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The dialogue between population genetics and evolutionary biology, which historically followed separate paths, has now developed into a complex and interdisciplinary field of study [...].

Paper mulberry (Broussonetia papyrifera) is a well-known woody tree historically used for Cai Lun papermaking, one of the four great inventions of ancient China. More recently, Paper mulberry has also been used as forage to address the shortage of feedstuff because of its digestible crude fiber and high protein contents. In this study, we obtained a chromosome-scale genome assembly for Paper mulberry using integrated approaches, including Illumina and PacBio sequencing platform as well as Hi-C, optical, and genetic maps. The assembled Paper mulberry genome consists of 386.83 Mb, which is close to the estimated size, and 99.25% (383.93 Mb) of the assembly was assigned to 13 pseudochromosomes. Comparative genomic analysis revealed the expansion and contraction in the flavonoid and lignin biosynthetic gene families, respectively, accounting for the enhanced flavonoid and decreased lignin biosynthesis in Paper mulberry. Moreover, the increased ratio of syringyl-lignin to guaiacyl-lignin in Paper mulberry underscores its suitability for use in medicine, forage, papermaking, and barkcloth making. We also identified the root-associated microbiota of Paper mulberry and found that Pseudomonas and Rhizobia were enriched in its roots and may provide the source of nitrogen for its stems and leaves via symbiotic nitrogen fixation. Collectively, these results suggest that Paper mulberry might have undergone adaptive evolution and recruited nitrogen-fixing microbes to promote growth by enhancing flavonoid production and altering lignin monomer composition. Our study provides significant insights into genetic basis of the usefulness of Paper mulberry in papermaking and barkcloth making, and as forage. These insights will facilitate further domestication and selection as well as industrial utilization of Paper mulberry worldwide., (Copyright © 2019 The Author. Published by Elsevier Inc. All rights reserved.)

Background: Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability., Objective: We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript., Methods: An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases., Findings: The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing., Conclusion: The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Royal Astronomical Society.)

Psychiatric genomics has the potential to radically improve the prevention and early intervention of serious mental and neurodevelopmental disorders worldwide. However, little work has been done on the ethics of psychiatric genomics-an oversight that could result in poor local uptake, reduced practical/clinical application, and ethical violations in this rapidly developing area of scientific research. As part of the Global Project of the Stanley Center for Psychiatric Research, the Global Initiative in Neuropsychiatric GenEthics (NeuroGenE) based at the University of Oxford aims to embed ethical inquiry within scientific investigation and engage with fundamental ethical questions around a psychiatric genomics approach to mental and neurodevelopmental disorder. This position paper sets out the core aims of the NeuroGenE research programme and explores the importance of a crosscutting research orientation in this field based on multidisciplinary methodologies which can ensure that efforts to translate and apply global psychiatric genomics in public policy and clinical practice are ethically grounded strategies, respectful of different cultures and contexts., (© 2018 Wiley Periodicals, Inc.)

The National Institute on Drug Abuse Genetics and Epigenetics Cross-Cutting Research Team convened a diverse group of researchers, clinicians, and healthcare providers on the campus of the University of California, San Diego, in June 2018. The goal was to develop strategies to integrate genetics and phenotypes across species to achieve a better understanding of substance use disorders through associations between genotypes and addictive behaviors. This conference (a) discussed progress in harmonizing large opioid genetics cohorts, (b) discussed phenotypes that are used for genetics studies in humans, (c) examined phenotypes that are used for genetics studies in animal models, (d) identified synergies and gaps in phenotypic analyses of human and animal models and (e) identified strategies to integrate genetics and genomics data with phenotypes across species. The meeting consisted of panels that focused on phenotype harmonization (Dr. Laura Bierut, Dr. Olivier George, Dr. Dan Larach and Dr. Sesh Mudumbai), translating genetic findings between species (Dr. Elissa Chesler, Dr. Gary Peltz and Dr. Abraham Palmer), interpreting and understanding allelic variations (Dr. Vanessa Troiani and Dr. Tamara Richards) and pathway conservation in animal models and human studies (Dr. Robert Hitzemann, Dr. Huda Akil and Dr. Laura Saba). There were also updates that were provided by large consortia (Dr. Susan Tapert, Dr. Danielle Dick, Dr. Howard Edenberg and Dr. Eric Johnson). Collectively, the conference was convened to discuss progress and changes in genome-wide association studies., (© 2019 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.)

