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Selection acting on indels and substitutions in protein coding sequences
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology. (Whelan Lab)ORCID iD: 0000-0003-3056-3173
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Patterns of selection acting on an expressed protein act to maintain or adapt its structure and function over time. The most widely used method for studying these selective forces is the ratio of synonymous to non-synonymous substitutions (dN/dS), which helps distinguish between neutral, purifying (negative), and adaptive (positive) selection. This ratio, however, examines only amino acid substitutions and ignores other evolutionary forces like small-scale insertions and deletions (indels) that may affect protein evolution. There are currently no statistically robust methods for studying the forces acting on protein sequence indels, with the few ad hoc solutions highly dependent on the gap patterns produced by alignment and filtering steps. This study broadens our understanding of how selection acts on indels in proteins by explicitly examining the relationship between selective constraint acting on substitutions and indels. We present a probabilistic model that jointly estimates dN/dS and the indel rate through statistical alignment, which removes biases in both parameter estimates caused by alignment error. We apply our method to thousands of genes from human-mouse and human-chicken pairwise analyses, revealing that the indel rate and selection (dN/dS) tends to be related, demonstrating that purifying selection acting in proteins tends to affect non-synonymous mutations and indels in a quantifiably similar way. We also investigate how the selective forces acting on substitutions and indels vary along genes. Our findings and methods offer the opportunity to begin studying the interaction between substitutions and indels, and the first widely applicable tools for understanding how they impact protein evolution.

Keywords [en]
Natural Selection, Protein Evolution, Pair hidden Markov models
National Category
Evolutionary Biology
Identifiers
URN: urn:nbn:se:uu:diva-360838OAI: oai:DiVA.org:uu-360838DiVA, id: diva2:1249288
Available from: 2018-09-18 Created: 2018-09-18 Last updated: 2018-09-19
In thesis
1. Evolutionary Approaches to Sequence Alignment
Open this publication in new window or tab >>Evolutionary Approaches to Sequence Alignment
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Molecular evolutionary biology allows us to look into the past by analyzing sequences of amino acids or nucleotides. These analyses can be very complex, often involving advanced statistical models of sequence evolution to construct phylogenetic trees, study the patterns of natural selection and perform a number of other evolutionary studies. In many cases, these evolutionary studies require a prerequisite of multiple sequence alignment (MSA) - a technique, which aims at grouping the characters that share a common ancestor, or homology, into columns. This information regarding shared homology is needed by statistical models to describe the process of substitutions in order to perform evolutionary inference. Sequence alignment, however, is difficult and MSAs often contain whole regions of wrongly aligned characters, which impact downstream analyses.

In this thesis I use two broad groups of approaches to avoid errors in the alignment. The first group addresses the analysis methods without sequence alignment by explicitly modelling the processes of substitutions, and insertions and deletions (indels) between pairs of sequences using pair hidden Markov models. I describe an accurate tree inference method that uses a neighbor joining clustering approach to construct a tree from a matrix of model-based evolutionary distances.

Next, I develop a pairwise method of modelling how natural selection acts on substitutions and indels. I further show the relationship between the constraints acting on these two evolutionary forces to show that natural selection affects them in a similar way.

The second group of approaches deals with errors in existing alignments. I use a statistical model-based approach to evaluate the quality of multiple sequence alignments.

First, I provide a graph-based tool for removing wrongly aligned pairs of residues by splitting them apart. This approach tends to produce better results when compared to standard column-based filtering.

Second, I provide a way to compare MSAs using a probabilistic framework. I propose new ways of scoring of sequence alignments and show that popular methods produce similar results.

The overall purpose of this work is to facilitate more accurate evolutionary analyses by addressing the problem of sequence alignment in a statistically rigorous manner.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 57
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1723
Keywords
molecular evolution, multiple sequence alignment, pair hidden Markov models
National Category
Evolutionary Biology
Research subject
Biology with specialization in Evolutionary Genetics
Identifiers
urn:nbn:se:uu:diva-360871 (URN)978-91-513-0445-8 (ISBN)
Public defence
2018-11-09, Ekmansalen, EBC, Norrbyvägen 14, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-10-17 Created: 2018-09-19 Last updated: 2018-11-19

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