Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023

Wang, Yiwei; Yang, Jiaxin; Zhuang, Xue; Gao, Yuan; Chen, Xiaoning; Xia, Zhiqiang; Zhou, Xin; Chao, Jinquan; Weimin, Tian; Wang, Wenquan; Huang, Yue; Xing, Peiqi; Liu, Zhaoqi; Lu, Mingming; Zhang, Yadong; Yang, Feng-Chun; Mai, Jialin; Gao, Qianwen; Xu, Xiaowei; Kang, Hongyu; Hou, Li; Qain, Qiheng; Liu, Jie; Jiang, Meiye; Zhang, Hao; Wang, Jinyue; Zhang, Zhewen; Zhang, Zaichao; Zeng, Jingyao; Li, Jiao; Pan, Siyu; Kang, Hongen; Liu, Xinxuan; Lin, Shiqi; Ni, Yuan; Jia, Peilin; Zheng, Xinchang; Li, Zhaohua; Bu, Congfan; Du, Zhenglin; Chen, Xu; Chen, Tingting; Sun, Yanling; Zhai, Shuang; Sun, Yuan; Qiancheng, Chen; Yang, Xiaoyu; Zhang, Xin; Sang, Zhengqi; Wang, Yonggang; Zhao, Yong; Chen, Huanxin; Li, Lan; Wang, Anke; Yu, Chao; Wang, Yanqing; Zhang, Sisi; Jia, Yaokai; Zhao, Xuetong; Chen, Meili; Dong, Lili; Liu, Xiaonan; Tian, Dongmei; Tang, Bixia; Pan, Yitong; Wang, Yi; Li, Cuiping; Gong, Zheng; Zhu, Junwei; Teng, Xufei; Li, Lun; Li, Na; Cui, Ying; Duan, Guangya; Kang, Hailong; Wang, Zhonghuang; Wu, Gangao; Huang, Tianhao; Jin, Enhui; Zhang, Tao; Song, Shuhui; Sang, Jian; Pan, Rong; Zhang, Yuanpu; Wang, Zhennan; Xu, Tianyi; Yao, Qiliang; Niu, Guangyi; Hao, Lili; Zhang, Mochen; Zhao, Wei; Wang, Guoliang; Yang, Fei; Wu, Song; Zhang, Xinran; Guo, Xutong; Ma, Yingke; Xiong, Zhuang; Li, Rujiao; Feng, Changrui; Zhao, Li; Qian, Qiheng; Zhu, Tongtong; Zong, Wenting; Shang, Yunfei; Jin, Tao; Zhang, Yuansheng; Wu, Zishan; Chu, Yuan; Zhang, Rongqin; Zou, Dong; Liu, Lin; Qin, Yuxin; Luo, Sicheng; Wei, Jing; Li, Qianpeng; Liu, Pei; Sun, Yu; Ma, Lina; Jiang, Shuai; Fan, Zhuojing; Shen, Wen-Kang; Zuo, Zhixiang; Liú, Dan; Zhang, Chi; Zhao, Zheng; Jiang, Tao; Wu, Wanying; Zhao, Fangqing; Meng, Xianwen; Gou, Yujie; Chen, Miaomiao; Peng, Di; Ning, Wanshan; Wan, Lei; Ling, Yunchao; Cao, Ruifang; Wei, Yuxiang; Yuan, Hao; Su, Tianhan; Zhang, Yong E.; Zhou, Chenfen; Wang, Pengyu; Zhang, Qiong; Fu, Shanlin; Tan, Xiaodan; Tang, Dachao; Zhang, Weizhi; Luo, Min; Xie, Yubin; Miao, Ya‐Ru; Zhou, Yincong; Guo, Guoji; Huang, Xinhe; Feng, Zhaoyong; Liu, Chun‐Jen; Liao, Xingyu; Gao, Xin; Wang, Jianxin; Xie, Gui-Yan; Yuan, Chunhui; Yang, De-Chang; Tian, Feng; Gao, Ge; Wu, Wei; Chen, Ming; Chen, Han; Xue, Yu; Cui, Qinghua; Xiao, Chunfu; Li, Chuan-Yun; Luo, Xiaotong; Ren, Jian; Zhang, Xinxin; Xiao, Yun; Li, Xia; Tang, Qing; Guo, An‐Yuan; Luo, Hao; Gao, Feng; Xue, Yongbiao; Bào, Yīmíng; Zhang, Zhang; Zhao, Wenming; Xiao, Jingfa; He, Shunmin; Zhang, Guoqing; Li, Yixue; Zhao, Guoping; Chen, Runsheng

doi:10.1093/nar/gkac1073

Cited by 133 publications

(51 citation statements)

References 63 publications

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“…The Illumina sequencing data have been deposited in the Genome Sequence Archive 63 in National Genomics Data Center 64 , China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences under accession number CRA011573 (temporary link for reviewers https://ngdc.cncb.ac.cn/gsa/s/Tby9C5yR). Plasmid sequences have been deposited in GenBase (accession ID: C_AA 031173.1, C_AA031174.1, and C_AA031175.1).…”

