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BACKGROUND: Currently, diverse minipigs have acquired a common dwarfism phenotype through independent artificial selections. Characterizing the population and genetic diversity in minipigs is important to unveil genetic mechanisms regulating their body sizes and effects of independent artificial selections on those genetic mechanisms. However, full understanding for the genetic mechanisms and phenotypic consequences in minipigs still lag behind. RESULTS: Here, using whole genome sequencing data of 41 pig breeds, including eight minipigs, we identified a large genomic diversity in a minipig population compared to other pig populations in terms of population structure, demographic signatures, and selective signatures. Selective signatures reveal diverse biological mechanisms related to body size in minipigs. We also found evidence for neural development mechanism as a minipig-specific body size regulator. Interestingly, selection signatures within those mechanisms containing neural development are also highly different among minipig breeds. Despite those large genetic variances, PLAG1, CHM, and ESR1 are candidate key genes regulating body size which experience different differentiation directions in different pig populations. CONCLUSIONS: These findings present large variances of genetic structures, demographic signatures, and selective signatures in the minipig population. They also highlight how different artificial selections with large genomic diversity have shaped the convergent dwarfism.

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Recent advancements in sequencing and genome assembly technologies have led to rapid generation of high-quality genome assemblies for various species and breeds. Despite the importance as minipigs an animal model in biomedical research, the construction of high-quality genome assemblies of minipigs still lags behind other pig breeds. To address this problem, we constructed a high-quality chromosome-level genome assembly of the Korean minipig (KMP) utilizing multiple different types of sequencing reads and reference genomes. The KMP assembly included 19 chromosome-level sequences with a total length of 2.52 Gb and N50 of 137 Mb. Comparative analyses with the pig reference genome (Sscrofa11.1) demonstrated comparable contiguity and completeness of the KMP assembly. Additionally, genome annotation analyses identified 22,666 protein-coding genes and repetitive elements occupying 40.10% of the genome. The KMP assembly and genome annotation provide valuable resources that can contribute to various future research on minipig and other pig breeds.

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BACKGROUND: DNA methylation forms 5-methylcytosine and its regulation in the hippocampus is critical for learning and memory. Indeed, dysregulation of DNA methylation is associated with neurological diseases. Alzheimer's disease (AD) is the predominant of dementia and a neurodegenerative disorder. METHODS: We examined the learning and memory function in 3- and 9-month-old wild-type and 5xfamiliar Alzheimer's disease (5xFAD) transgenic mice by performing the object recognition memory and Y-maze tests, and identified the hippocampal amyloid beta burden. To investigate the epigenetically regulated genes involved in the development or neuropathology of AD, we performed genome-wide DNA methylation sequencing and RNA sequencing analyses in the hippocampus of 9-month-old wild-type and 5xFAD tg mice. To validate the genes inversely regulated by epigenetics, we confirmed their methylation status and mRNA levels. RESULTS: At 9 months of age, 5xFAD tg mice showed significant cognitive impairment and amyloid-beta plaques in the hippocampus. DNA methylation sequencing identified a total of 13,777 differentially methylated regions, including 4484 of hyper- and 9293 of hypomethylated regions, that are associated with several gene ontology (GO) terms including 'nervous system development' and 'axon guidance'. In RNA sequencing analysis, we confirmed a total of 101 differentially expressed genes, including 52 up- and 49 downregulated genes, associated with GO functions such as 'positive regulation of synaptic transmission, glutamatergic' and 'actin filament organization'. Through further integrated analysis of DNA methylation and RNA sequencing, three epigenetically regulated genes were selected: thymus cell antigen 1, theta (Thy1), myosin VI (Myo6), and filamin A-interacting protein 1-like (Filip1l). The methylation level of Thy1 decreased and its mRNA levels increased, whereas that of Myo6 and Filip1l increased and their mRNA levels decreased. The common functions of these three genes may be associated with the neural cytoskeleton and synaptic plasticity. CONCLUSIONS: We suggest that the candidate genes epigenetically play a role in AD-associated neuropathology (i.e., amyloid-beta plaques) and memory deficit by influencing neural structure and synaptic plasticity. Furthermore, counteracting dysregulated epigenetic changes may delay or ameliorate AD onset or symptoms.

