KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data.

During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. Here, we introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups.

BACKGROUND: Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics. RESULTS: Here, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype-phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories. CONCLUSIONS: Collectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome-phenome associations. The large-scale pathological whole genome-wide omics data will become a powerful set for genome-phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.

Comprehensive profiling of DNA methylation in Korean patients with colorectal cancer.

Alterations in DNA methylation play an important pathophysiological role in the development and progression of colorectal cancer. We comprehensively profiled DNA methylation alterations in 165 Korean patients with colorectal cancer (CRC), and conducted an in-depth investigation of cancer-specific methylation patterns. Our analysis of the tumor samples revealed a significant presence of hypomethylated probes, primarily within the gene body regions; few hypermethylated sites were observed, which were mostly enriched in promoter-like and CpG island regions. The CpG Island Methylator PhenotypeHigh (CIMP-H) exhibited notable enrichment of microsatellite instability-high (MSI-H). Additionally, our findings indicated a significant correlation between methylation of the MLH1 gene and MSI-H status. Furthermore, we found that the CIMP-H had a higher tendency to affect the right-side of the colon tissues and was slightly more prevalent among older patients. Through our methylome profile analysis, we successfully verified the thylation patterns and clinical characteristics of Korean patients with CRC. This valuable dataset lays a strong foundation for exploring novel molecular insights and potential therapeutic targets for the treatment of CRC. [BMB Reports 2024; 57(2): 110-115].

Exploring the DNA methylome of Korean patients with colorectal cancer consolidates the clinical implications of cancer-associated methylation markers.

Aberrant DNA methylation plays a critical role in the development and progression of colorectal cancer (CRC), which has high incidence and mortality rates in Korea. Various CRC-associated methylation markers for cancer diagnosis and prognosis have been developed; however, they have not been validated for Korean patients owing to the lack of comprehensive clinical and methylome data. Here, we obtained reliable methylation profiles for 228 tumor, 103 adjacent normal, and two unmatched normal colon tissues from Korean patients with CRC using an Illumina Infinium EPIC array; the data were corrected for biological and experiment biases. A comparative methylome analysis confirmed the previous findings that hypermethylated positions in the tumor were highly enriched in CpG island and promoter, 5' untranslated, and first exon regions. However, hypomethylated positions were enriched in the open-sea regions considerably distant from CpG islands. After applying a CpG island methylator phenotype (CIMP) to the methylome data of tumor samples to stratify the CRC patients, we consolidated the previously established clinicopathological findings that the tumors with high CIMP signatures were significantly enriched in the right colon. The results showed a higher prevalence of microsatellite instability status and MLH1 methylation in tumors with high CMP signatures than in those with low or non-CIMP signatures. Therefore, our methylome analysis and dataset provide insights into applying CRC-associated methylation markers for Korean patients regarding cancer diagnosis and prognosis. [BMB Reports 2024; 57(3): 161-166].

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Epigenetic insights into colorectal cancer: comprehensive genome-wide DNA methylation profiling of 294 patients in Korea.

DNA methylation regulates gene expression and contributes to tumorigenesis in the early stages of cancer. In colorectal cancer (CRC), CpG island methylator phenotype (CIMP) is recognized as a distinct subset that is associated with specific molecular and clinical features. In this study, we investigated the genomewide DNA methylation patterns among patients with CRC. The methylation data of 1 unmatched normal, 142 adjacent normal, and 294 tumor samples were analyzed. We identified 40,003 differentially methylated positions with 6,933 (79.8%) hypermethylated and 16,145 (51.6%) hypomethylated probes in the genic region. Hypermethylated probes were predominantly found in promoter-like regions, CpG islands, and N shore sites; hypomethylated probes were enriched in open-sea regions. CRC tumors were categorized into three CIMP subgroups, with 90 (30.6%) in the CIMP-high (CIMP-H), 115 (39.1%) in the CIMP-low (CIMP-L), and 89 (30.3%) in the non-CIMP group. The CIMP-H group was associated with microsatellite instabilityhigh tumors, hypermethylation of MLH1, older age, and rightsided tumors. Our results showed that genome-wide methylation analyses classified patients with CRC into three subgroups according to CIMP levels, with clinical and molecular features consistent with previous data. [BMB Reports 2023; 56(10): 563-568].