Section: Data Availabilitymentioning

confidence: 99%

Overriding Mendelian inheritance inArabidopsiswith a CRISPR toxin-antidote gene drive that impairs pollen germination

Liu,

Jiao,

Champer

et al. 2023

Preprint

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Synthetic gene drives, inspired by natural selfish genetic elements, present transformative potential for disseminating traits that benefit humans throughout wild populations, irrespective of potential fitness costs. Here, we constructed a gene drive system called CRISPR-Assisted Inheritance utilizing NPG1 (CAIN), which employs a toxin-antidote mechanism in the male germline to override Mendelian inheritance in plants. Specifically, a gRNA-Cas9 cassette targets the essential No Pollen Germination 1 (NPG1) gene, serving as the toxin to block pollen germination. A recoded, CRISPR-resistant copy of NPG1 serves as the antidote, providing rescue only in pollen cells that carry the drive. To limit potential consequences of inadvertent release, we used self-pollinating Arabidopsis thaliana as a model. The drive demonstrated a robust 88-99% transmission rate over two successive generations, producing minimal resistance alleles that are unlikely to inhibit drive spread. Our study provides a strong basis for rapid genetic modification or suppression of outcrossing plant populations.

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Section: Data Availabilitymentioning

confidence: 99%

Overriding Mendelian inheritance inArabidopsiswith a CRISPR toxin-antidote gene drive that impairs pollen germination

Liu,

Jiao,

Champer

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Data and materials availability: Raw sequence data generated during this study have been deposited in the BIG sub ( 42 ) with accession nos. CRA011946 and CRA011945 for RNA-seq.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Biofortification of iron content by regulating a NAC transcription factor in maize

Yan,

Du,

Chen

et al. 2023

Science

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Iron (Fe) deficiency remains widespread among people in developing countries. To help solve this problem, breeders have been attempting to develop maize cultivars with high yields and high Fe concentrations in the kernels. We conducted a genome-wide association study and identified a gene, ZmNAC78 ( NAM/ATAF/CUC DOMAIN TRANSCRIPTION FACTOR 78 ), that regulates Fe concentrations in maize kernels. We cultivated maize varieties with both high yield and high Fe concentrations in their kernels by using a molecular marker developed from a 42–base pair insertion or deletion (indel) in the promoter of ZmNAC78 . ZmNAC78 expression is enriched in the basal endosperm transfer layer of kernels, and the ZmNAC78 protein directly regulates messenger RNA abundance of Fe transporters. Our results thus provide an approach to develop maize varieties with Fe-enriched kernels.

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“…The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive [57,58]…”

Section: Author Contributionsmentioning

confidence: 99%

Multi-omics analysis reveals novel interplays between intratumoral bacteria and glioma

Li,

Zhao,

Peng

et al. 2023

Preprint

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Emerging evidence highlights the potential impact of intratumoral microbiota on cancer. However, the microbial composition and function in glioma remains elusive. Consequently, our study aimed to investigate the microbial community composition in glioma tissues and elucidate its role in glioma development. We parallelly performed microbial profiling, transcriptome sequencing and metabolomics detection on tumor and adjacent normal brain tissues obtained from 50 glioma patients. We employed immunohistochemistry, multicolor immunofluorescence and FISH staining to observe the presence and location of bacteria. Furthermore, an animal model was employed to validate the impact of key bacteria on glioma development. Six genera were found to be significantly enriched in glioma tissues compared to its adjacent normal brain tissues, includingFusobacterium,Longibaculum,Intestinimonas,Pasteurella,LimosilactobacillusandArthrobacter. Both bacterial RNA and LPS were observed in glioma tissues. Multicolor immunofluorescence analysis showed higher bacterial LPS levels in tumor cells than in macrophages and in glioma tissue than in adjacent normal brain tissue. Integrated microbiomics, transcriptomics, and metabolomics revealed that genes associated with intratumoral microbes were enriched in multiple synapse-associated pathways and that metabolites associated with intratumoral microbes were (R)-N-methylsalsolinol, N-acetylaspartylglutamic acid, and N-acetyl-L-aspartic acid. Further mediation analysis suggested that intratumoral microbiome may affect the expression of neuron-related genes through bacteria-associated metabolites. In addition, a glioma mouse model suggested thatFusobacterium nucleatumpromoted glioma growth by increasing the levels of N-acetylneuraminic acid and the expression levels of CCL2, CXCL1, and CXCL2. In conclusion, our findings shed light on the intricate interplays between intratumoral bacteria and glioma.

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Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023

Cited by 133 publications

References 63 publications

Overriding Mendelian inheritance inArabidopsiswith a CRISPR toxin-antidote gene drive that impairs pollen germination

Overriding Mendelian inheritance inArabidopsiswith a CRISPR toxin-antidote gene drive that impairs pollen germination

Biofortification of iron content by regulating a NAC transcription factor in maize

Multi-omics analysis reveals novel interplays between intratumoral bacteria and glioma

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