Database Resources of the BIG Data Center in 2019

Zhang, Zhang; Zhao, Wenming; Xiao, Jingfa; Bào, Yīmíng; Wang, Fan; Hao, Lili; Zhu, Junwei; Chen, Tingting; Zhang, Sisi; Chen, Xu; Tang, Bixia; Zhou, Qing; Wang, Zhonghuang; Dong, Lili; Wang, Yanqing; Ma, Yingke; Zhang, Zhe-Wen; Chen, Meili; Tian, Dongmei; Li, Cuiping; Teng, Xufei; Du, Zhenglin; Ni, Yuan; Zeng, Jingyao; Wang, Jinyue; Shi, Shuo; Zhang, Yadong; Wang, Qi; Pan, Mengyu; Qian, Qiheng; Song, Shuhui; Niu, Guangyi; Li, Man; Xia, Lin; Zou, Dong; Zhang, Yuansheng; Sang, Jian; Li, Mengwei; Zhang, Yang; Wang, Pei; Gao, Qianwen; Fang, Liang; Li, Rujiao; Liu, Lin; Cao, Jiabao; Abbasi, Amir Ali; Shireen, Huma; Zhao, Li; Xiong, Zhuang; Jiang, Meiye; Guo, Tongkun; Li, Zhaohua; Zhang, Hao; Ma, Lina; Gao, Ran; Zhang, Tao; Li, Wulue; Zhang, Xiangquan; Li, Lan; Zhai, Shuang; Zhang, Yaping; Wang, Guodong; Wang, Zhennan; Xue, Yongbiao; Sun, Yuan; Yu, Lei; Sun, Mingyuan; Chen, Huanxin; Hu, Hui; Guo, An‐Yuan; Lin, Shaofeng; Xue, Yu; Wang, Chenwei; Ning, Wanshan; Zhang, Ying; Luo, Hao; Gao, Feng; Guo, Yaping; Zhang, Qiong; Zhou, Jiaqi; Huang, Zhou; Cui, Qinghua; Miao, Ya‐Ru; Ruan, Chen; Yuan, Chunhui; Ming, Chi; Jin, Jin-Pu; Gao, Ge; Xu, Haodong; Li, Yumei; Li, Chuan-Yun; Tang, Qing; Peng, Di; Deng, Wankun

doi:10.1093/nar/gky993

Cited by 123 publications

(39 citation statements)

References 32 publications

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“…The raw sequence data reported in this study have been deposited in the Genome Sequence Archive 42 in the BIG Data Center 43 (Beijing Institute of Genomics (BIG), Chinese Academy of Sciences) under accession number CRA001957, which is publicly accessible at https://bigd. big.ac.cn/gsa.…”

Section: Transcriptomic Analysismentioning

confidence: 99%

Transcriptome profiles reveal that gibberellin-related genes regulate weeping traits in crape myrtle

Zheng

Zhuo

et al. 2020

Hortic Res

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Plant architecture includes vital traits that influence and benefit crops, and economically important trees. Different plant architectures provide natural beauty. Weeping ornamental plants are aesthetically appealing to people. The regulatory mechanism controlling the weeping trait is poorly understood in crape myrtle. To investigate the weeping trait mechanism, transcriptional profiling of different organs in weeping and upright crape myrtle was performed based on phenotype. Phenotypic and histological analyses demonstrated that endodermal cells were absent, and that new shoot phenotypes could be rescued by the GA3 treatment of weeping plants. The transcriptional analysis and coexpression network analysis (WGCNA) of differentially expressed genes indicated that GA synthesis and signal transduction pathways play a role in weeping traits. When the expression level of a negative element of GA signaling, LfiGRAS1, was reduced by virus-induced gene silencing (VIGS), new branches grew in infected plants in a negatively geotropic manner. An integrated analysis implied that GA had a strong influence on weeping crape myrtle by interacting with other factors. This study helps to elucidate the mechanism governing the weeping trait and can improve the efficiency of breeding in Lagerstroemia.

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Section: Transcriptomic Analysismentioning

confidence: 99%

Transcriptome profiles reveal that gibberellin-related genes regulate weeping traits in crape myrtle

Zheng

Zhuo

et al. 2020

Hortic Res

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“…All raw sequence data generated in this research has been deposited in the Genome Sequence Archive (GSA) 46 in BIG Data Center 47…”

Section: Ethics Approval and Consent To Participate This Study Was Amentioning

confidence: 99%

Gut Microbiota Dysbiosis Associated with Bile Acid Metabolism in Neonatal Cholestasis Disease