Introduction of the Korea BioData Station (K-BDS) for sharing biological data.

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

Longitudinal transmission of bacterial and fungal communities from seed to seed in rice.

Vertical transmission of microbes is crucial for the persistence of host-associated microbial communities. Although vertical transmission of seed microbes has been reported from diverse plants, ecological mechanisms and dynamics of microbial communities from parent to progeny remain scarce. Here we reveal the veiled ecological mechanism governing transmission of bacterial and fungal communities in rice across two consecutive seasons. We identify 29 bacterial and 34 fungal members transmitted across generations. Abundance-based regression models allow to classify colonization types of the microbes. We find that they are late colonizers dominating each community at the ripening stage. Ecological models further show that the observed temporal colonization patterns are affected by niche change and neutrality. Source-sink modeling reveals that parental seeds and stem endosphere are major origins of progeny seed microbial communities. This study gives empirical evidence for ecological mechanism and dynamics of bacterial and fungal communities as an ecological continuum during seed-to-seed transmission.

A comparative genomic analysis of lichen-forming fungi reveals new insights into fungal lifestyles.

Lichen-forming fungi are mutualistic symbionts of green algae or cyanobacteria. We report the comparative analysis of six genomes of lichen-forming fungi in classes Eurotiomycetes and Lecanoromycetes to identify genomic information related to their symbiotic lifestyle. The lichen-forming fungi exhibited genome reduction via the loss of dispensable genes encoding plant-cell-wall-degrading enzymes, sugar transporters, and transcription factors. The loss of these genes reflects the symbiotic biology of lichens, such as the absence of pectin in the algal cell wall and obtaining specific sugars from photosynthetic partners. The lichens also gained many lineage- and species-specific genes, including those encoding small secreted proteins. These genes are primarily induced during the early stage of lichen symbiosis, indicating their significant roles in the establishment of lichen symbiosis.Our findings provide comprehensive genomic information for six lichen-forming fungi and novel insights into lichen biology and the evolution of symbiosis.

Alternative splicing diversifies the transcriptome and proteome of the rice blast fungus during host infection.

Alternative splicing (AS) contributes to diversifying and regulating cellular responses to environmental conditions and developmental cues by differentially producing multiple mRNA and protein isoforms from a single gene. Previous studies on AS in pathogenic fungi focused on profiling AS isoforms under a limited number of conditions. We analysed AS profiles in the rice blast fungus Magnaporthe oryzae, a global threat to rice production, using high-quality transcriptome data representing its vegetative growth (mycelia) and multiple host infection stages. We identified 4,270 AS isoforms derived from 2,413 genes, including 499 genes presumably regulated by infection-specific AS. AS appears to increase during infection, with 32.7% of the AS isoforms being produced during infection but absent in mycelia. Analysis of the isoforms observed at each infection stage showed that 636 AS isoforms were more abundant than corresponding annotated mRNAs, especially after initial hyphal penetration into host cell. Many such dominant isoforms were predicted to encode regulatory proteins such as transcription factors and phospho-transferases. We also identified the genes encoding distinct proteins via AS and confirmed the translation of some isoforms via a proteomic analysis, suggesting potential AS-mediated neo-functionalization of some genes during infection. Comprehensive profiling of the pattern of genome-wide AS during multiple stages of rice-M. oryzae interaction established a foundational resource that will help investigate the role and regulation of AS during rice infection.

Genome-wide profiling of long non-coding RNA of the rice blast fungus Magnaporthe oryzae during infection.

BACKGROUND: Long non-coding RNAs (lncRNAs) play essential roles in developmental processes and disease development at the transcriptional and post-transcriptional levels across diverse taxa. However, only few studies have profiled fungal lncRNAs in a genome-wide manner during host infection. RESULTS: Infection-associated lncRNAs were identified using lncRNA profiling over six stages of host infection (e.g., vegetative growth, pre-penetration, biotrophic, and necrotrophic stages) in the model pathogenic fungus, Magnaporthe oryzae. We identified 2,601 novel lncRNAs, including 1,286 antisense lncRNAs and 980 intergenic lncRNAs. Among the identified lncRNAs, 755 were expressed in a stage-specific manner and 560 were infection-specifically expressed lncRNAs (ISELs). To decipher the potential roles of lncRNAs during infection, we identified 365 protein-coding genes that were associated with 214 ISELs. Analysis of the predicted functions of these associated genes suggested that lncRNAs regulate pathogenesis-related genes, including xylanases and effectors. CONCLUSIONS: The ISELs and their associated genes provide a comprehensive view of lncRNAs during fungal pathogen-plant interactions. This study expands new insights into the role of lncRNAs in the rice blast fungus, as well as other plant pathogenic fungi.