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Tagetes erecta Linn. (TE) is traditionally used to treat cardiovascular, renal, and gastrointestinal diseases. In this study, we investigated the active compounds and targets of TE extract that may exert antiviral effects against influenza A. Active compounds and targets of TE extract were identified using the Traditional Chinese Medicine Systems Pharmacology database (TCSMP). The influenza A-related gene set was screened using GeneCards and the Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was built to establish the hub targets. Pathway and target studies were conducted using Gene Expression Omnibus (GEO). The interactions between active compounds and potential targets were assessed by molecular docking. An in vitro study was performed using antiviral and plaque reduction assays. From the compound and target search, we identified 6 active compounds and 95 potential targets. We retrieved 887 influenza-associated target genes and determined 14 intersecting core targets between TE and influenza. After constructing a compound-target network, we discovered lutein and beta-carotene to be the key compounds. Next, PPI network analysis identified the top three hub genes associated with influenza (IL-6, HIF1A, and IL-1ß). Similarly, GEO analysis revealed IL-6, TGFB1, and CXCL8 to be the top three target genes. In our docking study, we identified that lutein and IL-6 had the strongest bindings. Our in vitro experimental results revealed that the TE extract exhibited therapeutic rather than prophylactic effects on influenza disease. We identified lutein as a main active compound in TE extract, and IL-6 as an important target associated with influenza, by using data mining and bioinformatics. Our in vitro findings indicated that TE extract exerted protective properties against the influenza A virus. We speculated that lutein, as a key active component in TE extract, is largely responsible for its antiviral effects. Therefore, we suggest TE extract as an alternative in the treatment of influenza.

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Advancements in next-generation sequencing (NGS) technologies have led to a substantial increase in the availability of population genetic variant data, thus prompting the development of various population analysis tools to enhance our understanding of population structure and evolution. The tools that are currently used to analyze population genetic variant data generally require different environments, parameters, and formats of the input data, which can act as a barrier preventing the wide-spread usage of such tools by general researchers who may not be familiar with bioinformatics. To address this problem, we have developed an automated and comprehensive pipeline called PAPipe to perform nine widely used population genetic analyses using population NGS data. PAPipe seamlessly interconnects and serializes multiple steps, such as read trimming and mapping, genetic variant calling, data filtering, and format converting, along with nine population genetic analyses such as principal component analysis, phylogenetic analysis, population tree analysis, population structure analysis, linkage disequilibrium decay analysis, selective sweep analysis, population admixture analysis, sequentially Markovian coalescent analysis, and fixation index analysis. PAPipe also provides an easy-to-use web interface that allows for the parameters to be set and the analysis results to be browsed in intuitive manner. PAPipe can be used to generate extensive results that provide insights that can help enhance user convenience and data usability. PAPipe is freely available at https://github.com/jkimlab/PAPipe.

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BACKGROUND: Many studies have been performed to identify various genomic loci and genes associated with the meat quality in pigs. However, the full genetic architecture of the trait still remains unclear in part because of the lack of accurate identification of related structural variations (SVs) which resulted from the shortage of target breeds, the limitations of sequencing data, and the incompleteness of genome assemblies. The recent generation of a new pig breed with superior meat quality, called Nanchukmacdon, and its chromosome-level genome assembly (the NCMD assembly) has provided new opportunities. RESULTS: By applying assembly-based SV calling approaches to various genome assemblies of pigs including Nanchukmacdon, the impact of SVs on meat quality was investigated. Especially, by checking the commonality of SVs with other pig breeds, a total of 13,819 Nanchukmacdon-specific SVs (NSVs) were identified, which have a potential effect on the unique meat quality of Nanchukmacdon. The regulatory potentials of NSVs for the expression of nearby genes were further examined using transcriptome- and epigenome-based analyses in different tissues. CONCLUSIONS: Whole-genome comparisons based on chromosome-level genome assemblies have led to the discovery of SVs affecting meat quality in pigs, and their regulatory potentials were analyzed. The identified NSVs will provide new insights regarding genetic architectures underlying the meat quality in pigs. Finally, this study confirms the utility of chromosome-level genome assemblies and multi-omics analysis to enhance the understanding of unique phenotypes.

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As plentiful high-quality genome assemblies have been accumulated, reference-guided genome assembly can be a good approach to reconstruct a high-quality assembly. Here, we present a chromosome-level genome assembly of the Korean crossbred pig called Nanchukmacdon (the NCMD assembly) using the reference-guided assembly approach with short and long reads. The NCMD assembly contains 20 chromosome-level scaffolds with a total size of 2.38 Gbp (N50: 138.77 Mbp). Its BUSCO score is 93.1%, which is comparable to the pig reference assembly, and a total of 20,588 protein-coding genes, 8,651 non-coding genes, and 996.14 Mbp of repetitive elements are annotated. The NCMD assembly was also used to close many gaps in the pig reference assembly. This NCMD assembly and annotation provide foundational resources for the genomic analyses of pig and related species.

