Genome-wide association mapping in a wild avian population identifies a link between genetic and phenotypic variation in a life-history trait

Understanding the genetic basis of traits involved in adaptation is a major challenge in evolutionary biology but remains poorly understood. Here, we use genome-wide association mapping using a custom 50 k single nucleotide polymorphism (SNP) array in a natural population of collared flycatchers to examine the genetic basis of clutch size, an important life-history trait in many animal species. We found evidence for an association on chromosome 18 where one SNP significant at the genome-wide level explained 3.9% of the phenotypic variance. We also detected two suggestive quantitative trait loci (QTLs) on chromosomes 9 and 26. Fitness differences among genotypes were generally weak and not significant, although there was some indication of a sex-by-genotype interaction for lifetime reproductive success at the suggestive QTL on chromosome 26. This implies that sexual antagonism may play a role in maintaining genetic variation at this QTL. Our findings provide candidate regions for a classic avian life-history trait that will be useful for future studies examining the molecular and cellular function of, as well as evolutionary mechanisms operating at, these loci.

Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability

A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

On the positive correlation between income inequality and unemployment

Several empirical studies in the literature have documented the existence of a positive correlation between income inequalitiy and unemployment. I provide a theoretical framework under which this correlation can be better understood. The analysis is based on a dynamic job search under uncertainty. I start by proving the uniqueness of a stationary distribution of wages in the economy. Drawing upon this distribution, I provide a general expression for the Gini coefficient of income inequality. The expression has the advantage of not requiring a particular specification of the distribution of wage offers. Next, I show how the Gini coefficient varies as a function of the parameters of the model, and how it can be expected to be positively correlated with the rate of unemployment. Two examples are offered. The first, of a technical nature, to show that the convergence of the measures implied by the underlying Markov process can fail in some cases. The second, to provide a quantitative assessment of the model and of the mechanism linking unemployment and inequality.

A search-theoretic explanation for the negative correlation between labor income and impatience

Lawrance (1991) has shown, through the estimation of consumption Euler equations, that subjective rates of impatience (time preference) in the U.S. are three to Öve percentage points higher for households with lower average labor incomes than for those with higher labor income. From a theoretical perspective, the sign of this correlation in a job-search model seems at Örst to be undetermined, since more impatient workers tend to accept wage o§ers that less impatient workers would not, thereby remaining less time unemployed. The main result of this paper is showing that, regardless of the existence of e§ects of opposite sign, and independently of the particular speciÖcations of the givens of the model, less impatient workers always end up, in the long run, with a higher average income. The result is based on the (unique) invariant Markov distribution of wages associated with the dynamic optimization problem solved by the consumers. An example is provided to illustrate the method.

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Speculative bubbles and contagion: analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model

Revendo a definição e determinação de bolhas especulativas no contexto de contágio, este estudo analisa a bolha do DotCom nos mercados acionistas americanos e europeus usando o modelo de correlação condicional dinâmica (DCC) proposto por Engle e Sheppard (2001) como uma explicação econométrica e, por outro lado, as finanças comportamentais como uma explicação psicológica. Contágio é definido, neste contexto, como a quebra estatística nos DCC’s estimados, medidos através das alterações das suas médias e medianas. Surpreendentemente, o contágio é menor durante bolhas de preços, sendo que o resultado principal indica a presença de contágio entre os diferentes índices dos dois continentes e demonstra a presença de alterações estruturais durante a crise financeira.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

Estimates of genetic parameters for visual scores and their correlation with production and reproductive traits in Brahman cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Correlações genéticas e fenotípicas em duas populações de milho (Zea mays L.) braquítico e suas implicações no melhoramento do teor de óleo no grão

Coeficientes de correlações genéticas e fenotípicas foram estimados entre os caracteres: altura da planta (AP); altura da espiga (AE); peso de espigas (PE) e teor de óleo (TO). As estimativas foram obtidas para duas populações braquíticas de milho (Piranão VD-2 e Piranão VF-1), baseado em espiga por fileira, utilizando-se testemunha intercalar, onde a cada duas progênies plantava-se uma fileira do híbrido simples AG 305-B. Os valores das correlações genéticas aditivas encontradas entre os caracteres altura da planta, altura da espiga e peso de espigas, foram todos positivos. Para o caráter teor de óleo, quando correlacionado com os demais caracteres, os valores das correlações obtidos foram negativos nas duas populações, exceção feita ao peso de espiga correlacionada com teor de óleo, na população Piranão VD-2, cujo valor foi positivo e próximo de zero. As respostas correlacionadas obtidas entre os caracteres, quando a seleção é praticada para o caráter teor de óleo e vice versa, independente do método de seleção empregado, mostram que a seleção para teor de óleo leva a modificação na estrutura da planta, para as duas populações.

Parâmetros Genéticos para a Produção de Leite, Gordura e Proteína em Bubalinos

The objective of this study was to estimate the genetic parameters affecting milk production (MP), fat (%F) and protein (%P) contents of buffalo milk. Restricted Maximum Likelihood (REML) using MTDFREML program under animal model analyzed a total of 1744 lactations records from 1268 cows. The means were: MP = 1259.47 +/- 523.09 kg, %F = 6.87 +/- 0.88% and %P = 3.91 +/- 0.61%. The estimates of repeatability and heritability coefficients were: MP = 0.38 and 0.24, %F = 0.28 and 0.21 and %P = 0.30 and 0.26, respectively. The estimated genetic and phenotypic correlations were MP x %F = -0.18 and -0.62, MP x %P = -0.23 and -0.59 and %F x %P = 0.50 and 0.77, respectively. According to these results it is possible to conclude that selection is a proper way to increase milk yield, fat and protein percentage. Although negative low values of genetic correlations among traits, it should be take into account that simultaneous selection based on these traits could not be so efficient.

Variabilidade fenotípica em genótipos de acerola

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)