimized eXtreme Gradient Boosting Regression (XGBR) model. Further, the SHapley Additive exPlanations (SHAP) analysis helped in exploring the interpretability of the XGBR model prediction and revealed the complex relationship between the molecular properties of nucleotides and their transmission functions by both global and local interpretable explanations. Hence, experimental integration of our proposed machine-learning-assisted transmission function prediction method can offer a new direction for the realization of cheap, accurate, and ultrafast DNA sequencing.

Genomics reveal population structure, evolutionary history, and signatures of selection in the northern bottlenose whale, Hyperoodon ampullatus

Information on wildlife population structure, demographic history, and adaptations are fundamental to understanding species evolution and informing conservation strategies. To study this ecological context for a cetacean of conservation concern, we conducted the first genomic assessment of the northern bottlenose whale, Hyperoodon ampullatus, using whole-genome resequencing data (n = 37) from five regions across the North Atlantic Ocean. We found a range-wide pattern of isolation-by-distance with a genetic subdivision distinguishing three subgroups: the Scotian Shelf, western North Atlantic, and Jan Mayen regions. Signals of elevated levels of inbreeding in the Endangered Scotian Shelf population indicate this population may be more vulnerable than the other two subgroups. In addition to signatures of inbreeding, evidence of local adaptation in the Scotian Shelf was detected across the genome. We found a long-term decline in effective population size for the species, which poses risks to their genetic diversity and may be exacerbated by the isolating effects of population subdivision. Protecting important habitat and migratory corridors should be prioritized to rebuild population sizes that were diminished by commercial whaling, strengthen gene flow, and ensure animals can move across regions in response to environmental changes.

Rapid and simple analysis of short and long sequencing reads using DuesselporeTM

Transcriptome analysis experiments enable researchers to gain extensive insights into the molecular mechanisms underlying cell physiology and disease. Oxford Nanopore Technologies (ONT) has recently been developed as a fast, miniaturized, portable, and cost-effective alternative to next-generation sequencing (NGS). However, RNA-Seq data analysis software that exploits ONT portability and allows scientists to easily analyze ONT data everywhere without bioinformatics expertise is not widely available. We developed Duesselpore^TM, an easy-to-follow deep sequencing workflow that runs as a local webserver and allows the analysis of ONT data everywhere without requiring additional bioinformatics tools or internet connection. Duesselpore^TM output includes differentially expressed genes and further downstream analyses, such as variance heatmap, disease and gene ontology plots, gene concept network plots, and exports customized pathways for different cellular processes. We validated Duesselpore^TM by analyzing the transcriptomic changes induced by PCB126, a dioxin-like PCB, and a potent aryl hydrocarbon receptor (AhR) agonist in human HaCaT keratinocytes, a well-characterized model system. Duesselpore^TM was specifically developed to analyze ONT data, but we also implemented NGS data analysis. Duesselpore^TM is compatible with Linux, Microsoft, and Mac operating systems and allows convenient, reliable, and cost-effective analysis of ONT and NGS data.

Genome Privacy and Trust

Genomics data are important for advancing biomedical research, improving clinical care, and informing other disciplines such as forensics and genealogy. However, privacy concerns arise when genomic data are shared. In particular, the identifying nature of genetic information, its direct relationship to health status, and the potential financial harm and stigmatization posed to individuals and their blood relatives call for a survey of the privacy issues related to sharing genetic and related data and potential solutions to overcome these issues. In this work, we provide an overview of the importance of genomic privacy, the information gleaned from genomics data, the sources of potential private information leakages in genomics, and ways to preserve privacy while utilizing the genetic information in research. We discuss the relationship between trust in the scientific community and protecting privacy, illuminating a future roadmap for data sharing and study participation.

