Littérature scientifique sur le sujet « Non-Additive genetic effects »

Abstract Non-additive genetic effects may have important roles in the phenotypic expression of performance and adaptation traits in livestock. Therefore, we aimed to evaluate the inclusion of non-additive genetic effects in genomic prediction models and variance component estimation of performance traits in a purebred pig population and heat tolerance indicators in a crossbred pig population. The first dataset consisted of 3,534 individuals with genotypes for 52,843 SNPs and five pre-adjusted phenotypes from a public database of a purebred pig line. Twelve models fitting or not dominance and/or epistasis effects (additive-by-additive, additive-by-dominance, and dominance-by-dominance) and inbreeding were used to estimate variance components. Prediction ability was assessed based on 10-fold cross-validation and the bias, dispersion, and accuracy estimates were computed based on the LR method. We also evaluated the impact of including non-additive genetic effects on the ranking of the animals’ breeding value and in the proportion of commonly selected individuals. The second dataset consisted of records from 1,645 lactating sows (Large White x Landrace cross) genotyped for 50,703 SNPs and traits related to heat stress response: skin temperature (ear, shoulder, rump, and tail), vaginal temperature measured every 10 minutes, and the average of the six records per hour corresponding to 08:00, 12:00, 16:00, and 20:00 hours during four days; respiration rate, panting score (PS; score scale from 0 to 3), and hair density (HD, score scale from 0 to 2). Four models including or not, inbreeding and the effect of dominance and additive-by-additive epistasis were used to estimate variance components. There was no effect on residual variance estimates due to the inclusion of non-additive genetic effects in the models for most traits. However, non-additive genetic effects reduced additive variance estimates, especially when additive-by-additive epistasis was fitted. Including non-additive genetic effects in the model did not improve the prediction accuracy of breeding values for purebreds, but there was a substantial change in the ranking of the animals and in the proportion of commonly selected individuals. For the crossbred traits, small non-additive genetic variance with large standard error estimates were obtained. Nevertheless, PS and HD presented notable additive-by-additive epistatic variance. PS presented h2aa estimates of 0.15 and additive-by-additive epistasis corresponding to 86.76% of the total genetic variance, while HD presented additive-by-additive epistatic heritability (h2aa) estimates from 0.46 to 0.49 and the proportion of total genetic variance explained by additive-by-additive epistasis ranged from 66.91% to 71.87%. In conclusion, including non-additive genetic effects did not improve the accuracy of prediction of breeding values for purebreds, but it changed the ranking of animals and selection decisions. Although PS and HD had large additive-by-additive epistasis effects, most of the traits related to heat stress in the crossbred population did not present relevant non-additive genetic effects.

ABSTRACT Pepper plants can be used as ornamental ones due to the contrasting traits of plants, flowers, and especially fruits. This variability can be exploited in genetic improvement programs aiming at identifying superior genotypes and obtaining hybrids. This work aimed to select parental and hybrid individuals through diallel analysis for fruit traits in Capsicum annuum. Seven pepper genotypes were crossed, and eleven fruit-related quantitative traits were evaluated. The data were subjected to diallel analysis using Griffing’s Method 1 (fixed model). There was a predominance of additive genetic effects on the fruit traits of ornamental pepper plants. Genotypes UFPB77.3 and UFPB390 are indicated as parents for the improvement of ornamental pepper plants, for fruit traits. Hybrids UFPB77.3 x UFPB099, UFPB390 x UFPB77.3, UFPB390 x UFPB001, UFPB390 x UFPB099, UFPB134 x UFPB77.3, and UFPB134 x UFPB390 present a potential for the production of hybrids and generation of segregating populations of ornamental peppers.

Selection has emphasized animal growth, leading to an increase in their mature size affecting in some cases the pregnancy of the cows and the efficiency of the systems. Usually, crossbreeding improve productivity because of the genetic effects that the cows exploit, but the impact on mature weight (MW) has not been studied. The present study aimed at estimating MW and genetic parameters associated with the MW in crosses between two British breeds: Hereford (H/H) and Angus (A/A), a Continental: Salers (S/S), and a Zebu: Nelore (N/N). MW was analyzed at 4; 4.5; 5; 5.5 and 6 years of age using a repeated-measure sire model. For parameters estimation, an additive – dominant model was used including the fixed effects of breed group, contemporary group, and age as covariate linear and quadratic, with the linear regression fitted by breed group. Permanent environmental and sire were included as random effects. According to the results, it is expected to observe heterosis between H/H and N/N, however, the structure of the data may not be enough for estimate accurately the genetic parameters in this trait. The A/H, N/H, S/H, S/SH and H/NH cows were heavier than the H/H cows. All the breed groups continue gaining weight until six years of age. The results revealed that British crossbred animals are heavier than H/H at the first crossing but not in the following. Crossbred cows with proportions of 0.5 and greater for the Continental breed are heavier than H/H cows. Crosses between British and Zebu cows have higher mature weight than H/H at the first crossing and in backcrosses toward the British in all ages.

Abstract Key message Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. Abstract In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.

The present review article aims to provide an overview of the additive and non-additive genetic effects of crossbreeding and their contribution to the improvement of growth and egg production traits in chickens. It discusses the advancement in crossbreeding effects and mating design contribution to a significant rate of genetic progress in indigenous chicken. In Ethiopia, crossbreeding practice may be used to enhance the performance of local chicken ecotypes. The article extensively reviews various papers related to crossbreeding trials conducted in Ethiopia, evaluating their effectiveness in improving growth and egg production. It discusses the mating design and breeds used in these programs, such as exotic breeds like Rhode Island Red, Fayoumi, White Leghorn, Koekoek, Sasso, Kuroiler, and local Ethiopian chicken ecotypes. Among the exotic breeds involved in crossbreeding, Rhode Island Red and Sasso are considered more favorable for improving growth rate and color preference, while White Leghorn is preferred for enhancing egg production traits. In opposite to these indigenous chickens are preferred for disease resistance and product quality. Additive genetic effects are typically responsible for the genetic improvement of traits over generations through selection. In egg production, additive genetic effects influence the overall capacity of a chicken to lay eggs, affecting traits like egg number and egg size. Whereas, In growth performance, additive genetic effects influence traits like body weight gain, feed conversion efficiency, and overall growth rate. Non-additive genetic effects include dominance and epistatic interactions between genes. These effects can lead to genetic heterogeneity and can impact traits like egg production and growth performance besides playing a role in hybrid vigor or heterosis. In conclusion, both additive and non-additive genetic effects play a crucial role in determining egg production and growth performance in chickens. Additive effects drive genetic improvement over generations, while non-additive effects provide immediate benefits like hybrid vigor. Understanding and utilizing both types of genetic effects is essential for enhancing these traits in poultry breeding programs. Chicken crossbreeding programs are highly important in the poultry industry as they continuously improve the genetic potential of chickens, leading to more efficient production systems and higher profitability for producers.

Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).

Abstract Motivation During the past decade, genome-wide association studies (GWAS) have been used to map quantitative trait loci (QTLs) underlying complex traits. However, most GWAS focus on additive genetic effects while ignoring non-additive effects, on the assumption that most QTL act additively. Consequently, QTLs driven by dominance and other non-additive effects could be overlooked. Results We developed ADDO, a highly efficient tool to detect, classify and visualize QTLs with additive and non-additive effects. ADDO implements a mixed-model transformation to control for population structure and unequal relatedness that accounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucleotide polymorphism effects as either additive, partial dominant, dominant or over-dominant. A matrix multiplication approach is used to accelerate the computation: a genome scan on 13 million markers from 900 individuals takes about 5 h with 10 CPUs. Analysis of simulated data confirms ADDO’s performance on traits with different additive and dominance genetic variance components. We showed two real examples in outbred rat where ADDO identified significant dominant QTL that were not detectable by an additive model. ADDO provides a systematic pipeline to characterize additive and non-additive QTL in whole genome sequence data, which complements current mainstream GWAS software for additive genetic effects. Availability and implementation ADDO is customizable and convenient to install and provides extensive analytics and visualizations. The package is freely available online at https://github.com/LeileiCui/ADDO. Supplementary information Supplementary data are available at Bioinformatics online.

AbstractExcellent reproductive performance (i.e. 365-day calving interval) is paramount to herd profit in seasonal-calving dairy systems. Reproductive targets are currently not being achieved in Irish dairy herds. Furthermore, most research on the genetics of reproductive performance in dairy cattle has focused primarily on lactating cows and relatively few studies have attempted to quantify the genetic contribution to differences in reproductive performance in nulliparae. The objective of the present study was to estimate the contribution of both the additive and non-additive genetic components, as well as the permanent environmental component, to phenotypic variation in the reproductive traits in nulliparous, primiparous and multiparous seasonal-calving dairy females. Reproductive phenotypes were available on up to 202,525 dairy females. Variance components were estimated using (repeatability where appropriate) linear animal mixed models; fixed effects included in the mixed models were contemporary group, parity (where appropriate), breed proportion, inter-breed specific heterosis coefficients and inter-breed specific recombination loss coefficients. Heritability of the reproductive traits ranged from 0.004 (pregnancy rate to first service) to 0.17 (age at first service in nulliparae), while repeatability estimates for the reproductive traits in cows ranged from 0.01 (calving interval) to 0.11 (pregnant in the first 42 days of the breeding season). Breed-specific heterosis regression coefficients suggest that, relative to the parental mean, a first-cross Holstein–Jersey crossbred was almost 7 days younger at first calving, had a 9-day shorter calving interval, a 6 percentage unit greater pregnancy rate in the first 42 days of the breeding season and a 3 percentage unit greater survival rate to next lactation. Heifer calving rate traits were strongly genetically correlated with age at first calving (–0.97 to –0.66) and calving rate in the first 42 days of the calving season for first parity cows (0.77 to 0.56), but genetic correlations with other cow reproductive traits were weak and inconsistent. Calving interval was strongly genetically correlated with the majority of the cow traits; 56%, 40%, and 92% of the genetic variation in calving interval was explained by calving to the first service interval, number of services and pregnant in the first 42 days of the breeding season, respectively. Permanent environmental correlations between the reproductive performance traits were generally moderate to strong. The existence of contributions from non-additive genetic and permanent environmental effects to phenotypic differences among cows suggests the usefulness of such information to rank cows on future expected performance; this was evidenced by a stronger correlation with future reproductive performance for an individual cow index that combined additive genetic, non-additive genetic and permanent environmental effects compared to an index based solely on additive genetic effects (i.e. estimated breeding values).

SummaryInferences about genetic values and prediction of phenotypes for a quantitative trait in the presence of complex forms of gene action, issues of importance in animal and plant breeding, and in evolutionary quantitative genetics, are discussed. Current methods for dealing with epistatic variability via variance component models are reviewed. Problems posed by cryptic, non-linear, forms of epistasis are identified and discussed. Alternative statistical procedures are suggested. Non-parametric definitions of additive effects (breeding values), with and without employing molecular information, are proposed, and it is shown how these can be inferred using reproducing kernel Hilbert spaces regression. Two stylized examples are presented to demonstrate the methods numerically. The first example falls in the domain of the infinitesimal model of quantitative genetics, with additive and dominance effects inferred both parametrically and non-parametrically. The second example tackles a non-linear genetic system with two loci, and the predictive ability of several models is evaluated.

