Distinct codon usage bias evolutionary patterns between weakly and strongly virulent respiratory viruses
Human respiratory viruses are of vastly different virulence, giving rise to symptoms ranging from common cold to severe pneumonia or even death. Although this most likely impacts molecular evolution of the corresponding viruses, the specific differences in their evolutionary patterns remain largely unknown. By comparing structural and nonstructural genes within respiratory viruses, greater similarities in codon usage bias (CUB) between nonstructural genes and humans were observed in weakly virulent viruses, whereas in strongly virulent viruses, it was structural genes whose CUBs were more similar to that of humans. Further comparisons between genomes of weakly and strongly virulent coronaviruses revealed greater similarities in CUBs between strongly virulent viruses and humans. Finally, using phylogenetic independent contrasts, dissimilation of viral CUB from that of humans was observed in SARS-CoV-2. Our work revealed distinct CUB evolutionary patterns between weakly and strongly virulent viruses, a previously unrecognized interaction between CUB and virulence in respiratory viruses.
期刊:
iScience
2021
作者:
Jian-Rong Yang,Feng Chen
DOI:10.1016/j.isci.2021.103682
Alignment of Cell Lineage Trees Elucidates Genetic Programs for the Development and Evolution of Cell Types
A full understanding of the developmental process requires fine-scale characterization of cell divisions and cell types, which are naturally organized as the developmental cell lineage tree (CLT). Technological breakthroughs facilitated determination of more CLTs, but complete comprehension of the data remains difficult without quantitative comparison among CLTs. We hereby quantified phenotypic similarity between CLTs using a novel computational method that exhaustively searches for optimal correspondence between individual cells meanwhile retaining their topological relationships. The revealed CLT similarities allowed us to infer functional similarity at the transcriptome level, identify cell fate transformations, predict functional relationships between mutants, and find evolutionary correspondence between cell types of different species. By allowing quantitative comparison between CLTs, our work is expected to greatly enhance the interpretability of relevant data and help answer the myriad of questions surrounding the developmental process.
期刊:
iScience
2020
作者:
Jian-Rong Yang,Xiaoshu Chen,Xueqin Wang,Guifeng Zheng,Zizhang Li,Xiaoyu Zhang,Feng Chen,Xiaolong Cao,Jinghua Lin,Xujiang Yang,Meng Yuan
DOI:10.1016/j.isci.2020.101273
Dissimilation of synonymous codon usage bias in virus–host coevolution due to translational selection
Eighteen of the 20 amino acids are each encoded by more than one synonymous codon. Due to differential transfer RNA supply within the cell, synonymous codons are not used with equal frequency, a phenomenon termed codon usage bias (CUB). Previous studies have demonstrated that CUB of endogenous genes trans-regulates the translational efficiency of other genes. We hypothesized similar effects for CUB of exogenous genes on host translation, and tested it in the case of viral infection, a common form of naturally occurring exogenous gene translation. We analysed public Ribo-Seq datasets from virus-infected yeast and human cells and showed that virus CUB trans-regulated tRNA availability, and therefore the relative decoding time of codons. Manipulative experiments in yeast using 37 synonymous fluorescent proteins confirmed that an exogenous gene with CUB more similar to that of the host would apply decreased translational load on the host per unit of expression, whereas expression of the exogenous gene was elevated. The combination of these two effects was that exogenous genes with CUB overly similar to that of the host severely impeded host translation. Finally, using a manually curated list of viruses and natural and symptomatic hosts, we found that virus CUB tended to be more similar to that of symptomatic hosts than that of natural hosts, supporting a general deleterious effect of excessive CUB similarity between virus and host. Our work revealed repulsion between virus and host CUBs when they are overly similar, a previously unrecognized complexity in the coevolution of virus and host.
期刊:
Nature Ecology & Evolution
2020
作者:
Jian-Rong Yang,Xiaoshu Chen,Jianzhi Zhang,Zheng Hu,Yutong Hou,Heng Zhang,Shuyun Deng,Peng Wu,Feng Chen
DOI:10.1038/s41559-020-1124-7
Computational comparison of developmental cell lineage trees by alignments
ABSTRACT The developmental cell lineage tree, which records every cell division event and the terminal developmental state of each single cell, is one of the most important traits of multicellular organisms, as well as key to many significant unresolved questions in biology. Recent technological breakthroughs are paving the way for direct determination of cell lineage trees, yet a general framework for the computational analysis of lineage trees, in particular an algorithm to compare two lineage trees, is still lacking. Based on previous findings that the same developmental program can be invoked by different cells on the lineage tree to produce highly similar subtrees, we designed D evelopmental C e ll L ineage T ree A lignment (DELTA), an algorithm that exhaustively searches for lineage trees with phenotypic resemblance in lineal organization of terminal cells, meanwhile resolving detailed correspondence between individual cells. Using simulated and nematode lineage trees, we demonstrated DELTA’s capability of revealing similarities of developmental programs by lineal resemblances. Moreover, DELTA successfully identifies gene deletion-triggered homeotic cell fate transformations, reveals functional relationship between mutants by quantifying their lineal similarities, and finds the evolutionary correspondence between cell types defined non-uniformly for different species. DELTA establishes novel foundation for comparative study of lineage trees, much like sequence alignment algorithm for biological sequences, and along with the increase of lineage tree data, will likely bring unique insights for the myriads of important questions surrounding cell lineage trees.
期刊:
bioRxiv
2019
作者:
Jian-Rong Yang,Xiaoshu Chen,Xueqin Wang,Guifeng Zheng,Zizhang Li,Xiaoyu Zhang,Feng Chen,Xiaolong Cao,Jinghua Lin,Xujiang Yang,Meng Yuan
DOI:10.1101/577809
