Genomic Studies Research Articles

Genomic and growth fitness study of extended spectrum β-lactamase-producing Escherichia coli from bloodstream infections after introduction of a national 4C antimicrobial stewardship policy in Scotland

Extended spectrum β-lactamase-producing Escherichia coli remains a major cause of hospital-acquired bloodstream infections in countries with high antimicrobial stewardship compliance. Isolates from bloodstream infections that occurred between 2010 and 2020 in a tertiary level hospital in North-East Scotland soon after introduction of the "4C" antimicrobial stewardship policy were analysed for phylogenetic structure, antimicrobial resistance, plasmid and virulence gene carriage. Growth fitness was measured in kinetic assays. Non-metric-multidimensional-scaling was used to evaluate clonal relationships, antimicrobial resistance, and virulence profiles in early and later years after the 4C policy introduction. Clonal and fitness trends over the study period were determined by generalized additive modelling. The relationship between clonal type, antimicrobial resistance, and fitness was evaluated by linear regression. Three hierarchical phylogenetic clusters were identified, with the most dominant cluster (O25:H4/fimH30) including all, and nearly exclusively, Clade C ST131 isolates as well as minor non-ST131 sequence types. The prevalence of ST131 was largely stable over the study period. Resistance to aminoglycosides and aztreonam in ST131 was lower (p=0.019 and p=0.004, respectively) during later years (2016-2020) by 28% on average compared to early years soon after 4C policy implementation (2010-2014). Carriage of virulence factors involved in bacterial adaptation was higher in ST131 compared to non-ST131 but mostly stable in early vs later years. Growth fitness of ST131 was lower than non-ST131 and declined steadily in later years (p<0.0001). Despite stable virulence factor carriage, population structure and resistance to cephalosporins, we show increased susceptibility of ST131 to aminoglycosides and aztreonam and concurrent fitness decline years after the introduction of the 4C policy.

Genome-wide association study for milking speed in Fleckvieh cattle

Milking speed is an important trait influencing udder health of dairy cows as well as labor efficiency. Yet, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual purpose Simmental) cattle. Genome-wide association studies were conducted using de-regressed breeding values of bulls as phenotypes. Six SNP on 4 autosomes were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observation of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within family variation may be caused by transmission of alternative alleles of bulls being heterozygous for a gene affecting milking speed. To check on this, we considered standard deviation of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on de-regressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose sub-processes have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions.

Gamma ray induced significant phenotypic and metabolomic sugarcane variants derived through in vitro mutagenesis

Sugarcane is an economically important polyploid crop whose genetic complexity and limited fertility poses a challenge for crop improvement programs. Gamma radiation-induced mutagenesis is an alternate approach for generating a diverse array of agronomically useful mutants, accelerating varietal development in long duration crop like sugarcane. To develop agronomically useful mutants of a commercial sugarcane genotype Co 99004, gamma ray inducedin vitro mutagenesis was studied. The phenotypic variants of Co 99004 in V1 generation could be categorized into five distinct phenotypically scorable classes, including three chlorophyll mutants (albina, chlorina and chlorina pigmented) and two green mutants like wild type control. SRAP marker analyses indicated distinct genomic variation among the phenotypic mutants and control plants, with the polymorphic information content (PIC) ranging from 0-0.472. Further, the phylogenetic dendrogram derived from the SRAP marker data grouped the mutants into four distinct clusters clearly differentiating the phenotypic classification. Sequencing of selected SRAP amplicons indicated deletion/insertion of gene specific fragments.Interestingly, the loss of chlorophyll in albina and chlorina mutantsshowed gamma irradiation-induced deletions in the gene encoding FAR1-RELATED SEQUENCE 5-like protein, which is involved in chlorophyll biosynthesis. GC-MS based metabolome profiling showed alteration in tetrapyrrole biosynthesis, MEP(Methylerythritol Phosphate), and fatty acid biosynthesis pathways, indicating a significant metabolic variation in the chlorophyll mutants.Further characterization of the genetically distinct, non-lethal green wild type mutants can lead to the identification of agronomically useful mutants. Further, the loss of function chlorophyll mutants can serve as a good source for comparative genomics studies aimed at gene-trait association.

