Genetic and environmental heterogeneity of residual variance of weight traits in Nellore beef cattle

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

Mitochondrial DNA sequence analysis from multiple gene fragments reveals genetic heterogeneity of Crassostrea ariakensis in East Asia

The native Asian oyster, Crassostrea ariakensis is one of the most common and important Crassostrea species that occur naturally along the coast of East Asia. Molecular species diagnosis is a prerequisite for population genetic analysis of wild oyster populations because oyster species cannot be discriminated reliably using external morphological characters alone due to character ambiguity. To date there have been few phylogeographic studies of natural edible oyster populations in East Asia, in particular this is true of the common species in Korea C. ariakensis. We therefore assessed the levels and patterns of molecular genetic variation in East Asian wild populations of C. ariakensis from Korea, Japan, and China using DNA sequence analysis of five concatenated mtDNA regions namely; 16S rRNA, cytochrome oxidase I, cytochrome oxidase II, cytochrome oxidase III, and cytochrome b. Two divergent C. ariakensis clades were identified between southern China and remaining sites from the northern region. In addition, hierarchical AMOVA and pairwise UST analyses showed that genetic diversity was discontinuous among wild populations of C. ariakensis in East Asia. Biogeographical and historical sea level changes are discussed as potential factors that may have influenced the genetic heterogeneity of wild C. ariakensis stocks across this region.

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar)

BACKGROUND: Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. RESULTS: Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. CONCLUSIONS: Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.

Effects of environmental variation on ecological and evolutionary dynamics

Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

Molecular screening of ADAMTSL2 gene in 33 patients reveals the genetic heterogeneity of geleophysic dysplasia.

Background Geleophysic dysplasia (GD, OMIM 231050) is an autosomal recessive disorder characterised by short stature, small hands and feet, stiff joints, and thick skin. Patients often present with a progressive cardiac valvular disease which can lead to an early death. In a previous study including six GD families, we have mapped the disease gene on chromosome 9q34.2 and identified mutations in the A Disintegrin And Metalloproteinase with Thrombospondin repeats-like 2 gene (ADAMTSL2). Methods Following this study, we have collected the samples of 30 additional GD families, including 33 patients and identified ADAMTSL2 mutations in 14/33 patients, comprising 13 novel mutations. The absence of mutation in 19 patients prompted us to compare the two groups of GD patients, namely group 1, patients with ADAMTSL2 mutations (n=20, also including the 6 patients from our previous study), and group 2, patients without ADAMTSL2 mutations (n=19). Results The main discriminating features were facial dysmorphism and tip-toe walking, which were almost constantly observed in group 1. No differences were found concerning heart involvement, skin thickness, recurrent respiratory and ear infections, bronchopulmonary insufficiency, laryngo-tracheal stenosis, deafness, and radiographic features. Conclusions It is concluded that GD is a genetically heterogeneous condition. Ongoing studies will hopefully lead to the identification of another disease gene.

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.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Genetic heterogeneity of Escherichia coli isolated from pasteurized milk in State of Paraná, Brazil

Food contamination caused by enteric pathogens is a major cause of diarrheal disease worldwide, resulting in high morbidity and mortality and significant economic losses. Bacteria are important agents of foodborne diseases, particularly diarrheagenic Escherichia coli. The present study assessed the genetic diversity and antimicrobial resistance of E. coli isolates from pasteurized milk processed in 21 dairies in northwestern State of Parana, Brazil. The 95 E. coli isolates were subjected to antimicrobial susceptibility testing according to the recommendations of the Clinical and Laboratory Standards Institute and assessed genotypically by Enterobacterial Repetitive Intergenic Consensus-Polymerase Chain Reaction (ERIC-PCR). The highest rate of resistance was observed for cephalothin (55.78%). ERIC-PCR revealed high genetic diversity, clustering the 95 bacterial isolates into 90 different genotypic patterns. These results showed a heterogeneous population of E. coli in milk samples produced in the northwestern region of Parana and the need for good manufacturing practices throughout the processing of pasteurized milk to reduce the risk of foodborne illnesses.

Genetic history of hepatitis C virus in Pakistan

Hepatitis C virus (HCV) genotype 3a accounts for similar to 80% of HCV infections in Pakistan, where similar to 10 million people are HCV-infected. Here, we report analysis of the genetic heterogeneity of HCV NS3 and NS5b subgenomic regions from genotype 3a variants obtained from Pakistan. Phylogenetic analyses showed that Pakistani genotype 3a variants were as genetically diverse as global variants, with extensive intermixing. Bayesian estimates showed that the most recent ancestor for genotype 3a in Pakistan was last extant in similar to 1896-1914 C.E. (range: 1851-1932). This genotype experienced a population expansion starting from similar to 1905 to similar to 1970 after which the effective population leveled. Death/birth models suggest that HCV 3a has reached saturating diversity with decreasing turnover rate and positive extinction. Taken together, these observations are consistent with a long and complex history of HCV 3a infection in Pakistan. Published by Elsevier B.V.

