996 resultados para Multiple Traits


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Background The Arabidopsis FILAMENTOUS FLOWER (FIL) gene encodes a YABBY (YAB) family putative transcription factor that has been implicated in specifying abaxial cell identities and thus regulating organ polarity of lateral organs. In contrast to double mutants of fil and other YAB genes, fil single mutants display mainly floral and inflorescence morphological defects that do not reflect merely a loss of abaxial identity. Recently, FIL and other YABs have been shown to regulate meristem organization in a non-cell-autonomous manner. In a screen for new mutations affecting floral organ morphology and development, we have identified a novel allele of FIL, fil-9 and characterized its floral and meristem phenotypes. Results The fil-9 mutation results in highly variable disruptions in floral organ numbers and size, partial homeotic transformations, and in defective inflorescence organization. Examination of meristems indicates that both fil-9 inflorescence and floral meristems are enlarged as a result of an increase in cell number, and deformed. Furthermore, primordia emergence from these meristems is disrupted such that several primordia arise simultaneously instead of sequentially. Many of the organs produced by the inflorescence meristems are filamentous, yet they are not considered by the plant as flowers. The severity of both floral organs and meristem phenotypes is increased acropetally and in higher growth temperature. Conclusions Detailed analysis following the development of fil-9 inflorescence and flowers throughout flower development enabled the drawing of a causal link between multiple traits of fil-9 phenotypes. The study reinforces the suggested role of FIL in meristem organization. The loss of spatial and temporal organization of fil-9 inflorescence and floral meristems presumably leads to disrupted cell allocation to developing floral organs and to a blurring of organ whorl boundaries. This disruption is reflected in morphological and organ identity aberrations of fil-9 floral organs and in the production of filamentous organs that are not perceived as flowers. Here, we show the role of FIL in reproductive meristem development and emphasize the potential of using fil mutants to study mersitem organization and the related effects on flower morphogenesis.

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Heterosis is widely used in breeding, but the genetic basis of this biological phenomenon has not been elucidated. We postulate that additive and dominance genetic effects as well as two-locus interactions estimated in classical QTL analyses are not sufficient for quantifying the contributions of QTL to heterosis. A general theoretical framework for determining the contributions of different types of genetic effects to heterosis was developed. Additive x additive epistatic interactions of individual loci with the entire genetic background were identified as a major component of midparent heterosis. On the basis of these findings we defined a new type of heterotic effect denoted as augmented dominance effect di* that comprises the dominance effect at each QTL minus half the sum of additive x additive interactions with all other QTL. We demonstrate that genotypic expectations of QTL effects obtained from analyses with the design III using testcrosses of recombinant inbred lines and composite-interval mapping precisely equal genotypic expectations of midparent heterosis, thus identifying genomic regions relevant for expression of heterosis. The theory for QTL mapping of multiple traits is extended to the simultaneous mapping of newly defined genetic effects to improve the power of QTL detection and distinguish between dominance and overdominance.

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This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

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A major function of angiosperm flowers is the recruitment of animal pollinators that serve to transfer pollen among conspecific plants. Distinct sets of floral characteristics, called pollination syndromes, are correlated with visitation by specific groups of pollinators. Switches among pollination syndromes have occurred in many plant families. Such switches must have involved coordinated changes in multiple traits and multiple genes. Two well-studied floral traits affecting pollinator attraction are petal color and scent production. We review current knowledge about the biosynthetic pathways for floral color and scent production and their interaction at the genetic and biochemical levels. A key question in the field concerns the genes that underlie natural variation in color and scent and how such genes affect pollinator preference, reproductive isolation, and ultimately speciation.

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Main conclusion Switches between pollination syndromes have happened frequently during angiosperm evolution. Using QTL mapping and reciprocal introgressions, we show that changes in reproductive organ morphology have a simple genetic basis. In animal-pollinated plants, flowers have evolved to optimize pollination efficiency by different pollinator guilds and hence reproductive success. The two Petunia species, P. axillaris and P. exserta, display pollination syndromes adapted to moth or hummingbird pollination. For the floral traits color and scent, genetic loci of large phenotypic effect have been well documented. However, such large-effect loci may be typical for shifts in simple biochemical traits, whereas the evolution of morphological traits may involve multiple mutations of small phenotypic effect. Here, we performed a quantitative trait locus (QTL) analysis of floral morphology, followed by an in-depth study of pistil and stamen morphology and the introgression of individual QTL into reciprocal parental backgrounds. Two QTLs, on chromosomes II and V, are sufficient to explain the interspecific difference in pistil and stamen length. Since most of the difference in organ length is caused by differences in cell number, genes underlying these QTLs are likely to be involved in cell cycle regulation. Interestingly, conservation of the locus on chromosome II in a different P. axillaris subspecies suggests that the evolution of organ elongation was initiated on chromosome II in adaptation to different pollinators. We recently showed that QTLs for pistil and stamen length on chromosome II are tightly linked to QTLs for petal color and volatile emission. Linkage of multiple traits will enable major phenotypic change within a few generations in hybridizing populations. Thus, the genomic architecture of pollination syndromes in Petunia allows for rapid responses to changing pollinator availability.