Repeated Shifts in Sociality Are Associated With Fine-tuning of Highly Conserved and Lineage-Specific Enhancers in a Socially Flexible Bee.

Comparative genomic studies of social insects suggest that changes in gene regulation are associated with evolutionary transitions in social behavior, but the activity of predicted regulatory regions has not been tested empirically. We used self-transcribing active regulatory region sequencing, a high-throughput enhancer discovery tool, to identify and measure the activity of enhancers in the socially variable sweat bee, Lasioglossum albipes. We identified over 36,000 enhancers in the L. albipes genome from 3 social and 3 solitary populations. Many enhancers were identified in only a subset of L. albipes populations, revealing rapid divergence in regulatory regions within this species. Population-specific enhancers were often proximal to the same genes across populations, suggesting compensatory gains and losses of regulatory regions may preserve gene activity. We also identified 1,182 enhancers with significant differences in activity between social and solitary populations, some of which are conserved regulatory regions across species of bees. These results indicate that social trait variation in L. albipes is associated with the fine-tuning of ancient enhancers as well as lineage-specific regulatory changes. Combining enhancer activity with population genetic data revealed variants associated with differences in enhancer activity and identified a subset of differential enhancers with signatures of selection associated with social behavior. Together, these results provide the first empirical map of enhancers in a socially flexible bee and highlight links between cis-regulatory variation and the evolution of social behavior.

First Complete Genome Sequence of Nigrospora osmanthi: A Fundamental Resource for Studying the Plant Pathogenic Fungus

Nigrospora osmanthi strain Z1 is a potential bioherbicide for the biological control of water lettuce, one of the most common invasive weeds. Here, the first high-quality genome assembly of N. osmanthi was obtained by a combination of PacBio and Illumina sequencing technologies. Twelve contigs representing the nuclear genome and one mitochondrial DNA were generated, with a total length of 45.94 Mb, an N50 equal to 6.99 Mb, and a GC content of 57.91%; 9 of the 12 nuclear contigs represented chromosomes from telomere to telomere characterized by telomeric-like repeats. A total of 11,051 genes were predicted using a combination of gene prediction tools, including 336 noncoding RNAs, 1,298 genes encoding secretory proteins, 1,735 genes encoding carbohydrate-active enzymes, 1,955 fungal virulence factors, and 50 putative secondary metabolite gene clusters. This complete genome sequence can serve as a valuable resource for future comparative genomic studies of the fungus Nigrospora for effective application in the biocontrol of invasive species and the discovery of fungal secondary metabolites. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Osteoarthritis year in review 2024: Genetics, genomics, and epigenetics

ObjectiveThe purpose of this narrative review is to highlight the advances made in the past 12 months in the field of osteoarthritis genetics, genomics and epigenetics. MethodsThe Medline and Embase databases were systematically searched for original publications using terminology, and combinations of terminology, relating to: “osteoarthritis”, “genetics”, “genomics”, and “epigenetics”. Only original research articles published in the English language between the OARSI congresses of April 2032 and April 2024 were considered. ResultsThis narrative review focuses only on studies using genome-wide omics techniques in human material. There was a rise in functional genomics studies across different osteoarthritis-relevant tissues, which have robustly identified an additional 26 genes involved in osteoarthritis pathology. Two of such previously identified genes (MGP, ALDH1A2) are currently the target of ongoing clinical trials for osteoarthritis. This past year also saw the use of single-cell transcriptomics and two relatively new omics: epitranscriptomics and mitochondrial genomics. ConclusionThis past year of genomics research has led to multiple exciting findings involving genes and mechanisms linked to osteoarthritis. Moreover, the comprehensive genome-wide omics datasets generated for diverse osteoarthritis tissues will prove invaluable for future research aimed at elucidating more causal biological mechanisms and possible therapeutic targets for osteoarthritis.