Characterizing Genetic Drivers of Lymphoma through High-Throughput Sequencing

The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution.

In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome.

In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma.

In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study.

In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.

Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.

Assessment of genetic diversity of zoonotic Brucella spp. recovered from livestock in Egypt using multiple locus VNTR analysis

Brucellosis is endemic in most parts of Egypt, where it is caused mainly by Brucella melitensis biovar 3, and affects cattle and small ruminants in spite of ongoing efforts devoted to its control. Knowledge of the predominant Brucella species/strains circulating in a region is a prerequisite of a brucellosis control strategy. For this reason a study aiming at the evaluation of the phenotypic and genetic heterogeneity of a panel of 17 Brucella spp. isolates recovered from domestic ruminants (cattle, buffalo, sheep, and goat) from four governorates during a period of five years (2002-2007) was carried out using microbiological tests and molecular biology techniques (PCR, MLVA-15, and sequencing). Thirteen strains were identified as B. melitensis biovar 3 while all phenotypic and genetic techniques classified the remaining isolates as B. abortus (n = 2) and B. suis biovar 1 (n = 2). MLVA-15 yielded a high discriminatory power (h = 0.801), indicating a high genetic diversity among the B. melitensis strains circulating among domestic ruminants in Egypt. This is the first report of the isolation of B. suis from cattle in Egypt which, coupled with the finding of B. abortus, suggests a potential role of livestock as reservoirs of several zoonotic Brucella species in the region.

Measurement of genetic and environmental variation in barley (Hordeum vulgare) grain hardness

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

Genetic determinants of clinical heterogeneity in sickle cell disease

L’anémie falciforme est une maladie monogénique causée par une mutation dans le locus de la β-globine. Malgré le fait que l’anémie falciforme soit une maladie monogénique, cette maladie présente une grande hétérogénéité clinique. On présume que des facteurs environnementaux et génétiques contribuent à cette hétérogénéité. Il a été observé qu’un haut taux d’hémoglobine fœtale (HbF) diminuait la sévérité et la mortalité des patients atteints de l’anémie falciforme. Le but de mon projet était d’identifier des variations génétiques modifiant la sévérité clinique de l’anémie falciforme. Dans un premier temps, nous avons effectué la cartographie-fine de trois régions précédemment associées avec le taux d’hémoglobine fœtale. Nous avons ensuite effectué des études d’association pan-génomiques avec deux complications cliniques de l’anémie falciforme ainsi qu’avec le taux d’hémoglobine fœtale. Hormis les régions déjà identifiées comme étant associées au taux d’hémoglobine fœtale, aucun locus n’a atteint le niveau significatif de la puce de génotypage. Pour identifier des groupes de gènes modérément associés au taux d’hémoglobine fœtale qui seraient impliqués dans de mêmes voies biologiques, nous avons effectué une étude des processus biologiques. Finalement, nous avons effectué l’analyse de 19 exomes de patients Jamaïcains ayant des complications cliniques mineures de l’anémie falciforme. Compte tenu de la taille des cohortes de réplication disponibles, nous n’avons pas les moyens de valider statistiquement les variations identifiées par notre étude. Cependant, nos résultats fournissent de bons gènes candidats pour des études fonctionnelles et pour les réplications futures. Nos résultats suggèrent aussi que le β-hydroxybutyrate en concentration endogène pourraient influencer le taux d’hémoglobine fœtale. De plus, nous montrons que la cartographie-fine des régions associées par des études pan-génomiques peut identifier des signaux d’association additionnels et augmenter la variation héritable expliquée par cette région.

Genetic composition, genetic diversity, and small-scale environmental variation matter for the experimental reintroduction of a rare plant

Aims Reintroduction has become an important tool for the management of endangered plant species. We tested the little-explored effects of small-scale environmental variation, genotypic composition (i.e. identity of genotypes), and genotypic diversity on the population survival of the regionally rare clonal plant Ranunculus reptans. For this species of periodically inundated lakeshores genetic differentiation had been reported between populations and between short-flooded and long-flooded microsites within populations.Methods We established 306 experimental test populations at a previously unoccupied lake shore, comprising either monocultures of 32 genotypes, mixtures of genotypes within populations or mixtures of genotypes between populations. In 2000, three years after planting out at the experimental site, a long-lasting flood caused the death of half of the experimental populations. In 2003, an extreme drought resulted in the lowest summer water levels ever measured.Important findings Despite these climatic extremes, 27 of the established populations survived until the end of the experiment in December 2003. The success of experimental populations largely differed between microsites. Moreover, the success of genotype monocultures depended on genotype and source population. Genetic differentiation between microsites played a minor role for the success of reintroduction. After the flood, populations planted with genotypes from different source populations increased in abundance, whereas populations with genotypes from single source populations and genotype monocultures decreased. We conclude that sources for reintroductions need to be selected carefully. Moreover, mixtures of plants from different populations appear to be the best choice for successful reintroduction, at least in unpredictably varying environments.