Multivariate analysis of genomic variables, effective population size, and mutation rate

Punit Bhattachan,Bo Dong

doi:10.1186/s13104-019-4097-3

Abstract

ObjectiveThe relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between genome size variation and organismal complexity. Previously, a clear correlation between genomic variables and effective population size and mutation rate (Neu) led to an important hypothesis to consider random genetic drift as a major evolutionary force during evolution of genome size and complexity. But recent reports also support natural selection as the leading evolutionary force. As such, the debate remains unresolved.ResultsHere, we used a multivariate method to explore the relationship between genomic variables and Neu in order to understand the evolution of genome. Previously reported patterns between genomic variables and Neu were not observed in our multivariate study. We found only one association between intron number and Neu, but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution. We, therefore, concluded that Neu influences intron evolution, while it may not be the only force that provides mechanistic insights into genome evolution and complexity.

Highlights

All eukaryotic genomes possess similar features such as genome size, gene number, intron size, intron number, and transposable elements
We found only one association between intron number and effective population size and mutation rate (Neu), but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution
We could not find relationship between genomic variables and Neu in principal component analysis (PCA) (Fig. 1a, b), cluster analysis (CA) (Fig. 2a, b), and exploratory factor analysis (EFA) (Fig. 3a, b) by applying raw data but in phylogenetically independent contrasts, we found only association between intron number and Neu

Summary

Results

We used raw data to compare with Lynch and Conery [1] analyses, while phylogenetically independent contrasts method was used to provide nonindependence of species in this study. We clearly observed that genomic variables and Neu were not at the same location in the plot, revealing that there were no hidden relationships between them in raw data (Fig. 3a) but in phylogenetically independent contrasts (Fig. 3b), intron number and Neu were located at similar position in the plot, indicating association between them we believe that intron evolution was modulated by Neu. In raw data, Factor 1 had the highest loading for average intron size than genome size, suggesting some correlation between these two variables, with 49% of total variance. We deduced that Neu played almost no part in the evolution of genome size and complexity but may have influenced intron evolution

Introduction

Main text

Discussion

Limitations