Chromosome-scale genome assembly of the mangrove climber species Dalbergia candenatensis

Consisting of trees, climbers and herbs exclusively in the intertidal environments, mangrove forest is one of the most extreme and vulnerable ecosystems of our planet and has long been of great interest for biologists and ecologists. Here, we first assembled the chromosome-scale genome of a climber mangrove plant, Dalbergia candenatensis. The assembled genome size is approximately 474.55 Mb, with a scaffold N50 of 48.1 Mb, a complete BUSCO score of 98.4%, and a high LTR Assembly Index value of 21. The genome contained 283.46 Mb (59.74%) repetitive sequences, and 29,554 protein-coding genes were predicted, of which 87.54% were functionally annotated in five databases. The high-quality genome assembly and annotation presented herein provide a valuable genomic resource that will expedite genomic and evolutionary studies of mangrove plants and facilitate the elucidation of molecular mechanisms underlying the salt- and water-logging-tolerance of mangrove plants.

Detectability of runs of homozygosity is influenced by analysis parameters and population-specific demographic history.

Wild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness. Detecting and characterizing runs of homozygosity (ROHs) is a popular strategy for assessing the extent of individual inbreeding present in a population and can also shed light on the genetic mechanisms contributing to inbreeding depression. Here, we analyze simulated and empirical datasets to demonstrate the downstream effects of program selection and long-term demographic history on ROH inference, leading to context-dependent biases in the results. Through a sensitivity analysis we evaluate how various parameter values impact ROH-calling results, highlighting its utility as a tool for parameter exploration. Our results indicate that ROH inferences are sensitive to factors such as sequencing depth and ROH length distribution, with bias direction and magnitude varying with demographic history and the programs used. Estimation biases are particularly pronounced at lower sequencing depths, potentially leading to either underestimation or overestimation of inbreeding. These results are particularly important for the management of endangered species, as underestimating inbreeding signals in the genome can substantially undermine conservation initiatives. We also found that small true ROHs can be incorrectly lumped together and called as longer ROHs, leading to erroneous inference of recent inbreeding. To address these challenges, we suggest using a combination of ROH detection tools and ROH length-specific inferences, along with sensitivity analysis, to generate robust and context-appropriate population inferences regarding inbreeding history. We outline these recommendations for ROH estimation at multiple levels of sequencing effort, which are typical of conservation genomics studies.

Towards functional maps of non-coding variants in cancer.

Large scale cancer genomic studies in patients have unveiled millions of non-coding variants. While a handful have been shown to drive cancer development, the vast majority have unknown function. This review describes the challenges of functionally annotating non-coding cancer variants and understanding how they contribute to cancer. We summarize recently developed high-throughput technologies to address these challenges. Finally, we outline future prospects for non-coding cancer genetics to help catalyze personalized cancer therapy.

Cardiomyopathies in 100,000 genomes project: interval evaluation improves diagnostic yield and informs strategies for ongoing gene discovery