Liu

Wang

et al. 2020

Sci Rep

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Neonatal cholestasis disease (NCD) is a complex and easily mis-diagnosed condition. We analyzed microbiota community structure in feces and measured short-chain fatty acids, bile acids (BAs) and liver function of 12 healthy, 13 NCD, and 13 treated infants after diagnosis. Based on 16S rRNA gene amplicon sequencing and gas-chromatographic-mass-spectrometric analysis of secondary BAs, we identified microbial genera and metabolites that associate with abnormal bile secretion. Streptococcus gallolyticus and Parabacteroides distasonis, and Lactobacillus gasseri had higher relative abundance in healthy and NCD infants respectively. Compared to NCD patients, healthy infants had higher LCA, CDCA and GCDCA fecal concentrations. The three microbial species and three secondary bile acids were selected as potential non-invasive combined biomarkers to diagnose NCD. We propose that microbiotametabolite combined biomarkers could be used for diagnosis of NCD, and this may contribute to improved early clinical diagnosis of NCD in the future. Neonatal cholestasis disease (NCD) affects approximately 1 in every 2500 term infants and is infrequently recognized by primary providers in the setting of physiologic jaundice. Cholestasis jaundice is mostly due to biliary atresia and frequently results from non-biliary atresia 1. The etiology of biliary atresia is unclear but is thought to involve bile duct dysmorphogenesis, viral infection, toxins, chronic inflammation, or autoimmune-mediated bile duct injury 2-5. Non-biliary atresia etiology of neonatal cholestasis may involve bacterial sepsis, galactosemia, tyrosinemia, panhypopituitarism, defective BA synthesis, or obstructive gallstones 1. The complex causes for NCD necessitate improved clinical practice guidelines for the care of infants with cholestasis. Hence, joint general recommendations of the North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition and the European Society for Pediatric Gastroenterology, Hepatology, and Nutrition are available for evaluation of NCD in infants, which identify: 1) the measurement of total and conjugated (direct) serum bilirubin for babies at 2 weeks of age; 2) physical examination for hepatomegaly, splenomegaly and appearance of illness; 3) direct visualization of stool pigment; 4) intra-operative cholangiogram and histological examination of the duct remnant 1. However, infants with biliary atresia usually appear healthy and grow normally, which may deceive the parent or physician into believing that the jaundice is physiologic or caused by breastfeeding 6. Thus, development of new or additional biomarkers is considered important in order to improve the care of NCD. Among the most studied causes of NCD in recent years are metabolic diseases and disorders of bile transport and BA synthesis. Cumulative evidence suggests that the composition and function of the gut microbiota plays a prominent role in the occurrence of human metabolic diseases, including type II diabetes 7 , obesity 8 , liver disease 9,10 , atherosclerosis 11...

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“…The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive [69] in BIG Data Center [70], Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers CRA002159, CRA002160 and CRA002185 that are publicly accessible at https://bigd.big.ac.cn/gsa. The collection of seeds complies with national guidelines.…”

Section: Supplementary Informationmentioning

confidence: 99%

Third-generation sequencing found LncRNA associated with heat shock protein response to heat stress in Populus qiongdaoensis seedlings

Zheng

et al. 2020

BMC Genomics

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Background: As air temperatures increase globally, more and more plants are exposed to heat-stress conditions. Although many studies have explored regulation networks in plants with the aim of improving their heat-stress tolerance, only few have revealed them in trees. Here, individuals of Populus qiongdaoensis seedlings, which grows naturally in tropical areas, exposed to heat at 40°C and the non-coding regulation networks were explored using the PacBio RSII and the Illumina sequencing platform. Results: In total, we obtained 88,161 full-length transcripts representing 39,343 genes using 5,498,988 long reads and 350,026,252 clean reads, and also 216 microRNAs (miRNAs) via 95,794,107 reads. We then identified 928 putative long non-coding RNAs (lncRNAs), consisting of 828 sense lncRNAs (89.22%), 34 long intergenic non-coding RNAs (3.66%), 16 antisense (1.72%), and 50 sense intronic lncRNAs (5.39%). Under the dual criteria of |log 2 fold-change| ≥ 1 and P-value < 0.05, 1690 genes, 25 lncRNAs, and 15 miRNAs were found differentially expressed under the heat stress treatment. Furthermore, 563 and 595 mRNAs were detected as target genes of 14 differently expressed miRNAs and 26 differentially expressed lncRNAs. Functional annotation analysis of these target genes demonstrated they were related to cell membrane stability, plant hormone signal transduction, antioxidation, and aldarate metabolism. Lastly, we uncovered a key interaction network of lncRNAs, miRNAs and mRNAs that consisted of miR1444d, miR482a.1, miR530a, lncHSP18.2, HSP18.1, and HSP18.2. Expression level analysis showed that miRNAs in the network were up-regulated, while mRNAs and lncRNA were down-regulated, and also found that lncHSP18.2 may cis-regulate HSP18.2.

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Database Resources of the BIG Data Center in 2019

Cited by 123 publications

References 32 publications

Transcriptome profiles reveal that gibberellin-related genes regulate weeping traits in crape myrtle

Transcriptome profiles reveal that gibberellin-related genes regulate weeping traits in crape myrtle

Gut Microbiota Dysbiosis Associated with Bile Acid Metabolism in Neonatal Cholestasis Disease

Third-generation sequencing found LncRNA associated with heat shock protein response to heat stress in Populus qiongdaoensis seedlings

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