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Seo Hyoseob,Kwon Hakyung,Satyawan Dani,Kim Moon Young,Ha Jungmin,Lee Suk-Ha 한국유전학회 2023 Genes & Genomics Vol.45 No.7
Background Flowering time is an important crop trait. Mungbean flowers do not flower simultaneously, leading to asynchronous pod maturity and laborious multiple harvests per individual plant. The genomic and genetic mechanisms of flowering in mungbean are largely unknown. Objective This study sought to discover new quantitative trait loci (QTLs) for days to first flowering in mungbean using a genome-wide association study (GWAS). Methods In total, 206 mungbean accessions collected from 20 countries were sequenced using genotyping by sequencing. A GWAS was conducted using 3,596 single nucleotide polymorphisms (SNPs) using TASSEL v5.2. Results Seven significant SNPs were associated with first flowering time. Based on the linkage disequilibrium (LD) decay distance, LD block was determined from upstream to downstream of each SNP up to 384 kb. The lead SNP (Chr2_51229568) was located in the DFF2-2 locus. Syntenic analysis between mungbean and soybean revealed the DFF2-2 locus had collinearity with soybean genomic regions containing flowering-related QTLs on Gm13 and Gm20. Conclusion Identification of flowering-related QTLs and SNPs is important for developing synchronous pod maturity and desirable flowering traits in mungbean.
1차원 Non-Fickian 하천혼합 해석을 위한 하천 저장대 모델링 연구 동향
김병욱,서일원,김준성,노효섭,Kim, Byunguk,Seo, Il Won,Kim, Jun Song,Noh, Hyoseob 한국수자원학회 2024 한국수자원학회논문집 Vol.57 No.4
Since the first introduction of one-dimensional transient storage modeling in the field of solute transport analysis in rivers, its application has notably expanded for various purposes, including for hydrology and geobiology over the past few decades. Despite strides in refining transient storage models, there remain unresolved challenges in simplifying complex river transport dynamics into concise formulas and a limited set of parameters. This review paper is dedicated to cataloging and assessing existing transient storage models, outlining the difficulties associated with model structures, parameters, and data, and suggesting directions for future research. We seek to enhance understanding of transient storage by highlighting the importance of continuously evaluating residence time distribution modeling, integrating hydrodynamic models, and using data with minimal assumptions. This paper would contribute to advance our comprehension of the transient storage process, offering insights into sophisticated modeling techniques, pinpointing uncertainty in parameters, and suggesting the necessary avenues for further study.