Publications

2024
Wenli Wang, Junghyun Kim, Teresa S. Martinez, Enamul Huq, and Sibum Sung . “COP1 controls light- dependent chromatin remodeling.” PNAS, 121, 8, Pp. 2312853121. Publisher's Version
2023
Hee Rang Yun, Chong Chen, Jee Hye Kim, Hae Eun Kim, Sivabalan Karthik, Hye Jeong Kim, Young-Soo Chung, Hee Soon Baek, Sibum Sung, Hyun Uk Kim, and Jae Bok Heo. “Genome-edited HEADING DATE 3a knockout enhances leaf production in Perilla frutescens.” Frontiers in Plant Science, 14, Pp. 1133518. Publisher's Version
Junghyun Kim, Yogendra Bordiya, Yanpeng Xi, Bo Zhao, Dong-Hwan Kim, Youngjae Pyo, Wei Zong, William A. Ricci, and Sibum Sung. “Warm temperature-triggered developmental reprogramming requires VIL1-mediated genome-wide H3K27me3 accumulation in Arabidopsis.” Development, 150, 5, Pp. dev201343. Publisher's Version
Highlighted in "Plants feel the heat via VIL1".” Development, 150, 5, Pp. e150_e0501. Publisher's Version
2022
Wei Zong, Junghyun Kim, Yogendra Bordiya, Hong Qiao, and Sibum Sung. “ABA negatively regulates the Polycomb‐mediated H3K27me3 through the PHD‐finger protein, VIL1.” New Phytol. , 235, 3, Pp. 1057-1069. Publisher's Version
Shaunak Kar, Yogendra Bordiya, Nestor Rodriguez, Junghyun Kim, Elizabeth C. Gardner, Jimmy D. Gollihar, Sibum Sung, and Andrew D. Ellington. “Orthogonal control of gene expression in plants using synthetic promoters and CRISPR-based transcription factors.” Plant Methods, 18, Pp. 42. Publisher's Version
Maddie Brightbill and Sibum Sung. “Temperature-mediated regulation of flowering time in Arabidopsis thaliana.” aBIOTECH, 3, Pp. 78-84. Publisher's Version
2021
Junghyun Kim and Sibum Sung. “Looping by RNA: Dynamic control of chromatin loop by long non-coding RNA in plants.” Molecular Plant, 14, 9, Pp. 1430-1432. Publisher's Version
Junghyun Kim, Yogendra Bordiya, Praveen Kumar Kathare, Bo Zhao, Wei Zong, Enamul Huq, and Sibum Sung . “Phytochrome B triggers light-dependent chromatin remodelling through the PRC2-associated PHD finger protein VIL1.” Nature Plants, 7, 9, Pp. 1213-1219. Publisher's Version
Bo Zhao, Yanpeng Xi, Junghyun Kim, and Sibum Sung. “Chromatin architectural proteins regulate flowering time by precluding gene looping..” Science Adv., 7, 24, Pp. eabg3097. Publisher's Version
Wei Zong, Bo Zhao, Yanpeng Xi, Yogendra Bordiya, Hyungwon Mun, Nicholas A Cerda, Dong-Hwan Kim, and Sibum Sung. “DEK domain-containing proteins control flowering time in Arabidopsis.” New Phytol., 231, 1, Pp. 182-192. Publisher's Version
Wenli Wang, Inyup Paik, Junghyun Kim, Xilin Hou, Sibum Sung, and Enamul Huq. “Direct phosphorylation of HY5 by SPA kinases to regulate photomorphogenesis in Arabidopsis.” New Phytol. , 230, 6, Pp. 2311-2326. Publisher's Version
2020
Yanpeng Xi, Sung-Rye Park, Dong-Hwan Kim, Eun-Deok Kim, and Sibum Sung. “Transcriptome and epigenome analyses of vernalization in Arabidopsis thaliana.” Plant J, 103, 4, Pp. 1490-1502. Publisher's Version
Chong Chen, Daewon Kim, Hee Rang Yun, Yun Mi Lee, Bordiya Yogendra, Zhao Bo, Hae Eun Kim, Jun Hong Min, Yong-Suk Lee, Yeong Gil Rim, Hyun Uk Kim, Sibum Sung, and Jae Bok Heo. “Nuclear import of LIKE HETEROCHROMATIN PROTEIN1 is redundantly mediated by importins α-1, α-2 and α-3.” Plant J, 103, 3, Pp. 1205-1214. Publisher's Version
2019
Eundeok Kim, Yuqing Xiong, Byung-Ho Kang, and Sibum Sung. “Identification of Long Noncoding RNAs in the Developing Endosperm of Maize..” Methods Mol Biol, 1933, Pp. 49-65. Publisher's Version
2018
Likai Wang, Yanpeng Xi, Sibum Sung, and Hong Qiao. “RNA-seq assistant: machine learning based methods to identify more transcriptional regulated genes.” BMC Genomics, 19, 1, Pp. 546. Abstract
BACKGROUND: Although different quality controls have been applied at different stages of the sample preparation and data analysis to ensure both reproducibility and reliability of RNA-seq results, there are still limitations and bias on the detectability for certain differentially expressed genes (DEGs). Whether the transcriptional dynamics of a gene can be captured accurately depends on experimental design/operation and the following data analysis processes. The workflow of subsequent data processing, such as reads alignment, transcript quantification, normalization, and statistical methods for ultimate identification of DEGs can influence the accuracy and sensitivity of DEGs analysis, producing a certain number of false-positivity or false-negativity. Machine learning (ML) is a multidisciplinary field that employs computer science, artificial intelligence, computational statistics and information theory to construct algorithms that can learn from existing data sets and to make predictions on new data