RNA interference (RNAi) is a useful tool to assess gene function by knocking down expression of a target gene and has been used successfully in domestic and laboratory organisms. However, the use of RNAi for functional genomics has not fully extended into ecological model organisms in natural environments. Assessment of gene function in the wild is important because gene function can be environmentally and context dependent. Here, we present a case study using RNAi to assess gene function in wild paper wasps Polistes metricus, to test roles for two candidate genes (NADH dehydrogenase (NADHdh) and retinoid and fatty acid binding protein (RfaBp)) in the development of reproductive castes. Previous studies have shown that these genes are upregulated in larvae that become queens compared to workers, but this pattern was reversed in the laboratory, making field-based studies necessary. We orally administered dsRNA to larvae in field colonies and found evidence of a short-term knockdown followed by a compensatory rebound in expression for RfaBp. We also observed the predicted worker-like decrease in lipid stores in NADHdh dsRNA treated wasps, suggesting a possible role for NADHdh in caste development. We discuss our results in the context of challenges for using RNAi for functional genomics in ecological model organisms in the field.

Next generation genomic sequencing (NGS) technologies-whole genome and whole exome sequencing-are now cheap enough to be within the grasp of many health care organizations. To many, NGS is symbolic of cutting edge health care, offering the promise of "precision" and "personalized" medicine. Historically, research and clinical application has been a two-way street in clinical genetics: research often driven directly by the desire to understand and try to solve immediate clinical problems affecting real, identifiable patients and families, accompanied by a low threshold of willingness to apply research-driven interventions without resort to formal empirical evaluations. However, NGS technologies are not simple substitutes for older technologies and need careful evaluation for use as screening, diagnostic, or prognostic tools. We have concerns across three areas. First, at the moment, analytic validity is unknown because technical platforms are not yet stable, laboratory quality assurance programs are in their infancy, and data interpretation capabilities are badly underdeveloped. Second, clinical validity of genomic findings for patient populations without pre-existing high genetic risk is doubtful, as most clinical experience with NGS technologies relates to patients with a high prior likelihood of a genetic etiology. Finally, we are concerned that proponents argue not only for clinically driven approaches to assessing a patient's genome, but also for seeking out variants associated with unrelated conditions or susceptibilities-so-called "secondary targets"-this is screening on a genomic scale. We argue that clinical uses of genomic sequencing should remain limited to specialist and research settings, that screening for secondary findings in clinical testing should be limited to the maximum extent possible, and that the benefits, harms, and economic implications of their routine use be systematically evaluated. All stakeholders have a responsibility to ensure that patients receive effective, safe health care, in an economically sustainable health care system. There should be no exception for genome-based interventions., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Next-generation sequencing technologies have revolutionized genomics and altered the scientific publication landscape. Life-science journals abound with genome papers-peer-reviewed descriptions of newly sequenced chromosomes. Although they once filled the pages of Nature and Science, genome papers are now mostly relegated to journals with low-impact factors. Some have forecast the death of the genome paper and argued that they are using up valuable resources and not advancing science. However, the publication rate of genome papers is on the rise. This increase is largely because some journals have created a new category of manuscript called genome reports, which are short, fast-tracked papers describing a chromosome sequence(s), its GenBank accession number and little else. In 2015, for example, more than 2000 genome reports were published, and 2016 is poised to bring even more. Here, I highlight the growing popularity of genome reports and discuss their merits, drawbacks and impact on science and the academic publication infrastructure. Genome reports can be excellent assets for the research community, but they are also being used as quick and easy routes to a publication, and in some instances they are not peer reviewed. One of the best arguments for genome reports is that they are a citable, user-generated genomic resource providing essential methodological and biological information, which may not be present in the sequence database. But they are expensive and time-consuming avenues for achieving such a goal., (© The Author 2016. Published by Oxford University Press.)

Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations., (© 2024. Springer Nature Limited.)

The genomics revolution has contributed enormously to research and disease management applications in plant pathology. This development has rapidly increased our understanding of the molecular mechanisms underpinning pathogenesis and resistance, contributed novel markers for rapid pathogen detection and diagnosis, and offered further insights into the genetics of pathogen populations on a larger scale. The availability of whole genome resources coupled with next-generation sequencing (NGS) technologies has helped fuel genomics-based approaches to improve disease resistance in crops. NGS technologies have accelerated the pace at which whole plant and pathogen genomes have become available, and made possible the metagenomic analysis of plant-associated microbial communities. Furthermore, NGS technologies can now be applied routinely and cost effectively to rapidly generate plant and/or pathogen genome or transcriptome marker sequences associated with virulence phenotypes in the pathogen or resistance phenotypes in the plant, potentially leading to improvements in plant disease management. In some systems, investments in plant and pathogen genomics have led to immediate, tangible benefits. This focus issue covers some of the systems. The articles in this focus issue range from overall perspective articles to research articles describing specific genomics applications for detection and control of diseases caused by nematode, viral, bacterial, fungal, and oomycete pathogens. The following are representative short summaries of the articles that appear in this Focus Issue .