Compositional Shift of Bacterial, Archaeal, and Fungal Communities Is Dependent on Trophic Lifestyles in Rice Paddy Soil.

The soil environment determines plants' health and performance during their life cycle. Therefore, ecological understanding on variations in soil environments, including physical, chemical, and biological properties, is crucial for managing agricultural fields. Here, we present a comprehensive and extensive blueprint of the bacterial, archaeal, and fungal communities in rice paddy soils with differing soil types and chemical properties. We discovered that natural variations of soil nutrients are important factors shaping microbial diversity. The responses of microbial diversity to soil nutrients were related to the distribution of microbial trophic lifestyles (oligotrophy and copiotrophy) in each community. The compositional changes of bacterial and archaeal communities in response to soil nutrients were mainly governed by oligotrophs, whereas copiotrophs were mainly involved in fungal compositional changes. Compositional shift of microbial communities by fertilization is linked to switching of microbial trophic lifestyles. Random forest models demonstrated that depletion of prokaryotic oligotrophs and enrichment of fungal copiotrophs are the dominant responses to fertilization in low-nutrient conditions, whereas enrichment of putative copiotrophs was important in high-nutrient conditions. Network inference also revealed that trophic lifestyle switching appertains to decreases in intra- and inter-kingdom microbial associations, diminished network connectivity, and switching of hub nodes from oligotrophs to copiotrophs. Our work provides ecological insight into how soil nutrient-driven variations in microbial communities affect soil health in modern agricultural systems.

Draft Genome Sequence of Xylaria grammica EL000614, a Strain Producing Grammicin, a Potent Nematicidal Compound.

An endolichenic fungus, Xylaria grammica strain EL000614, showed strong nematicidal effects against plant pathogenic nematode, Meloidogyne incognita by producing grammicin. We report genome assembly of X. grammica EL000614 comprised of 25 scaffolds with a total length of 54.73 Mb, N50 of 4.60 Mb, and 99.8% of BUSCO completeness. GC contents of this genome were 44.02%. Gene families associated with biosynthesis of secondary metabolites or regulatory proteins were identified out of 13,730 gene models predicted.

Comparative genome analyses of four rice-infecting Rhizoctonia solani isolates reveal extensive enrichment of homogalacturonan modification genes.

BACKGROUND: Plant pathogenic isolates of Rhizoctonia solani anastomosis group 1-intraspecific group IA (AG1-IA) infect a wide range of crops causing diseases such as rice sheath blight (ShB). ShB has become a serious disease in rice production worldwide. Additional genome sequences of the rice-infecting R. solani isolates from different geographical regions will facilitate the identification of important pathogenicity-related genes in the fungus. RESULTS: Rice-infecting R. solani isolates B2 (USA), ADB (India), WGL (India), and YN-7 (China) were selected for whole-genome sequencing. Single-Molecule Real-Time (SMRT) and Illumina sequencing were used for de novo sequencing of the B2 genome. The genomes of the other three isolates were then sequenced with Illumina technology and assembled using the B2 genome as a reference. The four genomes ranged from 38.9 to 45.0 Mbp in size, contained 9715 to 11,505 protein-coding genes, and shared 5812 conserved orthogroups. The proportion of transposable elements (TEs) and average length of TE sequences in the B2 genome was nearly 3 times and 2 times greater, respectively, than those of ADB, WGL and YN-7. Although 818 to 888 putative secreted proteins were identified in the four isolates, only 30% of them were predicted to be small secreted proteins, which is a smaller proportion than what is usually found in the genomes of cereal necrotrophic fungi. Despite a lack of putative secondary metabolite biosynthesis gene clusters, the rice-infecting R. solani genomes were predicted to contain the most carbohydrate-active enzyme (CAZyme) genes among all 27 fungal genomes used in the comparative analysis. Specifically, extensive enrichment of pectin/homogalacturonan modification genes were found in all four rice-infecting R. solani genomes. CONCLUSION: Four R. solani genomes were sequenced, annotated, and compared to other fungal genomes to identify distinctive genomic features that may contribute to the pathogenicity of rice-infecting R. solani. Our analyses provided evidence that genomic conservation of R. solani genomes among neighboring AGs was more diversified than among AG1-IA isolates and the presence of numerous predicted pectin modification genes in the rice-infecting R. solani genomes that may contribute to the wide host range and virulence of this necrotrophic fungal pathogen.