Cette thèse explore et développe des méthodes pour exploiter les effets génétiques de dominance ou/et d'épistasie sur des modèles de sélection génomique dans les schémas de sélection utilisant le croisement chez le porc et le maïs. Le Chapitre 2 a consisté à estimer et à exploiter la variance de dominance intra-race à travers des stratégies de planification des accouplements pour maximiser le progrès génétique global de l’âge à 100 kg (AGE), de l’épaisseur de lard dorsal (BD) et du poids moyen des porcelets par portée (APWL), dans une population porcine de race Landrace française. La maximisation de la valeur génétique totale au lieu de la seule partie additive dans la planification des accouplements a donné à la descendance un avantage moyen de -0,79 jour, -0,04 mm et 11,3 g pour AGE, BD et APWL, respectivement. En contrepartie, le gain génétique additif attendu a légèrement été réduit (1,8% pour AGE par exemple). Ces résultats indiquent que la planification des accouplements peut améliorer les performances des descendants sans compromettre considérablement le progrès génétique. Dans le Chapitre 3, l'efficacité de la planification des accouplements et de l’évaluation génomique, en tenant compte des effets additifs et de dominance, pour améliorer les performances des individus croisés (CB) a été étudiée par simulation dans un croisement à deux voies chez le porc. Les effets de l’utilisation de différentes sources d'informations dans l'évaluation génétique (uniquement des données de race pure (PB) ou des données PB et CB), de plusieurs valeurs d'héritabilité au sens étroit et large, et de plusieurs stratégies d’accouplement pour produire les animaux CB (accouplements au hasard, minimisant la consanguinité future ou maximisant la valeur génétique totale attendue des animaux CB) ont été évaluées. La sélection des animaux PB sur leurs performances en PB a donné un gain génétique de 0,2 écart-type génétique par génération pour le caractère « performance en croisement ». Ce gain a été doublé lorsque les animaux PB étaient sélectionnés sur leur performance en croisés. Les stratégies d’accouplement a entraîné une légère augmentation des performances des animaux CB. Lorsque la corrélation génétique entre les performances exprimées chez les animaux PB et CB est faible, la sélection des animaux PB pour leur performance en croisés en utilisant les informations CB est une stratégie plus efficace pour exploiter l'hétérosis et augmenter les performances des animaux CB au niveau commercial. Dans le Chapitre 4, la théorie des modèles d'évaluation génétique chez des hybrides à partir du croisement de lignées pures (comme pour le maïs) a été revue dans un contexte génomique. La covariance entre les hybrides due aux effets de substitution additifs, à la dominance et à l’épistasie a été dérivée analytiquement. En utilisant les marqueurs SNP, il est possible de décomposer l’aptitude spécifique à la combinaison (SCA) en dominance et épistasie intergroupes, et de décomposer les aptitudes générales à la combinaison (GCA) en effets additifs intra-lignée et une épistasie additive par additive intra-ligne. Un jeu de données publiques sur des hybrides Dent × Flint a été analysé. Le modèle proposé a été comparé à d'autres modèles génomiques en termes d'estimations des composantes de variance et de capacité prédictive, y compris un modèle supposant un effet commun des gènes des lignées pures. L'étude confirme que la majeure partie de la variabilité observée chez les hybrides est expliquée par la GCA et que les variances dues à la dominance et à l'épistasie sont moins importants et du même ordre de grandeur. Les modèles basés sur la définition d’effets différents (comme traditionnellement considérés chez le maïs), ou commun aux origines (comme considérés intra-race en sélection animale) ont abouti à des capacités prédictives similaires pour les hybrides
This thesis explores and develops methodology to exploit dominance or/and epistasis genetic effects on genomic selection models in pig and maize crossbreeding schemes. The Chapter 2 consisted of estimating and exploiting within-breed dominance variance through mate allocation strategies to maximize the overall genetic merit of the traits age at 100 Kg (AGE), backfat depth (BD) and average piglet weight per litter (APWL), in a French Landrace pig population. Maximizing total genetic values instead of breeding values in matings gave to the progeny an average advantage of 0.79 days, 0.04 mm, and 11.3 g for AGE, BD and APWL, respectively, but slightly reduced the expected additive genetic gain (e.g. 1.8 % for AGE). These results indicate that genomic mate allocation can improve the performance of the offspring without dramatically compromising the additive genetic gain. In Chapter 3, the effectiveness of mate allocation strategies and genomic evaluations, accounting for additive and dominance effects, to improve crossbred (CB) performance were investigated by simulation in a two-way pig crossbreeding scheme. Effects of the sources of information used in the genetic evaluation (only purebred (PB) data or PB and CB data), of several narrow and broad-sense heritability values, and of several options for mate allocation to produce the CB (mating at random, minimizing expected future inbreeding, or maximizing the expected total genetic value of crossbred animals) were evaluated. Selecting PB animals for PB performance yielded a genetic gain of 0.2 genetic standard deviations of the trait “CB performance” per generation, whereas selecting PB animals for CB performance doubled the genetic response. Mate allocation strategy resulted in a slight increase of the CB performance. When the genetic correlation between PB and CB is low, selecting PB animals for CB performance using CB information is a more efficient strategy to exploit heterosis and increase performance at the CB commercial level. In Chapter 4, the theory of hybrid genetic evaluation models from single-cross of pure lines (as in maize) was revisited in a genomic context. Covariance between hybrids due to additive substitution effects and dominance and epistatic deviations were analytically derived. Using SNP genotypes, it is possible to split specific combining ability (SCA) into dominance and across-groups epistasis, and to split general combining ability (GCA) into within-line additive effects and within-line additive by additive epistasis. A publicly available maize data set of Dent × Flint hybrids was analyzed. The proposed model was compared to other genomic models in terms of variance components estimation and predictive ability, including a model assuming a common effect of genes across origins. The study confirms that most variation in hybrids is accounted for by GCA, and that variances due to dominance and epistasis are small and have similar magnitudes. Models based on defining effects either differently (as it is traditionally done in maize) or identically across origins (as it is done in single breeds in livestock) resulted in similar predictive abilities for hybrids