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Measures of agro-ecosystems genetic variability are essential to sustain scientific-based actions and policies tending to protect the ecosystem services they provide. To build the genetic variability datum it is necessary to deal with a large number and different types of variables. Molecular marker data is highly dimensional by nature, and frequently additional types of information are obtained, as morphological and physiological traits. This way, genetic variability studies are usually associated with the measurement of several traits on each entity. Multivariate methods are aimed at finding proximities between entities characterized by multiple traits by summarizing information in few synthetic variables. In this work we discuss and illustrate several multivariate methods used for different purposes to build the datum of genetic variability. We include methods applied in studies for exploring the spatial structure of genetic variability and the association of genetic data to other sources of information. Multivariate techniques allow the pursuit of the genetic variability datum, as a unifying notion that merges concepts of type, abundance and distribution of variability at gene level.

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A eficiência econômica da bovinocultura leiteira está relacionada à utilização de animais que apresentem, concomitantemente, bom desempenho quanto à produção, reprodução, saúde e longevidade. Nisto, o índice de seleção configura-se como ferramenta importante ao aumento da lucratividade nesse sistema, visto que permite a seleção de reprodutores para várias características simultaneamente, considerando a relação entre elas bem como a relevância econômica das mesmas. Com a recente disponibilidade de dados genômicos tornou-se ainda possível expandir a abrangência e acurácia dos índices de seleção por meio do aumento do número e qualidade das informações consideradas. Nesse contexto, dois estudos foram desenvolvidos. No primeiro, o objetivo foi estimar parâmetros genéticos e valores genéticos (VG) para características relacionadas à produção e qualidade do leite incluindo-se a informação genômica na avaliação genética. Foram utilizadas medidas de idade ao primeiro parto (IPP), produção de leite (PROD), teor de gordura (GOR), proteína (PROT), lactose, caseína, escore de células somáticas (ECS) e perfil de ácidos graxos de 4.218 vacas bem como os genótipos de 755 vacas para 57.368 polimorfismos de nucleotídeo único (SNP). Os componentes de variância e VG foram obtidos por meio de um modelo misto animal, incluindo-se os efeitos de grupos de contemporâneas, ordem de lactação, dias em lactação e os efeitos aditivo genético, ambiente permanente e residual. Duas abordagens foram desenvolvidas: uma tradicional, na qual a matriz de relacionamentos é baseada no pedigree; e uma genômica, na qual esta matriz é construída combinando-se a informação de pedigree e dos SNP. As herdabilidades variaram de 0,07 a 0,39. As correlações genéticas entre PROD e os componentes do leite variaram entre -0,45 e -0,13 enquanto correlações altas e positivas foram estimadas entre GOR e os ácidos graxos. O uso da abordagem genômica não alterou as estimativas de parâmetros genéticos; contudo, houve aumento entre 1,5% e 6,8% na acurácia dos VG, à exceção de IPP, para a qual houve uma redução de 1,9%. No segundo estudo, o objetivo foi incorporar a informação genômica no desenvolvimento de índices econômicos de seleção. Neste, os VG para PROD, GOR, PROT, teor de ácidos graxos insaturados (INSAT), ECS e vida produtiva foram combinados em índices de seleção ponderados por valores econômicos estimados sob três cenários de pagamento: exclusivamente por volume de leite (PAG1); por volume e por componentes do leite (PAG2); por volume e componentes do leite incluindo INSAT (PAG3). Esses VG foram preditos a partir de fenótipos de 4.293 vacas e genótipos de 755 animais em um modelo multi-característica sob as abordagens tradicional e genômica. O uso da informação genômica influenciou os componentes de variância, VG e a resposta à seleção. Entretanto, as correlações de ranking entre as abordagens foram altas nos três cenários, com valores entre 0,91 e 0,99. Diferenças foram principalmente observadas entre PAG1 e os demais cenários, com correlações entre 0,67 e 0,88. A importância relativa das características e o perfil dos melhores animais foram sensíveis ao cenário de remuneração considerado. Assim, verificou-se como essencial a consideração dos valores econômicos das características na avaliação genética e decisões de seleção.