BackgroundCardiomyopathies are clinically important conditions, with a strong genetic component. National genomic initiatives such as 100,000 Genome Project (100KGP) provide opportunity to study these rare conditions at scale beyond conventional research studies.MethodsWe present the clinical and molecular characteristics of the 100KGP cohort, comparing paediatric and adult probands with diverse cardiomyopathies. We assessed the diagnostic yield and spectrum of genetic aetiologies across clinical presentations. We re-analysed existing genomic data using an updated analytical strategy (revised gene panels; unbiased analyses of de novo variants; and improved variant prioritisation strategies) to identify new causative variants in genetically unsolved children.ResultsWe identified 1918 individuals (1563 probands, 355 relatives) with cardiomyopathy (CM) in 100KGP. Probands, comprising 273 children and 1290 adults, were enrolled under > 55 different recruitment categories. Paediatric probands had higher rates of co-existing congenital heart disease (12%) compared to adults (0.9%). Diagnostic yield following 100KGP’s initial analysis was significantly higher for children (19%) than for adults (11%) with 11% of diagnoses overall made in genes not on the existing UK paediatric or syndromic CM panel. Our re-analysis of paediatric probands yields a potential diagnosis in 40%, identifying new probable or possible diagnoses in 49 previously unsolved paediatric cases. Structural and intronic variants accounted for 11% of all potential diagnoses in children while de novo variants were identified in 17%.Conclusions100KGP demonstrates the benefit of genome sequencing over a standalone panel in CM. Re-analysis of paediatric CM probands allowed a significant uplift in diagnostic yield, emphasising the importance of iterative re-evaluation in genomic studies. Despite these efforts, many children with CM remain without a genetic diagnosis, highlighting the need for better gene-disease relationship curation and ongoing data sharing. The 100KGP CM cohort is likely to be useful for further gene discovery, but heterogeneous ascertainment and key technical limitations must be understood and addressed.

Cardiovascular Disease Pathogenicity Predictor (CVD-PP): A Tissue-Specific In Silico Tool for Discriminating Pathogenicity of Variants of Unknown Significance in Cardiovascular Disease Genes.

Interpretation of variants of uncertain significance (VUSs) remains a challenge in the care of patients with inherited cardiovascular diseases (CVDs); 56% of variants within CVD risk genes are VUS, and machine learning algorithms trained upon large data resources can stratify VUS into higher versus lower probability of contributing to a CVD phenotype. We used ClinVar pathogenic/likely pathogenic and benign/likely benign variants from 47 CVD genes to build a predictive model of variant pathogenicity utilizing measures of evolutionary constraint, deleteriousness, splicogenicity, local pathogenicity, cardiac-specific expression, and population allele frequency. Performance was validated using variants for which the ClinVar pathogenicity assignment changed. Functional validation was assessed using prior studies in >900 identified VUS. The model utility was demonstrated using the Catheterization Genetics cohort. We identified a top-ranked model that accurately prioritized variants for which ClinVar clinical significance had changed (n=663; precision-recall area under the curve, 0.97) and performed well compared with conventional in silico methods. This model (CVD pathogenicity predictor) also had high accuracy in prioritizing VUS with functional effects in vivo (precision-recall area under the curve, 0.58). In Catheterization Genetics, there was a greater burden of higher CVD pathogenicity predictor scored VUS in individuals with dilated cardiomyopathy compared with controls (P=8.2×10-15). Of individuals in Catheterization Genetics who harbored highly ranked CVD pathogenicity predictor VUS meeting clinical pathogenicity criteria, 27.6% had clinical evidence of disease. Variant prioritization using this model increased genetic diagnosis in Catheterization Genetics participants with a known clinical diagnosis of hypertrophic cardiomyopathy (7.8%-27.2%). We present a cardiac-specific model for prioritizing variants underlying CVD syndromes with high performance in discriminating the pathogenicity of VUS in CVD genes. Variant review and phenotyping of individuals carrying VUS of pathogenic interest support the clinical utility of this model. This model could also have utility in filtering variants as part of large-scale genomic sequencing studies.

Analyzes of pan-genome and resequencing atlas unveil the genetic basis of jujube domestication

Jujube (Ziziphus jujuba Mill.), belonging to the Rhamnaceae family, is gaining increasing prominence as a perennial fruit crop with significant economic and medicinal values. Here, we conduct de novo assembly of four reference-grade genomes, encompassing one wild and three cultivated jujube accessions. We present insights into the population structure, genetic diversity, and genomic variations within a diverse collection of 1059 jujube accessions. Analyzes of the jujube pan-genome, based on our four assemblies and four previously released genomes, reveal extensive genomic variations within domestication-associated regions, potentially leading to the discovery of a candidate gene that regulates flowering and fruit ripening. By leveraging the pan-genome and a large-scale resequencing population, we identify two candidate genes involved in domestication traits, including the seed-setting rate, the bearing-shoot length and the leaf size in jujube. These genomic resources will accelerate evolutionary and functional genomics studies of jujube.