Les études d'association pan-génomiques (GWAS) ont révolutionné ces 15 dernières années la recherche en génétique humaine en permettant l'identification de milliers de variants génétiques associés à des maladies complexes comme les maladies cardiovasculaires et des traits biologiques comme des facteurs de la coagulation. Toutefois, ces études reposent principalement sur des modèles additifs qui ne permettent pas de capturer toute la complexité des mécanismes génétiques qui peuvent être mis en jeu. Les interactions entre gènes (épistasie), entre gènes et facteurs environnementaux ainsi que les effets épigénétiques dû à l’empreinte parentale, sont ainsi négligés. L'objectif principal de cette thèse est de détecter des effets génétiques non additifs dans des études d'association pan-génomiques sur les taux plasmatiques de 2 facteurs importants de la cascade de la coagulation : le facteur V et le facteur de Willebrand. Pour cela, une méthodologie statistique peu connue et reposant sur une modification du test de Brown-Forsythe a été utilisée dans plusieurs cohortes du consortium CHARGE. Cette méthodologie a permis d’identifier le locus PSKH2 comme nouvel acteur participant à la régulation des taux plasmatiques de Facteur V. L’application de cette stratégie de recherche aux taux plasmatiques de Facteur de Willebrand a mis en évidence les limites de la méthode en présence de plusieurs polymorphismes en déséquilibre de liaison et influençant le phénotype étudié. À l'avenir, il serait intéressant de poursuivre ces recherches en explorant d'autres facteurs de la coagulation et en utilisant d’autres méthodologies statistiques moins sujettes à l’influence du déséquilibre de liaison. Les études d’association pan-génomiques (GWAS) ont révolutionné ces 15 dernières années la recherche en génétique humaine en permettant l’identification de milliers de variants génétiques associés à des maladies complexes comme les maladies cardiovasculaires et des traits biologiques comme des facteurs de la coagulation. Toutefois, ces études reposent principalement sur des hypothèses d’effets génétiques additifs qui ne permettent pas de capturer toute la complexité des mécanismes génétiques qui peuvent être mis en jeu. Les interactions entre gènes (épistasie), entre gènes et facteurs environnementaux ainsi que les effets épigénétiques dus par exemple à l’empreinte parentale, sont ainsi négligés. L’objectif principal de cette thèse est de détecter des effets génétiques non additifs influençant les taux plasmatiques de 2 facteurs importants de la cascade de la coagulation : le Facteur V et le Facteur de von Willebrand, et ce à partir de données génétiques pan-génomiques. Pour cela, une méthodologie statistique peu connue et reposant sur une modification du test de Brown-Forsythe a été utilisée dans plusieurs cohortes du consortium CHARGE. Cette méthodologie a permis d’identifier le locus PSKH2 comme nouvel acteur participant à la régulation des taux plasmatiques de Facteur V. L’application de cette stratégie de recherche aux taux plasmatiques de Facteur de von Willebrand a mis en évidence les limites de la méthode en présence de plusieurs polymorphismes en déséquilibre de liaison et influençant le phénotype étudié. À l’avenir, il serait intéressant de poursuivre ces recherches en explorant d’autres facteurs de la coagulation et en utilisant d’autres méthodologies statistiques moins sujettes à l’influence du déséquilibre de liaison
Genome-wide association studies (GWAS) have revolutionized human genetics research over the past 15 years by enabling the identification of thousands of genetic variants associated with complex diseases, such as cardiovascular diseases, and biological traits, such as coagulation factors. However, these studies primarily rely on additive models, which do not capture the full complexity of genetic mechanisms that may be involved. Interactions between genes (epistasis), gene-environment interactions, and epigenetic effects such as those due to parental imprinting are thus neglected. The main objective of this thesis is to detect, from GWAS data, non-additive genetic effects on plasma levels of two important factors in the coagulation cascade: Factor V and von Willebrand Factor. To achieve this, a neglected statistical methodology based on a modification of the Brown-Forsythe test was applied in several cohorts from the CHARGE consortium. This methodology identified the PSKH2 locus as a novel player in the regulation of plasma Factor V levels. Applying this research strategy to von Willebrand Factor plasma levels highlighted the limitations of the method in the presence of multiple polymorphisms in linkage disequilibrium that influence the studied phenotype. In the future, it would be interesting to pursue this research by exploring other coagulation factors and using other statistical methodologies less subject to the influence of linkage disequilibrium

Non-additive effects may affect the evolution of populations by lowering the heritability of the traits that they affect, thus causing inbreeding depression within populations and playing a role in the conversion of non-additive into additive variation during bottlenecks and in the evolution and maintenance of negative genetic correlations between traits (Crnokrak and Roff 1995, Wolf et al. 2000). Furthermore, dominance variance should be present to a greater degree in traits closer to fitness (Crnokrak and Roff 1995). This study uses diallel cross analyses of inbred lines of the sand cricket Gryllus firmus, to examine the sources of variation in weight at age, adult size, development time, fecundity and flight muscle weight and in particular the ratios of additive, dominance and maternal variance to total variance. We also examine the genetic relationships between the traits.
Our study also examines the presence of maternal effects in growth traits and adult size in the sand cricket Gryllus firmus using diallel cross analyses of inbred lines.

Nas últimas décadas, a produção e exportação de carne bovina no Brasil consolidaram o país como um importante fornecedor no mercado internacional. No ano de 2012 o Brasil produziu aproximadamente 17% da demanda mundial de carne, exportando 1.325 milhão de toneladas (USDA, 2012). No entanto, apesar desta posição privilegiada, a produção brasileira é caracterizada pela criação extensiva dos animais e pela baixa qualidade do produto final. O rebanho é composto basicamente por animais Bos indicus e seus cruzamentos, com predominância da raça Nelore. Estes animais, por sua vez, apresentam ótima adaptabilidade e resistência ao ambiente tropical, porém com qualidade de carne e carcaça inferior quando comparados a bovinos Bos taurus. Assim, buscando indivíduos com maior rusticidade e com melhores índices de crescimento e acabamento de carcaça, os produtores vem utilizando cruzamentos entre bovinos Bos taurus X Bos indicus, aproveitando os efeitos de heterose e complementariedade entre raças. Os resultados já obtidos reforçam a contribuição dos mestiços na produção de carne, sendo utilizados com maior frequência em ambientes onde animais puros não apresentariam bons desempenhos. Diante disso, a identificação e seleção de animais superiores para ambientes tropicais possibilitariam o atendimento das demandas do mercado, principalmente no que diz respeito à qualidade da carne produzida. Portanto, efeitos genéticos aditivos e não aditivos que influenciam as características de importância econômica devem ser considerados nas avaliações genéticas de animais cruzados. Desta forma, os objetivos deste trabalho foram: I) Estudar a influência dos efeitos genéticos não aditivos na estimação de componentes de variância, parâmetros genéticos e ranking dos animais através de diferentes modelos; II) Estudar a influência da regressão de cumeeira ponderada na redução de colinearidade e na estimação de componentes de variância e parâmetros genéticos. A partir dos resultados foi possível observar que modelos que consideraram efeitos genéticos aditivos e não aditivos da epistasia e de heterozigose foram em geral os mais adequados para descrever o peso a desmama e o ganho de peso da desmama ao sobreano. Para a análise de peso ao nascer, peso aos 12 meses, área do olho do lombo e a espessura de gordura da picanha o efeito da epistasia foi desprezível. Da mesma maneira, foi possível observar que a aplicação da regressão ridge ponderada diminuiu a inflação da variância associada aos efeitos fixos genéticos diretos e maternos e, proporcionou estimativas mais estáveis e plausíveis para as características de crescimento. Em relação aos componentes de variância não foram verificadas diferenças em função da aplicação de regressão ridge ponderada em características de crescimento.
In last year Brazilian beef production and exportation consolidated the country as an important provider in the international market. Thus, in 2012, Brazil provided approximately 17% of global meat demand, exporting 1,325 million tons (USDA, 2012). However, Brazilian production is characterized by extensive grazing system and low meat quality. The Brazilian herd is composed mainly of Bos indicus (mostly Nelore) and their crosses. These animals have great adaptability and resistance to tropical environment, but they show lower carcass and meat quality than Bos taurus cattle. Thus, looking for individuals with more rusticity and better growth rates and carcass traits, the farmers have been using crossbreed between Bos taurus X Bos indicus, exploring the heterosis and complementarity effects. Results obtained affirmed the crossbred contribution in meat production, especially in environments where purebred animals would not show good performances. Therefore, the identification and selection of genetically superior animals would meet specific market needs. Thus, is necessary to consider additive and non-additive genetic effects in genetic evaluation. The aims of this study were: I) to study the influence of non-additive genetic effects in the estimation of genetic parameters and ranking of animals across different models. II) To study the influence of weighted ridge regression in collinearity reduction and their effects in genetic parameters estimation. The results showed that models that considered non-additive genetic effects of epistasis and heterozygosity were generally the most suitable to describe the weaning weight and weight gain from weaning to yearling. The epistasis effect was unimportant for birth weight, weight at 12 months, loin rib eye area and fat thickness of. Similarly, it was observed that ridge regression application allowed decreased the inflation variance and provided stable and plausible estimates. No differences due to the application of ridge regression were observed in growth traits.