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La théorie biodémographique liée à l’âge prédit un compromis entre l’allocation reproductrice au début de la vie et la reproduction tardive, la survie, ou ces deux composantes de la valeur adaptative à la fois. Actuellement, la notion de compromis a été démontrée par plusieurs études en milieu naturel. Par contre, l’effet des conditions environnementales et de la qualité des individus a rarement été étudié. Grâce aux données longitudinales récoltées dans la population de chèvres de montagne (Oreamnos americanus) de Caw Ridge, Alberta, nous avons pu examiner l’influence de l’âge à la première reproduction (APR) et du succès reproducteur au début de la vie (SRD) sur la longévité et sur le succès reproducteur tardif, en tenant compte des conditions environnementales natales et de la qualité des individus. Contrairement à nos prédictions, nous n’avons pas détecté la présence d’un compromis entre l’allocation reproductrice au début de la vie et la performance tardive dans cette population. Au contraire, l’APR et le SRD avaient des effets directs et faiblement positifs sur le succès reproducteur tardif. La densité de population à la naissance d’une femelle a fortement réduit le succès reproducteur tardif de manière directe. Elle l’affectait également de manière indirecte par son effet sur l’APR et le SRD. La densité était le seul facteur déterminant de la longévité, par un effet direct et fortement négatif. Tel que démontré dans des études précédentes sur la même population, les femelles de bonne qualité avaient un SRD élevé par rapport aux femelles de mauvaise qualité. Ces résultats fournissent une vision intégrée des compromis au début et à la fin de la vie, en soulignant l’importance de tenir compte des conditions environnementales, qui pourraient engendrer des implications à long terme sur la dynamique des populations.

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Facial attractiveness is a particularly salient social cue that influences many important social outcomes. Using a standard key-press task to measure motivational salience of faces and an old/new memory task to measure memory for face photographs, this thesis investigated both within-woman and between-women variations in response to facial attractiveness. The results indicated that within-woman variables, such as fluctuations in hormone levels, influenced the motivational salience of facial attractiveness. However, the between-women variable, romantic relationship status, did not appear to modulate women’s responses to facial attractiveness. In addition to attractiveness, dominance also contributed to both the motivational salience and memorability of faces. This latter result demonstrates that, although attractiveness is an important factor for the motivational salience of faces, other factors might also cause faces to hold motivational salience. In Chapter 2, I investigated the possible effects of women’s salivary hormone levels (estradiol, progesterone, testosterone, and estradiol-to-progesterone ratio) on the motivational salience of facial attractiveness. Physically attractive faces generally hold greater motivational salience, replicating results from previous studies. Importantly, however, the effect of attractiveness on the motivational salience of faces was greater in test sessions where women had high testosterone levels. Additionally, the motivational salience of attractive female faces was greater in test sessions where women had high estradiol-to-progesterone ratios. While results from Chapter 2 suggested that the motivational salience of faces was generally positively correlated with their physical attractiveness, Chapter 3 explored whether physical characteristics other than attractiveness contributed to the motivational salience of faces. To address this issue, I first had the faces rated on multiple traits. Principal component analysis of third-party ratings of faces for these traits revealed two orthogonal components that were highly correlated with trustworthiness and dominance ratings respectively. Both components were positively and independently related to the motivational salience of faces. While Chapter 2 and 3 did not examine the between-woman differences in response to facial attractiveness, Chapter 4 examined whether women’s responses to facial attractiveness differed as a function of their romantic partnership status. As several researchers have proposed that partnership status influences women’s perception of attractiveness, in Chapter 4 I compared the effects of men’s attractiveness on partnered and unpartnered women’s performance on two response measures: memory for face photographs and the motivational salience of faces. Consistent with previous research, women’s memory was poorer for face photographs of more attractive men and more attractive men’s faces held greater motivational salience. However, in neither study were the effects of attractiveness modulated by women’s partnership status or partnered women’s reported commitment to or happiness with their romantic relationship. A key result from Chapter 4 was that more attractive faces were harder to remember. Building on this result, Chapter 5 investigated the different characteristics that contributed to the memorability of face photographs. While some work emphasizes relationships with typicality, familiarity, and memorability ratings, more recent work suggests that ratings of social traits, such as attractiveness, intelligence, and responsibility, predict the memorability of face photographs independently of typicality, familiarity, and memorability ratings. However, what components underlie these traits remains unknown, as well as whether these components relate to the actual memorability of face photographs. Principal component analysis of all these face ratings produced three orthogonal components that were highly correlated with trustworthiness, dominance, and memorability ratings, respectively. Importantly, each of these components also predicted the actual memorability of face photographs.

