Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design

Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables.

Evidence of a genetic bottleneck in an El Nino affected population of South American fur seals, Arctocephalus australis

The South American fur seal, Arctocephalus australis, was one of the earliest otariid seals to be exploited by humans: at least 6000 years ago on the Atlantic coast and 4000 on the Pacific coast of South America. More than 750,000 fur seals were killed in Uruguay until 1991. However, a climatological phenomenon-the severe 1997-1998 El Nino Southern Oscillation (ENSO)-was responsible for the decline of 72% Of the Peruvian fur seal population due to starvation as a consequence of warming of sea-surface temperatures and primary productivity reduction. Currently, there is no precise information on global population size or on the species` conservation status. The present study includes the first bottleneck test for the Pacific and Atlantic populations of A. australis based on the analysis of seven microsatellite loci. Genetic bottleneck compromises the evolutionary potential of a population to respond to environmental changes. The perspective becomes even more alarming due to current global warming models that predict stronger and more frequent ENSO events in the future. Our analysis found moderate support for deviation from neutrality-equilibrium for the Pacific population of fur seals and none for the Atlantic population. This difference among population reflects different demographic histories, and is consistent with a greater reduction in population size in the Pacific. Such an event could be a result of the synergic effects of recurrent ENSO events and the anthropogenic impact (sealing and prey overfishing) on this population.

Package models and the information crisis of prebiotic evolution

The coexistence between different types of templates has been the choice solution to the information crisis of prebiotic evolution, triggered by the finding that a single RNA-like template cannot carry enough information to code for any useful replicase. In principle, confining d distinct templates of length L in a package or protocell, whose Survival depends on the coexistence of the templates it holds in, could resolve this crisis provided that d is made sufficiently large. Here we review the prototypical package model of Niesert et al. [1981. Origin of life between Scylla and Charybdis. J. Mol. Evol. 17, 348-353] which guarantees the greatest possible region of viability of the protocell population, and show that this model, and hence the entire package approach, does not resolve the information crisis. In particular, we show that the total information stored in a viable protocell (Ld) tends to a constant value that depends only on the spontaneous error rate per nucleotide of the template replication mechanism. As a result, an increase of d must be followed by a decrease of L, so that the net information gain is null. (C) 2008 Elsevier Ltd. All rights reserved.

Symmetry in biology: from genetic code to stochastic gene regulation

Mathematical models, as instruments for understanding the workings of nature, are a traditional tool of physics, but they also play an ever increasing role in biology - in the description of fundamental processes as well as that of complex systems. In this review, the authors discuss two examples of the application of group theoretical methods, which constitute the mathematical discipline for a quantitative description of the idea of symmetry, to genetics. The first one appears, in the form of a pseudo-orthogonal (Lorentz like) symmetry, in the stochastic modelling of what may be regarded as the simplest possible example of a genetic network and, hopefully, a building block for more complicated ones: a single self-interacting or externally regulated gene with only two possible states: ` on` and ` off`. The second is the algebraic approach to the evolution of the genetic code, according to which the current code results from a dynamical symmetry breaking process, starting out from an initial state of complete symmetry and ending in the presently observed final state of low symmetry. In both cases, symmetry plays a decisive role: in the first, it is a characteristic feature of the dynamics of the gene switch and its decay to equilibrium, whereas in the second, it provides the guidelines for the evolution of the coding rules.

Genetic Heteroscedasticity for Domestic Animal Traits

Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean. The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows. The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased. For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Estimates of genetic parameters for visual scores and daily weight gain in Brangus animals

(Co) variance components were estimated for visual scores of conformation (CY), early finishing (PY) and muscling (MY) at 550 days of age (yearling), average daily gain from weaning to yearling (GWY), conformation (CW), early finishing (PW) and muscling (MW) scores at weaning, and average daily gain from birth to weaning (GBW) in animals forming the Brazilian Brangus breed born between 1986 and 2002 from the livestock files of GenSys Consultants Associados S/C Ltda. The data set contained 53 683; 45 136; 52 937; 56 471; 24 531; 21 166; 24 006 and 25 419 records for CW, PW, MW, GBW, CY, PY, MY and GWY, respectively. Data were analyzed by the restricted maximum likelihood method using single-and two-trait animal models. Direct heritability estimates obtained by single-trait analysis were 0.12, 0.14, 0.13 and 0.14 for CY, PY and MY scores and GWY, respectively. A positive association was observed between the same visual scores at weaning and yearling, with correlations ranging from 0.64 to 0.94. Estimated correlations between GBW and weaning and yearling scores ranged from 0.60 to 0.77. The genetic correlation between GBW and GWY was low (0.10), whereas correlations of 0.55, 0.37 and 0.47 were observed between GWY and CY, PY and MY, respectively. Moreover, GWY showed a weak correlation with CW (0.10), PW (-0.08) and MW (-0.03) scores. These results indicate that selection of the traits that was studied would result in a small response. In addition, selection based on average daily gain may have an indirect effect on visual scores as the correlations between GWY and visual scores were generally strong.

Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens

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

Genetic associations between age at first calving and heifer body weight and scrotal circumference in Nelore cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

Estimates of genetic correlations between days to calving and reproductive and weight traits in Nelore cattle

Data comprising 53,181 calving records were analyzed to estimate the genetic correlation between days to calving (DC), and days to first calving (DFC), and the following traits: scrotal circumference (SC), age at first calving (AFC), and weight adjusted for 550 d of age (W550) in a Nelore herd. (Co)variance components were estimated using the REML method fitting bivariate animal models. The fixed effects considered for DC were contemporary group, month of last calving, and age at breeding season (linear and quadratic effects). Contemporary groups were composed by herd, year, season, and management group at birth; herd and management group at weaning; herd, season, and management group at mating; and sex of calf and mating type (multiple sires, single sire, or AI). In DFC analysis, the same fixed effects were considered excluding the month of last calving. For DC, a repeatability animal model was applied. Noncalvers were not considered in analyses because an attempt to include them, attributing a penalty, did not improve the identification of genetic differences between animals. Heritability estimates ranged from 0.04 to 0.06 for DC, from 0.06 to 0.13 for DFC, from 0.42 to 0.44 for SC, from 0.06 to 0.08 for AFC, and was 0.30 for W550. The genetic correlation estimated between DC and SC was low and negative (-0.10), between DC and AFC was high and positive (0.76), and between DC and W550 was almost null (0.07). Similar results were found for genetic correlation estimates between DFC and SC (-0.14), AFC (0.94), and W550 (-0.02). The genetic correlation estimates indicate that the use of DC in the selection of beef cattle may promote favorable correlated responses to age at first mating and, consequently, higher gains in sexual precocity can be expected.

Genetic parameters for milk yield of Bubalus bubalis using unadjusted and adjusted milk production for days in milk.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

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