Ortholog detection (OD) is a lynchpin of most statistical methods in comparative genomics. This task involves accurately identifying genes across species that descend from a common ancestral sequence. OD methods comprise a wide variety of approaches, each with their own benefits and costs under a variety of evolutionary and practical scenarios. In this article, we examine the proteomes of ten mammals by using four methodologically distinct, rigorously filtered OD methods. In head-to-head comparisons, we find that these algorithms significantly outperform one another for 38-45% of the genes analyzed. We leverage this high complementarity through the development MOSAIC, or Multiple Orthologous Sequence Analysis and Integration by Cluster optimization, the first tool for integrating methodologically diverse OD methods. Relative to the four methods examined, MOSAIC more than quintuples the number of alignments for which all species are present while simultaneously maintaining or improving functional-, phylogenetic-, and sequence identity-based measures of ortholog quality. Further, this improvement in alignment quality yields more confidently aligned sites and higher levels of overall conservation, while simultaneously detecting of up to 180% more positively selected sites. We close by highlighting a MOSAIC-specific positively selected sites near the active site of TPSAB1, an enzyme linked to asthma, heart disease, and irritable bowel disease. MOSAIC alignments, source code, and full documentation are available at http://pythonhosted.org/bio-MOSAIC., (Copyright © 2015 Maher and Hernandez.)

Cryptococcus gattii is an emerging global pathogen. Recent reports suggest that C. gattii cryptococcosis is more common in immunocompetent as well as HIV-infected AIDS patients than earlier estimated. An ongoing outbreak of C. gattii in Vancouver, Canada, and the US Pacific Northwest has heightened public health awareness in North America. We have few clues as to what causes emergence or re-emergence of highly pathogenic strains, why C. gattii split up from its sibling pathogen C. neoformans, why it thrives in trees instead, and why immunocompetent individuals are vulnerable to this pathogen? C. gattii comprises of four distinct lineages, but the information on the genome of C. gattii is inadequate and unrepresentative as it is limited to two strains, R265 and WM276, which are MATα, serotype B, genotype VGII/VGI from Canada and Australia, respectively. There is a wide gap in knowledge about the genomes of VGIII and VGIV strains, serotype C strains, and MATa strains. The geographical representation is inadequate in the absence of strains from California, South America, Asia, and Africa. Additional obstacles to work with this pathogen are the following: (a) complex molecular typing schemes and (b) lack of functional genomics analyses. We propose to complete genome sequencing of 12 reference strains by next-generation sequencing technology and to map their transcriptomes by RNA-Seq technology. This effort would lead to new resources for the scientific community including (1) insight from additional C. gattii genomes to anchor future research studies, (2) validation of single-nucleotide polymorphisms (SNPs) for molecular typing to improve epidemiology studies, and (3) transcript analyses from strains under relevant pathogenic and non-pathogenic conditions to accelerate the discovery of proteins for diagnostics, drug targets, and vaccines.

Keeping up with the rapidly growing literature has become virtually impossible for most scientists. This can have dire consequences. First, we may waste research time and resources on reinventing the wheel simply because we can no longer maintain a reliable grasp on the published literature. Second, and perhaps more detrimental, judicious (or serendipitous) combination of knowledge from different scientific disciplines, which would require following disparate and distinct research literatures, is rapidly becoming impossible for even the most ardent readers of research publications. Text mining - the automated extraction of information from (electronically) published sources - could potentially fulfil an important role - but only if we know how to harness its strengths and overcome its weaknesses. As we do not expect that the rate at which scientific results are published will decrease, text mining tools are now becoming essential in order to cope with, and derive maximum benefit from, this information explosion. In genomics, this is particularly pressing as more and more rare disease-causing variants are found and need to be understood. Not being conversant with this technology may put scientists and biomedical regulators at a severe disadvantage. In this review, we introduce the basic concepts underlying modern text mining and its applications in genomics and systems biology. We hope that this review will serve three purposes: (i) to provide a timely and useful overview of the current status of this field, including a survey of present challenges; (ii) to enable researchers to decide how and when to apply text mining tools in their own research; and (iii) to highlight how the research communities in genomics and systems biology can help to make text mining from biomedical abstracts and texts more straightforward.

