SorGSD: updating and expanding the sorghum genome science database with new contents and tools.
Yuanming Liu, Zhonghuang Wang, Xiaoyuan Wu, Junwei Zhu, Hong Luo, Dongmei Tian, Cuiping Li, Jingchu Luo, Wenming Zhao, Huaiqing Hao, Hai-Chun Jing
Author Information
- Yuanming Liu: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- Zhonghuang Wang: University of Chinese Academy of Sciences, Beijing, 100049, China.
- Xiaoyuan Wu: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- Junwei Zhu: China National Center for Bioinformation, Beijing, 100101, China.
- Hong Luo: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- Dongmei Tian: China National Center for Bioinformation, Beijing, 100101, China.
- Cuiping Li: China National Center for Bioinformation, Beijing, 100101, China.
- Jingchu Luo: College of Life Sciences and Center for Bioinformatics, Peking University, Beijing, 100871, China.
- Wenming Zhao: University of Chinese Academy of Sciences, Beijing, 100049, China. zhaowm@big.ac.cn.
- Huaiqing Hao: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. hqhao@ibcas.ac.cn. ORCID
- Hai-Chun Jing: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
BACKGROUND: As the fifth major cereal crop originated from Africa, sorghum (Sorghum bicolor) has become a key C model organism for energy plant research. With the development of high-throughput detection technologies for various omics data, much multi-dimensional and multi-omics information has been accumulated for sorghum. Integrating this information may accelerate genetic research and improve molecular breeding for sorghum agronomic traits.
RESULTS: We updated the Sorghum Genome SNP Database (SorGSD) by adding new data, new features and renamed it to Sorghum Genome Science Database (SorGSD). In comparison with the original version SorGSD, which contains SNPs from 48 sorghum accessions mapped to the reference genome BTx623 (v2.1), the new version was expanded to 289 sorghum lines with both single nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs), which were aligned to the newly assembled and annotated sorghum genome BTx623 (v3.1). Moreover, phenotypic data and panicle pictures of critical accessions were provided in the new version. We implemented new tools including ID Conversion, Homologue Search and Genome Browser for analysis and updated the general information related to sorghum research, such as online sorghum resources and literature references. In addition, we deployed a new database infrastructure and redesigned a new user interface as one of the Genome Variation Map databases. The new version SorGSD is freely accessible online at http://ngdc.cncb.ac.cn/sorgsd/ .
CONCLUSIONS: SorGSD is a comprehensive integration with large-scale genomic variation, phenotypic information and incorporates online data analysis tools for data mining, genome navigation and analysis. We hope that SorGSD could provide a valuable resource for sorghum researchers to find variations they are interested in and generate customized high-throughput datasets for further analysis.