Full-length transcriptome assembly of black amur bream (Megalobrama terminalis) as a reference resource.

The genus Megalobrama holds significant economic value in China, with M. terminalis (Black Amur bream) ranking second in production within this group. However, lacking comprehensive genomic and transcriptomic data has impeded research progress. This study aims to fill this gap through an extensive transcriptomic analysis of M. terminalis. We utilized PacBio Isoform Sequencing to generate 558,998 subreads, totaling 45.52 Gb, which yielded 22,141 transcripts after rigorous filtering and clustering. Complementary Illumina short-read sequencing corrected 967,114 errors across these transcripts. Our analysis identified 12,426 non-redundant isoforms, with 11,872 annotated in various databases. Functional annotation indicated 11,841 isoforms matched entries in the NCBI non-redundant protein sequences database. Gene Ontology analysis categorized 10,593 isoforms, revealing strong associations with cellular processes and binding functions. Additionally, 8203 isoforms were mapped to pathways in the Kyoto Encyclopedia of Genes and Genomes, highlighting significant involvement in immune system processes and complement cascades. We notably identified key immune molecules such as alpha-2-macroglobulin and complement component 3, each with multiple isoforms, underscoring their potential roles in the immune response. Our analysis also uncovered 853 alternative splicing events, predominantly involving retained introns, along with 672 transcription factors and 426 long non-coding RNAs. The high-quality reference transcriptome generated in this study provides a valuable resource for comparative genomic studies within the Megalobrama genus, supporting future research to enhance aquaculture stocks.

Reconciling theories of dominance with the relative rates of adaptive substitution on sex chromosomes and autosomes.

The dominance of beneficial mutations is a key evolutionary parameter affecting the rate and genetic basis of adaptation, yet it is notoriously difficult to estimate. A leading method to infer it is to compare the relative rates of adaptive substitution for X-linked and autosomal genes, which-according to a classic model by Charlesworth et al. (1987)-is a simple function of the dominance of new beneficial mutations. Recent evidence that rates of adaptive substitution are faster for X-linked genes implies, accordingly, that beneficial mutations are usually recessive. However, this conclusion is incompatible with leading theories of dominance, which predict that beneficial mutations tend to be dominant or overdominant with respect to fitness. To address this incompatibility, we use Fisher's geometric model to predict the distribution of fitness effects of new mutations and the relative rates of positively selected substitution on the X and autosomes. Previous predictions of faster-X theory emerge as a special case of our model in which the phenotypic effects of mutations are small relative to the distance to the phenotypic optimum. But as mutational effects become large relative to the optimum, we observe an elevated tempo of positively selected substitutions on the X relative to the autosomes across a broader range of dominance conditions, including those predicted by theories of dominance. Our results imply that, contrary to previous models, dominant and overdominant beneficial mutations can plausibly generate patterns of faster-X adaptation. We discuss resulting implications for genomic studies of adaptation and inferences of dominance.

In silico analysis of R2R3-MYB transcription factors in the basal eudicot model, Aquilegia coerulea

