Back

Evolution and molecular characteristics of SARS-CoV-2 genome

Bai, Y.; Jiang, D.; Lon, J. R.; Chen, X.; Hu, M.; Lin, S.; Chen, Z.; Meng, Y.; Du, H.

2020-04-24 bioinformatics
10.1101/2020.04.24.058933 bioRxiv
Show abstract

ObjectivesTo reveal epidemic trend and possible origins of SARS-CoV-2 by exploring its evolution and molecular characteristics based on a large number of genomes since it has infected millions of people and spread quickly all over the world. MethodsVarious evolution analysis methods were employed. ResultsThe estimated Ka/Ks ratio of SARS-CoV-2 is 1.008 or 1.094 based on 622 or 3624 SARS-CoV-2 genomes, and the time to the most recent common ancestor (tMRCA) was inferred in late September 2019. Further 9 key specific sites of highly linkage and four major haplotypes H1, H2, H3 and H4 were found. The Ka/Ks, detected population size and development trends of each major haplotype showed H3 and H4 subgroups were going through a purify evolution and almost disappeared after detection, indicating H3 and H4 might have existed for a long time, while H1 and H2 subgroups were going through a near neutral or neutral evolution and globally increased with time. Notably the frequency of H1 was generally high in Europe and correlated to death rate (r>0.37). ConclusionsIn this study, the evolution and molecular characteristics of more than 16000 genomic sequences provided a new perspective for revealing epidemiology of SARS-CoV-2.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Genomics, Proteomics & Bioinformatics
188 papers in training set
Top 0.2%
9.0%
2
Frontiers in Genetics
○ 230 papers in training set
Top 0.2%
7.8%
Similar papers in this journal
3
Briefings in Bioinformatics
◐ 354 papers in training set
Top 1%
7.1%
Similar papers in this journal
4
PeerJ
◐ 308 papers in training set
Top 0.5%
6.6%
Similar papers in this journal
5
Virologica Sinica
○ 11 papers in training set
Top 0.1%
5.4%
Similar papers in this journal
6
Frontiers in Microbiology
○ 427 papers in training set
Top 2%
5.4%
7
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 0.6%
5.4%
8
Journal of Medical Virology
○ 140 papers in training set
Top 0.4%
4.8%
50% of probability mass above
9
Science China Life Sciences
○ 29 papers in training set
Top 0.1%
4.3%
10
Gene
○ 46 papers in training set
Top 0.2%
4.0%
11
Scientific Reports
○ 3612 papers in training set
Top 34%
3.2%
12
eLife
● 5828 papers in training set
Top 36%
3.2%
13
Cell Discovery
○ 57 papers in training set
Top 0.3%
2.4%
14
PLOS ONE
● 5266 papers in training set
Top 45%
1.9%
15
The Innovation
○ 13 papers in training set
Top 0.1%
1.7%
16
BMC Genomics
○ 406 papers in training set
Top 4%
1.7%
17
Database
◐ 61 papers in training set
Top 0.5%
1.7%
18
Journal of Genetics and Genomics
○ 38 papers in training set
Top 0.3%
1.7%
19
Genomics
○ 64 papers in training set
Top 1.0%
1.4%
20
Genes
○ 144 papers in training set
Top 2%
1.3%
21
Science Bulletin
○ 21 papers in training set
Top 0.3%
1.1%
22
iScience
○ 1154 papers in training set
Top 37%
0.8%
23
Viruses
○ 332 papers in training set
Top 5%
0.8%
24
Biochemical and Biophysical Research Communications
○ 84 papers in training set
Top 3%
0.8%
25
Protein & Cell
◐ 25 papers in training set
Top 0.5%
0.8%
26
iMeta
○ 10 papers in training set
Top 0.2%
0.6%