A set of PCR primers that should amplify all subgroups of arbuscular mycorrhizal fungi (AMF, Glomeromycota), but exclude sequences from other organisms, was designed to facilitate rapid detection and identification directly from field-grown plant roots. The small subunit rRNA gene was targeted for the new primers (AML1 and AML2) because phylogenetic relationships among the Glomeromycota are well understood for this gene. Sequence comparisons indicate that the new primers should amplify all published AMF sequences except those from Archaeospora trappei. The specificity of the new primers was tested using 23 different AMF spore morphotypes from trap cultures and Miscanthus sinensis, Glycine max and Panax ginseng roots sampled from the field. Non-AMF DNA of 14 plants, 14 Basidiomycota and 18 Ascomycota was also tested as negative controls. Sequences amplified from roots using the new primers were compared with those obtained using the established NS31 and AM1 primer combination. The new primers have much better specificity and coverage of all known AMF groups.

Summary We have determined the complete mitochondrial genome sequence of an isolate of Glomus intraradices, a widespread and well‐studied species of arbuscular mycorrhizal fungus. The total genomic DNA of 24 spores from an in vitro root organ culture of the Swiss isolate G. intraradices 494 was amplified by multiple displacement and sequenced using the Roche 454 FLX platform. Contigs were joined by PCR and Sanger sequencing. The circular genome map of 70 606 bp has a G + C content of 37.2%. All the standard fungal mitochondrial genes are present and encoded on the same strand. There are 26 introns and five complete LAGLIDADG homing endonuclease genes. There is no evidence of substantial sequence variation. A well‐supported phylogeny based on 14 mitochondrially encoded proteins indicates that the Glomeromycota are not the sister group of the Dikarya.

Arbuscular mycorrhizas (AM) have mutualistic symbiosis with plants and thus efforts have been placed on application of these symbiotic relationships to agricultural and environmental fields. In this study, AM fungi were collected from 25 sites growing with 16 host plant species in Korea and cultured with Sorghum bicolor in greenhouse condition. AM fungal spores were extracted and identified using both morphological and molecular methods. Using morphological characters, total 15 morpho-speices were identified. DNA was extracted from single spore of AM fungi and a partial region on 18S rDNA was amplified using nested PCR with AM fungal specific primers AML1/AML2. A total of 36 18S rDNA sequences were analyzed for phylogenetic analysis and 15 groups of AM fungi were identified using both morphological and molecular data of spores. Among the species, 4 species, Archaeospora leptoticha, Scutellospora castanea, S. cerradensis, S. weresubiae were described for the first time in Korea and two species in Glomus and a species in Gigaspora were not identified. Morphological and molecular identification of AM fungal spores in this study would help identify AM fungal community colonizing roots.

Instruction Tuning on Large Language Models is an essential process for model to function well and achieve high performance in specific tasks. Accordingly, in mainstream languages such as English, instruction-based datasets are being constructed and made publicly available. In the case of Korean, publicly available models and datasets all rely on using the output of ChatGPT or translating datasets built in English. In this paper, We introduce KIT-19 as an instruction dataset for the development of LLM in Korean. KIT-19 is a dataset created in an instruction format, comprising 19 existing open-source datasets for Korean NLP tasks. In this paper, we train a Korean Pretrained LLM using KIT-19 to demonstrate its effectiveness. The experimental results show that the model trained on KIT-19 significantly outperforms existing Korean LLMs. Based on the its quality and empirical results, this paper proposes that KIT-19 has the potential to make a substantial contribution to the future improvement of Korean LLMs' performance.