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Background: Superior vena cava (SVC) stenosis during follow-up is a major concern after heart transplantation, and many technical modifications have been introduced. We analyzed the surgical results of the SVC intima layer-only suture technique in heart transplantation. Methods: We performed SVC anastomosis with sutures placed only in the intima during heart transplantation. We measured the area of the SVC at 3 different points (above the anastomosis, at the anastomosis, and below the anastomosis) in an axial view by freely drawing regions of interest, and then evaluated the degree of stenosis. Patients who underwent cardiac computed tomography (CT) at 2 years postoperatively between June 2017 and May 2020 were included in this study. Results: We performed heart transplantation in 41 patients. Among them, 24 patients (16 males and 8 females) underwent follow-up cardiac CT at 2 years postoperatively. The mean age at operation was 49.4±4.9 years. The diagnoses at time of operation were dilated cardiomyopathy (n=12), ischemic heart disease (n=8), valvular heart disease (n=2), hypertrophic cardiomyopathy (n=1), and congenital heart disease (n=1). No cases of postoperative bleeding requiring intervention occurred. The mean CT follow-up duration was 1.9±0.7 years. At follow-up, the mean areas at the 3 key points were 2.7±0.8 cm2, 2.7±0.8 cm2, and 2.7±1.0 cm2 (p=0.996). There were no SVC stenosis-related symptoms during follow-up. Conclusion: The suture technique using only the SVC intimal layer is a safe and effective method for use in heart transplantation.

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BACKGROUND: Current international guidelines recommend against deep sedation as it is associated with worse outcomes in the intensive care unit (ICU). However, in Korea the prevalence of deep sedation and its impact on patients in the ICU are not well known. METHODS: From April 2020 to July 2021, a multicenter, prospective, longitudinal, noninterventional cohort study was performed in 20 Korean ICUs. Sedation depth extent was divided into light and deep using a mean Richmond Agitation-Sedation Scale value within the first 48 hours. Propensity score matching was used to balance covariables; the outcomes were compared between the two groups. RESULTS: Overall, 631 patients (418 [66.2%] and 213 [33.8%] in the deep and light sedation groups, respectively) were included. Mortality rates were 14.1% and 8.4% in the deep and light sedation groups (P = 0.039), respectively. Kaplan-Meier estimates showed that time to extubation (P < 0.001), ICU length of stay (P = 0.005), and death (P = 0.041) differed between the groups. After adjusting for confounders, early deep sedation was only associated with delayed time to extubation (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.55-0.80; P < 0.001). In the matched cohort, deep sedation remained significantly associated with delayed time to extubation (HR, 0.68; 95% CI, 0.56-0.83; P < 0.001) but was not associated with ICU length of stay (HR, 0.94; 95% CI, 0.79-1.13; P = 0.500) and in-hospital mortality (HR, 1.19; 95% CI, 0.65-2.17; P = 0.582). CONCLUSION: In many Korean ICUs, early deep sedation was highly prevalent in mechanically ventilated patients and was associated with delayed extubation, but not prolonged ICU stay or in-hospital death.

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Constructing accurate microbial genome assemblies is necessary to understand genetic diversity in microbial genomes and its functional consequences. However, it still remains as a challenging task especially when only short-read sequencing technologies are used. Here, we present a new read-clustering algorithm, called RBRC, for improving de novo microbial genome assembly, by accurately estimating read proximity using multiple reference genomes. The performance of RBRC was confirmed by simulation-based evaluation in terms of assembly contiguity and the number of misassemblies, and was successfully applied to existing fungal and bacterial genomes by improving the quality of the assemblies without using additional sequencing data. RBRC is a very useful read-clustering algorithm that can be used (i) for generating high-quality genome assemblies of microbial strains when genome assemblies of related strains are available, and (ii) for upgrading existing microbial genome assemblies when the generation of additional sequencing data, such as long reads, is difficult.