This thesis addresses several key issues related to the genetic architecture of traits relevant to the genetic improvement of Eucalypts globulus for pulpwood and solid wood production. It comprises three main studies, that address (i) the long-term effect of inbreeding, (ii) the genetic association between pulp-wood and solid wood selection traits and (iii) the importance of non-additive genetic effects. The long-term effect of inbreeding was studied using a 28 year-old field trial comprising outcrossed, selfed and open-pollinated (OP) families of Eucalyptus globulus and a commonly cooccurring species E. ovata. These species have a mixed mating system, where open-pollinated (OP) progenies are expected to include selfs and outcrosses. Inbreeding depression for early age growth due to selfing was high (age 4: 27% for E. globulus and 49% for E. ovata) but diminished with age, as size-dependent mortality resulted in the purging of smaller inbred progenies. Most mortality occurred between the ages 4 and 13 years, and size-dependent mortality resulted in a shift in inbreeding depression from growth to survival with age. OP progenies exhibited intermediate levels of inbreeding depression, but later-age survivors exhibited no evidence of inbreeding depression, consistent with the purging of selfs. General higher mortality rate in all cross-types of E. ovata compared with E. globulus was suggested to be due to climatic maladaptation, arising from the onset of drought conditions after 10 years of comparable growth, with the inbred progeny of both species appearing more susceptible. To further explore the genetics of growth and wood properties of E. globulus, two OP progeny trials were studied and the genetic association of selection traits important to pulpwood and solid wood breeding objectives were examined. These base population trials comprised of 135 families derived from native stand seed collections of the 13 races from which the Australian National E. globulus Breeding Population was founded. Significant additive genetic variation was found for all traits (stem diameter at breast height [DBH], stem straightness, acoustic wave velocity, wood basic density and pulp yield). There was no adverse race or additive level genetic correlation of DBH with any of the other traits studied. While race and additive genetic correlations were usually aligned, significant opposing genetic correlations were evident at these different genetic scales for pulp yield and wood basic density. Furthermore, key breeding objective-specific traits were either favourably (pulp yield - acoustic wave velocity) or not significantly (pulp yield - straightness) genetically correlated, arguing that genetic improvement between pulpwood and solid wood are well aligned and that breeding for one objective will have no adverse impact on the other. Wood basic density in the previous study was assessed using wood cores taken from standing trees using a mechanical corer. This is a relatively expensive assessment approach and has limited the large-scale assessment of wood density in breeding trials. A hand-held IML Power Drill series instrument (RESI) is starting to be used in the forest industry to measure wood basic density. The RESI trace also can be used to extract measures of stem diameter and bark thickness. This study quantified and confirmed the genetic association between RESI resistance values and core basic density (≥0.95). It also confirmed high genetic correlations (>0.90) of bark thickness and diameter (DBH) estimated from RESI to the analogous traditional methods. Significant family and subrace differentiation were detected for the three RESI-derived traits, with the subrace differentiation for bark thickness exhibited among the highest subrace differentiation (QST > 0.63) reported to date for E. globulus, signalling divergent selection. This study confirmed that traditional measurements of wood density, DBH and bark thickness can be replaced with RESI measurements, for the genetic studies of Eucalyptus globulus. While OP trials have been useful to demonstrate significant racial variation within E. globulus and provide the initial estimates of the levels of additive genetic variation for selection traits, they do not allow the estimation of non-additive genetic effects. This is a key issue now that the advanced generations of the Australian National E. globulus Breeding Program comprise full-sib families and there are deployment options for exploiting non-additive genetic effects through full-sib family deployment. The relative importance of non-additive genetic effects, including inter-race heterosis, was examined using a trial derived from first generation selections from the breeding program. The trial was 9 year-old and established from 515 full-sib families derived from a diallel crossing design involving intra- and inter-race hybrids of the three most widely used races in the breeding program. Growth (diameter at breast height; DBH) was assessed at ages 2, 4, 6, and 8 years, allowing the detection and monitoring of changes in additive, dominance/heterosis as well as maternal and reciprocal effects with age. Key findings include the generally insignificant maternal and reciprocal effects, significant dominance variance (22 to 34% of the additive variance) and significant inter-race heterosis which increased with age (2.2% to 6.5%). While not significant, all inter-race combinations were better than the best of their intra-race crosses (‘better-parent’ heterosis), consistent with low levels of inbreeding in intra-race crosses. Three replicates of the trial were non-destructively assessed for pulp yield using NIR spectroscopy, and resistance drilling (RESI) used to assess wood basic density as well as bark thickness. The reliability of the RESI basic density estimates were validated, and in contrast to growth, these traits were shown to be predominantly under additive genetic control. In summary, the studies of both open-pollinated (OP) and control-pollinated progeny trials have provided novel insights into the genetic architecture of growth, wood property traits and bark thickness in Eucalyptus globulus. The demonstration of significant non-additive genetic effects for growth demonstrates the advantage of identifying the best heterotic full-sib families for deployment through mass-supplementary pollination, which also gives the additional benefit of avoiding inbreeding. In addition, the study confirms the neutral or favourable association between pulpwood and solid wood traits in this species, arguing that with the breeding so far focused on pulpwood, pulpwood-selected germplasm and current plantations will not be degraded in terms of their genetic suitability to use them for solid-wood products.