R2R3-MYBs are an important group of transcription factors that regulate crucial developmental processes across the plant kingdom; yet no comprehensive analysis of the R2R3-MYBs in the early-diverging eudicot clade of Ranunculaceae has been conducted so far. In the present study, Aquilegia coerulea is chosen to understand the extent of conservation and divergence of R2R3-MYBs as a representative of the family by analysing the genomic distribution, organization, gene structure, physiochemical properties, protein architecture, evolution and possible mode of expansion. Genome-wide analysis showed the presence of 82 putative homologues classified into 21 subgroups, based on phylogenetic analysis of full-length protein sequences. The domain has remained largely conserved across all homologues with few differences from the characterized Arabidopsis thaliana R2R3-MYBs. The topology of the phylogenetic tree remains the same when full-length protein sequences are used, indicating that the evolution of R2R3-MYBs is driven by the domain region only. This is supported by the presence of similar structures of exon–intron and conserved motifs within the same subgroup. Furthermore, comparisons of the AqcoeR2R3-MYB members with monocots and core-eudicots revealed the evolutionary expansion of a few functional clades, such as A. thaliana R2R3-MYB subgroup 6 (SG6), the upstream regulatory factors of floral pigment biosynthesis and floral color. The reconstructed evolutionary history of SG6-like genes across angiosperms highlights the occurrence of independent duplication events in the genus Aquilegia. AqcoeR2R3-MYB genes are present in all seven chromosomes of A. coerulea, most of which result from local and segmental duplications. Selection analysis of these duplicated gene pairs indicates purifying selection except one, and the physiochemical analyses of R2R3-MYBs reveal differences among the MYBs signifying their functional diversification. This study paves the way for further investigation of paralogous copies and their probable role in the evolution of different floral traits in A. coerulea. It lays the foundation for functional genomic studies of R2R3-MYBs in the basal eudicots and facilitates comparative studies among angiosperms. The work also provides a framework for deciphering novel genetic regulatory pathways that govern the diversity of floral morphology.

Artificial Intelligence in Medical Diagnostics

Artificial intelligence (AI) is an essential tool in the medical sector that contributes significantly to medical imaging, medical pathology, histology, genomic study, predictive analysis, etc. It is being increasingly used not only in breast and lung cancer diagnosis and screening, and genetic disease identification but also in personalized decision-making during the treatment of these diseases. The quality and availability of unbiased data is a key challenge. Algorithmic bias and interpretability are significant concerns as well. Improving the use of AI in medical diagnostics could be achieved through continuous monitoring, access to highly accurate datasets, and timely intervention by healthcare professionals. J Bangladesh Coll Phys Surg 2024; 42: 379-382

Geographically widespread and novel hemotropic mycoplasmas and bartonellae in Mexican free-tailed bats and sympatric North American bat species.

Bacterial pathogens remain poorly characterized in bats, especially in North America. We describe novel (and in some cases panmictic) hemoplasmas (10.5% positivity) and bartonellae (25.5% positivity) across three colonies of Mexican free-tailed bats (Tadarida brasiliensis), a partially migratory species that can seasonally travel hundreds of kilometers. Molecular analyses identified three novel Candidatus hemoplasma species most similar to another novel Candidatus species in Neotropical molossid bats. We also detected novel hemoplasmas in sympatric cave myotis (Myotis velifer) and pallid bats (Antrozous pallidus), with sequences in the latter 96.5% related to C. Mycoplasma haemohominis. We identified nine Bartonella genogroups, including those in cave myotis with 96.7% similarity to C. Bartonella mayotimonensis. We also detected Bartonella rochalimae in migratory Mexican free-tailed bats, representing the first report of this human pathogen in the Chiroptera. The seasonality and diversity of these bacteria observed here suggest that additional longitudinal, genomic, and immunological studies in bats are warranted.

Tree species and drought: Two mysterious long-standing counterparts.

Around 252 million years ago (Late Permian), Earth experienced one of its most significant drought periods, coinciding with a global climate crisis, resulting in a devastating loss of forest trees with no hope of recovery. In the current epoch (Anthropocene), the worsening of drought stress is expected to significantly affect forest communities. Despite extensive efforts, there is significantly less research at the molecular level on forest trees than on annual crop species. Would it not be wise to allocate equal efforts to woody species, regardless of their importance in providing essential furniture and sustaining most terrestrial ecosystems? For instance, the poplar genome is roughly quadruple the size of the Arabidopsis genome and has 1.6 times the number of genes. Thus, a massive effort in genomic studies focusing on forest trees has become inevitable to understand their adaptation to harsh conditions. Nevertheless, with the emerging role and development of high-throughput DNA sequencing systems, there is a growing body of literature about the responses of trees under drought at the molecular and eco-physiological levels. Therefore, synthesizing these findings through contextualizing drought history and concepts is essential to understanding how woody species adapt to water-limited conditions. Comprehensive genomic research on trees is critical for preserving biodiversity and ecosystem function. Integrating molecular insights with eco-physiological analysis will enhance forest management under climate change.