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BACKGROUND: Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic. AIMS: This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations. MATERIALS AND METHODS: The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues. RESULTS: We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models. DISCUSSION: In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC. CONCLUSION: This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

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E3 ubiquitin ligase, HOIL1-interacting protein (HOIP), forms the linear ubiquitin chain assembly complex (LUBAC) with HOIL and SHANK-associated RH domain interactor and catalyzes linear ubiquitination, directly linking the N- and C-termini of ubiquitin. Recently, several studies have implicated linear ubiquitination in aging and Alzheimer disease (AD). However, little is currently known about the roles of HOIP in brain aging and AD pathology. Here, we investigated the role of linear ubiquitin E3 ligase (LUBEL), a Drosophila HOIP ortholog, in brain aging and amyloid ß (Aß) pathology in a Drosophila AD model. DNA double-strand breaks (DSBs) were increased in the aged brains of neuron-specific LUBEL-knockdown flies compared to the age-matched controls. Silencing of LUBEL in the neuron of AD model flies increased the neuronal apoptosis and neurodegeneration, whereas silencing in glial cells had no such effect. Aß aggregation levels and DSBs were also increased in the LUBEL-silenced AD model fly brains, but autophagy and proteostasis were not affected by LUBEL silencing. Collectively, our results suggest that LUBEL protects neurons from aging-induced DNA damage and Aß neurotoxicity.

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BACKGROUND: DNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties. RESULTS: Here we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses. CONCLUSION: msPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe .

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Metabolic abnormalities, such as preexisting diabetes or hyperglycemia or hypoglycemia during hospitalization aggravated the severity of COVID-19. We evaluated whether diabetes history, hyperglycemia before and during extracorporeal membrane oxygenation (ECMO) support, and hypoglycemia were risk factors for mortality in patients with COVID-19. This study included data on 195 patients with COVID-19, who were aged ≥19 years and were treated with ECMO. The proportion of patients with diabetes history among nonsurvivors was higher than that among survivors. Univariate Cox regression analysis showed that in-hospital mortality after ECMO support was associated with diabetes history, renal replacement therapy (RRT), and body mass index (BMI) < 18.5 kg/m2. Glucose at admission >200 mg/dL and glucose levels before ventilator >200 mg/dL were not associated with in-hospital mortality. However, glucose levels before ECMO >200 mg/dL and minimal glucose levels during hospitalization <70 mg/dL were associated with in-hospital mortality. Multivariable Cox regression analysis showed that glucose >200 mg/dL before ECMO and minimal glucose <70 mg/dL during hospitalization remained risk factors for in-hospital mortality after adjustment for age, BMI, and RRT. In conclusion, glucose >200 mg/dL before ECMO and minimal glucose level <70 mg/dL during hospitalization were risk factors for in-hospital mortality among COVID-19 patients who underwent ECMO.

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Decrypting the rearrangements that drive mammalian chromosome evolution is critical to understanding the molecular bases of speciation, adaptation, and disease susceptibility. Using 8 scaffolded and 26 chromosome-scale genome assemblies representing 23/26 mammal orders, we computationally reconstructed ancestral karyotypes and syntenic relationships at 16 nodes along the mammalian phylogeny. Three different reference genomes (human, sloth, and cattle) representing phylogenetically distinct mammalian superorders were used to assess reference bias in the reconstructed ancestral karyotypes and to expand the number of clades with reconstructed genomes. The mammalian ancestor likely had 19 pairs of autosomes, with nine of the smallest chromosomes shared with the common ancestor of all amniotes (three still conserved in extant mammals), demonstrating a striking conservation of synteny for ∼320 My of vertebrate evolution. The numbers and types of chromosome rearrangements were classified for transitions between the ancestral mammalian karyotype, descendent ancestors, and extant species. For example, 94 inversions, 16 fissions, and 14 fusions that occurred over 53 My differentiated the therian from the descendent eutherian ancestor. The highest breakpoint rate was observed between the mammalian and therian ancestors (3.9 breakpoints/My). Reconstructed mammalian ancestor chromosomes were found to have distinct evolutionary histories reflected in their rates and types of rearrangements. The distributions of genes, repetitive elements, topologically associating domains, and actively transcribed regions in multispecies homologous synteny blocks and evolutionary breakpoint regions indicate that purifying selection acted over millions of years of vertebrate evolution to maintain syntenic relationships of developmentally important genes and regulatory landscapes of gene-dense chromosomes.

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BACKGROUND: Metagenomic assembly using high-throughput sequencing data is a powerful method to construct microbial genomes in environmental samples without cultivation. However, metagenomic assembly, especially when only short reads are available, is a complex and challenging task because mixed genomes of multiple microorganisms constitute the metagenome. Although long read sequencing technologies have been developed and have begun to be used for metagenomic assembly, many metagenomic studies have been performed based on short reads because the generation of long reads requires higher sequencing cost than short reads. RESULTS: In this study, we present a new method called PLR-GEN. It creates pseudo-long reads from metagenomic short reads based on given reference genome sequences by considering small sequence variations existing in individual genomes of the same or different species. When applied to a mock community data set in the Human Microbiome Project, PLR-GEN dramatically extended short reads in length of 101 bp to pseudo-long reads with N50 of 33 Kbp and 0.4% error rate. The use of these pseudo-long reads generated by PLR-GEN resulted in an obvious improvement of metagenomic assembly in terms of the number of sequences, assembly contiguity, and prediction of species and genes. CONCLUSIONS: PLR-GEN can be used to generate artificial long read sequences without spending extra sequencing cost, thus aiding various studies using metagenomes.