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Ornamental colours usually evolve as honest signals of quality, which is supported by the fact that they frequently depend on individual condition. It has generally been suggested that some, but not all types of ornamental colours are condition dependent, indicating that different evolutionary mechanisms underlie the evolution of multiple types of ornamental colours even when these are exhibited by the same species. Stress hormones, which negatively affect condition, have been shown to affect colour traits based on different pigments and structures, suggesting that they mediate condition dependence of multiple ornament types both among and within individuals. However, studies investigating effects of stress hormones on different ornament types within individuals are lacking, and thus, evidence for this hypothesis is scant. Here, we investigated whether corticosterone mediates condition dependence of multiple ornaments by manipulating corticosterone levels and body condition (via food availability) using a two-factorial design and by assessing their effect on multiple colour traits in male common lizards. Corticosterone negatively affected ventral melanin- and carotenoid-based coloration, whereas food availability did not affect coloration, despite its significant effect on body condition. The corticosterone effect on melanin- and carotenoid-based coloration demonstrates the condition dependence of both ornaments. Moreover, corticosterone affected ventral coloration and had no effect on the nonsexually selected dorsal coloration, showing specific effects of corticosterone on ornamental ventral colours. This suggests that corticosterone simultaneously mediates condition dependence of multiple colour traits and that it therefore accounts for covariation among them, which may influence their evolution via correlational selection.

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Background: Prolificacy is the most important trait influencing the reproductive efficiency of pig production systems. The low heritability and sex-limited expression of prolificacy have hindered to some extent the improvement of this trait through artificial selection. Moreover, the relative contributions of additive, dominant and epistatic QTL to the genetic variance of pig prolificacy remain to be defined. In this work, we have undertaken this issue by performing one-dimensional and bi-dimensional genome scans for number of piglets born alive (NBA) and total number of piglets born (TNB) in a three generation Iberian by Meishan F2 intercross. Results: The one-dimensional genome scan for NBA and TNB revealed the existence of two genome-wide highly significant QTL located on SSC13 (P < 0.001) and SSC17 (P < 0.01) with effects on both traits. This relative paucity of significant results contrasted very strongly with the wide array of highly significant epistatic QTL that emerged in the bi-dimensional genome-wide scan analysis. As much as 18 epistatic QTL were found for NBA (four at P < 0.01 and five at P < 0.05) and TNB (three at P < 0.01 and six at P < 0.05), respectively. These epistatic QTL were distributed in multiple genomic regions, which covered 13 of the 18 pig autosomes, and they had small individual effects that ranged between 3 to 4% of the phenotypic variance. Different patterns of interactions (a × a, a × d, d × a and d × d) were found amongst the epistatic QTL pairs identified in the current work.Conclusions: The complex inheritance of prolificacy traits in pigs has been evidenced by identifying multiple additive (SSC13 and SSC17), dominant and epistatic QTL in an Iberian × Meishan F2 intercross. Our results demonstrate that a significant fraction of the phenotypic variance of swine prolificacy traits can be attributed to first-order gene-by-gene interactions emphasizing that the phenotypic effects of alleles might be strongly modulated by the genetic background where they segregate.

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Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

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Managing ecosystems to ensure the provision of multiple ecosystem services is a key challenge for applied ecology. Functional traits are receiving increasing attention as the main ecological attributes by which different organisms and biological communities influence ecosystem services through their effects on underlying ecosystem processes. Here we synthesize concepts and empirical evidence on linkages between functional traits and ecosystem services across different trophic levels. Most of the 247 studies reviewed considered plants and soil invertebrates, but quantitative trait–service associations have been documented for a range of organisms and ecosystems, illustrating the wide applicability of the trait approach. Within each trophic level, specific processes are affected by a combination of traits while particular key traits are simultaneously involved in the control of multiple processes. These multiple associations between traits and ecosystem processes can help to identify predictable trait–service clusters that depend on several trophic levels, such as clusters of traits of plants and soil organisms that underlie nutrient cycling, herbivory, and fodder and fibre production. We propose that the assessment of trait–service clusters will represent a crucial step in ecosystem service monitoring and in balancing the delivery of multiple, and sometimes conflicting, services in ecosystem management.

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The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

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Stabilizing selection has been predicted to change genetic variances and covariances so that the orientation of the genetic variance-covariance matrix (G) becomes aligned with the orientation of the fitness surface, but it is less clear how directional selection may change G. Here we develop statistical approaches to the comparison of G with vectors of linear and nonlinear selection. We apply these approaches to a set of male sexually selected cuticular hydrocarbons (CHCs) of Drosophila serrata. Even though male CHCs displayed substantial additive genetic variance, more than 99% of the genetic variance was orientated 74.9degrees away from the vector of linear sexual selection, suggesting that open-ended female preferences may greatly reduce genetic variation in male display traits. Although the orientation of G and the fitness surface were found to differ significantly, the similarity present in eigenstructure was a consequence of traits under weak linear selection and strong nonlinear ( convex) selection. Associating the eigenstructure of G with vectors of linear and nonlinear selection may provide a way of determining what long-term changes in G may be generated by the processes of natural and sexual selection.