Visualizing genomic evolution in Caenorhabditis through WormSynteny

Understanding the syntenic relationships among genomes is crucial to elucidate the genomic mechanisms that drive the evolution of species. The nematode Caenorhabditis is a good model for studying genomic evolution due to the well-established biology of Caenorhabditis elegans and the availability of > 50 genomes in the genus. However, effective alignment of more than ten species in Caenorhabditis has not been conducted before, and there is currently no tool to visualize the synteny of more than two species. In this study, we used Progressive Cactus, a recently developed multigenome aligner, to align the genomes of eleven Caenorhabditis species. Through the progressive alignment, we reconstructed nine ancestral genomes, analyzed the mutational types that cause genomic rearrangement during speciation, and found that insertion and duplication are the major driving forces for genome expansion. Dioecious species appear to expand their genomes more than androdioecious species. We then built an online interactive app called WormSynteny to visualize the syntenic relationship among the eleven species. Users can search the alignment dataset using C. elegans query sequences, construct synteny plots at different genomic scales, and use a set of options to control alignment output and plot presentation. We showcased the use of WormSynteny to visualize the syntenic conservation of one-to-one orthologues among species, tandem and dispersed gene duplication in C. elegans, and the evolution of exon and intron structures. Importantly, the integration of orthogroup information with synteny linkage in WormSynteny allows the easy visualization of conserved genomic blocks and disruptive rearrangement. In conclusion, WormSynteny provides immediate access to the syntenic relationships among the most widely used Caenorhabditis species and can facilitate numerous comparative genomics studies. This pilot study with eleven species also serves as a proof-of-concept to a more comprehensive larger-scale analysis using hundreds of nematode genomes, which is expected to reveal mechanisms that drive genomic evolution in the Nematoda phylum. Finally, the WormSynteny software provides a generalizable solution for visualizing the output of Progressive Cactus with interactive graphics, which would be useful for a broad community of genome researchers.

Association Between Consumption of Foods Containing Vitamin D and All-Cause Mortality in Korea.

Sufficient vitamin D levels are reported to be a factor in reducing various chronic diseases and resulting mortality rates. Well-dried mushrooms and blue-backed fish are known to be rich in vitamin D. In this study, the association between mortality rates and the intake of vitamin D-rich foods was confirmed using data from the Korean Genome and Epidemiological Study (KoGES). Among the KoGES database, we followed up a total of 6844 adults who participated in the Ansung-Ansan cohort study recruited from 2001 to 2002 and continued for an average of 16.7 years until 2018. The main findings were analyzed using Cox regression analysis. During follow-up, 439 cases of all-cause mortality, 149 cases of cancer-related mortality, and 91 cases of cardiovascular mortality were confirmed. In the fully adjusted model, the hazard ratio (HR) for all-cause mortality in quartile 3 of mushroom consumption was 0.709 (95% confidence interval [CI], 0.525-0.958) compared with quartile 1. In addition, the HRs for cardiovascular mortality in quartile 3 of mushroom consumption were 0.348 (95% CI, 0.154-0.787) compared with those in quartile 1. The HRs of cardiovascular mortality for quartiles 3 and 4 of fish consumption were 0.442 (95% CI, 0.226-0.865) and 0.533 (95% CI, 0.285-0.998), respectively, compared with quartile 1. In conclusion, moderate consumption of mushrooms was related to decreased risk of all-cause and cardiovascular mortality, while heightened fish consumption was inversely related to cardiovascular mortality.