Abstract Research in psychiatric genetics is not for the fainthearted. Mental disorders pose great challenges to genetic analyses because, in the majority of cases, they result from the predisposing effects of alleles at an unknown number of different genes, as well as environmental influences. Further complexities include the likelihood of non-additive genetic effects, including gene–gene interactions (epistasis), and potential gene–environment (physical and experiential) interactions. Genetic complexity is compounded by possible epigenetic factors (Gottesman 2001; Petronis 2001), stochastic effects (McGuffin et al. 1994; Woolf 1997) and nosological complexity and uncertainty.

Arterial hypertension is a leading cause of mortality, affecting at least a quarter of the adult population, with its effects having devastating consequences to the global economy. Unfortunately, the underlying causes and pathophysiology of the disease often remain unclear. Ongoing research in this important field investigates the mechanisms involved in the genesis of hypertension. Magnetic resonance imaging is a well-established imaging technique that is widely used for anatomical organ and vascular evaluation. According to the latest European Society of Hypertension (ESC) guidelines, cardiovascular magnetic resonance can be used in the assessment of hypertensive patients. But the authors advocate a more comprehensive and multisystem use of the varied and novel sequences of MRI scanners to provide an even better understanding of the development of hypertension and its consequences. The extensive and detailed data that can be derived, with the additive focus on the concept of the ‘selfish brain hypothesis’, might further assist us in altering and providing a more individualised therapeutic approach to one of the greatest non-communicable causes of human mortality and morbidity.

From the previous chapters you will see that understanding the pharmacological aspects of the drugs you are administering is vital to keeping your patients safe. Nurses need to understand the pharmacodynamics of a medicine, or how it actually works within the body, since this will need to be explained to patients and carers. For example, how will you ensure that a patient understands the importance of taking their treatment for hypertension (especially if they are experiencing no symptoms) if you are unable to explain how the medicine will be working? Similarly, your understanding of the pharmacokinetics (the absorption, distribution, metabolism, and excretion) of individual medicines is vital to ensure compromised patients are not administered inappropriate medicines. For example, you would question the prescribing of a non-steroidal anti-inflammatory drug (NSAID) to a patient with significant renal impairment, because the kidney is essential to the elimination of NSAIDs so the drug could accumulate if the kidneys are not functioning properly. From the point of view of ensuring patient safety, you will need to understand the principles of drug interactions so that you can understand how two medicines (or food and medicine) could interact and be alert to signs that this may be happening. There are several good textbooks dealing with the uses and actions of individual medicines, including interactions. However, these will not be discussed here because at this stage of your career you are not expected to have a detailed knowledge of particular medicines, but rather an understanding of the key principles. As nurses, we are concerned with how the body handles medicines (pharmacokinetics) so that we can see how this may be affected by age, genetics, or illness, and how the actions of medicines may conflict with one another or produce toxicity because their effects are additive. Equally, we need to look at occasions in which two medicines produce the same response by two different routes; such interactions can be beneficial to the patient and avoid having to give large doses of a single medicine because the same result can be achieved with smaller doses of two medicines, thereby reducing the risk of adverse effects.

This paper presents the current status and scientific approaches from the ESA project DeLeMIS. Within that, e:fs and DLR Robotics investigate state-of-the-art approaches of self-learning methods to enable improvements in planetary space missions. The main objective of DeLeMIS is the autonomous navigation of a rover on unknown terrain without human intervention. To this end, algorithms from the latest research in the AI and control engineering community are used for environmental perception and behaviour control. On the one hand, the rover is supposed to learn the ground conditions of different areas and their boundaries, both through camera inputs and through the interaction of the wheels with the ground. On the other hand, the system is intended to learn the best behaviour and the most appropriate strategy for its motion and navigation across different ground surfaces, taking into account safety and robustness aspects. Overall goal is to achieve a better motion behaviour, e.g. regarding the deviation from the desired trajectory, the energy consumption or the safety of the rover on unknown and challenging terrain. The motion control of the rover, the corresponding concepts, learning-based approaches and first results from the project are presented in this paper. Furthermore, the test and validation platform, including a simulation environment, is described which is also used to generate data for the ML approaches in the future work. The considered scenario is based on DLR's LRU (Lightweight Rover Unit) in DLR’s test facilities. A model of the LRU is also implemented in the simulation environment for rapid testing and data generation. The task of the motion control subsystem is to follow a given trajectory on a partially known or unknown ground. It is desired that the task is performed better after every iteration, which is taken as an indication for the learning. To isolate the effect of the learning-based controller, the position and the orientation of the rover is assumed to be exactly known. For easier and faster development during the project, a simulation environment was created, including a model of the LRU rover, a lunar surface and a flexible interface architecture for the integration of the different algorithms. This gazebo simulator (https://gazebosim.org/), embedded in the ROS (https://www.ros.org/) framework serves also as a data generator for the ML-based methods and as a test and verification platform for the algorithm development. To increase the representativeness and the reliability of the simulation, data from DLR’s facilities will be (By the deadline of the final paper, this will be done. We plan a first test campaign already in February) gathered and used to verify the behaviour of the simulated rover in relevant and comparable scenarios. To this end, the rover will ride pre-defined trajectories in DLR’s test facility containing a new lunar soil simulant, which is the same as the one that will be used for the new DLR/ESA lunar test facility “LUNA” in Cologne. The resulting trajectory data will be then compared to those from the simulator and simulation parameter will be adjusted accordingly. The overall closed loop system consists of several components, for instance, the rover or the representing simulation model, sensors and perception, low-level actuator controller and high-level motion controller. The perception module is not within the scope of this paper. There are two control modules which are designed each to be tested and analysed independently. Furthermore, the algorithms and the interfaces are generic to be applicable to both the rover and the simulation. Static (non-learning) algorithms are implemented for tasks such as trajectory planning and interfacing the wheel actuators. Also, a non-linear, Lyapunov-based, controller is applied for trajectory tracking control. Besides, three modules with learning-based components are involved. The perception module includes image recognition for segmentation and classification of the surface. The learning-based kinematics adjustments module manipulates the low-level wheel steering controller and the learning-based motion control is applied on a high-level. Below, first implementations of each of the two latter algorithms are presented and results are discussed. For the learning-based kinematics adjustments module a first algorithm is implemented to manipulate the currently available wheel steering controller on the rover using an additive term to the input. For this purpose, an approximation function is trained from the simulated trajectory tracking errors to predict correction control action. Simulation results show that Gaussian Process Regression (GPR) is suitable as approximation function for online learning and leads to improvement. For the learning-based motion controller, a learning-based model predictive controller (MPC) is developed with a parametric model for trajectory tracking. Simulation results show that the proposed controller is able to track a given trajectory while considering state and input constraints and improving performance with the time. In summary, at the current stage of the project, a solid framework for the development of different learning-based algorithms has been created, including a simulation environment for data generation and verification of the learning-based methods. In addition, first promising approaches have been developed and implemented. Next steps are to replace the parametric approach of the LBMPC by a neural network for which the training data is being generated by the validated simulator. Finally, results will be verified using the rover to compare to those from the simulation. At the end of the project, a test and demonstration campaign is planned at DLR’s facilities.