The avian gut microbiota: Diversity, influencing factors, and future directions

The gut microbiota is viewed as the “second genome” of animals, sharing intricate relationships with their respective hosts. Because the gut microbial community and its diversity are affected by many intrinsic and extrinsic factors, studying intestinal microbes has become an important research topic. However, publications are dominated by studies on domestic or captive birds, while research on the composition and response mechanism of environmental changes in the gut microbiota of wild birds remains scarce. Therefore, it is important to understand the co-evolution of host and intestinal bacteria under natural conditions to elucidate the diversity, maintenance mechanisms, and functions of gut microbes in wild birds. Here, the existing knowledge of gut microbiota in captive and wild birds is summarized, along with previous studies on the composition and function, research methods employed, and factors influencing the avian gut microbial communities. Furthermore, research hotspots and directions were also discussed to identify the dynamics of the avian gut microbiota, aiming to contribute to studies of avian microbiology in the future.

K-Mer Spectrum-Based Error Correction Algorithm for Next-Generation Sequencing Data

In the mid-1970s, the first-generation sequencing technique (Sanger) was created. It used Advanced BioSystems sequencing devices and Beckman's GeXP genetic testing technology. The second-generation sequencing (2GS) technique arrived just several years after the first human genome was published in 2003. 2GS devices are very quicker than Sanger sequencing equipment, with considerably cheaper manufacturing costs and far higher throughput in the form of short reads. The third-generation sequencing (3GS) method, initially introduced in 2005, offers further reduced manufacturing costs and higher throughput. Even though sequencing technique has result generations, it is error-prone due to a large number of reads. The study of this massive amount of data will aid in the decoding of life secrets, the detection of infections, the development of improved crops, and the improvement of life quality, among other things. This is a challenging task, which is complicated not just by a large number of reads and by the occurrence of sequencing mistakes. As a result, error correction is a crucial duty in data processing; it entails identifying and correcting read errors. Various k-spectrum-based error correction algorithms' performance can be influenced by a variety of characteristics like coverage depth, read length, and genome size, as demonstrated in this work. As a result, time and effort must be put into selecting acceptable approaches for error correction of certain NGS data.

Advancements in Genomic and Behavioral Neuroscience Analysis for the Study of Normal and Pathological Brain Function

Psychiatric and neurological disorders are influenced by an undetermined number of genes and molecular pathways that may differ among afflicted individuals. Functionally testing and characterizing biological systems is essential to discovering the interrelationship among candidate genes and understanding the neurobiology of behavior. Recent advancements in genetic, genomic, and behavioral approaches are revolutionizing modern neuroscience. Although these tools are often used separately for independent experiments, combining these areas of research will provide a viable avenue for multidimensional studies on the brain. Herein we will briefly review some of the available tools that have been developed for characterizing novel cellular and animal models of human disease. A major challenge will be openly sharing resources and datasets to effectively integrate seemingly disparate types of information and how these systems impact human disorders. However, as these emerging technologies continue to be developed and adopted by the scientific community, they will bring about unprecedented opportunities in our understanding of molecular neuroscience and behavior.

Sub-5 nm nanogap electrodes towards single-molecular biosensing

Nanogap electrodes (NGEs) with sub-5 nm gap has been widely used in single-molecule sensing and sequencing, with the characteristics of label-free, high sensitivity, rapid detection and low-cost. However, the fabrication of sub-5 nm gap electrodes with high controllability and reproducibility still remains a great challenge that impedes the experimental research and the commercialization of the nanogap device. Here, we review the common currently used fabrication methods of nanogap electrodes, such as gap narrowing deposition, mechanical controllable break junctions and the fabrication methods combined with nanopore or nanochannel. We then highlight the typical applications of nanogap electrodes in biological/chemical sensing fields, including single molecule recognition, single molecule sequencing and chemical kinetics analysis. Finally, the challenges of nanogap electrodes in single molecule sensing/sequencing are outlined and the future directions for sensing perspectives are suggested.

