Chang Liu

Prof. Chang Liu

Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine from the Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, PR C

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
8 May 2019 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
LSLinchun Shi
Linchun Shi
HCHaimei Chen
Haimei Chen
MJMei Jiang
Mei Jiang
LWLiqiang Wang
Liqiang Wang
XWXi Wu
Xi Wu
CLChang Liu
Chang Liu
We previously developed a web server CPGAVAS for annotation, visualization and GenBank submission of plastome sequences. Here, we upgrade the server into CPGAVAS2 to address the following challenges: (i) inaccurate annotation in the reference sequence likely causing the propagation of errors; (ii) difficulty in the annotation of small exons of genes petB, petD and rps16 and trans-splicing gene rps12; (iii) lack of annotation for other genome features and their visualization, such as repeat elements; and (iv) lack of modules for diversity analysis of plastomes. In particular, CPGAVAS2 provides two reference datasets for plastome annotation. The first dataset contains 43 plastomes whose annotation have been validated or corrected by RNA-seq data. The second one contains 2544 plastomes curated with sequence alignment. Two new algorithms are also implemented to correctly annotate small exons and trans-splicing genes. Tandem and dispersed repeats are identified, whose results are displayed on a circular map together with the annotated genes. DNA-seq and RNA-seq data can be uploaded for identification of single-nucleotide polymorphism sites and RNA-editing sites. The results of two case studies show that CPGAVAS2 annotates better than several other servers. CPGAVAS2 will likely become an indispensible tool for plastome research and can be accessed from http://www.herbalgenomics.org/cpgavas2.

1 January 2023 in Molecular Ecology Resources
Verified
Journal Article
Closed access
SLShengyu Liu
Shengyu Liu
YNYang Ni
Yang Ni
JLJingling Li
Jingling Li
XZXinyi Zhang
Xinyi Zhang
HYHeyu Yang
Heyu Yang
CLChang Liu
Chang Liu

1 January 2012 in BMC Genomics
Verified
Journal Article
Open access
PDF file
CLChang Liu
Chang Liu
LSLinchun Shi
Linchun Shi
YZYingjie Zhu
Yingjie Zhu
HCHaimei Chen
Haimei Chen
JZJianhui Zhang
Jianhui Zhang
XGXiaojun Guan
Xiaojun Guan
The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas .

3 September 2014 in Molecular Ecology Resources
Verified
Journal Article
Closed access
PDF file
XWXin‐Cun Wang
Xin‐Cun Wang
CLChang Liu
Chang Liu
LHLiang Huang
Liang Huang
JBJohan Bengtsson-Palme
Johan Bengtsson-Palme
HCHaimei Chen
Haimei Chen
JLJian‐Qin Li
Jian‐Qin Li

9 November 2024 in Plant Communications
Verified
Journal Article
Open access
JLJingling Li
Jingling Li
YNYang Ni
Yang Ni
QLQianqi Lu
Qianqi Lu
HCHaimei Chen
Haimei Chen
CLChang Liu
Chang Liu

26 October 2010 in BMC Ecology and Evolution
Verified
Journal Article
Open access
TGTing Gao
Ting Gao
HYHui Yao
Hui Yao
JSJingyuan Song
Jingyuan Song
YZYingjie Zhu
Yingjie Zhu
CLChang Liu
Chang Liu
SCShilin Chen
Shilin Chen
Background: Five DNA regions, namely, rbcL, matK, ITS, ITS2, and psbA-trnH, have been recommended as primary DNA barcodes for plants. Studies evaluating these regions for species identification in the large plant taxon, which includes a large number of closely related species, have rarely been reported. Results: The feasibility of using the five proposed DNA regions was tested for discriminating plant species within Asteraceae, the largest family of flowering plants. Among these markers, ITS2 was the most useful in terms of universality, sequence variation, and identification capability in the Asteraceae family. The species discriminating power of ITS2 was also explored in a large pool of 3,490 Asteraceae sequences that represent 2,315 species belonging to 494 different genera. The result shows that ITS2 correctly identified 76.4% and 97.4% of plant samples at the species and genus levels, respectively. In addition, ITS2 displayed a variable ability to discriminate related species within different genera. Conclusions: ITS2 is the best DNA barcode for the Asteraceae family. This approach significantly broadens the application of DNA barcoding to resolve classification problems in the family Asteraceae at the genera and species levels.