Two nuclear effectors of the rice blast fungus modulate host immunity via transcriptional reprogramming.

Pathogens utilize multiple types of effectors to modulate plant immunity. Although many apoplastic and cytoplasmic effectors have been reported, nuclear effectors have not been well characterized in fungal pathogens. Here, we characterize two nuclear effectors of the rice blast pathogen Magnaporthe oryzae. Both nuclear effectors are secreted via the biotrophic interfacial complex, translocated into the nuclei of initially penetrated and surrounding cells, and reprogram the expression of immunity-associated genes by binding on effector binding elements in rice. Their expression in transgenic rice causes ambivalent immunity: increased susceptibility to M. oryzae and Xanthomonas oryzae pv. oryzae, hemibiotrophic pathogens, but enhanced resistance to Cochliobolus miyabeanus, a necrotrophic pathogen. Our findings help remedy a significant knowledge deficiency in the mechanism of M. oryzae-rice interactions and underscore how effector-mediated manipulation of plant immunity by one pathogen may also affect the disease severity by other pathogens.

TGFam-Finder: a novel solution for target-gene family annotation in plants.

Whole-genome annotation error that omits essential protein-coding genes hinders further research. We developed Target Gene Family Finder (TGFam-Finder), an alternative tool for the structural annotation of protein-coding genes containing target domain(s) of interest in plant genomes. TGFam-Finder took considerably reduced annotation run-time and improved accuracy compared to conventional annotation tools. Large-scale re-annotation of 50 plant genomes identified an average of 150, 166 and 86 additional far-red-impaired response 1, nucleotide-binding and leucine-rich-repeat, and cytochrome P450 genes, respectively, that were missed in previous annotations. We detected significantly higher number of translated genes in the new annotations using mass spectrometry data from seven plant species compared to previous annotations. TGFam-Finder along with the new gene models can provide an optimized platform for comprehensive functional, comparative, and evolutionary studies in plants.

Draft Genome Sequence of Daldinia childiae JS-1345, an Endophytic Fungus Isolated from Stem Tissue of Korean Fir.

The fungus Daldinia childiae strain JS-1345, isolated from stem tissue of Abies koreana (Korean fir), has shown strong anti-inflammatory activity. Here, we report the genome sequence of D. childiae JS-1345. The final assembly consisted of 133 scaffolds totaling 38,652,569 bp (G+C content, 44.07%).

Domestication of Oryza species eco-evolutionarily shapes bacterial and fungal communities in rice seed.

BACKGROUND: Plant-associated microbiomes, which are shaped by host and environmental factors, support their hosts by providing nutrients and attenuating abiotic and biotic stresses. Although host genetic factors involved in plant growth and immunity are known to shape compositions of microbial communities, the effects of host evolution on microbial communities are not well understood. RESULTS: We show evidence that both host speciation and domestication shape seed bacterial and fungal community structures. Genome types of rice contributed to compositional variations of both communities, showing a significant phylosymbiosis with microbial composition. Following the domestication, abundance inequality of bacterial and fungal communities also commonly increased. However, composition of bacterial community was relatively conserved, whereas fungal membership was dramatically changed. These domestication effects were further corroborated when analyzed by a random forest model. With these changes, hub taxa of inter-kingdom networks were also shifted from fungi to bacteria by domestication. Furthermore, maternal inheritance of microbiota was revealed as a major path of microbial transmission across generations. CONCLUSIONS: Our findings show that evolutionary processes stochastically affect overall composition of microbial communities, whereas dramatic changes in environments during domestication contribute to assembly of microbiotas in deterministic ways in rice seed. This study further provides new insights on host evolution and microbiome, the starting point of the holobiome of plants, microbial communities, and surrounding environments.