Modulation of autoimmune diabetes by N-ethyl-N-nitrosourea- induced mutations in non-obese diabetic mice

Genetic association studies of type 1 diabetes (T1D) in humans, and in congenic non-obese diabetic (NOD) mice harboring DNA segments from T1D-resistant mice, face the challenge of assigning causation to specific gene variants among many within loci that affect disease risk. Here, we created random germline mutations in NOD/NckH mice and used automated meiotic mapping to identify mutations modifying T1D incidence and age of onset. In contrast with association studies in humans or congenic NOD mice, we analyzed a relatively small number of genetic changes in each pedigree, permitting implication of specific mutations as causative. Among 844 mice from 14 pedigrees bearing 594 coding/splicing changes, we identified seven mutations that accelerated T1D development, and five that delayed or suppressed T1D. Eleven mutations affected genes not previously known to influence T1D (Xpnpep1, Herc1, Srrm2, Rapgef1, Ppl, Zfp583, Aldh1l1, Col6a1, Ccdc13, Cd200r1, Atrnl1). A suppressor mutation in Coro1a validated the screen. Mutagenesis coupled with automated meiotic mapping can detect genes in which allelic variation influences T1D susceptibility in NOD mice. Variation of some of the orthologous/paralogous genes may influence T1D susceptibility in humans.

Analysis of fungal dynamic changes in the natural fermentation broth of 'Hongyang' kiwifruit

'Hongyang' kiwifruit (Actinidia chinensis Planch.) is an ideal kiwifruit wine variety. At present, there is no research on the dynamic changes of yeast during the natural fermentation of kiwifruit wine. In this study, a high-throughput was employed to analyze the fungal population composition and diversity in the samples cultured in yeast extract peptone dextrose (YPD) medium and enriched in the natural fermentation process of 'Hongyang' kiwifruit at four time points, day one (D1T), day three (D3T), day five (D5T), and day fifteen (D15T). Five hundred and eighty-two operational taxonomic units (OTUs) were obtained from 131 genera and 178 species samples. The diversity analysis results showed that in the early natural fermentation stage, the dominant species was Aureobasidium pullulans, and as natural fermentation proceeded, the genus Pichia became the dominant species. Pichia kluyveri was an important species at the later stages of natural fermentation. An analysis of the metabolic pathways shows that P. kluyveri plays an aromatic-producing role in the natural fermentation of 'Hongyang' kiwifruit. These results could provide a theoretical basis for the studies of kiwifruit fungal diversity and fungal changes during fermentation. The findings could fix a major deficiency in the production of kiwifruit fruit wine, which lacks a specific flavor-producing yeast species or strain.

Genetics Matters: Voyaging from the Past into the Future of Humanity and Sustainability

The understanding of how genetic information may be inherited through generations was established by Gregor Mendel in the 1860s when he developed the fundamental principles of inheritance. The science of genetics, however, began to flourish only during the mid-1940s when DNA was identified as the carrier of genetic information. The world has since then witnessed rapid development of genetic technologies, with the latest being genome-editing tools, which have revolutionized fields from medicine to agriculture. This review walks through the historical timeline of genetics research and deliberates how this discipline might furnish a sustainable future for humanity.

In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes

Background

Whole genome sequencing analyzed by core genome multi-locus sequence typing (cgMLST) is widely used in surveillance of the pathogenic bacteria Listeria monocytogenes. Given the heterogeneity of available bioinformatics tools to define cgMLST alleles, our aim was to identify parameters influencing the precision of cgMLST profiles.

Methods

We used three L. monocytogenes reference genomes from different phylogenetic lineages and assessed the impact of in vitro (i.e. tested genomes, successive platings, replicates of DNA extraction and sequencing) and in silico parameters (i.e. targeted depth of coverage, depth of coverage, breadth of coverage, assembly metrics, cgMLST workflows, cgMLST completeness) on cgMLST precision made of 1748 core loci. Six cgMLST workflows were tested, comprising assembly-based (BIGSdb, INNUENDO, GENPAT, SeqSphere and BioNumerics) and assembly-free (i.e. kmer-based MentaLiST) allele callers. Principal component analyses and generalized linear models were used to identify the most impactful parameters on cgMLST precision.

Results

The isolate’s genetic background, cgMLST workflows, cgMLST completeness, as well as depth and breadth of coverage were the parameters that impacted most on cgMLST precision (i.e. identical alleles against reference circular genomes). All workflows performed well at ≥40X of depth of coverage, with high loci detection (> 99.54% for all, except for BioNumerics with 97.78%) and showed consistent cluster definitions using the reference cut-off of ≤7 allele differences.

