A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions. (1st September 2021)

• Record Type: Journal Article
• Authors: Loewenthal, Gil; Rapoport, Dana; Avram, Oren; Moshe, Asher; Wygoda, Elya; Itzkovitch, Alon; Israeli, Omer; Azouri, Dana; Cartwright, Reed A; Mayrose, Itay; Pupko, Tal
• Editors: Xia, Xuhua
• Is Part Of: Molecular biology and evolution. Volume 38:Number 12(2021)
• Page Start: 5769
• Page End: 5781
• Publication Date: 2021-09-01
• Subjects: molecular evolution -- evolutionary models -- indels -- alignments -- approximate Bayesian computation; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msab266
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: Insertions and deletions (indels) are common molecular evolutionary events. However, probabilistic models for indel evolution are under-developed due to their computational complexity. Here, we introduce several improvements to indel modeling: 1) While previous models for indel evolution assumed that the rates and length distributions of insertions and deletions are equal, here we propose a richer model that explicitly distinguishes between the two; 2) we introduce numerous summary statistics that allow approximate Bayesian computation-based parameter estimation; 3) we develop a method to correct for biases introduced by alignment programs, when inferring indel parameters from empirical data sets; and 4) using a model-selection scheme, we test whether the richer model better fits biological data compared with the simpler model. Our analyses suggest that both our inference scheme and the model-selection procedure achieve high accuracy on simulated data. We further demonstrate that our proposed richer model better fits a large number of empirical data sets and that, for the majority of these data sets, the deletion rate is higher than the insertion rate.