coalescent analysis
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Author(s):  
Rajesh Raghunanth Pharande ◽  
Sharmila Badal Majee ◽  
Satish S. Gaikwad ◽  
S. D. Moregoankar ◽  
AnilKumar Bannalikar ◽  
...  

Nearly 1.7 million cases of dog bites are reported every year in India and many cases of animal rabies are left unattended and undiagnosed. Therefore, a mere diagnosis of rabies is not sufficient to understand the epidemiology and the spread of the rabies virus (RV) in animals. There is a paucity of information about the evolutionary dynamics of RV in dogs and its biodiversity patterns in India. In total, 50 dog-brain samples suspected of rabies were screened by the nucleoprotein- (N) and glycoprotein- (G) gene PCR. The N and G genes were subsequently sequenced to understand the molecular evolution in these genes. The phylogenetic analysis of the N gene revealed that six isolates in the Mumbai region belonged to a single Arctic lineage. Time-scaled phylogeny by Bayesian coalescent analysis of the partial N gene revealed that the time to the most recent common ancestor (TMRCA) for the sequences belonged to the cluster from 2006.68 with a highest posterior density of 95 % betweeen 2005–2008, which is assigned to Indian lineage I. Migration pattern revealed a strong Bayes factor between Mumbai to Delhi, Panji to Hyderabad, Delhi to Chennai, and Chennai to Chandigarh. Phylogenetic analysis of the G gene revealed that the RVs circulating in the Mumbai region are divided into three lineages. Time-scaled phylogeny by the Bayesian coalescent analysis method estimated that the TMRCA for sequences under study was from 1993 and Indian clusters was from 1962. In conclusion, the phylogenetic analysis of the N gene revealed that six isolates belonged to single Arctic lineages along with other Indian isolates and they were clustered into a single lineage but divided into three clades based on the G-gene sequences. The present study highlights and enhances the current molecular epidemiology and evolution of RV and revealed strong location bias and geographical clustering within Indian isolates on the basis of N and G genes.


2020 ◽  
Author(s):  
Zeqi Yao ◽  
Kehui Liu ◽  
Shanjun Deng ◽  
Xionglei He

AbstractConventional coalescent inferences of population history make the critical assumption that the population under examination is panmictic. However, most populations are structured. This complicates the prevailing coalescent analyses and sometimes leads to inaccurate estimates. To develop a coalescent method unhampered by population structure, we perform two analyses. First, we demonstrate that the coalescent probability of two randomly sampled alleles from the immediate preceding generation (one generation back) is independent of population structure. Second, motivated by this finding, we propose a new coalescent method: i-coalescent analysis. i-coalescent analysis computes the instantaneous coalescent rate (iCR) by using a phylogenetic tree of sampled alleles. Using simulated data, we broadly demonstrate the capability of i-coalescent analysis to accurately reconstruct population size dynamics of highly structured populations, although we find this method often requires larger sample sizes for structured populations than for panmictic populations. Overall, our results indicate i-coalescent analysis to be a useful tool, especially for the inference of population histories with intractable structure such as the developmental history of cell populations in the organs of complex organisms.


2018 ◽  
Vol 31 (11) ◽  
pp. 1623-1631 ◽  
Author(s):  
Lucas Freitas ◽  
Beatriz Mello ◽  
Carlos G. Schrago

2017 ◽  
Vol 8 (2) ◽  
pp. 1206-1216 ◽  
Author(s):  
Carlos G. Schrago ◽  
Beatriz Mello ◽  
Anieli G. Pereira ◽  
Carolina Furtado ◽  
Hector N. Seuánez

2014 ◽  
Author(s):  
Einar Árnason

Darwin's dictum on false facts and false views points the way to opening the road to truth via cogent criticism of the published record. Here I discuss a case in which a truncated dataset (false facts) is used for coalescent analysis of historical demography that reaches a foregone conclusion of a bottleneck of numbers (false views).


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