Current Biology· 2014Q1
Detecting Regular Sound Changes in Linguistics as Events of Concerted Evolution
- 528citations
- Q1SCImago
- 2014year
Short summary
A new statistical model detects over 70 historical regular sound changes in the Turkic language family, improving phylogenetic inference and yielding more reliable dates by accounting for concerted evolution.
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Key points
- Developed a statistical model to detect concerted evolutionary changes in sequence data.
- Identified over 70 historical regular sound change events in the Turkic language family.
- The model improved characterization of linguistic change by approximately 4-fold over simpler models.
- Inferred a dated phylogenetic tree with more reliable and plausible dates for evolutionary events.
AI-generated from the title and abstract; the full text is not read.
Abstract
BACKGROUND: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. RESULTS: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. CONCLUSIONS: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.
The authors' abstract, as published at the source. Current Biology, 2014 · DOI ↗
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Field: Cultural Studies
Cultural StudiesSocial Sciences