Fluctuating Asymmetry: Methods, Theory, and Applications

Graham, John H.; Raz, Shmuel; Hel‐Or, Hagit; Nevo, Eviatar

doi:10.3390/sym2020466

Cited by 329 publications

(388 citation statements)

References 335 publications

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“…Developmental instability (DI) results when stress affects the buffering capacity of the processes that provide stability to an organism's development [5]. The theoretical argument that stressed individuals have greater DI is supported by some research showing a positive relationship between DI and the intensity of stress [4,[6][7][8][9][10][11][12]. However, empirical studies supporting its general adequacy for monitoring species or populations are generally lacking or contradictory [4,[13][14][15][16].…”

Section: Developmental Instabilitymentioning

confidence: 99%

“…Some studies use variances of morphological characters or phenotypic variance (σ 2 p) [12,[16][17][18], where the estimate may be blurred by genetic variation (σ 2 g), while other studies use fluctuating asymmetry (FA) [1,4,7].…”

Section: Developmental Instabilitymentioning

confidence: 99%

“…It is believed that an individual's ability to buffer its development against these random perturbations is influenced by genotype, environment and/or genotype-environment interactions [1][2][3][4]. Developmental instability (DI) results when stress affects the buffering capacity of the processes that provide stability to an organism's development [5].…”

Section: Developmental Instabilitymentioning

confidence: 99%

See 2 more Smart Citations

A New Fluctuating Asymmetry Index, or the Solution for the Scaling Effect?

Pertoldi

Kristensen

2015

Symmetry

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Two principal methods are commonly employed for the estimation of developmental instability at the population level. Some studies use variances of morphological traits (σ 2 p), while others use fluctuating asymmetry (FA). In both cases, differences in the degree of developmental instability can be tested with an F-test, which is the most common way to compare variances. However, the variance is expected to scale proportionally to the square of the mean as there is a tendency in biological data for σ 2 p to scale proportionally to the square of the mean ( μ ): σ 2 p = Zμ ξ , where ξ is the scaling exponent, which is expected to be two for pure statistical reasons, μ is the mean of the trait and Z is a measure of individual-level variability. Because of this scaling effect, the fluctuating asymmetry will be affected, FA is estimated as the variance between the right and the left sides of a trait (σ 2 r − l = σ 2 r + σ 2 l − 2rσrσl), where σ 2 r and σ 2 l are the variances of the right and the left trait values, respectively. In this paper, we propose a novel method that allows an exact correction of the scaling effect, which will enable a proper comparison of the degree of fluctuating asymmetry for a trait. The problem of the scaling of the FA with the trait size is quite crucial if FA is to be considered an indicator of fitness or an indicator of environmental or genetic stress, as different stresses or fitness levels are typically accompanied by a change of the traits' μ .

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Section: Developmental Instabilitymentioning

confidence: 99%

Section: Developmental Instabilitymentioning

confidence: 99%

Section: Developmental Instabilitymentioning

confidence: 99%

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A New Fluctuating Asymmetry Index, or the Solution for the Scaling Effect?

Pertoldi

Kristensen

2015

Symmetry

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show abstract

“…The NNA ↔ NNG mirror leaves the standard code invariant for 28 out of the 32 permuted codons and is thus a near symmetry of the standard code, but an exact symmetry of the mitochondrial codes comprising two Met and two Trp codons [33,34]. (Exact symmetries are exceedingly rare, but near symmetries are common in biology [35]. For example, the left and right hand of the same individual are nearly symmetric: they are mirror images, but not mathematically or physically perfect mirror images.)…”

Section: Exact and Near Symmetries Of The Codementioning

confidence: 99%

The Graph, Geometry and Symmetries of the Genetic Code with Hamming Metric

Lenstra¹

2015

Symmetry

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Abstract:The similarity patterns of the genetic code result from similar codons encoding similar messages. We develop a new mathematical model to analyze these patterns. The physicochemical characteristics of amino acids objectively quantify their differences and similarities; the Hamming metric does the same for the 64 codons of the codon set. (Hamming distances equal the number of different codon positions: AAA and AAC are at 1-distance; codons are maximally at 3-distance.) The CodonPolytope, a 9-dimensional geometric object, is spanned by 64 vertices that represent the codons and the Euclidian distances between these vertices correspond one-to-one with intercodon Hamming distances. The CodonGraph represents the vertices and edges of the polytope; each edge equals a Hamming 1-distance. The mirror reflection symmetry group of the polytope is isomorphic to the largest permutation symmetry group of the codon set that preserves Hamming distances. These groups contain 82,944 symmetries. Many polytope symmetries coincide with the degeneracy and similarity patterns of the genetic code. These code symmetries are strongly related with the face structure of the polytope with smaller faces displaying stronger code symmetries. Splitting the polytope stepwise into smaller faces models an early evolution of the code that generates this hierarchy of code symmetries. The canonical code represents a class of 41,472 codes with equivalent symmetries; a single class among an astronomical number of symmetry classes comprising all possible codes.

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“…Palmer and Strobeck [2], [3] termed these deviations as 'developmental noise' which are environmentally or epigenetically induced stresses. Unlike the other types of (AS), fluctuating asymmetry (FA) have long been viewed as a measure of developmental instability [4] due to environmental stress [5]- [8], adaptation and coadaptation [9] and fitness or individual quality [10], [11]. There are several methods available in computing asymmetries.…”

mentioning

confidence: 99%

Asymmetry Analysis of Brontispa longissima Gestro, 1885 (Coleoptera: Chrysomelidae) Metasternum Using Symmetry and Asymmetry on Geometric Data (SAGE)

Genotiva¹,

Tabugo²,

Manting³

et al. 2014

IJBBB

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Abstract-Variations in the patterns of asymmetry in coconut leaf beetle Brontispa longissima metasternum from ten (10) populations in Northern Mindanao, Philippines were evaluated using the landmark-based advanced geometric morphometrics Symmetry and Asymmetry in Geometric Data (SAGE) version 1.04 tool. Coconut leaf beetle has been infesting the country. However, primary information to the pest's ability to develop traits efficiently is still to be investigated. B. longissima metasternum was digitized and analyzed using Procrustes Analysis of Variance (ANOVA). Results have shown absence of fluctuating asymmetry between sexes and locations. Conversely, directional asymmetry and individual shape variation is evident for male and female samples in all sites. IndexTerms-Brontispa longissima, asymmetry, metasternum, procrustes ANOVA.

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Fluctuating Asymmetry: Methods, Theory, and Applications

Cited by 329 publications

References 335 publications

A New Fluctuating Asymmetry Index, or the Solution for the Scaling Effect?

A New Fluctuating Asymmetry Index, or the Solution for the Scaling Effect?

The Graph, Geometry and Symmetries of the Genetic Code with Hamming Metric

Asymmetry Analysis of Brontispa longissima Gestro, 1885 (Coleoptera: Chrysomelidae) Metasternum Using Symmetry and Asymmetry on Geometric Data (SAGE)

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