Conclusions

This highlights that bioinformatics workflows dedicated to cgMLST allele calling are largely robust when paired-end reads are of high quality and when the sequencing depth is ≥40X.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08437-4.

National Genome Initiatives in Europe and the United Kingdom in the Era of Whole-Genome Sequencing: A Comprehensive Review

Identification of genomic variability in population plays an important role in the clinical diagnostics of human genetic diseases. Thanks to rapid technological development in the field of massive parallel sequencing technologies, also known as next-generation sequencing (NGS), complex genomic analyses are now easier and cheaper than ever before, which consequently leads to more effective utilization of these techniques in clinical practice. However, interpretation of data from NGS is still challenging due to several issues caused by natural variability of DNA sequences in human populations. Therefore, development and realization of projects focused on description of genetic variability of local population (often called "national or digital genome") with a NGS technique is one of the best approaches to address this problem. The next step of the process is to share such data via publicly available databases. Such databases are important for the interpretation of variants with unknown significance or (likely) pathogenic variants in rare diseases or cancer or generally for identification of pathological variants in a patient's genome. In this paper, we have compiled an overview of published results of local genome sequencing projects from United Kingdom and Europe together with future plans and perspectives for newly announced ones.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

Modifying Bacterial Artificial Chromosomes for Extended Genome Modification

Bacterial artificial chromosomes have been used extensively for the exploration of mammalian genomes. Although novel approaches made their initial function expendable, the available BAC libraries are a precious source for life science. Their comprising of extended genomic regions provides an ideal basis for creating a large targeting vector. Here, we describe the identification of suitable BACs from their libraries and their verification prior to manipulation. Further, protocols for modifying BAC, confirming the desired modification and the preparation of transfection into mammalian cells are given.

Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods

Identifying the reactions that govern a dynamical biological system is a crucial but challenging task in systems biology. In this work, we present a data-driven method to infer the underlying biochemical reaction system governing a set of observed species concentrations over time. We formulate the problem as a regression over a large, but limited, mass-action constrained reaction space and utilize sparse Bayesian inference via the regularized horseshoe prior to produce robust, interpretable biochemical reaction networks, along with uncertainty estimates of parameters. The resulting systems of chemical reactions and posteriors inform the biologist of potentially several reaction systems that can be further investigated. We demonstrate the method on two examples of recovering the dynamics of an unknown reaction system, to illustrate the benefits of improved accuracy and information obtained.

Decrypting the complexity of the human malaria parasite biology through systems biology approaches

The human malaria parasite, Plasmodium falciparum, is a unicellular protozoan responsible for over half a million deaths annually. With a complex life cycle alternating between human and invertebrate hosts, this apicomplexan is notoriously adept at evading host immune responses and developing resistance to all clinically administered treatments. Advances in omics-based technologies, increased sensitivity of sequencing platforms and enhanced CRISPR based gene editing tools, have given researchers access to more in-depth and untapped information about this enigmatic micro-organism, a feat thought to be infeasible in the past decade. Here we discuss some of the most important scientific achievements made over the past few years with a focus on novel technologies and platforms that set the stage for subsequent discoveries. We also describe some of the systems-based methods applied to uncover gaps of knowledge left through single-omics applications with the hope that we will soon be able to overcome the spread of this life-threatening disease.

Whole Exome-Sequencing of Pooled Genomic DNA Samples to Detect Quantitative Trait Loci in Esotropia and Exotropia of Strabismus in Japanese

BACKGROUND

Esotropia and exotropia are two major phenotypes of comitant strabismus. It remains controversial whether esotropia and exotropia would share common genetic backgrounds. In this study, we used a quantitative trait locus (QTL)-sequencing pipeline for diploid plants to screen for susceptibility loci of strabismus in whole exome sequencing of pooled genomic DNAs of individuals.