Heterosis, the enigmatic phenomenon in which whole genome heterozygous hybrids demonstrate superior fitness compared to their homozygous parents, is the main cornerstone of modern crop plant breeding. One explanation for this non-additive inheritance of hybrids is interaction of alleles within the same locus. This proposal aims at screening, identifying and investigating heterosis trait loci (HTL) for different yield traits by implementing a novel integrated mapping approach in Sorghum bicolor as a model for other crop plants. Originally, the general goal of this research was to perform a genetic dissection of heterosis in a diallel built from a set of Sorghum bicolor inbred lines. This was conducted by implementing a novel computational algorithm which aims at associating between specific heterozygosity found among hybrids with heterotic variation for different agronomic traits. The initial goals of the research are: (i) Perform genotype by sequencing (GBS) of the founder lines (ii) To evaluate the heterotic variation found in the diallel by performing field trails and measurements in the field (iii) To perform QTL analysis for identifying heterotic trait loci (HTL) (iv) to validate candidate HTL by testing the quantitative mode of inheritance in F2 populations, and (v) To identify candidate HTL in NAM founder lines and fine map these loci by test-cross selected RIL derived from these founders. The genetic mapping was initially achieved with app. 100 SSR markers, and later the founder lines were genotyped by sequencing. In addition to the original proposed research we have added two additional populations that were utilized to further develop the HTL mapping approach; (1) A diallel of budding yeast (Saccharomyces cerevisiae) that was tested for heterosis of doubling time, and (2) a recombinant inbred line population of Sorghum bicolor that allowed testing in the field and in more depth the contribution of heterosis to plant height, as well as to achieve novel simulation for predicting dominant and additive effects in tightly linked loci on pseudooverdominance. There are several conclusions relevant to crop plants in general and to sorghum breeding and biology in particular: (i) heterosis for reproductive (1), vegetative (2) and metabolic phenotypes is predominantly achieved via dominance complementation. (ii) most loci that seems to be inherited as overdominant are in fact achieving superior phenotype of the heterozygous due to linkage in repulsion, namely by pseudooverdominant mechanism. Our computer simulations show that such repulsion linkage could influence QTL detection and estimation of effect in segregating populations. (iii) A new height QTL (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 in sorghum, and its genetic dissection in RIL population demonstrated that it affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. (iv) HTL mapping for grain nitrogen content in sorghum grains has identified several candidate genes that regulate this trait, including several putative nitrate transporters and a transcription factor belonging to the no-apical meristem (NAC)-like large gene family. This activity was combined with another BARD-funded project in which several de-novo mutants in this gene were identified for functional analysis.

Project Objectives 1. Develop and amplify two interspecific populations (annual and perennial teosintes x elite maize inbred) as the basis for genetic analysis of grain quality. 2. Identify quantitative trait loci (QTLs) from teosinte that improve oil, protein, and essential amino acid composition of maize grain. 3. Develop near isogenic lines (NILs) to quantify QTL contributions to grain quality and as a resource for future breeding and gene cloning efforts. 4. Analyze the contribution of these QTLs to hybrid performance in both the US and Israel. 5. Measure the yield potential of improved grain quality hybrids. (NOTE: Yield potential could not be evaluated due to environmentally-caused failure of the breeding nursery where seed was produced for this evaluation.) Background: Maize is a significant agricultural commodity worldwide. As an open pollinated crop, variation within the species is large and, in most cases, sufficient to supply the demand for modem varieties and for new environments. In recent years there is a growing demand for maize varieties with special quality attributes. While domesticated sources of genetic variation for high oil and protein content are limited, useful alleles for these traits may remain in maize's wild relative, teosinte. We utilized advanced backcross (AB) analysis to search for QTLs contributing to oil and protein content from two teosinte accessions: Zea mays ssp. mexicana Race Chalco, an annual teosinte (referred to as Chalco), and Z diploperennis Race San Miguel, a perennial teosinte (referred to as Diplo). Major Conclusions and Achievements Two NILs targeting a Diplo introgression in bin 1.04 showed a significant increase in oil content in homozygous sib-pollinated seed when compared to sibbed seed of their counterpart non-introgressed controls. These BC4S2 NILs, referred to as D-RD29 and D-RD30, carry the Diplo allele in bin 1.04 and the introgression extends partially into bins 1.03 and 1.05. These NILs remain heterozygous in bins 4.01 and 8.02, but otherwise are homozygous for the recurrent parent (RD6502) alleles. NILs were developed also for the Chalco introgression in bin 1.04 but these do not show any improvement in oil content, suggesting that the Chalco alleles differ from the Diplo alleles in this region. Testcross Fl seed and sibbed grain from these Fl plants did not show any effect on oil content from this introgression, suggesting that it would need to be present in both parents of a maize hybrid to have an effect on oil content. Implications, both Scientific and Agricultural The Diplo region identified increases oil content by 12.5% (from 4.8% to 5.4% oil in the seed). Although this absolute difference is not large in agronomic terms, this locus could provide additive increases to oil content in combination with other maize-derived loci for high oil. To our knowledge, this is the first confirmed report of a QTL from teosinte for improved grain oil content in maize. It suggests that further research on grain quality alleles from maize wild relatives would be of both scientific and agricultural interest.

