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      Development shapes the evolutionary diversification of rodent stripe patterns

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          Significance

          How and why did diverse animal color patterns evolve? Explanations for pattern diversification typically emphasize the ecological forces that select for color patterns (e.g., camouflage or sexual selection). However, pattern diversification may also critically depend on the developmental mechanisms that provide the substrate for pattern evolution. Here, drawing on empirical advances, we explore theoretically how development shapes rodent pattern diversification. We show that pattern diversification can indeed be partly explained by underlying developmental mechanisms. Specifically, development can both facilitate and constrain pattern evolution by enabling evolutionary changes in stripe number while limiting changes in stripe positioning. Thus, by integrating developmental data, models of pattern formation, and empirical data on pattern diversity, our work helps bridge the gap between pattern evolution and pattern development.

          Abstract

          Vertebrate groups have evolved strikingly diverse color patterns. However, it remains unknown to what extent the diversification of such patterns has been shaped by the proximate, developmental mechanisms that regulate their formation. While these developmental mechanisms have long been inaccessible empirically, here we take advantage of recent insights into rodent pattern formation to investigate the role of development in shaping pattern diversification across rodents. Based on a broad survey of museum specimens, we first establish that various rodents have independently evolved diverse patterns consisting of longitudinal stripes, varying across species in number, color, and relative positioning. We then interrogate this diversity using a simple model that incorporates recent molecular and developmental insights into stripe formation in African striped mice. Our results suggest that, on the one hand, development has facilitated pattern diversification: The diversity of patterns seen across species can be generated by a single developmental process, and small changes in this process suffice to recapitulate observed evolutionary changes in pattern organization. On the other hand, development has constrained diversification: Constraints on stripe positioning limit the scope of evolvable patterns, and although pattern organization appears at first glance phylogenetically unconstrained, development turns out to impose a cryptic constraint. Altogether, this work reveals that pattern diversification in rodents can in part be explained by the underlying development and illustrates how pattern formation models can be leveraged to interpret pattern evolution.

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          phytools: an R package for phylogenetic comparative biology (and other things)

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            The Chemical Basis of Morphogenesis

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              TESTING FOR PHYLOGENETIC SIGNAL IN COMPARATIVE DATA: BEHAVIORAL TRAITS ARE MORE LABILE

              The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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                Author and article information

                Contributors
                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                23 October 2023
                7 November 2023
                23 April 2024
                : 120
                : 45
                : e2312077120
                Affiliations
                [1] aDepartment of Ecology and Evolutionary Biology, Princeton University , Princeton, NJ 08544
                [2] bCenter for Computational Biology, Flatiron Institute , New York, NY 10010
                [3] cDepartment of Molecular Biology, Princeton University , Princeton, NJ 08544
                Author notes
                1To whom correspondence may be addressed. Email: mstaps@ 123456princeton.edu or rmallarino@ 123456princeton.edu .

                Edited by Clifford Tabin, Harvard Medical School, Boston, MA; received July 15, 2023; accepted September 13, 2023

                2C.E.T. and R.M. contributed equally to this work.

                Author information
                https://orcid.org/0000-0003-4476-0012
                Article
                202312077
                10.1073/pnas.2312077120
                10636316
                37871159
                221aece3-302b-48b9-8335-3acf63c826dc
                Copyright © 2023 the Author(s). Published by PNAS.

                This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 15 July 2023
                : 13 September 2023
                Page count
                Pages: 10, Words: 8788
                Funding
                Funded by: HHS | NIH | National Institute of General Medical Sciences (NIGMS), FundRef 100000057;
                Award ID: R35GM133758
                Award Recipient : Ricardo Mallarino
                Funded by: Gordon and Betty Moore Foundation (GBMF), FundRef 100000936;
                Award ID: 7800
                Award Recipient : Corina E Tarnita
                Categories
                research-article, Research Article
                evolution, Evolution
                418
                Biological Sciences
                Evolution

                color patterns,pattern development,pattern evolution,developmental constraints,self-organization

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