METHODS

Pooled genomic DNA (2.5 ng each) of 20 individuals in three groups, Japanese patients with esotropia and exotropia, and normal members in the families, was sequenced twice after exome capture, and the first and second sets of data in each group were combined to increase the read depth. The SNP index, as the ratio of variant genotype reads to all reads, and Δ(SNP index) values, as the difference of SNP index between two groups, were calculated by sliding window analysis with a 4 Mb window size and 10 kb slide size. The rows of 200 "N"s were inserted as a putative 200-b spacer between every adjoining locus to depict Δ(SNP index) plots on each chromosome. SNP positions with depth < 20 as well as SNP positions with SNP index of <0.3 were excluded.

RESULTS

After the exclusion of SNPs, 12,242 SNPs in esotropia/normal group and 12,108 SNPs in exotropia/normal group remained. The patterns of the Δ(SNP index) plots on each chromosome appeared different between esotropia/normal group and exotropia/normal group. When the consecutive groups of SNPs on each chromosome were set at three patterns: SNPs in each cytogenetic band, 50 consecutive sliding SNPs, and SNPs in 4 Mb window size with 10 kb slide size, p values (Wilcoxon signed rank test) and Q values (false discovery rate) in a few loci as Manhattan plots showed significant differences in comparison between the Δ(SNP index) in the esotropia/normal group and exotropia/normal group.

CONCLUSIONS

The pooled DNA sequencing and QTL mapping approach for plants could provide overview of genetic background on each chromosome and would suggest different genetic backgrounds for two major phenotypes of comitant strabismus, esotropia and exotropia.

It takes guts to learn: machine learning techniques for disease detection from the gut microbiome

Associations between the human gut microbiome and expression of host illness have been noted in a variety of conditions ranging from gastrointestinal dysfunctions to neurological deficits. Machine learning (ML) methods have generated promising results for disease prediction from gut metagenomic information for diseases including liver cirrhosis and irritable bowel disease, but have lacked efficacy when predicting other illnesses. Here, we review current ML methods designed for disease classification from microbiome data. We highlight the computational challenges these methods have effectively overcome and discuss the biological components that have been overlooked to offer perspectives on future work in this area.

Dietary Recommendations of the French Society for Rheumatology for Patients with Chronic Inflammatory Rheumatic Diseases

This article presents the 1^st set of dietary recommendations of the French Society for Rheumatology for patients suffering from chronic inflammatory rheumatic diseases (IRD) made by a working group consisting of 12 rheumatology experts, 3 physician nutrition specialists, 1 internal medicine specialist, 1 registered dietician and 3 representatives from patient associations. This group relied on a systematic literature review and on expert opinions, while taking into consideration not only the joint effects of diet in IRD but also the extra-articular ones. Eight general principles and nine recommendations were established. The general principles emphasize that nutritional advice is not a substitute for pharmacological treatment of IRD and that it is an integral part of the patients' overall care, which could help the patient actively participate in their care. The recommendations propose supporting weight loss in subjects who are overweight or obese, a Mediterranean-type diet and supplementation in polyunsaturated fatty acids, mainly omega-3. Conversely, gluten-free diets (in the absence of celiac disease), vegetarian/vegan diets, fasting and elimination of dairy products should not be proposed. Supplementation with vitamins or trace elements is not indicated for controlling chronic IRD activity, while the use of probiotics or spices is not recommended given the limited or disparate data.

DNA sequencing: an overview of solid-state and biological nanopore-based methods

The field of sequencing is a topic of significant interest since its emergence and has become increasingly important over time. Impressive achievements have been obtained in this field, especially in relations to DNA and RNA sequencing. Since the first achievements by Sanger and colleagues in the 1950s, many sequencing techniques have been developed, while others have disappeared. DNA sequencing has undergone three generations of major evolution. Each generation has its own specifications that are mentioned briefly. Among these generations, nanopore sequencing has its own exciting characteristics that have been given more attention here. Among pioneer technologies being used by the third-generation techniques, nanopores, either biological or solid-state, have been experimentally or theoretically extensively studied. All sequencing technologies have their own advantages and disadvantages, so nanopores are not free from this general rule. It is also generally pointed out what research has been done to overcome the obstacles. In this review, biological and solid-state nanopores are elaborated on, and applications of them are also discussed briefly.