LSD 3.0: a comprehensive resource for the leaf senescence research community.
Zhonghai Li, Yang Zhang, Dong Zou, Yi Zhao, Hou-Ling Wang, Yi Zhang, Xinli Xia, Jingchu Luo, Hongwei Guo, Zhang Zhang
Author Information
- Zhonghai Li: Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.
- Yang Zhang: National Genomics Data Center, Beijing 100101, China.
- Dong Zou: National Genomics Data Center, Beijing 100101, China.
- Yi Zhao: College of Life Sciences, Peking University, Beijing 100871, China.
- Hou-Ling Wang: Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.
- Yi Zhang: Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.
- Xinli Xia: Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.
- Jingchu Luo: College of Life Sciences, Peking University, Beijing 100871, China.
- Hongwei Guo: Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.
- Zhang Zhang: National Genomics Data Center, Beijing 100101, China.
The leaf senescence database (LSD) is a comprehensive resource of senescence-associated genes (SAGs) and their corresponding mutants. Through manual curation and extensive annotation, we updated the LSD to a new version LSD 3.0, which contains 5853 genes and 617 mutants from 68 species. To provide sustainable and reliable services for the plant research community, LSD 3.0 (https://bigd.big.ac.cn/lsd/) has been moved to and maintained by the National Genomics Data Center at Beijing Institute of Genomics, Chinese Academy of Sciences. In the current release, we added some new features: (i) Transcriptome data of leaf senescence in poplar were integrated; (ii) Leaf senescence-associated transcriptome data information in Arabidopsis, rice and soybean were included; (iii) Senescence-differentially expressed small RNAs (Sen-smRNA) in Arabidopsis were identified; (iv) Interaction pairs between Sen-smRNAs and senescence-associated transcription factors (Sen-TF) were established; (v) Senescence phenotypes of 90 natural accessions (ecotypes) and 42 images of ecotypes in Arabidopsis were incorporated; (vi) Mutant seed information of SAGs in rice obtained from Kitbase was integrated; (vii) New options of search engines for ecotypes and transcriptome data were implemented. Together, the updated database bears great utility to continue to provide users with useful resources for studies of leaf senescence.
Aging
Arabidopsis
Computational Biology
Databases, Genetic
Gene Expression Profiling
Gene Expression Regulation, Plant
Genes, Plant
Molecular Sequence Annotation
Mutation
Phenotype
Plant Leaves
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