The use of socially learned information (culture) is central to human adaptations. We investigate the hypothesis that the process of cultural evolution has played an active, leading role in the evolution of genes. Culture normally evolves more rapidly than genes, creating novel environments that expose genes to new selective pressures. Many human genes that have been shown to be under recent or current selection are changing as a result of new environments created by cultural innovations. Some changed in response to the development of agricultural subsistence systems in the Early and Middle Holocene. Alleles coding for adaptations to diets rich in plant starch (e.g., amylase copy number) and to epidemic diseases evolved as human populations expanded (e.g., sickle cell and G6PD deficiency alleles that provide protection against malaria). Large-scale scans using patterns of linkage disequilibrium to detect recent selection suggest that many more genes evolved in response to agriculture. Genetic change in response to the novel social environment of contemporary modern societies is also likely to be occurring. The functional effects of most of the alleles under selection during the last 10,000 years are currently unknown. Also unknown is the role of paleoenvironmental change in regulating the tempo of hominin evolution. Although the full extent of culture-driven gene-culture coevolution is thus far unknown for the deeper history of the human lineage, theory and some evidence suggest that such effects were profound. Genomic methods promise to have a major impact on our understanding of gene-culture coevolution over the span of hominin evolutionary history.

Unlabelled: There is an explosion in the numbers of nurse authors exploring new and exciting opportunities to understand genomic medicine because of international success on The Human Genome Project., Objectives: The primary purpose of this paper is to spotlight and to promote collaborative interdisciplinary and international nursing research within genetics and genomics., Design: Review of the literature., Data Sources: Research in nursing pertaining to genetics and genomics, policy statements, and opinion papers., Review Methods: Synthesis of the literature in four areas: genetic nursing research, genomic medicine, barriers to international collaboration, and elements that foster international collaboration., Results: Genetics and genomic medicine have implications for virtually all diseases in all health care settings in developed and still developing nations. Research in nursing, genetics and genomics is scarce. There is a gap in nursing literature about how to address barriers to foster international collaboration., Conclusions: The authors who have engaged in international collaboration offer a tentative road map for establishing and assessing the progress of research collaboration. New funding mechanisms to support international nursing research in this area are needed.

The stability of DNA in dried blood samples obtained from the neonatal screening program in Thailand was retrospectively studied in order to determine the conditions necessary for the long term storage of samples for DNA banking. Specimens from 1991 to 2001, which had been kept in the ambient conditions at the Department of Medical Science, Ministry of Public Health, Thailand, were randomly sampled and used for the study. Genomic DNA was extracted from the samples and DNA fragments of the PAX8 and beta-globin genes were amplified by PCR to determine DNA stability. The study showed that 255-bp and 674-bp fragments of the PAX8 gene could be amplified from all the samples. The DNA fragment of 1,039 bp of the beta-globin gene could be detected in all of the samples for the years 1993 to 2001, but only in seven and five out of the ten studied samples for each of the years 1991 and 1992, respectively. Our study shows that genomic DNA is stable in dried blood stored on filter paper at ambient tropical conditions for at least 11 years. However, DNA quality for amplification of larger DNA fragments decreased when the specimens were stored for longer than 10 years.

Background: Although, there is a wealth of information in the medical literature on the usefulness of genomic testing in assessing risk and its application in medical oncology decision making, there are no theoretical reflections in the nursing field. Aim: To understand the implications of molecular biology in nursing practice and highlight the role of Nursing Theory in guiding nurses' reasoning. Materials and Methods: Searching literature published between 2000 and 2022 in Medline and Google Scholar. Scientific evidence was analysed by the authors expert in different fields. Results: Based on the findings of the literature, concerns have been raised about the proper care of cancer patients who have a genomic risk profile determination. In particular, the absence of theoretical thinking and conceptual models that consider developments in molecular biology and their impact on nursing, in addition to the prevalence of heuristic thinking and the application of clinical patterns in nursing practice, could induce patient misjudgement with inadequate planning of preventive, curative, rehabilitative and educational nursing interventions. Nurses working in the field of oncology should be aware that the risk profile determined by genomics tests is merely the visible and stated portion of the cancer patient: the tip of iceberg. Discussion: This study demonstrates how genomic testing takes into account a fraction of genes discovered in tumour tissue to establish a risk profile. This subset differs, for example, from the social genome, which can determine the risk of dementia, cancer and cardiovascular disease, but in response to social adversity. Nursing theory, which views the environment as a metaparadigm, must consider a conceptual model that can integrate the findings of genomic testing with recommendations from studies on the social genome of humans to make it easier to build nursing treatments that can better reduce these risks. Conclusion: A nursing theoretical discourse on genomics is a paramount requirement for developing effective nursing care. [ABSTRACT FROM AUTHOR]

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA., (© 2023. Springer Nature Limited.)