set. ML-based differential network analysis has been applied to predict stress-responsive genes through learning the patterns of 32 expression characteristics of known stress-related genes. In addition, the epigenetic regulation plays critical roles in gene expression, therefore, DNA and histone methylation data has been shown to be powerful for ML-based model for prediction of gene expression in many systems, including lung cancer cells. Therefore, it is promising that ML-based methods could help to identify the DEGs that are not identified by traditional RNA-seq method. RESULTS: We identified the top 23 most informative features through assessing the performance of three different feature selection algorithms combined with five different classification methods on training and testing data sets. By comprehensive comparison, we found that the model based on InfoGain feature selection and Logistic Regression classification is powerful for DEGs prediction. Moreover, the power and performance of ML-based prediction was validated by the prediction on ethylene regulated gene expression and the following qRT-PCR. CONCLUSIONS: Our study shows that the combination of ML-based method with RNA-seq greatly improves the sensitivity of DEGs identification.
2017
Dong-Hwan Kim and Sibum Sung. “Accelerated vernalization response by an altered PHD-finger protein in Arabidopsis.” Plant Signal Behav, 12, 5, Pp. e1308619. Abstract
Vernalization is a response to the winter cold to acquire the competence to flower in next spring. VERNALIZATION INSENSITIVE 3 (VIN3) is a PHD-finger protein that binds to modified histones in vitro. VIN3 is induced by long-term cold and is necessary for Polycomb Repression Complex 2 (PRC2)-mediated tri-methylation of Histone H3 Lysine 27 (H3K27me3) at the FLC locus in Arabidopsis. An alteration in the PHD-finger domain of VIN3 changes the binding specificity of the PHD-finger domain of VIN3 in vitro and results in an accelerated vernalization response in vivo. The acceleration in vernalization response is achieved by increased enrichments of VIN3 and tri-methylation of Histone H3 Lysine 27 (H3K27me3) at the FLC locus without invoking the increased enrichment of Polycomb Repressive Complex 2. This result indicates that the binding specificity of the PHD-finger domain of VIN3 plays a role in mediating a proper vernalization response in Arabidopsis. Furthermore, this work shows a potential that the alteration of PHD-finger domains could be applied to alter various developmental processes in plants.
Dong-Hwan Kim and Sibum Sung. “The Binding Specificity of the PHD-Finger Domain of VIN3 Moderates Vernalization Response.” Plant Physiol, 173, 2, Pp. 1258-1268. Abstract
Vernalization is a response to winter cold to initiate flowering in spring. VERNALIZATION INSENSITIVE3 (VIN3) is induced by winter cold and is essential to vernalization response in Arabidopsis (Arabidopsis thaliana). VIN3 encodes a PHD-finger domain that binds to modified histones in vitro. An alteration in the binding specificity of the PHD-finger domain of VIN3 results in a hypervernalization response. The hypervernalization response is achieved by increased enrichments of VIN3 and trimethylation of Histone H3 Lys 27 at the FLC locus without invoking the increased enrichment of Polycomb Repressive Complex 2. Our result shows that the binding specificity of the PHD-finger domain of VIN3 plays a role in mediating a proper vernalization response in Arabidopsis.
Dong-Hwan Kim, Yanpeng Xi, and Sibum Sung. “Modular function of long noncoding RNA, COLDAIR, in the vernalization response.” PLoS Genet, 13, 7, Pp. e1006939. Abstract
The long noncoding RNA COLDAIR is necessary for the repression of a floral repressor FLOWERING LOCUS C (FLC) during vernalization in Arabidopsis thaliana. The repression of FLC is mediated by increased enrichment of Polycomb Repressive Complex 2 (PRC2) and subsequent trimethylation of Histone H3 Lysine 27 (H3K27me3) at FLC chromatin. In this study we found that the association of COLDAIR with chromatin occurs only at the FLC locus and that the central region of the COLDAIR transcript is critical for this interaction. A modular motif in COLDAIR is responsible for the association with PRC2 in vitro, and the mutations within the motif that reduced the association of COLDAIR with PRC2 resulted in vernalization insensitivity. The vernalization insensitivity caused by mutant COLDAIR was rescued by the ectopic expression of the wild-type COLDAIR. Our study reveals the molecular framework in which COLDAIR lncRNA mediates the PRC2-mediated repression of FLC during vernalization.

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