Project Objectives 1. Develop and amplify two interspecific populations (annual and perennial teosintes x elite maize inbred) as the basis for genetic analysis of grain quality. 2. Identify quantitative trait loci (QTLs) from teosinte that improve oil, protein, and essential amino acid composition of maize grain. 3. Develop near isogenic lines (NILs) to quantify QTL contributions to grain quality and as a resource for future breeding and gene cloning efforts. 4. Analyze the contribution of these QTLs to hybrid performance in both the US and Israel. 5. Measure the yield potential of improved grain quality hybrids. (NOTE: Yield potential could not be evaluated due to environmentally-caused failure of the breeding nursery where seed was produced for this evaluation.) Background: Maize is a significant agricultural commodity worldwide. As an open pollinated crop, variation within the species is large and, in most cases, sufficient to supply the demand for modem varieties and for new environments. In recent years there is a growing demand for maize varieties with special quality attributes. While domesticated sources of genetic variation for high oil and protein content are limited, useful alleles for these traits may remain in maize's wild relative, teosinte. We utilized advanced backcross (AB) analysis to search for QTLs contributing to oil and protein content from two teosinte accessions: Zea mays ssp. mexicana Race Chalco, an annual teosinte (referred to as Chalco), and Z diploperennis Race San Miguel, a perennial teosinte (referred to as Diplo). Major Conclusions and Achievements Two NILs targeting a Diplo introgression in bin 1.04 showed a significant increase in oil content in homozygous sib-pollinated seed when compared to sibbed seed of their counterpart non-introgressed controls. These BC4S2 NILs, referred to as D-RD29 and D-RD30, carry the Diplo allele in bin 1.04 and the introgression extends partially into bins 1.03 and 1.05. These NILs remain heterozygous in bins 4.01 and 8.02, but otherwise are homozygous for the recurrent parent (RD6502) alleles. NILs were developed also for the Chalco introgression in bin 1.04 but these do not show any improvement in oil content, suggesting that the Chalco alleles differ from the Diplo alleles in this region. Testcross Fl seed and sibbed grain from these Fl plants did not show any effect on oil content from this introgression, suggesting that it would need to be present in both parents of a maize hybrid to have an effect on oil content. Implications, both Scientific and Agricultural The Diplo region identified increases oil content by 12.5% (from 4.8% to 5.4% oil in the seed). Although this absolute difference is not large in agronomic terms, this locus could provide additive increases to oil content in combination with other maize-derived loci for high oil. To our knowledge, this is the first confirmed report of a QTL from teosinte for improved grain oil content in maize. It suggests that further research on grain quality alleles from maize wild relatives would be of both scientific and agricultural interest.

Original objectives . 1. Test anti-fungal gene products for activity against Uncinula necator, Aspergillus niger, Rhizopus stolonifer and Botrytis cinerea. 2. For Agrobacterium transformation, design appropriate vectors with gene combinations. 3. Use biolistic bombardment and Agrobacterium for transformation of important cultivars. 4. Characterize gene expression in transformants, as well as level of powdery mildew and Botrytis resistance in foliage of transformed plants. Background The production of new grape cultivars by conventional breeding is a complex and time-consuming process. Transferring individual traits via single genes into elite cultivars was proposed as a viable strategy, especially for vegetatively propagated crops such as grapevines. The availability of effective genetic transformation procedures, the existence of genes able to reduce pathogen stress, and improved in vitro culture methods for grapes, were combined to serve the objective of this proposal. Effective deployment of resistance genes would reduce production costs and increase crop quality, and several such genes and combinations were used in this project. Progress The efficacy of two-way combinations of Trichoderma endochitinase (CHIT42), synthetic peptide ESF12 and resveratrol upon the control of growth of Botrytis cinerea and Penicillium digitatum were evaluated in vitro. All pairwise interactions were additive but not synergistic. Per objective 2, suitable vectors with important gene combinations for Agrobacterium transformation were designed. In addition, multiple gene co-transformation by particle bombardment was also tested successfully. In New York, transformation work focused on cultivars Chardonnay and Merlot, while the technology in Israel was extended to 41B, R. 110, Prime, Italia, Gamay, Chardonnay and Velika. Transgenic plant production is summarized in the appendix. Among plants developed in Israel, endochitinase expression was assayed via the MuchT assay using material just 1-5 days after co-cultivation. Plants of cv. Sugraone carrying the gene coding for ESF12, a short anti-fungal lytic peptide under the control of the double 358 promoter, were produced. Leaf extracts of two plants showed inhibition zones that developed within 48 h indicating the inhibitory effect of the leaf extracts on the six species of bacteria. X fastidiosa, the causal organism of Pierce's disease, was very sensitive to leaf extracts from ESF12 transformed plants. Further work is needed to verify the agricultural utility of ESF12 transformants. In New York, some transformants were resistant to powdery mildew and Botrytis fruit rot. Major conclusions, solutions, achievements and implications The following scientific achievements resulted from this cooperative BARD project: 1. Development and improvement of embryogenesis and tissue culture manipulation in grape, while extending these procedures to several agriculturally important cultivars both in Israel and USA. 2. Development and improvement of novel transformation procedures while developing transformation techniques for grape and other recalcitrant species. 3. Production of transgenic grapevines, characterization of transformed vines while studying the expression patterns of a marker gene under the control of different promoter as the 35S CaMV in different part of the plants including flowers and fruits. 4. Expression of anti-fungal genes in grape: establishment of transgenic plants and evaluation of gene expression. Development of techniques to insert multiple genes. 5. Isolation of novel grape specific promoter to control the expression of future antimicrobial genes. It is of great importance to report that significant progress was made in not only the development of transgenic grapevines, but also in the evaluation of their potential for increased resistance to disease as compared with the non engineered cultivar. In several cases, increased disease resistance was observed. More research and development is still needed before a product can be commercialized, yet our project lays a framework for further investigations.