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Deep learning has been applied for solving many biological problems, and it has shown outstanding performance. Applying deep learning in research requires knowledge of deep learning theories and programming skills, but researchers have developed diverse deep learning platforms to allow users to build deep learning models without programming. Despite these efforts, it is still difficult for biologists to use deep learning because of limitations of the existing platforms. Therefore, a new platform is necessary that can solve these challenges for biologists. To alleviate this situation, we developed a user-friendly and easy-to-use web application called DLEB (Deep Learning Editor for Biologists) that allows for building deep learning models specialized for biologists. DLEB helps researchers (i) design deep learning models easily and (ii) generate corresponding Python code to run directly in their machines. DLEB provides other useful features for biologists, such as recommending deep learning models for specific learning tasks and data, pre-processing of input biological data, and availability of various template models and example biological datasets for model training. DLEB can serve as a highly valuable platform for easily applying deep learning to solve many important biological problems. DLEB is freely available at http://dleb.konkuk.ac.kr/.

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The Jahn-Teller effect (JTE) is one of the most important determinators of how much stress layered cathode materials undergo during charge and discharge; however, many reports have shown that traces of superstructure exist in pristine layered materials and irreversible phase transitions occur even after eliminating the JTE. A careful consideration of the energy of cationic distortion using a Taylor expansion indicated that second-order JTE (pseudo-JTE) is more widespread than the aforementioned JTE because of the various bonding states that occur between bonding and antibonding molecular orbitals in transition-metal octahedra. As a model case, a P2-type Mn-rich cathode (Na3/4MnO2) was investigated in detail. MnO6 octahedra are well known to undergo either elongation or contraction in a specific direction due to JTE. Here, the substitution of Li for Mn (Na3/4(Li1/4Mn3/4)O2) helped to oxidize Mn3+ to Mn4+ suppressing JTE; however, the MnO6 octahedra remained asymmetric with a clear trace of the superstructure. With various advanced analyses, we disclose the pseudo-JTE as a general reason for the asymmetric distortions of the MnO6 octahedra. These distortions lead to the significant electrochemical degradation of Na3/4Li1/4Mn3/4O2. The suppression of the pseudo-JTE modulates phase transition behaviors during Na intercalation/deintercalation and thereby improves all of the electrochemical properties. The insight obtained by coupling a theoretical background for the pseudo-JTE with verified layered cathode material lattice changes implies that many previous approaches can be rationalized by regulating pseudo-JTE. This suggests that the pseudo-JTE should be thought more important than the well-known JTE for layered cathode materials.

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BACKGROUND: There is no national survey on medical school faculty members' burnout in Korea. This study aimed to investigate burnout levels and explore possible factors related to burnout among faculty members of Korean medical schools. METHODS: An anonymous online questionnaire was distributed to 40 Korean medical schools from October 2020 to December 2020. Burnout was measured by a modified and revalidated version of the Maslach Burnout Inventory-Human Service Survey. RESULTS: A total of 996 faculty members participated in the survey. Of them, 855 answered the burnout questions, and 829 completed all the questions in the questionnaire. A significant number of faculty members showed a high level of burnout in each sub-dimension: 34% in emotional exhaustion, 66.3% in depersonalization, and 92.4% in reduced personal accomplishment. A total of 31.5% of faculty members revealed a high level of burnout in two sub-dimensions, while 30.5% revealed a high level of burnout in all three sub-dimensions. Woman faculty members or those younger than 40 reported significantly higher emotional exhaustion and depersonalization. Long working hours (≥ 80 hours/week) showed the highest reduced personal accomplishment scores (F = 4.023, P = 0.018). The most significant stressor or burnout source was "excessive regulation by the government or university." The research was the most exasperating task, but the education was the least stressful. CONCLUSION: This first nationwide study alerts that a significant number of faculty members in Korean medical schools seem to suffer from a high level of burnout. Further studies are necessary for identifying the burnout rate, related factors, and strategies to overcome physician burnout.

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